14,838 Matching Annotations
  1. Jul 2018
    1. On 2014 Nov 13, Robert Eibl commented:

      Dear Readers,

      Here is a link to my critical comment on this paper, which might be interesting to the reader: http://scitation.aip.org/content/aip/journal/apl/104/23/10.1063/1.4882182

      Pubmed does not include my comment as a reference, although it recently added the response to my comment. This seems to be due to the publisher who only recommends NIH-funded comments and replies to be listed in Pubmed. In contrast, my comment is accurately mentioned in other scientific libraries, for example IEEE Xplore. For those interested in my research field of specific cell adhesion on living cells measured by nanotech methods and on a single-molecule level, I include a list of references; some of my book chapters are also not included in Pubmed.

      Best regards,

      Dr. Robert Eibl

      REFERENCES

      1. Moy VT et al. , Science (1994)

      2. Eibl RH and Moy VT, Atomic force microscopy measurements of protein-ligand interactions on living cells. In: Protein-Ligand Interactions, (Editor: G.Ulrich Nienhaus), Humana Press, Totowa, NJ, U.S.A., pp. 437-448 (2005)

      3. Benoit M et al. Nature Cell Biology (2000)

      4. Eibl RH and Benoit M, Molecular resolution of cell adhesion forces. IEE - Nanobiotechnology 151(3):128-132 (2004)

      5. Eibl RH, Direct force measurements of receptor-ligand interactions on living cells. In: Applied Scanning Probe Methods XII - Characterization. Bhushan B, Fuchs H (Editors), Springer, pp. 1-31, (2009)

      6. Eibl RH, Cell adhesion receptors studied by AFM-based single-molecule force spectroscopy. In: Scanning Probe Microscopy in Nanoscience and Nanotechnology 2, Bhushan B. (Editor), Springer, pp.197-215, (2011)

      7. Eibl RH, Single-molecule studies of integrins by AFM-based force spectroscopy on living cells. In: Scanning Probe Microscopy in Nanoscience and Nanotechnology 3, Bhushan B. (Editor), Springer, pp.137-169, (2013)

      8. Eibl RH, Comment on “A method to measure cellular adhesion utilizing a polymer micro-cantilever” [Appl. Phys. Lett. 103, 123702 (2013)]. Applied Physics Letters, 104, 236103 (2014)


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    1. On 2015 Feb 11, Michael E Miller commented:

      The subgroup analyses reported in our paper were in fact not affected by imbalance between groups. Our finding that “Compared to standard therapy, ACCORD’s intensive glycemia strategy resulted in a higher incidence of cardiovascular mortality in the younger participants but not in older participants (p=0.03 for interaction)” was not a comparison of cardiovascular mortality in younger versus older participants in the same treatment. It compared the effect of the allocated intervention within younger (HR=1.71) versus the effect within older participants (HR=0.97). Thus, among younger participants, the intensive strategy resulted in a higher CV mortality rate compared to the standard strategy; whereas, this treatment group effect was not observed among the older participants. With approximately 3400 participants in both intensive and standard glycemia groups within younger participants and 1700 participants in each group among older participants, baseline characteristics of the intensive and standard groups within age groups were well-balanced. The suggestion that “differences in the baseline characteristics, not the glycemic control in the intensive group might have been responsible for increased mortality in younger participants” is therefore incorrect. Indeed, mortality was not greater in the younger group (see Figure 1). We wrote: “As expected, the older subgroup had higher absolute event rates for all outcomes considered within both treatment arms.” Were we to statistically compare incidence rates in younger versus older participants within the same treatment (which our paper did not do), then clearly many health related characteristics of younger and older participants would be different (as we reported in Supplementary Table 1 of the online appendix) and this would contribute to any differences within treatment groups between age groups.


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    2. On 2015 Feb 07, Jayaprakash Sahoo commented:

      We read with interest the article by Miller et al in which they have analyzed the impact of baseline age on the effect of intensive blood glucose lowering in the ACCORD trial(1). One of the conclusions of this analysis is that intensive glycemic strategy results in a higher incidence of cardiovascular mortality in the younger but not in older participants. This odd conclusion has to be subjected to scrutiny.

      There is a concept that the quality of output is determined by the quality of the input and this applies to statistical analysis also. The basic requirement for comparison of two groups (input data) prior to any analysis is matching of their baseline characteristics. Any conclusion (output data) reached as a result of an analysis without matching is bound to be associated with bias. The baseline characteristics of the intensive and standard therapy arms of the original ACCORD trial were perfectly matched (2). So, the increased mortality in the intensive arm might have been the effect of glycemic control per se in that study. However, the post hoc analysis of the original ACCORD data comparing the adverse events, cardiovascular disease and mortality in older versus younger adults has discrepant baseline characteristics like body mass index (BMI), waist circumference (WC), glycated hemoglobin (HbA1c), blood pressure (BP), and lipid profile. It is probably because this was not the primary objective of the original study. The older participants had a favorable risk factor profile of significantly lower BMI, WC, HbA1c, diastolic BP, LDL cholesterol, triglycerides and high HDL cholesterol as compared to younger participants. The differences in the baseline characteristics, not the glycemic control in the intensive group might have been responsible for increased mortality in younger participants. The authors have discussed role of hypoglycemia and rate of decline in HbA1C as possible causes of increased mortality, but they could not reach any conclusion (3-4). They have not touched upon the impact of differences in baseline characteristics on mortality. In addition, the contributions from blood pressure and lipid control towards the end points leading to inferences in this study has to be taken into account(5). So, the conclusions drawn from analysis of retrospective data, where two groups compared had different baseline characteristics should be taken with caution.

      References:

      1. Miller ME, Williamson JD, Gerstein HC, et al. Effects of randomization to intensive glucose control on adverse events, cardiovascular disease, and mortality in older versus younger adults in the ACCORD trial. Diabetes Care 2014; 37:634-643.

      2. Gerstein HC, Miller ME, Byington RP, et al.; Action to Control Cardiovascular Risk in Diabetes Study Group. Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 2008; 358:2545–2559.

      3. Bonds DE, Miller ME, Bergenstal RM, et al. The association between symptomatic, severe hypoglycaemia and mortality in type 2 diabetes: retrospective epidemiological analysis of the ACCORD study. BMJ 2010; 340:b4909.

      4. Riddle MC, Ambrosius WT, Brillon DJ, et al.; Action to Control Cardiovascular Risk in Diabetes Investigators. Epidemiologic relationships between A1C and all-cause mortality during a median 3.4-year follow up of glycemic treatment in the ACCORD trial. Diabetes Care 2010; 33:983–990.

      5. Margolis KL, O'Connor PJ, Morgan TM, et al. Outcomes of combined cardiovascularrisk factor management strategies in Type 2 diabetes: The ACCORD randomized trial. Diabetes Care. 2014 Mar 4.


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    1. On 2013 Nov 12, Christophe Dessimoz commented:

      A preprint of this book chapter can be freely downloaded from arXiv: http://arxiv.org/abs/1211.2160.


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    1. On 2015 Aug 15, John Tucker commented:

      A major shortcoming of the paper is a lack of detailed comparison of the characteristics of published and non-published trials. Although the authors speculate that non-publication of large studies may result from a "discrepancy between observed and desired results" or the desire to protect intellectual property, a quick survey of the unpublished trials listed in the supplementary material shows that most involved drugs that never received regulatory approval for marketing. Thus the leading cause of non-publication appears to be simple irrelevance.


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    1. On 2014 Jan 21, Amanda Capes-Davis commented:

      As a small comment on this study: INT-407 cells are not intestinal. The INT-407 cell line is known to be cross-contaminated and is actually HeLa. A list of known cross-contaminated cell lines can be found at http://iclac.org/databases/cross-contaminations/.


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    1. On 2014 Oct 15, Amanda Capes-Davis commented:

      The cell lines used here - HEp-2 and KB - are both known to be cross-contaminated. Unfortunately, that means that both of these models are actually HeLa, from cervical carcinoma.

      HEp-2 and KB are widely used in the literature as models for head and neck SCC, even though they are not appropriate models for this tissue type. Always be careful to test cell lines to check that they are not cross-contaminated, using a consensus method such as short tandem repeat (STR) profiling.

      For a list of known cross-contaminated or otherwise misidentified cell lines, see http://iclac.org/databases/cross-contaminations/.


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    1. On 2013 Nov 06, Brian Walcott commented:

      Without reversal agents readily available, novel oral anticoagulants can result in catastrophic hemorrhage. While the absolute risk reduction for intracranial hemorrhage may be lower with these agents, there is no way perform emergent reversal (indicated to arrest hematoma growth or allow for emergency surgery). The development and availability of rapid reversal agents are necessary prior to widespread use of this next generation of anticoagulation.


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    1. On 2013 Nov 06, Rafael Najmanovich commented:

      None


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    2. On 2013 Nov 06, Rafael Najmanovich commented:

      As someone involved in the development of the field (see Najmanovich R, 2008, http://f1000research.com/articles/2-117/v2 and Najmanovich RJ, 2005) I find the subject area of this article highly relevant for the goal of understanding protein function and its prediction from structure. However, I have several reservations concerning the current paper. These are presented in what follows in decreasing order of importance which is in fact the exact opposite order in which the results mentioned here are presented in the paper followed by some final remarks.

      1 - Recovery of Holo Structures using the Apo Structure as a Query. In this section the authors calculate binding site similarities between each Apo protein form (unbound) and the entire set of Holo protein forms (bound). The authors set out, in their words to assess 'the likelihood of correctly identifying the cognate parter of each detected apo binding site’. This language is unclear as we don’t know if they are assessing the probability of finding as most similar a binding-site that binds a similar ligand or the binding-site of the Holo protein that is identical to the Apo form used as query. They find that in 87% of cases ‘the binding sites were correctly matched’. The authors appear to show that they are able to detect based on binding-site similarities the Holo form of a given Apo form for the same protein in 87% of cases. That is to say, the method is capable of accounting for whatever amount of flexibility exists between Apo and Holo forms in 87% of cases as it detects an identical binding site (except for flexibility) as top ranking. This result does not in any way measure the ability of the method to predict function (defined as detecting the correct binding ligand). As a side note, a simple sequence alignment would obviously detect the correct holo partner from the Apo in 100% of cases. To test the prediction capabilities of the method, the authors should use a truly non-redundant dataset (see point 3) and detect as high scoring the Holo forms of other proteins (not the one that pairs with the query) that bind the same or highly similar ligands (for details see Najmanovich R, 2008).

      2 - Detection of Binding Sites on Structures with or without Ligands Bound. In this section the authors seek to quantify the ability of the method to detect the cavity that represents the binding site (i.e., where the bound ligand is found) out of all possible cavities. They search against the cavities in the holo or the Apo sets and report 91% and 88% success rates respectively. While these results may at first seem impressive, it is important to note, as reported already in 1996 that the largest volume cavity is the cavity that contains the binding-site in 83% of cases (Laskowski RA, 1996). The challenge is not to detect the cavity that contains the binding-site but the actual binding-site, that is, the residues with atoms in contact with ligand atoms.

      3 - Curated LigASite Database. The authors mention that they use the non-redundant LigASite dataset (Dessailly BH, 2008), however, it is important to highlight that redundancy is always relative to the question at hand. The context here is the prediction of function from structure. In such a context, it is necessary to use a dataset that from the point of view of the proteins within, does not contain any redundancy at the level of protein folds in addition to sequence. As an example, human protein kinases can have very low sequence identity, below the 25% threshold used in LigASite, but almost 100% binding site similarity, sequence or otherwise. Additionally from the point of view of the ligands, a quick inspection of the originally reported LigASite non-redundant dataset shows an over-representation of nucleotide-containing molecules (MG ADP MN ATP NAG NAD GOL GDP PO4 GLC NAP GAL COA AMP ANP).

      Finally, the authors apply some extra filters to the LigASite dataset available at the time of their study but do not publish the final dataset, thus preventing any careful analysis of non-redundancy or allowing future works to compare their results to the ones reported here. In summary, the data presented here does not allow a reader to evaluate in any way the quality of the method. To truly test a method one has to compare it to existing methods that perform the same tasks (such as IsoCleft above and many others that exist) as well as use a dataset that is non-redundant for the particular questions.


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    1. On 2014 Feb 15, Amanda Capes-Davis commented:

      There are a number of references that refer to KB as oral cancer. Unfortunately, Gartler showed in 1967 that KB is cross-contaminated with HeLa and is actually cervical adenocarcinoma. For a list of known cross-contaminated cell lines, see http://iclac.org/databases/cross-contaminations/.


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    1. On 2014 Jun 20, James Q Zheng commented:

      Thank you for your comment and it is a good point. However, in the discussion, 3rd paragraph, we explicitly discussed the possible involvement of GSK3alpha. Quoted here:

      It should be noted that these studies do not preclude a similar role for the GSK3b homologue, GSK3a, in dendritic development and maintenance. The kinase domains of both GSK3a and GSK3b are highly similar, and there are numerous contexts where both have been demonstrated to be at least partially functionally redundant (39,40).


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    2. On 2014 Jun 19, Jim Woodgett commented:

      Disappointing that the authors did not assess (or even mention) the possible role of GSK-3alpha in these processes, since it is highly redundant with GSK-3beta, has tightly overlapping substrate specificity, similar ubiquitous expression and is equivalently regulated by PI3K and Wnt. For example, does GSK-3alpha also bind Gephryn?


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    1. On 2014 Aug 07, Raha Pazoki commented:

      The study by Lambert and co-workers is an interesting piece of work on a sample consisting of more than 50,000 cases and controls. The authors performed a multi-stage genome wide association study with meta-analysis of the results and identified several new loci for Alzheimer disease. The final loci were searched for eQTL effects in online eQTL database from Pritchard laboratory which provides eQTLs from different resources.

      While this is a comprehensive approach to identify functional genetic loci, there are still other eQTL databases available online that may provide more information about the functionality of these loci. For example, a quick search in the GTEx online eQTL database (GTEx Consortium., 2013) shows that rs1476679 (identified in the present work of Lambert and co-workers) is additionally an eQTL for the gene PVRIG2P with effect size of 0.34 and P<2× 10<sup>-6.</sup> PVRIG2P has not been previously implicated in Alzheimer’s disease but could be a target for further research along with other findings of Lambert and co-workers.


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    2. On 2013 Oct 31, Ben Busby commented:

      Congratulations to these authors for acquiring a staggering amount of data, the production of which was funded by various government and non-profit sources; this made for some interesting findings that may be directly relevant in the clinic. It is my sincere hope that the researchers will go even farther in investigating subsets of this data, and in doing so, identify genomic subgroups of patients with the Alzheimer's phenotype. I would recommend this paper to anyone interested in using patient-sequence datasets to investigate disease.


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    1. On 2016 Nov 03, Morten Oksvold commented:

      None


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    2. On 2016 Apr 05, Md. Shahidul Islam commented:

      Please read "Expression of concern—Tracheobronchial transplantation with a stem-cell-seeded bioartificial nanocomposite: a proof-of-concept study".

      http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)30091-5/fulltext?rss=yes


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    3. On 2016 Feb 23, Md. Shahidul Islam commented:

      Please read the comments of the Royal Swedish Academy of Science http://www.thelancet.com/pb/assets/raw/Lancet/pdfs/S0140673616005201.pdf


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    4. On 2016 Feb 23, Md. Shahidul Islam commented:

      Please read the comment of Richard Horton editor of Lancet in this link http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)00341-X/fulltext?rss=yes


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    5. On 2015 Aug 12, Md. Shahidul Islam commented:

      Please read Vogel G 2015 Regenerative medicine. Report finds misconduct by surgeon. Science 2015 May 29;348(6238):954-5. doi: 10.1126/science.348.6238.954-b


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    6. On 2015 May 26, Md. Shahidul Islam commented:

      None


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    1. On 2013 Oct 29, John Cannell commented:

      I congratulate the authors on an important work but it shows how little communication is occurring among autism scientists. Each scientist seems to be immersed in his or her own research interest but oblivious to the larger body of autism research.

      While the below Harvard study was published to late for the authors to cite, it showed that preterm infants have significantly lower serum 25(OH)D levels than do full term infants.

      Burris HH, Van Marter LJ, McElrath TF, Tabatabai P, Litonjua AA, Weiss ST, Christou H. Vitamin D status among preterm and full-term infants at birth. Pediatr Res. 2013 Oct 11. doi: 10.1038/pr.2013.174. [Epub ahead of print]. Burris HH, 2014

      Thus the vitamin D theory of autism (vitamin D deficiency is the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with autism. Two of the studies below (Mostafa et al and Gong et al) also found autism severity, as rated on standard autism rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of 25(OH)D with autism severity.

      Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

      Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

      Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

      DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

      Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

      Furthermore, the vitamin D theory of autism explains many of the epidemiological facts of autism.

      Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

      Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day.

      Cannell JJ. Autism, will vitamin D treat core symptoms? Medical Hypotheses. 2013 Aug;81(2):195-8. Cannell JJ, 2013

      Some autism researcher seem cognizant of the entire body of autism research. For example a group of well-known European autism researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into vitamin D and autism. However, these scientists appear to be in the minority.

      Kočovská E, Fernell E, Billstedt E, Minnis H, Gillberg C. Vitamin D and autism: clinical review. Res Dev Disabil. 2012 Sep-Oct;33(5):1541-50. doi: 10.1016/j.ridd.2012.02.015. Epub 2012 Apr 21.Kočovská E, 2012

      Until all autism researchers become cognizant of the wider body of autism research, we will continue to wonder how to prevent - and perhaps even treat - this modern day plague.

      John J Cannell Vitamin D Council http://www.vitamindcouncil.org


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    1. On 2013 Oct 30, Woo Jae Kim commented:

      I agree, however, we need strong genetic tools that we can use in Drosophila from other species we will use to study complex behaviors. I guess evolutionary biologists and Drosophila geneticists should meet for this common purpose to build strong genetic tools in other insect species.


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    1. On 2014 Nov 24, Roger Keller Celeste commented:

      If I read correctly, authors were looking for failure of implants placed after radiotherapy versus those place in bone not irradiated.

      Time after radiotherapy is an important variable that was not considered. Implants placed in irradiated bone, after long time since radiotherapy, may have similar success probability to those placed in non-irradiated bone. The idea that 6 months of healing is enough may not be true.

      We have conducted a similar review Claudy MP, et al. Time Interval after Radiotherapy and Dental Implant Failure: Systematic Review of Observational Studies and Meta-Analysis, but comparing implants placed in bone irradiated between 6-12 months after radiotherapy versus implants placed after 12 months.

      In our finding, the difference between groups was smaller, and we also detected influence of one study in the results. We were also able to include more studies, so to assess influence of publication bias and heterogeneity. Thanks, Roger Keller Celeste, PhD in Epidemiology Federal University of Rio Grande do Sul, Brazil Faculty of Dentistry


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    1. On 2013 Oct 28, Leslie Vosshall commented:

      Feng Zhang and co-workers present a further optimization of the CRISPR-Cas9 system that that minimizes off-target cleavage. This technique keeps getting more compelling as a genome-editing tool because unlike TALENs and ZFNs, CRISPR-Cas9 can be implemented cheaply and easily in any laboratory.


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    1. On 2013 Oct 31, John Cannell commented:

      I wonder if the authors are aware that the genes for the antioxidants superoxide dismutase and thioredoxin reductase are directly up-regulated by the secosteroid 1,25 di-hydroxy vitamin D3 (calcitriol). I believe both genes also harbor a vitamin D response element.

      Peehl DM, Shinghal R, Nonn L, Seto E, Krishnan AV, Brooks JD, Feldman D. Molecular activity of 1,25‐dihydroxyvitamin D3 in primary cultures of human prostatic epithelial cells revealed by cDNA microarray analysis. J. Steroid Biochem Mol. Biol 2004;92:131–141. Peehl DM, 2004

      Calcitriol also directly up-regulates glutathione reductase and increases glutathione levels.

      Jain SK, Micinski D.Vitamin D upregulates glutamate cysteine ligase and glutathione reductase, and GSH formation, and decreases ROS and MCP-1 and IL-8 secretion in high-glucose exposed U937 monocytes. Biochem Biophys Res Commun. 2013 Jul 19;437(1):7-11. doi: 10.1016/j.bbrc.2013.06.004. Jain SK, 2013

      Also, supplemental vitamin D significantly reduces oxidative stress in humans.

      Nikooyeh B, et al. Daily intake of vitamin D- or calcium-vitamin D-fortified Persian yogurt drink (doogh) attenuates diabetes-induced oxidative stress: evidence for antioxidative properties of vitamin D.J Hum Nutr Diet. 2013 Jul 5. doi: 10.1111/jhn.12142. Nikooyeh B, 2014

      Asemi Z, et al. Vitamin D supplementation affects serum high-sensitivity C-reactive protein, insulin resistance, and biomarkers of oxidative stress in pregnant women. J Nutr. 2013 Sep;143(9):1432-8. doi: 10.3945/jn.113.177550. Asemi Z, 2013

      Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

      Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

      Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

      Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

      Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

      DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

      Eyles DW, Burne TH, McGrath JJ. Vitamin D, effects on brain development, adult brain function and the links between low levels of vitamin D and neuropsychiatric disease. Front Neuroendocrinol. 2013 Jan;34(1):47-64. doi: 10.1016/j.yfrne.2012.07.001. Epub 2012 Jul 11. Review. Eyles DW, 2013

      Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

      Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

      Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day and few to


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    1. On 2014 Feb 13, Bruno Ramalho Carvalho commented:

      In their interesting article, Gizzo et al affirmed that modern concepts on fertility sparing consider ovarian reserve to be the most important independent female fertility predictor, even being more important than chronological age. I would say that, based on scientific evidence, such an affirmative is at least controversial.

      First of all, that affirmative was attributed to a narrative review article and an article on fertility preservation in women with cancer, which are supposed to be unaproppriate references. Adequate evidences should include prospective and controlled studies, with large populations.

      Until today, the bulk of literature supports age as the single most important factor in determining theoretical reproductive capability of women. In historical cohorts, the respective rates of infertility among married women at the age groups of 20-24, 25-29, 30-34, 35-39 and 40-44 years were 6%, 9%, 15%, 30% and 64% [Menken et al, Science 1986].

      Women undergoing artificial insemination with donor sperm because of partner azoospermia presented with lower rates of conception or needed more cycles to achieve it after 35 years of age [Schwartz & Mayaux N Eng J Med 1982]. According to recent data, similar results were obtained in in vitro fertilization (IVF) cycles using non donor fresh eggs; birth rates for age groups of < 35, 35-37, 38-40, 41-42 and > 42 years were 36%, 28%, 18%, 10% and 4% per cycle, respectively [CDC, http://apps.nccd.cdc.gov/art/Apps/NationalSummaryReport.aspx].

      Data from Red Latinoamericana de Reproducción Asistida demonstrated a significant age-dependent reduction of pregnancy rates per IVF cycle: 38% for women with 30-34 years of age; 31% for women with 35-39 years of age and 16% for older patients [Zegers-Hochschild et al, 2008; http://www.redlara.com/imagens/arq/2008_registro 2008.pdf]. Furthermore, studies have shown that women of advanced maternal age unable to achieve pregnancy through IVF were able to conceive using donor oocytes from younger women [Steiner & Paulson, 2006].

      Despite the points enhanced along Gizzo et al discussion, some should note that their results clearly demonstrate that age is the best predictor of IVF results, since they reported ongoing pregnancy rates of 6.7% in the fifth decade of life, with no pregnancy after 46 years of age. It is noticeable that the authors did not mention live birth rates, which should be expected to be lower, as late pregnancy loss are very probable among the study population.

      A recent study by Luke et al demonstrated that the results of cycles of IVF/ICSI diminish in direct relationship with increasing maternal age and the number of cycles performed with autologous oocytes. Live birth rates were estimated, respectively, to be of 63.3 % and 74.6 %, in conservative and ideal perspectives for women under 30 years of age, 18.6% and 27.8 % after 41 or 42 years of age, and 6.6% and 11.3 % for women after 43 or more years of age at the end of a third cycle of IVF/ICSI with their own oocytes. However, those rates were higher than 60% and 80% for all ages when donors’ oocytes were used [Luke et al. N Eng J Med 2012].

      The literature suggests that follicle development is impaired in women with advanced age, even if they present apparently normal steroidogenesis and regular menstrual cycles. In such a population, deficiencies in insulin-like growth factors (IGF) I and II, and even in the endogenous luteinizing hormone secretion, have been suggested as cofactors to explain the phenomenon [Santoro et al. JCEM 2003].

      Finally, it is well known that both the quantity and quality of ovarian follicles significantly decrease as a woman advances in age, and that many women who postpone maternity may be infertile at the time they are willing to become pregnant. The main purpose of ovarian reserve evaluation, especially before ART, is to identify women with poor ovarian reserve for their chronological age. This is exactly the reason why age must always be the first marker to be considered in ovarian reserve assessment.

      In my opinion, it is very clear that older women may benefit from ovarian reserve tests and the authors have reinforced it. However, their results do not support to exclude women’s chronological age as the main element to define treatment chances in the management of “elderly” infertile couples. They may help clinicians to find out acceptable chances of pregnancy through IVF, but, until now, it is not acceptable to guarantee positive results based on ovarian reserve tests, alone or in association.


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    1. On 2015 Apr 02, Harri Hemila commented:

      The Cochrane review “vitamin C supplementation for asthma”, withdrawn by Kaur B, 2013, misled readers for over a decade.

      The first version of this Cochrane review “vitamin C supplementation for asthma” was published in 2001 by Kaur B, 2001. The 2001 version had serious errors in the extraction and analysis of data, which are summarized in Pubmed Commons. Those 2001 errors were thereafter passed on to the 2004 update by Ram FS, 2004 and thereafter on to the 2009 update by Kaur B, 2009. See a summary of the major errors in the 2009 version of the Cochrane review in Pubmed Commons. Thus, the Cochrane review “vitamin C supplementation for asthma”, initially published in 2001 by Kaur B, 2001, misled readers for over a decade before it was withdrawn.


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    1. On 2014 Mar 20, Jonathan Eisen commented:

      Lynn Schriml, the senior author of this paper, wrote a guest post for the "Microbiology of the Built Environment (microBEnet)" blog about the development of these standards. See Guest Post: Metadata for the Built Environment – MIxS-BE package.


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    1. On 2016 Apr 09, Sergio Uribe commented:

      Strange results. The Fuji II LC had a mean microleakage of 7.99 and SD of 9.57. Hence some samples had a leakage of -1.58 um....

      also, a group with mean(SD) of 1.28(0.98) was not statistically different from another with 7.99(9.57), but both were different from a third with 4.36(5.64). (See Table 2)

      After reading the paper, is it not clear if they compared the repeated meaures against the baseline measurement or against each other. The description of the statistical procedure in the paper states: "Finally, the data were analyzed by repeated measures and Duncan (a=0.05) tests." Uninformative.

      Maybe the authors can give a more detailed explanation on how they assess the differences among groups.


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    1. On 2015 Oct 05, Jan Egger commented:

      For a video demonstrating the interactive real-time segmentation of a prostate central gland (PCG) in 2D, please see here: https://www.youtube.com/watch?v=dr6QLwmxoOg

      Best wishes, Jan


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    1. On 2013 Nov 01, Erick H Turner commented:

      A related idea that might be interesting would be to see how many journals explicitly welcome submissions regardless of the strength and direction of results. The ICMJE has declared that its members journals have an "obligation to publish negative studies" (http://www.icmje.org/publishing_1negative.html), but it seems that few journals have incorporated this directive into their policies.


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    1. On 2013 Oct 23, Rafael Najmanovich commented:

      It would be interesting to study this gene in patients with colitis caused by C. difficile infections.


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    1. On 2013 Dec 12, Matthew Inglis commented:

      In a post to the "Had I Been A Reviewer" blog, Lucy Cragg and I raised four questions about the statistical analyses used in this paper. Briefly, we ask about (i) the appropriateness of using one-tailed tests, (ii) the sampling methods, (iii) the appropriateness of using a Fisher's r-to-z transform to compare dependent correlation coefficients, and (iv) the lack of Bonferroni corrections.

      The full post is available here: http://ow.ly/qCri6


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    1. On 2014 Feb 06, Simon Young commented:

      This paper, demonstrating that giving humans tryptophan (TRP) in order to increase brain serotonin promotes interpersonal trust, is an interesting contribution to the literature on serotonin and social behavior. However, the authors’ interpretation of the results in relation to nutrition is problematic. They conclude their paper by stating:

      “Food may thus act as a cognitive enhancer that modulates the way one thinks and perceives the physical and social world. In particular, TRP supplements, or TRP-containing diets, may promote interpersonal trust in inexpensive, efficient, and healthy ways.”

      The word diet can refer to the food that a person habitually eats, or foods that are eaten for a special reason. In relation to the first definition of diet the Introduction of the paper mentions:

      “TRP is an essential amino acid contained in food such as fish, soybeans, eggs, and spinach.”

      TRP is a constituent of nearly all proteins and therefore all foods that contain protein contain TRP. Fish, soybeans and eggs are high in protein and are therefore relatively high in TRP, while spinach is low in protein and therefore TRP. Among the amino acids TRP is the least abundant in most proteins Heine W, 1995. While ingestion of normal foods containing protein will increase plasma TRP levels, it will not increase brain TRP or serotonin Sainio EL, 1996. This is because TRP is taken up into the brain from the blood by a transport system that is active towards all the large neutral amino acids (LNAA). The different amino acids compete with each other for the transport system, and as a rough approximation brain TRP levels will follow the plasma ratio of TRP to the other LNAA (TRP/LNAA). Because of the low abundance of TRP in most proteins this ratio will decline after ingestion of a normal meal. While the decline is small enough that there is unlikely to be any important decline in brain TRP and serotonin synthesis, normal protein-containing meals definitely do not raise brain serotonin Teff KL, 1989. Thus, normal meals would not promote trust by increasing serotonin. The statement in the paper that food may act as a cognitive enhancer may be true, but has nothing to do with TRP and serotonin. The acute improvement in memory after a meal is well known and is associated with an increase in blood glucose Smith MA, 2011. All macronutrients may have beneficial effects on cognition as protein, carbohydrate and fat meals all improve performance on different cognitive tests in humans Kaplan RJ, 2001. Among the dietary components that can potentially influence brain function acutely, in addition to TRP, are tyrosine and phenylalanine, which are precursors of the catecholamines, histidine, the precursor of histamine, choline, the precursor of acetylcholine, and threonine, after conversion into glycine Young SN, 1996. Furthermore, while real meals can have acute effects on cognition and mood these effects are influenced by context Sommer W, 2013. If normal meals were found to increase interpersonal trust such an effect would not be mediated by changes in TRP and serotonin. The second meaning of diet is foods, that may be specially prepared, that are eaten for a special purpose. One such specially prepared food that has been studied is alpha-lactalbumin, a protein that is a minor constituent of milk and has a higher than normal proportion of TRP Heine W, 1995. When purified alpha-lactalbumin is given to humans it increases the TRP/LNAA Markus CR, 2008 and can in some circumstances have effects on mood and cognition Markus CR, 2000. However, alpha-lactalbumin could not be considered a special diet that may “promote interpersonal trust in inexpensive, efficient, and healthy ways”. Colzato et al. gave the participants in their study 0.8g of TRP. When humans were given either 0.8g of pure TRP or 0.8g of TRP in alpha-lactalbumin (15g) the rise in TRP/ LNAA is much greater after the TRP than after the alpha-lactalbumin, because the alpha-lactalbumin contains the other LNAA Markus CR, 2008. Furthermore, the TRP/LNAA reached a peak 2 hours after ingestion of the alpha-lactalbumin and then declined. To increase serotonin synthesis sufficiently to promote interpersonal trust would presumably involve doses of alpha-lactalbumin greater than 15g, taken at relatively frequent intervals throughout the day. This would not be inexpensive and efficient as suggested by Colzato et al., and might not even be healthy given that the effects of frequent ingestion of a protein supplement that has calories but no minerals, vitamins or antioxidants could potentially have adverse effects on total dietary intake. In some countries TRP is sold as a dietary supplement (although in others such as Canada it is regulated as a prescription drug). This raises the question of whether TRP could be given long-term in pure form to promote interpersonal trust. When TRP is given for a few weeks it can help regulate behavior in pathologically aggressive patients Morand C, 1983, and promote more pro-social behavior in healthy people Moskowitz DS, 2001 aan het Rot M, 2006. However, taking TRP long-term to promote trust would be neither inexpensive, convenient, given that TRP has to be taken several time a day to ensure that brain serotonin remains elevated Moskowitz DS, 2001, or without risk Fernstrom JD, 2012. Barriers to obtaining more information on the effects of diet on mood and behavior include the complexities of the effects of dietary components on brain function, the fact that effects of food intake on brain function can be modulated by the setting, and the difficulties of carrying out randomized trials with altered diets. At this time research has not revealed any simple dietary strategy to increase brain serotonin, in spite of the potential benefits of such an approach.


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    1. On 2014 Apr 08, Dr Nicholas D Gollop commented:

      Dear Jamil Hajj-Chahine, thank you for your comments on our paper: ‘Comparison of drug-eluting and bare-metal stents in patients with diabetes undergoing primary percutaneous coronary intervention: what is the evidence?’ [1].

      Percutaneous coronary intervention (PCI) is the preferred method of revascularization in the management of acute ST elevation myocardial infarction (STEMI). However, in a specific subset of patients, CABG may be appropriate.

      For example, coronary angiography may reveal anatomy that is unsuitable for balloon angioplasty or stenting. In these patients, CABG may be indicated for the treatment of acute STEMI.

      Furthermore, CABG is indicated when primary PCI has failed to achieve reperfusion of the myocardium in addition to persistent hemodynamic instability or life-threatening ventricular arrhythmia due to extensive ischemia (left main or 3-vessel disease). There are several limitations to CABG in the management of acute STEMI.

      It has been shown that CABG performed within 2 days of hospitalization for acute STEMI is associated with a higher incidence of mortality in comparison to CABG carried out 3 or more days after acute STEMI [2].

      The incidence of Rethoracotomy is significantly greater when CABG is performed within the first 3 days following acute STEMI in contrast to CABG carried out between day 4 and 30 [3]. Furthermore, post-operative intra-aortic balloon pump devices are required for longer, there is a higher incidence of bleeding complications, more inotropic drugs are required and there is a longer intensive care and total hospital stay when CABG is carried out within 3 days of presentation.

      When compared against PCI, CABG is associated with a higher risk of stroke within the 30 day post-operative period [4].

      References

      [1] Gollop ND, Henderson DB, Flather MD. Interact Cardiovasc Thorac Surg. 2014 Jan; 18 (1): 112-6. In diabetic patients does the utilization of Drug Eluting Stents (DES) instead of Bare Metal Stents (BMS) reduce restenosis rate without compromising the efficacy and safety of Primary Percutaneous Coronary Intervention? [2] Weiss ES, Chang DD, Joyce DL, Nwakanma LU, Yuh DD. J Thorac Cardiovasc Surg. 2008 Mar; 135 (3): 503-11, 511.e1-3. Optimal timing of coronary artery bypass after acute myocardial infarction: a review of California discharge data. [3] Gu YL, van der Horst IC, Douglas YL, Svilaas T, Mariani MA, Zijlstra F. Neth Heart J. 2010 Aug; 18 (7-8): 348-54. Role of coronary artery bypass grafting during the acute and subacute phase of ST-elevation myocardial infarction. [4] Palmerini T, Biondi-Zoccai G, Riva DD, Mariani A, Savini C, Di Eusanio M, Genereux P, Frati G, Marullo AG, Landoni G, Greco T, Branzi A, De Servi S, Di Credico G, Taglieri N, Williams MR, Stone GW. Am Heart J. 2013 Jun; 165(6) :910-917.e14. Risk of stroke with percutaneous coronary intervention compared with on-pump and off-pump coronary artery bypass graft surgery: Evidence from a comprehensive network meta-analysis.


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    2. On 2014 Jan 18, Jamil Hajj-Chahine commented:

      I read with great interest the paper by Gollop et al regarding the best available stenting technology for diabetic patients undergoing percutaneous coronary intervention [1]. After reviewing the relevant literature, they concluded that drug-eluting stents are superior to bare- metal stents in this subset of patients with regard to clinical outcomes.

      I would like to take the opportunity to discuss the place of coronary artery bypass grafting (CABG) in the era of drug-eluting stent for diabetic patients with multi-vessel coronary disease. CABG was shown to be more beneficial than bare-metal stent for patients with diabetes and multi -vessel disease [2]. However, the improvement in restenosis rate with drug -eluting stents has accelerated the wide use of stenting in patients with extensive coronary disease and extended to include patients with diabetes. Reports mainly from retrospective studies showed that CABG is the preferred modality of treatment in diabetic patients with multi-vessel disease [3-4].

      In 2012, the results of FRREEDOM (Future Revascularization Evaluation in Patients with Diabetes Mellitus: Optimal Management of Multivessel Disease) trial were published [5]. This international trial was specially designed to include only patients with diabetes. Freedom trial randomly assigned 1900 patients in140 centres to undergo either percutaneous coronary intervention with drug-eluting stents or CABG. The primary outcome was a composite of death from any cause, nonfatal myocardial infarction, or nonfatal stroke and it did not include the need for repeat revascularization. The primary end point occurred more frequently in the interventional group 26,6% compared with CABG group 18,7% (p=0,005) at five years post-procedure. CABG in patients with diabetes and multi- vessel disease reduced significantly the rates of death and myocardial infarction. However, stroke rate was the major drawback of surgery with 5- year rates of 2.4% in the stenting group and 5.2% in the CABG group (P=0.03).

      In this subset of high-risk patients, we can conclude that the substantial survival advantage of surgery is still valid even in the era of drug-eluting stents.

      References

      [1] Gollop ND, Henderson DB, Flather MD. Comparison of drug-eluting and bare-metal stents in patients with diabetes undergoing primary percutaneous coronary intervention: what is the evidence? Interact Cardiovasc Thorac Surg. 2013 doi:10.1093/icvts/ivt454.

      [2] Influence of diabetes on 5-year mortality and morbidity in a randomized trial comparing CABG and PTCA in patients with multivessel disease: the Bypass Angioplasty Revascularization Investigation (BARI). Circulation. 1997;96:1761-9.

      [3] Yang JH, Gwon HC, Cho SJ, Hahn JY, Choi JH, Choi SH, et al. Comparison of coronary artery bypass grafting with drug-eluting stent implantation for the treatment of multivessel coronary artery disease. Ann Thorac Surg. 2008;85:65-70.

      [4] Hueb W, Gersh BJ, Costa F, Lopes N, Soares PR, Dutra P, et al. Impact of diabetes on five-year outcomes of patients with multivessel coronary artery disease. Ann Thorac Surg. 2007;83:93-9.

      [5] Farkouh ME, Domanski M, Sleeper LA, Siami FS, Dangas G, Mack M, et al; FREEDOM Trial Investigators. Strategies for multivessel revascularization in patients with diabetes. N Engl J Med. 2012;367:2375- 84.


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    1. On 2013 Oct 24, John Cannell commented:

      Great points. While many know about the role of inflammation on diseases of the elderly like Alzheimer's, fewer know of inflammation's role in diseases of children, such as in autism. Fewer yet know about the profound anti-inflammatory effects of vitamin D. While many will not read any further when they see the word "vitamin," calcitriol is actually a neurosteroid.

      The scientists below discovered that the absolute level of an autoimmune anti-neural antibody was inversely related to 25(OH)D levels with a R value of -.86. So far, six anti-neural antibodies have been discovered in autism, as well as elevated levels of inflammatory cytokines. Two studies showed the levels of these antibodies are inversely related to autism severity with high R values.

      http://www.ncbi.nlm.nih.gov/pubmed/22898564

      http://www.ncbi.nlm.nih.gov/pubmed/23239393


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    1. On 2017 Sep 21, Hendrik S. Fischer commented:

      In response to Dr. Fleming’s comment: Odds ratios (OR) must not be misinterpreted as risk ratios (RR). If outcomes are rare, OR approximate RR. If outcomes are common, OR and RR differ, but both OR and RR still have specific advantages and disadvantages (Cummings P. The relative merits of risk ratios and odds ratios. Arch Pediatr Adolesc Med. 2009;163:438–45). Importantly, OR cannot exaggerate differences across groups given as RR. They are just two different methods to express these differences. In the present meta-analysis, the odds ratio (95% confidence interval) of death or BPD is 0.83 (0.71–0.96) and the risk ratio is 0.90 (0.83–0.98). Admittedly, both OR and RR may be difficult to interpret from a clinical point of view. We therefore recommend that meta-analyses should calculate a number needed to treat (NNT) as a meaningful measure of effect for the clinician. In our meta-analysis, the NTT was 35, indicating the small but beneficial effect of avoiding mechanical ventilation, which we have discussed in the abstract and in our paper.


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    2. On 2017 Jul 12, Robert Fleming commented:

      In the meta-analysis presented in this manuscript, the results are presented as odds ratio (OR) rather than relative risk (RR). When an outcome (BPD in this setting) is common (> 10% in the unexposed group, which is the case for these studies), using OR can exaggerate differences across the groups. The original report from the SUPPORT trial reports a RR of 0.9. In this meta-analysis the OR from the same study is reported as 0.81. Likewise, converting the OR from this meta-analysis (0.83) to RR results in a value of 0.9. This point is made not to imply that mechanical ventilation should not be avoided; however the effect of avoiding mechanical ventilation on the incidence of BPD calculates to be less than concluded in this meta-analysis.


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    1. On 2014 Jul 30, David Keller commented:

      Doctors should replace handshakes with fist bumps, sanitize stethoscopes and ditch white coats & neckties

      The recommendation to substitute fist bumps for handshakes to decrease bacterial transmission makes sense. In addition to the much briefer contact time and much smaller area of skin contact during a fist bump, fist contact occurs only on the dry skin of the dorsal hand, not the moist and sweaty palms which support higher bacterial counts. The widespread neglect of hand-washing has been documented. Fist bumps reduce exposure to gram negative bacteria like salmonella (due to fecal contamination) and gram positive bacteria like Staph Aureus (due to nose-picking) on unwashed hands.

      Substituting fist bumps for handshakes is excellent advice for clinicians, along with eliminating other sources of documented pathogen transmission: unsanitary stethoscopes (1) and rarely-laundered neckties (2) & white coats (3).

      References

      1: Longtin Y, Schneider A, Tschopp C, Renzi G, Gayet-Ageron A, Schrenzel J, Pittet D. Contamination of stethoscopes and physicians' hands after a physical examination. Mayo Clin Proc. 2014 Mar;89(3):291-9. doi: 10.1016/j.mayocp.2013.11.016. PubMed PMID: 24582188.

      2: Day M. Doctors are told to ditch "disease spreading" neckties. BMJ. 2006 Feb 25;332(7539):442. PubMed PMID: 16497745; PubMed Central PMCID: PMC1382570.

      3: Banu A, Anand M, Nagi N. White coats as a vehicle for bacterial dissemination. J Clin Diagn Res. 2012 Oct;6(8):1381-4. doi: 10.7860/JCDR/2012/4286.2364. PubMed PMID: 23205352; PubMed Central PMCID: PMC3471503.


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    1. On 2016 Nov 01, Michael Axtell commented:

      The URLs for ShortStack software and test data given in this paper are out of date:

      ShortStack software is now available on github .. the latest release is at https://github.com/MikeAxtell/ShortStack/releases

      The ShortStack test data / tutorial is now at https://psu.app.box.com/v/axtelldata , in directory 'ShortStack_TestData'

      Also note that some of the options and settings in this work no longer apply to current version of ShortStack.

      Thanks, Mike Axtell


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    1. On 2014 Mar 20, Jae-Weon Kim commented:

      As Dr. Wright pointed out, previous report by Walsh et al at 2005 was not a universal finding. Recently we, Korean Gynecologic Oncology Group, reported that the incidence of synchronous ovarian malignancies in young women with endometrial cancer was quiet low (4.5%), unlike previous studies have revealed (11-29%). You can check our report at PMID: 24051220.


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    1. On 2014 Apr 19, Karthik Balachandran commented:

      The authors describe an industry sponsored and industry designed trial of saroglitazar- a dual PPAR alpha and gamma agonist, explaining establishment of safety and efficacy as the raison de etre. However, closer scrutiny raises several questions.

      1.First of all, the value of triglyceride reduction has not been clearly demonstrated in patients with type 2 diabetes. In fact, the largest trial on lipid management in diabetes till date- the ACCORD LIPID trial shows that the additional triglyceride reduction with fenofibrate was not useful for CV mortality reduction. Thus targeting “residual cardiovascular risk” in statin treated patients is questionable, especially with the surrogate endpoints- lab values- instead of real world outcomes like mortality or cardiovascular events.

      2.More importantly this trial includes patients whose triglycerides were not adequately controlled on statin therapy. The dose of atorvastatin used(10 mg) given for a period of 4 weeks, is hardly the maximum dose or the duration that can be called as “inadequately controlled on statin." 3.Furthermore, the authors compare saroglitazar with placebo for no sound scientific reason. The use of inappropriate comparator has the potential to make the study drug look superior because it has been compared with a dummy sugar pill!

      4.The drug is declared safe with 12 weeks of data and a voluntary(read optional) 24 week visit. This is especially important as the predecessors of the drug(muraglitazar and aleglitazar) were discontinued due to increased all cause and cardiovascular mortality. It is unlikely that the cardiovascular safety of any drug can be ascertained in the short time of 12 weeks. One must bear in mind that drugs for dyslipidemia are taken life long.

      5.The study was conducted in 29 centers across India to get a sample size of 302. As the cost of training personnel is less, the integrity of data is more and is eminently possible to get 300 odd diabetics from any single center of a populous country like India, it makes one suspect whether this was a seeding trial. A seeding trial is done with the express purpose of giving marketing advantage to the company and not to glean any useful scientific information. Use of prominent senior academics as the authors means their name exists for the purpose of giving the illusion of scientific rigor. This combined with manuscript preparation and editorial assistance by the company employees manufacturing the drug means, this could be a ghost written document- promotional material masquerading as an academic article.Although seeding trials or ghost writing  is not illegal, it is considered unethical.

      6.The article also mentions that the trial was approved by ethics committee of individual sites, many of which are private clinics.It is difficult to believe that private clinics have independent ethics committees. So, the question remains - does the drug do anything that cannot be done at half the cost by existing medicines? Is it safe in the long run?


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    1. On 2015 Mar 18, Adrian Barnett commented:

      Suffering a hospital-acquired complication is a time-dependent variable as some patients will experience it some days after their admission. These patients cannot be discharged between admission and the complication. Unfortunately the statistical analysis used ignores this fact and hence the estimates are subject to the length bias and are likely to be over-estimates of the extra length of stay. A solution is to use multi-state models combined with Cox survival models with day of admission as the time variable. A hospital-acquired complication is a transient state between admission and discharge. This accounts for the timing of complications and correctly estimates the extra length of stay due to a complication.


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    1. On 2013 Oct 22, Jonathan Eisen commented:

      This paper represents a landmark study in something that has intrigued many microbial diversity / human microbiome researchers for many years. Early in the history of sequencing rRNA genes from human microbiome samples, researchers discovered something a bit weird - quite a few sequences were coming from what appeared to be close relatives of Cyanobacteria. This was weird because all known Cyanobacteria were thought to be photosynthetic and - well - there is not too much light in the human gut. Now - one possible explanation for this was that these sequences were coming from photosynthetic bacteria but these bacteria were not residents of the human gut but came via consumable items (i.e., food and drink). Perhaps they were actually from chloroplasts of something in the diet (after all - chloroplasts are derived versions of cyanobacteria). This idea was discussed at many meetings I attended. But there was no evidence for this. Another possibility was that there was in fact some light in the human gut - leaking through from the outside or being produced from the inside. And perhaps this was enough to do a little photosynthesis. Sound crazy? Well, not so crazy after reports of photosynthesis in the deep sea. A third possibility was that these sequences were coming from residents of the human gut that were related to (or even within) cyanobacteria but were not photosynthetic. More detail on possible explanations are in this new paper and in some of the material cited therein. Anyway - Ruth Ley has been discussing these unusual sequences for years and now in this paper her group and the group of Jill Banfield at Berkeley (along with some others) has used metagenomics and detailed assembly and phylogenetic analysis to reveal many new insights into these sequences.

      (this comment is based on a blog post I wrote about the paper: http://phylogenomics.blogspot.com/2013/10/who-are-microbes-in-your-neighborhood.html)


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    1. On 2013 Nov 01, Allison Stelling commented:

      The FTIR ATR instrument highlighted in the infrared section of this interesting overview was recently used in a study on patients with brain tumors, normal mice, and tissue cell lines by the same authors (and me): Stelling AL, 2013.


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    1. On 2015 Jul 27, Simon Young commented:

      While the aims of this article are good it has some problems: 1. The Abstract states “Because serotonin levels in the brain are dependent on the availability of the food-derived precursor tryptophan, foods such as chicken, soyabeans, cereals, tuna, nuts and bananas may serve as an alternative to improve mood and cognition”. However, as the authors state correctly in the Discussion “contrary to popular belief, most common foods high in Trp do not increase the plasma TRP:LNAA ratio enough to exert any positive effects on mood/cognition, because they also contain large amounts of other LNAA.” Ingestion of chicken, soyabeans, cereals, tuna and nuts would certainly not, as suggested in the Abstract, improve mood and cognition due to increased brain serotonin synthesis, as they would not increase brain synthesis. Why bananas are included in the list is not clear. Bananas contain high serotonin levels Feldman JM, 1985, but as mentioned in the article serotonin in food does not cross the blood-brain barrier. Apparently the high level of serotonin in bananas has resulted in the popular belief that bananas must contain high tryptophan levels. A search in Google using the key words banana and tryptophan finds numerous sites stating that bananas have high levels of serotonin. However, the United States Department of Agriculture Nutrient Database http://ndb.nal.usda.gov/ndb/foods gives the tryptophan content of bananas as 9mg per 100g, a very low level that would contribute a negligible fraction of the normal daily intake of tryptophan even if several bananas were eaten. 2. Another problem with the article is that the authors ignore that fact that food may act as a cognitive enhancer through mechanisms other than alterations in tryptophan and serotonin. The acute improvement in memory after a meal is well known and is, in whole or in part, associated with an increase in blood glucose, which may improve cognition through an increase in acetylcholine, but not serotonin Smith MA, 2011. All macronutrients may have beneficial effects on cognition as protein, carbohydrate and fat meals all improve performance on different cognitive tests in humans Kaplan RJ, 2001. Thus, for example, the enhancement of memory due to a high carbohydrate diet mentioned in relation to citation 111 in the article may have nothing to do with changes in brain serotonin synthesis. 3. Hulsken et al discuss the effect of tryptophan supplementation using alpha-lactalbumin, a protein with high levels of tryptophan, and egg protein hydrolysate. They also mention some studies using pure tryptophan, but omit mention of many articles in which mood and/or cognition were measured after administration of pure tryptophan. The first such study was published more than 50 years ago SMITH B, 1962. Many of the missing studies on healthy participants are cited in a recent review Silber BY, 2010. Numerous studies in which tryptophan was given to vulnerable subjects were not cited by Hulsken et al. A Cochrane Database Systematic Review concluded that the available evidence suggests that tryptophan is better than placebo at alleviating depression Shaw K, 2002. Tryptophan has also been used in other conditions. For example, while the article mentions the beneficial effects of a high carbohydrate diet and alpha-lactalbumin on premenstrual mood it does not mention a clinical trial in which tryptophan (6g per day) was better than placebo in treating premenstrual dysphoria Steinberg S, 1999. Given the high dose of tryptophan given, studies such as this clinical trial need to be taken into account when assessing the authors’ suggestion that “Unphysiological high increases in brain Trp lead to negative effects on mood in both healthy and vulnerable subjects”.


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    1. On 2014 Jan 22, Markus Meissner commented:

      Regulation of actin cytoskeleton networks is fundamental for cell migration. These networks can power the protrusion of the cell plasma membrane, termed lamellipodia, for movement. Actin-related proteins 2 and 3 (Arp2/3) form a complex which can nucleate or form branching of actin filaments. There has been a number of nucleating promoting factors identified for the Arp2/3 complex in different cellular locations. However, there is less evidence of inhibitory factors for the Arp2/3 complex. To date the only inhibitory factors for Arp2/3 identified are in endocytic pits and endosomes and until recently it was an unknown whether a protein could inhibit Arp2/3 at the lamellipodia.<br> This study is the first to present evidence of an inhibitory protein for the Arp2/3 complex in lamellipodia protrusion which counteracts the WAVE complex in actin polymerisation. The authors demonstrate with convincing experiments that a novel protein, termed Arpin, can inhibit the Arp2/3 complex in vitro. Using a range of different model systems they validate that Arpin controls cell migration and ‘steering’ and hence appears to be evolutionary conserved.. In both, mammalian cells and amoeba, the Arpin knockout causes the cells to cover an extensive territory owing to the inability of the cells to slow down and change trajectories. Moreover, when Arpin is injected into fish keratocytes, they observed a marked alteration in cell movements.<br> Overall, the paper is very interesting and convincingly shows that Arpin is a conserved inhibitor of Arp2/3. Despite the amount of data, demonstrating a highly complex interaction of Arp2/3, Wave and Arp, the authors present a rather simplified model that will certainly increase in complexity over time.

      Review by Jamie Whitelaw on behalf of the Glagow Toxoplasma journal club (Allison Jackson, Clare Harding, Elena Jimenez-Ruis, Eleanor Wong, Nicole Andenmatten, Saskia Egarter, Fernanda LaTorre Barragan, Robyn Kent, Johannes Stortz, Gurman Pall, Lilach Sheiner, Gary Ward and Markus Meissner).


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    1. On 2013 Nov 08, Tom Kindlon commented:

      I posted two replies on the BMJ site.

      The first was a short one that was short enough for them to include in the print edition, "Author's response: Criticisms of the PACE Trial were justified" (which can be read by anyone at: http://www.bmj.com/content/347/bmj.f5963/rr/667107).

      When it was clear that was not going to be published, I wrote a longer reply: "PACE Trial: Simply giving a reason why an outcome measure was changed is not necessarily sufficient" (which can be read by anyone at: http://www.bmj.com/content/347/bmj.f5963/rr/670755).


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    1. On 2016 Aug 23, Ben Goldacre commented:

      This trial has the wrong trial registry ID associated with it on PubMed: both in the XML on PubMed, and in the originating journal article. The ID given is NCT012073190. We believe the correct ID, which we have found by hand searching, is NCT01307319.

      This comment is being posted as part of the OpenTrials.net project<sup>[1]</sup> , an open database threading together all publicly accessible documents and data on each trial, globally. In the course of creating the database, and matching documents and data sources about trials from different locations, we have identified various anomalies in datasets such as PubMed, and in published papers. Alongside documenting the prevalence of problems, we are also attempting to correct these errors and anomalies wherever possible, by feeding back to the originators. We have corrected this data in the OpenTrials.net database; we hope that this trial’s text and metadata can also be corrected at source, in PubMed and in the accompanying paper.

      Many thanks,

      Jessica Fleminger, Ben Goldacre*

      [1] Goldacre, B., Gray, J., 2016. OpenTrials: towards a collaborative open database of all available information on all clinical trials. Trials 17. doi:10.1186/s13063-016-1290-8 PMID: 27056367

      * Dr Ben Goldacre BA MA MSc MBBS MRCPsych<br> Senior Clinical Research Fellow<br> ben.goldacre@phc.ox.ac.uk<br> www.ebmDataLab.net<br> Centre for Evidence Based Medicine<br> Department of Primary Care Health Sciences<br> University of Oxford<br> Radcliffe Observatory Quarter<br> Woodstock Road<br> Oxford OX2 6GG


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    1. On 2016 Mar 01, Peishun Shou commented:

      A focus on the role of osteopontin (OPN) in MSC differentiation. http://onlinelibrary.wiley.com/doi/10.1002/stem.1567/full

      Recently reviewed in a Cell Death & Differentiation paper entitled "Fate decision of MSCs" http://dx.doi.org/10.1038/cdd.2015.168


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    1. On 2013 Oct 24, Rebecca Balter commented:

      we read this article for our center's journal club. Truly impressive paper, a rare treat to see such good behavioral pharmacology in Nature.

      Considering that KYNA acts on the cannabinoid system through modulation of nicotinic ACh receptor activity I wonder how Ro 61-8048 would alter responses to tobacco/nicotine.


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    1. On 2013 Oct 24, Farris Timimi commented:

      Although hampered, as many behavioral studies focused on social networking, by a lack of granularity or the compliment of attitudinal data, this is a fascinating observational examination of demographic behavior correlate with social comments. Realistically, I suspect that this may well serve as a model for other health-care social media data scraping assays, i.e., adverse drug reactions, etc.


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    1. On 2015 Dec 21, Amy Baxter commented:

      The authors use the same methodology to evaluate their free-flow collection device versus prolonged Buzzy application as they did previously, using their free-flow device versus a standard tourniquet at varying times from 30 seconds to 180s. https://www.ncbi.nlm.nih.gov/pubmed/21414180 They found similar 2.6-23.8% differences in RBC, HgB, HCT, Eos and Basos when leaving a tourniquet on 2 minutes, as they did with Buzzy in this study which found 2.0-2.2% for RBC, HgB, and HCT only. As the article does not reference the previous work by the authors showing the same changes due to tourniquet application, an invited editorial comment is now linked. Disclosure: I invented and researched Buzzy. The Buzzy device is used for 120s in this study, which is off-label. We do not recommend any prolonged application of the tourniquet/Buzzy device.


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    1. On 2015 Apr 07, Sandro Mandolesi commented:

      Reflections on the Canadian study by Traboulsee et al. Prevalence of extracranial venous narrowing on catheter venography in people with multiple sclerosis, their siblings, and unrelated healthy controls: a blinded, case-control study

      http://www.pagepressjournals.org/index.php/vl/article/view/vl.2015.5100


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    2. On 2014 Dec 27, Paolo Zamboni commented:

      Dear Colleagues,the rate of stenosis in angiography is calculated by comparing the diameter of the stricture with that of the segment immediately preceding it. In this article it has been proposed a novel method which compares, along the entire anatomical length of the internal jugular vein, the widest with the narrowest point.However,the jugular in normal cases is characterized by a big variability in size, with >50% variation of the diameter by comparing the bulb with any other point of the vein. This is the reason because the proposed methodology was unable to separate healthy controls from MS cases. If someone should be interested in the assessment of primary venous obstruction please click the link below http://www.pagepressjournals.org/index.php/vl/article/view/vl.2014.4195


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    1. On 2014 Dec 27, Paolo Zamboni commented:

      Dear Colleagues,the rate of stenosis in angiography is calculated by comparing the diameter of the stricture with that of the segment immediately preceding it. In the article herein commented, it has been proposed a novel method which compares, along the entire anatomical length of the internal jugular vein, the widest with the narrowest point.However,the jugular in normal cases is characterized by a big variability in size, with >50% variation of the diameter by comparing the bulb with any other point of the vein. This is the reason because the proposed methodology was unable to separate healthy controls from MS cases. If someone should be interested in the assessment of primary venous obstruction please click the link below http://www.pagepressjournals.org/index.php/vl/article/view/vl.2014.4195


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    1. On 2013 Dec 09, John Cannell commented:

      The authors report that immune system dysregulation is common in depression and autism spectrum disorder (ASD). The question is why does this immune dysregulation occur and, in the case of autism, what has caused such dysregulation to skyrocket in recent decades?

      Vitamin D deficiency produces very similar immune dysregulation to what the authors reported.

      Prietl B, 2013

      Kamen DL, 2010

      Yang CY, 2013

      Baeke F, 2010

      Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

      Gong ZL, 2014

      Meguid NA, 2010

      Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely affect brain development.

      DeLuca GC, 2013

      Eyles DW, 2013

      Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

      Cannell JJ, 2010

      Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day and few toddlers or pregnant women get any sunshine due to the sun scare. As vitamin D fortified milk consumption and sun exposure has declined, so have toddlers and pregnant women’s vitamin D levels. The dramatic increase in the incidence of ASD occurred during the same time vitamin D levels were falling in toddlers and pregnant women.

      Some autism researchers seem cognizant of the entire body of autism research. For example, a group of well-known European ASD researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into the vitamin D deficiency theory of ASD.

      Kočovská E, 2012

      As the authors point out, immune dysregulation is common in ASD. The question is why now and what is causing it?

      John J Cannell, MD

      Vitamin D Council

      http://www.vitamindcouncil.org


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    1. On 2013 Dec 18, Dorothy V M Bishop commented:

      I'm interested in cerebral lateralization in relation to dyslexia, and I would be grateful if the authors could provide additional data that would allow me to relate their work to other findings in the literature. Where atypical lateralization is seen, this could either reflect a reduction in the strength of left-sided lateralization, or inclusion of a higher than usual proportion of individuals with right-sided lateralization (see Illingworth S, Bishop DVM: Atypical cerebral lateralisation in adults with compensated developmental dyslexia demonstrated using functional transcranial Doppler ultrasound. Brain Lang 2009, 111:61-65). It would be good to know how these data compare, and whether the effect size is comparable to previous studies. Could the authors please provide a table showing the laterality indices from vWFA and IFG for all individual subjects in the dyslexic and control groups? I I should add that I think more caution is needed in interpreting the correlational data reported here, given the sample sizes of 15 and 16. For instance, the correlations shown in Figure 4B have overlapping confidence intervals. With N of 15, a correlation of -.12 has 95% CI from -.6 to .42; a correlation of -.66 has 95% CI from -.88 to -.22. Thus the differences between these correlations could be due to sampling error.


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    1. On 2013 Dec 06, Rafael Delgado-Ruíz commented:

      The long term evaluation of retrieved implants, provide us with the best evidence of the behavior under real daily conditions, so I am really grateful with analysis similar to the presented in this work.


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    1. On 2013 Dec 12, Adam Eyre-Walker commented:

      I thank Dr. Cherry for another set of insightful comments.

      He points out we may have overestimated the stochasticity associated with the accumulation of citations. He correctly notes that if assessors tend to err erroneously in the same direction in their judgments, then the errors associated with their assessments will be correlated. One might imagine, for example, that assessors tend to over-rate papers in high impact factor journals, by particular authors, or from a particular institution. Such correlated errors will mean that the correlation between assessor scores underestimates the error associated with making an assessment and this will in turn imply that the stochasticity associated with the accumulation of citations is less than we have estimated. However, if the error associated the accumulation of citations is also correlated to the error associated with the assessment then the stochasticity associated with the accumulation of citations may have been underestimated. The errors associated with assessments and citations might be correlated given that citations depend, to some extent, on post-publication subjective assessment.

      A likely bias, and hence a source of correlated erros, is a tendency for assessors to overestimate papers in high-ranking journals. As we showed, the partial correlation between assessor scores and between assessor scores and the number of citations, controlling for impact factor, are very weak (r<0.20). This suggests that within journals, subjective estimates of merit and the accumulation of citations are dominated by error. The weaknesses of these correlations might be because there is little variation in merit within journals, with most of the variance in merit being between journals. However, it seems unlikely that journals are a perfect arbiter of merit because their judgments are based on subjective assessment, which we have demonstrated to be poor. Furthermore, as noted above, it is quite likely that the errors associated with assessments are correlated to errors associated with the accumulation of citations. The system is clearly complex and it may prove to be very difficult to accurately estimate the variance associated with the accumulation of citations.

      We argued in our original paper that the impact factor might be the best of the methods currently available for assessing merit, though we emphasized that it was likely to be very error prone. We argued that it might be a reasonable measure, because the IF is a form of pre-publication review – in accepting a paper for a particular journal, the scientific community has decided that the paper of sufficient merit to be published where it is accepted. This decision is likely to be the consensus of several individuals, with some individuals, such as editors, having a greater say than others. Dr. Cherry points out that using the IF as a measure of merit might potentially be matched by combining the post-publication assessments of several individuals. He shows that if we ignore any potential biases (i.e. correlated errors), for example assessors being influenced by the IF, then the estimated correlation between assessor score and merit is 0.60, and the correlation between the IF and merit is expected to be 0.80. Dr. Cherry arrives at these estimates in the following manner (he elaborated upon this in a subsequent email). If the errors are uncorrelated then the correlation between two variables, which are correlated to X, is expected to be the product of their correlation to X; e.g. if the correlation between variable 1 and X is r1 and the correlation between variable 2 and X is r2 then the correlation between 1 and 2 is expected to be r1*r2. The correlation between assessor scores in the Wellcome Trust data is 0.36, which implies the correlation between a single assessor score and merit is SQRT(0.36) = 0.60. The square of this is the proportion of the variance in score explained by merit, which is equivalent to our equation 1 (the square of the correlation between a single assessor and merit is the expected correlation between two assessors). From this equation we can estimate the ratio of the error to merit variance, which is 1.78 from the Wellcome Trust data. If we have n independent assessors we expect this ratio to be reduced by a factor n; hence the expected correlation between the mean score from n assessors and merit is 0.60 (n=1), 0.73 (n=2) and 0.80 (n=3). The inferred correlation between the IF and merit is 0.80; this comes from noting that the correlation between assessor score and IF is expected to be the product of the correlation between assessor score and merit, and the IF and merit; given that the correlation between assessor score and merit has been estimated to be 0.60, and the observed correlation between assessor score and IF is 0.48, we estimate that the correlation between IF and merit is 0.80. Hence we would need 3 independent assessors to match the correlation between IF and merit. For comparison, the correlation between the number of citations and merit is inferred to be 0.69 if we use the correlation between IF and the number of citations, and 0.63 if we use the correlation between assessor score and the number of citations to make the estimate. Hence the IF is the best measure of merit, and would only be rivaled by subjective assessment if we engage 3 independent reviewers; the number of citations is estimated to be better than a single reviewer, but worse than two reviewers. However, I would emphasise that these estimates all assume that errors are uncorrelated.

      Finally, Dr. Cherry points out a problem with using the correlation coefficient on a bounded scale. The correlation coefficient is typically scale independent – i.e. if you add, subtract, multiply or divide one of the variables by some value then the correlation coefficient remains unchanged. However, this is only true if the scale is unbounded; if there is a maximum or minimum value then the correlation may be poor, even if the reviewers agree on the ranking of the papers. For example, if one assessor tends to rate harshly and another generously then the correlation may be poor because most of the harsh reviewer’s scores are the lowest mark and most of the liberal reviewer’s scores are the highest mark. The solution to this problem is to offer an essentially unbounded scale. However, as we pointed out in our original article, the tendency for reviewers to differ in their average mark could potentially have serious consequences in an assessment exercise, particularly if individuals or universities are assessed by a limited number of individuals.


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    2. On 2013 Nov 11, Joshua L Cherry commented:

      I thank Dr. Eyre-Walker for a wonderful response that should serve as a model for the rest of us.

      I have some additional comments about the paper's interpretation of the reported correlation coefficients. I would question the conclusion that journal impact factor (IF) is the "least bad" measure of article merit.

      1) The authors conclude that citation is a highly stochastic process and that citation number is a poor measure of article merit. This interpretation rests on assumptions that preclude the possibility that citation information contains any unique wisdom. In technical terms, the problematic assumption is that the errors made by different assessors in judging merit are uncorrelated, so that citation number can at best provide a less noisy estimate of what assessors estimate. It seems quite reasonable that, contrary to this assumption, different assessors tend to systematically err in the same ways, and that citation number is comparatively free of such errors.

      Suppose that it had turned out that assessor scores correlated perfectly with each other, but still only moderately well with citation number. The authors' reasoning would compel us to believe that the assessors were correct, and that the low correlation with citation number was entirely due to stochasticity of citation. This is not, however, the only reasonable interpretation. The assessors might simply agree in over-rating the merit of some papers and under-rating that others, while the citation number came closer to the truth.

      This point applies even when, as in reality, between-assessor correlation is far from perfect. Imagine, to take an extreme case, that citation number is a flawless measure of merit. Suppose further that different assessors tend to err in the same way in judging merit, but also disagree with each other to some extent. What, then, would the correlation coefficients look like? They might have exactly the values that were observed in this study. Thus, there seems to be no basis for dismissing citation number as a measure of merit.

      2) It is enlightening, nonetheless, to consider performance of the metrics under the assumption that assessor errors are uncorrelated. Under this assumption, the average of scores given by a large number of assessors approaches perfect correlation with merit. It is true that IF correlates better with that average (equivalently, with merit) than does a single assessor score (a correlation of ~0.8 as compared to ~0.6 for the WT data). However, we can also calculate that, for the WT data, the mean of two assessor scores would do about as well as IF, and the mean of three or more assessor scores would be superior to IF as a measure of merit.

      3) Perhaps the most important observation in the paper is the weakness of the correlation between scores given to the same paper by different post-publication assessors. This is at the heart of the conclusion that assessors do a poor job of assessing merit and that their ratings should not be used.

      One possible source of assessor disagreement is that some assessors tend to rate all papers more highly than others do. If a generous assessor is paired with a harsh assessor, the two will often rate a paper differently even if they agree on its merit relative to that of other papers. In principle, even if all assessors agreed perfectly on their ranking of all papers, a low between-assessor correlation could result. The correlation would be high if we considered just two assessors and maintained assessor identity in the calculations. However, the data analyzed in the paper involved many assessors, and assessor order was deliberately randomized, so the correlation would be diminished if assessors effectively use different scales.

      This type of disagreement would not be troubling with respect to assessors' ability to discern merit. It would present a practical problem, but this problem would be amenable to correction, which might be extremely valuable. One can imagine schemes of assessor assignment and score analysis that largely remove this effect. This might yield much improved estimates of merit that, with just two assessors per paper, greatly outperform the suggested use of IF. Even with a single assessor per paper, the position of a paper in the assessor's ranking might be superior to IF as a measure of merit.


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    3. On 2013 Nov 01, Adam Eyre-Walker commented:

      We thank the author for his insightful comments. Unfortunately Dr. Cherry is correct (see below); controlling for merit, using a noisy measure such as the number of citations, will leave a correlation between assessor score and the impact factor whether or not there is a tendency for assessors to overrate papers in high impact journals. Since we did not previously appreciate this problem, and it wasn’t caught by a number of referees that looked at our paper prior to publication, it might be worth elaborating why this is the case. Imagine that we consider all papers that have received 100 citations; we assumed in our analysis that these represented papers of equal merit. However, because the number of citations is a noisy measure of merit, some of these papers will be papers of poor merit that by chance got more than their fair share of citations, and others will be papers of good merit than received less than their fair share of citations. As a consequence there is variation in merit amongst papers that received 100 citations. Hence, if assessors tend to rate better papers more highly and better journals publish better papers, then there will be a correlation between assessor score and the impact factor even when the number of citations is controlled for. Furthermore, the decrease in the correlation between assessor scores, and between assessor score and the number of citations, when the impact factor is controlled for, may simply reflect the decrease in the variance in merit within journals.

      So as Dr. Cherry concludes, there is no evidence from our analysis that assessors overrate science in high impact journals. This tendency may exist, but there is simply no evidence from our analysis. However, the majority of our conclusions are unaffected by this insight; there is a rather poor correlation between assessor scores and between assessor score and the number of citations, whether or not the impact factor is controlled for. These correlations demonstrate that either assessors do not agree on what constitutes merit or they are not good at identifying merit, and that the accumulation of citations is highly stochastic.

      Finally, we note the correlation between assessor score and impact factor is stronger than either the correlation between assessor scores, and the correlation between assessor scores and the number of citations. These correlations therefore suggest that the impact factor is the best measure of merit if there is no tendency for assessors to be influenced by the journal in which a paper is published.

      There might be two approaches to determining whether assessors overrate papers in high-ranking journals. Developing a mathematical model of the relationship between assessor score, the number of citations and the impact factor of a journal – so far our attempts to do this have failed. Or to independently assess a range of papers before and after publication.


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    4. On 2013 Oct 29, Joshua L Cherry commented:

      This article claims to have demonstrated that post-publication assessors are strongly influenced by their knowledge of the journal in which a paper was published. Specifically, it is claimed that they "tend to over-rate papers published in journals with high impact factors". Furthermore, it is suggested that "scientists have little ability to judge...the intrinsic merit of a paper".

      These conclusions, which are based on coefficients of correlation between article metrics, do not follow from the data. The inferences involved are akin to taking correlation as proof of causation.

      The authors first observe that journal impact factor (IF) correlates with assessor score even when citation number is controlled for. They interpret this as evidence that (assessor knowledge of) IF directly influences assessor score. The observed partial correlation is in fact expected for imperfect measures of a latent variable even in the absence of causal effects among the measures. If, for example, all three variables (assessor score, IF, and citation number) are noisy measures of article merit with uncorrelated noise, any two are necessarily correlated with each other even when the third is controlled for. Even if we took citation number as a perfect measure of merit (which we have no reason to do), the correlations would show only that assessor score and IF tend to err in the same way, not that one of them influences the other. Note that controlling for citation number does not eliminate the correlation between the scores given by two assessors, but it would be erroneous to conclude that one affected the other. The authors even tell us that citation number is "a very poor measure of the underlying merit of the science, because the accumulation of citations is highly stochastic". Controlling for such a variable could not possibly eliminate the correlation between assessor score and IF, so the authors' reasoning would suggest a strong assessor bias even if no such bias existed.

      The authors also point out that controlling for IF significantly reduces the correlation between scores given by different assessors. They conclude that much of the correlation between assessors is due to their both being influenced by their knowledge of IF, rather than reflecting assessment based directly on intrinsic merit. This inference, too, is unfounded. Controlling for one of three intercorrelated variables can reduce the correlation between the other two under a range of conditions that do not involve causal connections. In fact, when two positively correlated variables positively correlate to the same extent with a third, as expected for assessor scores (since ordering of assessors is arbitrary), controlling for the third variable necessarily decreases the correlation between the first two. Thus, the observed reduction in correlation will occur whenever assessor scores correlate positively with IF, which certainly does not require the posited causal effect.

      This is not to say that the claimed effect can be disproven or is implausible, but only that it has not been demonstrated. The observed correlation structure is entirely consistent with the complete absence of such an effect, and in the presence of such an effect the authors' reasoning would likely overestimate it drastically.


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    1. On 2014 Apr 16, Eric Uhlmann commented:

      The further data collection and analysis reported by Silberzahn, Simonsohn, & Uhlmann (in press, Psychological Science) overturn the conclusions of our original paper. Using a matched-names analysis, which compares each noble-meaning name with the 50 most similarly frequent names, we find no differences between noble names and other names in terms of the attainment of managerial roles. Therefore at present no significant relationship between having a noble-meaning name and career outcomes can be confirmed.

      For more details, here is a link to the full text and supplementary materials for the Silberzahn, Simonsohn, & Uhlmann (in press) collaborative commentary:

      http://www.socialjudgments.com/docs/Silberzahn_Simonsohn_Uhlmann_2014_Collaborative_Commentary_and_Online_Supplement.pdf

      The dataset for the new paper is publicly posted at:

      http://figshare.com/articles/Dataset_for_SSU_2014/988763

      Reference:

      Silberzahn, R., Simonsohn, U., & Uhlmann, E.L. (in press). Matched names analysis reveals no evidence of name meaning effects: A collaborative commentary on Silberzahn and Uhlmann (2013). Psychological Science.

      -- Raphael Silberzahn and Eric Luis Uhlmann


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    1. On 2014 Feb 10, Andrea Messori commented:

      We have carried out an equivalence test based on the data published by Signorovitch and co-workers. The end-point was major molecular response at 1 year; the equivalence margins for this end point were set at ±15%. Figure 1 (available at http://www.osservatorioinnovazione.net/papers/bld2014_figure1.pdf) shows the results of this equivalence test. Coauthors: Valeria Fadda, Dario Maratea, Sabrina Trippoli.


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    1. On 2013 Oct 31, John Cannell commented:

      I wonder if the authors are aware that the genes for the antioxidants superoxide dismutase and thioredoxin reductase are directly up-regulated by the secosteroid 1,25 di-hydroxy vitamin D3 (calcitriol). I believe both genes also harbor a vitamin D response element.

      Peehl DM, Shinghal R, Nonn L, Seto E, Krishnan AV, Brooks JD, Feldman D. Molecular activity of 1,25‐dihydroxyvitamin D3 in primary cultures of human prostatic epithelial cells revealed by cDNA microarray analysis. J. Steroid Biochem Mol. Biol 2004;92:131–141. PMID:15555907>

      Calcitriol also directly up-regulates glutathione reductase and increases glutathione levels.

      Jain SK, et alo. Vitamin D upregulates glutamate cysteine ligase and glutathione reductase, and GSH formation, and decreases ROS and MCP-1 and IL-8 secretion in high-glucose exposed U937 monocytes. Biochem Biophys Res Commun. 2013 Jul 19;437(1):7-11. doi: 10.1016/j.bbrc.2013.06.004. Jain SK, 2013

      Also, supplemental vitamin D significantly reduces oxidative stress in humans.

      Nikooyeh B, et al. Daily intake of vitamin D- or calcium-vitamin D-fortified Persian yogurt drink (doogh) attenuates diabetes-induced oxidative stress: evidence for antioxidative properties of vitamin D.J Hum Nutr Diet. 2013 Jul 5. doi: 10.1111/jhn.12142. Nikooyeh B, 2014

      Asemi Z, et al. Vitamin D supplementation affects serum high-sensitivity C-reactive protein, insulin resistance, and biomarkers of oxidative stress in pregnant women. J Nutr. 2013 Sep;143(9):1432-8. doi: 10.3945/jn.113.177550. Asemi Z, 2013

      Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

      Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

      Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

      Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

      Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

      DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

      Eyles DW, Burne TH, McGrath JJ. Vitamin D, effects on brain development, adult brain function and the links between low levels of vitamin D and neuropsychiatric disease. Front Neuroendocrinol. 2013 Jan;34(1):47-64. doi: 10.1016/j.yfrne.2012.07.001. Epub 2012 Jul 11. Review. Eyles DW, 2013

      Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

      Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

      Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day and few toddle


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    1. On 2014 Oct 28, Kaccie Li commented:

      The treatment of the amplitude component of the pupil function was not provided in this paper, so the results and conclusions may very well be incorrect. I also don't believe any optical surface profiles capable of producing such phase characteristics currently exist. The authors claim that the major impact of this work will be in vision which involve chromatic, monochromatic and off-axis aberrations none of which were mentioned in the manuscript.


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    1. On 2014 Jan 29, Peter Beerli commented:

      Inheritance patterns in diploid and triploid water frog hybrids (Pelophylax esculentus) – a comment on Pruvost et al.

      Jörg Plötner<sup>1,</sup> Gaston-Denis Guex<sup>2,</sup> Peter Beerli<sup>3,</sup> and Thomas Uzzell<sup>4</sup>

      (Addresses at the end)

      Pruvost et al. (2013) described the gamete production and ploidy of water frogs from five populations in Germany, Poland, and Slovakia. Two populations were composed of P. lessonae (genotype LL), P. ridibundus (RR) and their hybridogenetic hybrid P. esculentus (LR, LLR, RRL) whereas three populations consisted of only diploid LR individuals and triploids (LLR, RRL). Based on crossing experiments involving 64 P. esculentus and the analysis of microsatellites, the authors found that diploid males (genotype LR) produced haploid gametes with a ridibundus (R) genome whereas LR females usually produced diploid eggs containing both parental genomes (LR gametes). Moreover, most of the triploid individuals transmitted to their gametes the genome that was present in two copies; i.e. the L genome was inherited from LLR triploids and the R genome from RRL triploids. Their findings confirm the principal inheritance patterns of P. esculentus, which have been known for more than three decades (e.g. Uzzell et al. 1975; Günther et al. 1979; Uzzell et al. 1980; Vinogradov et al. 1990). Transmission of two L genomes by LLR males, which was observed in the Slovakian population Šajdíkove (Mikulíček and Kotlík 2001, Pruvost et al. 2013), can be considered a rare exception. It is not certain, however, that all LLR males of this population produce only LL sperm (nine of 14 LLR males transmitted only LL gametes, but five such males produced no progeny) nor is it certain that LR males in this population transmit only the R genome (only eight F1 individuals from two crosses involving a single male could be genotyped). That no P. lessonae individuals were found in a sample of 169 individuals from this population (Mikulíček and Kotlík 2001; Provost et al. 2013) suggests that the LR individuals in this population originate from LR x LLR and/or LR x LR crosses; as mentioned by Pruvost et al., both LLR males and occasionally LR males and females are able to produce L gametes (Binkert et al. 1982; Günther 1983). Only a few crosses in which either the diploid or the triploid parent produced L gametes would be sufficient for the persistence of such all-hybrid populations; in a relatively large Polish esculentus population comprising 300-400 females, for example, less than 1% of the eggs laid transformed to tadpoles (Berger 1988). Thus, even a high number of artificial crossing experiments does not guarantee that rare inheritance patterns, which may be critical to population persistence, are discovered. Based on the 10 genetic markers that they used, Pruvost et al. suggested that the two L genomes transmitted by LLR males from Šajdíkove are identical. Identity of markers does not, however, necessarily mean identity of genomes. Mikulíček and Kotlík (2001) investigated one LLR male from this population electrophoretically and found two distinct lessonae-specific alleles at the ldh-1 locus, which is evidence that the L genomes of this male differed from each other. On the other hand, it is not certain that in all cases “triploid hybrids recombine the genome they have in double dose” (Pruvost et al. 2013), although evidence for recombination between the double genomes in triploids comes from enzyme loci (Günther et al. 1979) and microsatellites (Christiansen and Reyer 2009). Because the few polymorphic markers available until recently do not allow distinguishing between the double genomes in many triploids, it cannot be said whether recombination between the two L or the two R genomes has taken place in such individuals. Biases in sex ratio of the progeny from crosses in which triploid individuals were involved (Günther et al. 1979; Berger and Günther 1988; 1991-1992), putative recombination between the L and the R genome in triploids (e.g. Plötner and Klinkhardt 1992; Christiansen et al. 2005), the occasional production of LL and LR eggs by some triploid (LLR) females (Christiansen et al. 2005; Christiansen 2009), the rare production of R or LL sperm by LLR males (Brychta and Tunner 1994; Christiansen et al. 2005), incomplete elimination of the R genome in some spermatogonia (Vinogradov et al. 1990), and chromosomal aberrations in meiosis of triploid males (Günther 1975) reflect the huge complexity of inheritance in triploid P. esculentus. P. esculentus may represent a useful model for hybrid speciation. It is not surprising, however, that hybrid forms in early stages of speciation exhibit a plethora of genetic disturbances and irregularities (Dobzhansky-Muller incompatibilities; e.g. reviewed by Landry et al. 2007; Maheshwari and Barbasch 2011) especially in gametogenesis and embryonic development expressed as fertility disorders in adults (Günther 1973), abnormal cleavage of eggs, malformations in larvae, and high mortality during larval development (e. g. Christiansen et al. 2005; reviewed by Ogielska 2009). The observed differences in the inheritance patterns of triploid water frog hybrids may thus be interpreted as a simple result of selection-mediated interactions between specific genomic features and spatial-environmental conditions of different evolutionary lineages representing a monophyletic group; at present there is no character-based evidence that triploid frogs are of polyphyletic origin as proposed by Pruvost et al. More genomic data are required to answer this and many other questions concerning the genetics and evolutionary history of western Palearctic water frogs.

      List of references can be downloaded from here

      http://www.peterbeerli.com/papers/misc/Reply_Pruvost_et_al_2013.pdf

      1 Museum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Invalidenstraße 43, 10115 Berlin. Germany. Email: joerg.ploetner@mfn-berlin.de

      2 Field Station Dätwil, 8452 Adlikon, Hauptstrasse 2, Switzerland

      3 Florida State University, Department of Scientific Computing, Tallahassee, FL 32306-4120, USA

      4 Academy of Natural Sciences, Laboratory for Molecular Systematics and Ecology, 1900 B. F. Parkway, PA 19103 Philadelphia, USA


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    1. On 2013 Oct 26, Tim D. Smith commented:

      This work was featured in a Research Highlight In Brief in Nature Reviews Immunology: Macrophages: the shape of things to come.


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    1. On 2016 Aug 23, Ben Goldacre commented:

      This trial has the wrong trial registry ID associated with it on PubMed: both in the XML on PubMed, and in the originating journal article. The ID given is NCT0131821. We believe the correct ID, which we have found by hand searching, is NCT01318213.

      This comment is being posted as part of the OpenTrials.net project<sup>[1]</sup> , an open database threading together all publicly accessible documents and data on each trial, globally. In the course of creating the database, and matching documents and data sources about trials from different locations, we have identified various anomalies in datasets such as PubMed, and in published papers. Alongside documenting the prevalence of problems, we are also attempting to correct these errors and anomalies wherever possible, by feeding back to the originators. We have corrected this data in the OpenTrials.net database; we hope that this trial’s text and metadata can also be corrected at source, in PubMed and in the accompanying paper.

      Many thanks,

      Jessica Fleminger, Ben Goldacre*

      [1] Goldacre, B., Gray, J., 2016. OpenTrials: towards a collaborative open database of all available information on all clinical trials. Trials 17. doi:10.1186/s13063-016-1290-8 PMID: 27056367

      * Dr Ben Goldacre BA MA MSc MBBS MRCPsych<br> Senior Clinical Research Fellow<br> ben.goldacre@phc.ox.ac.uk<br> www.ebmDataLab.net<br> Centre for Evidence Based Medicine<br> Department of Primary Care Health Sciences<br> University of Oxford<br> Radcliffe Observatory Quarter<br> Woodstock Road<br> Oxford OX2 6GG


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    1. On 2014 Jul 30, Jim Woodgett commented:

      From the data published, this compound was not tested against GSK-3alpha. Given the virtual identity in the active (ATP binding) site of these two isoforms, it is extremely probable that 6-(4-Pyridyl)pyrimidin-4(3H)-ones also inhibit GSK-3alpha (and are not specific for GSK-3beta). Notably, this molecule appears to pass through the blood brain barrier unlike many other inhibitors to this kinase providing avenues for targeting this kinase in Alzheimers and other neuropsychiatric conditions.


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    1. On 2016 Jul 20, Daniel Schwartz commented:

      Interestingly, this trial is using a mobile app (Calculate by QxMD) to facilitate navigation through STARRT-AKI enrolment and exclusion criteria.

      https://www.qxmd.com/calculate/calculator_362/starrt-aki-enrollment-criteria

      Conflict of interest: Medical Director, QxMD


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    1. On 2016 Jun 23, Jaime A. Teixeira da Silva commented:

      Teixeira da Silva, J.A., Al-Khatib, A. (2016) Questioning the ethics of John Bohannon’s hoaxes and stings in the context of science publishing. KOME 4(1): 84-88. http://komejournal.com/files/KOME_TdaSAceil.pdf DOI: 10.17646/KOME.2016.16


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    2. On 2013 Nov 16, George McNamara commented:

      Please read Michael Eisen's column at

      http://www.michaeleisen.org/blog/?p=1439

      thanks.


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    1. On 2014 Feb 21, Serge Ahmed commented:

      This remarkable study suggests, perhaps for the first time, that the orbitofrontal cortex (OFC) imposes “its” values to other value-coding brain regions (e.g., dorsal striatum) to guide choice and preference. Under normal circumstances, the values of hierarchically lower brain regions are in line with those of the OFC and no conflict arises. However, when these values diverge, the OFC would take the lead and impose “its” values to guide behavior, even if they are less accurate or up-to-date than those of hierarchically lower brain regions. A key challenge for future research will be to better understand how and under what circumstances the OFC acquires a set of values that diverges from reality and from that acquired by other brain regions.


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    1. On 2014 Aug 02, Christopher Southan commented:

      For the record, since MeSH did not resolve AR79, the image from http://www.ncbi.nlm.nih.gov/pubmed/23872097 maps to https://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=53302375 that incudes a link to https://open.surechem.com/en/document/WO-2011089416-A1/


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    2. On 2014 Jul 30, Jim Woodgett commented:

      The inhibitor used here, AR79, inhibits both GSK-3alpha and GSK-3beta with very similar potency (as do virtually all small molecule GSK-3 inhibitors developed to date). This is clearly shown in Table 1 of cited reference 11 (http://www.ncbi.nlm.nih.gov/pubmed/23872097) where the Ki against GSK-3beta is 3.2 nM vs an IC50 of 5.5nM for GSK-3alpha. Notably, the Astra-Zeneca authors are careful to term AR7 (and its related compounds) GSK-3 inhibitors.


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    1. On 2015 May 17, Gustavo Glusman commented:

      The full text in PMC has the wrong author list and abstract - both from this paper: http://www.ncbi.nlm.nih.gov/pubmed/24878723


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    1. On 2017 Nov 01, Kenneth Witwer commented:

      Thanks for this interesting study. The data link "http://www.ebi.ac.uk/ena/data/view/PRJEB4152" does not appear to be functional. Could an updated link be posted? Thank you.


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    1. On 2017 Mar 04, Jing-Dong J Han commented:

      The CoCiter website was down for a couple of days due to server maintenance. It is now up and running. Sorry about the inconvenience!


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    2. On 2017 Feb 08, Jeff Kiefer commented:

      The resource URL is no longer viable so tool is not available.


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    3. On 2015 Sep 02, Jeff Kiefer commented:

      None


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    1. On 2014 Nov 17, Raphael Levy commented:

      Comments available at my blog, authored by 1) Mathias Brust, Liverpool, 2) Quanmin Guo, Birmingham and, 3) Philip Moriarty, Nottingham.

      A detailed analysis of this article, and more broadly of this body of work is published today in PloS One by Stirling et al; from the abstract: “through a combination of an exhaustive re-analysis of the original data with new experimental measurements of a simple control sample comprising entirely unfunctionalised particles, we conclusively show that all of the STM evidence for striped nanoparticles published to date can instead be explained by a combination of well-known instrumental artefacts, strong observer bias, and/or improper data acquisition/analysis protocols.


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    1. On 2016 Oct 16, Jaime A. Teixeira da Silva commented:

      This paper has been retracted: "BioMed Research International has retracted this article. The article was found to contain images with signs of duplication and manipulation in Figures 1, 3, 4, 5(A), 5(B), 6, 8(b), 9(C), 9(G), 9(I), and 9(J)."


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    1. On 2014 Apr 16, T Eugene Day commented:

      This is a very interesting study that uses DES to examine a generic ED model and assess the impact of discharge strategies on length of stay and readmission rates. Though the described model itself is fairly rudimentary with regard to care processes, it shows reasonable accordance to published throughput data, and I was pleased to see that the authors made a point of including their methods of validation, which is too frequently glossed-over, or omitted, in healthcare-based DES work. The bounds on the real-world values obtained from the literature and their expert panel were very large. However, real world variation in LOS is very large, and using expert panels when necessary is appropriate in validation. Ideally, it would be nice to compare the simulation to prospectively gathered multi-site data, but I recognize that that's a high bar to set.

      Given the general nature of the simulation, the authors make appropriate conclusions with regard to crowding, and readmissions. With regard to the influence of the discharge strategy on individual patient outcomes, it is of course plausible that this is true, but I am reluctant to draw such a conclusion from simulation alone.

      On the whole, an excellent article demonstrating the strength of using DES to glean insight into systemic behavior.


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    1. On 2014 Jan 08, Brett Snodgrass commented:

      Dear Authors,

      Thank you for publishing an excellent report.

      Is it possible that a vessel of Wearn was patent throughout life, but unappreciable due to "sloshing?"

      http://bit.ly/JTWearn

      For additional commentary, please consider https://twitter.com/BrettSnodgrass1/status/413134010991529984

      Comments and suggestions are welcome.

      Thank you kindly.


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    1. On 2016 Jan 16, Arnaud Chiolero MD PhD commented:

      A fantastic review to understand the basics of health care regional variation.


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    1. On 2015 May 07, Tullio Pozzan commented:

      We believe that the discrepancy between the data presented in our paper (Filadi et al. PNAS 2015 Apr 28;112(17):E2174-81. doi: 10.1073/pnas.1504880112. Epub 2015 Apr 13.) and those of Schneeberger et al. (Cell. 2013 Sep 26;155(1):172-87. doi: 10.1016/j.cell.2013.09.003) may be only apparent. In particular, Schneeberger et al. demonstrate (Fig 1 D and E) that in mice rendered obese by high fat diet there is a major reduction in mitochondria/ER contacts in POMC neurons and an early reduction in Mfn2 expression. They then show that mice with a selective KO of Mfn2 in POMC neurons become obese and show, at this stage, a reduction in mitochondria-ER contacts. Given that Schneeberger et al, investigated the reduction in ER-mitochondria close contacts only in 18 week old mice (i.e. when obesity is evident and not after a short high fat diet treatment (4 days), when Mfn2 reduction is already visible, but obesity is not), it is not possible to distinguish whether the change in ER-mitochondria close contacts is a consequence of Mfn2 reduction or of obesity (and/or of the very complex alteration of metabolism occurring in those conditions). In other words, the data presented in the very elegant paper by Schneeberger et al. do not clarify whether the reduction in ER-mitochondria close contacts is a direct consequence of Mfn2-KO in POMC neurons or an indirect effect of different altered pathways that lead to obesity and metabolism alteration. On the contrary, in the experiment by Filadi et al., in cultured MEF cells, acute down-regulation of Mfn2 results in a rapid increase of ER-mitochondria tethering. A similar result, i.e. increase in ER-mitochondria close contacts, has been also observed in a stable Mfn2 ablated cell line (and rescued by Mfn2 re-expression) independently by Filadi et al and by Cosson et al. Thus, in our opinion the role played by Mfn2 in different metabolic pathways leading to obesity is multiple and cell type-specific (see also the paper by Dietrich et al., in the same Cell issue) and not causally linked to its structural function on ER-mitochondria tethering, as actually pointed out by the same Authors suggesting a main role for Mfn2 in POMC neurons as an ER-stress modulating molecule.


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    1. On 2013 Oct 23, Hilda Bastian commented:

      This paper by Jager and Leek (Jager LR, 2014) challenges Ioannidis' conclusion that "most published research papers are false" (Ioannidis JP, 2005). Ioannidis responds to this discussion, challenging the data and analytical approach here: (Ioannidis JP, 2014). The conclusions of this paper (Ioannidis JP, 2005) were also challenged by Goodman and Greenfield in 2007 (and responded to by Ioannidis JP, 2007). (I discuss this debate in a blog post.)


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    2. On 2013 Oct 23, Larry Wasserman commented:

      I agree with Rob that this is an interesting paper. However, it does assume that the p-values are uniform under the null. Hidden biases can compromise this assumption leading to a distribution for the p-value that is skewed towards 0.


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    3. On 2013 Oct 22, Scott D McGinnis commented:

      None


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    4. On 2013 Oct 22, Robert Tibshirani commented:

      A really interesting paper and discussion, that calls into question Ioannidis' 2007 widely cited paper "Why Most Published Research Findings Are False". Definitely worth reading: includes a discussion by D.R. Cox, probably the world's most famous living statistician.


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    1. On 2014 May 06, Swapnil Hiremath commented:

      This article was discussed on April 29th 2014 on the open online nephrology journal club, #NephJC, on twitter. An introductory comment is available here and the pdf transcript of the live chat is archived here. A wrap up post, along with some reactions from the authors, is available at the same link (just scroll down).

      Interested individuals can track and join in the conversation by following @NephJC or #NephJC, or visit the webpage at www.NephJC.com.


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    1. On 2017 Jun 13, David Keller commented:

      The above letter to the editor is freely available at the following link, and is posted here to stimulate discussion, and perhaps elicit answers to questions raised in the study:

      http://www.nejm.org/doi/full/10.1056/NEJMc1309586#SA1?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub=pubmed

      To the Editor:

      Anderson et al. (June 20 issue)[1] describe the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial 2 (INTERACT2), in which patients received alpha-blockers, diuretics, combined alpha- and beta-blockers, calcium-channel blockers, nitrates, hydralazine, and other anti-hypertensive agents. These medications lower blood pressure by means of different mechanisms and therefore have different effects on relevant physiological variables such as vascular smooth-muscle tone, intravascular volume, heart rate, and pulse pressure. For example, the authors indicate that 16.2% of patients in the intensive-treatment group received a calcium-channel blocker “such as nicardipine or nimodipine” versus 8.5% of patients in the standard-treatment group. Nimodipine is known to reduce adverse outcomes associated with arterial vasospasm when administered after subarachnoid hemorrhage.[2] If more of the patients in the intensive-treatment group received nimodipine and benefited from this additional protection, independent of its antihypertensive effect, then this imbalance would tend to inflate the apparent benefit of intensive blood-pressure lowering. How much of the overall benefit seen with intensive treatment was due to lower blood pressure per se, and how much was due to pleiotropic effects of the medications used?

      David L. Keller, M.D. Providence Medical Group, Torrance, CA

      email: davidlouiskeller@gmail.com

      No potential conflict of interest relevant to this letter was reported.

      References

      1: Anderson CS, Heeley E, Huang Y, et al. Rapid blood-pressure lowering in patients with acute intracerebral hemorrhage. N Engl J Med 2013;368:2355-2365

      2: Allen GS, Ahn HS, Preziosi TJ, et al. Cerebral arterial spasm -- a controlled trial of nimodipine in patients with subarachnoid hemorrhage. N Engl J Med 1983;308:619-624


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    1. On 2016 Sep 02, Anderson Santos commented:

      Dear Pannotator users, I am pleased to inform a new Pannotator release available at the site: http://pannotator.facom.ufu.br. It is a preliminary version that I'm expecting to become the version 2.0. Notice that the official website, as published by the GMR paper, is outdated till current date (September 2016); It does not contain the novel features presented in this release. I'm working with the site administrators from Virginia Commonwealth University to fix that. Meanwhile, I would like to indicate the version published at http://pannotator.facom.ufu.br.

      My best regards, Anderson Santos - First author of the pannotator paper


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    1. On 2014 Feb 02, John Armour commented:

      Thanks Dorothy - I agree that could be a more incisive test of a weak right-shift model, but I also agree that power is a real problem, because the target population for such an analysis (right-handers with discordant MZ twins) is likely to constitute about 18-20% of monozygotic pairs (in our study, we looked at 862 MZ twins, of which 157 were discordant). In our data set we would therefore be looking at fewer “case” individuals than in a more direct sampling of left-handers as the “case” phenotype, so the extra power gained by specifying the phenotype of interest more precisely could be offset in any data set by the loss of numbers. My guess (though I haven’t done any further exploration to back up this instinct) is therefore that any study that would have enough discordant MZ twins to do this job well would probably also be in a good position to demonstrate the same shift even as a simple additive determinant of handedness, treating each twin as a random member of a wider population. As I’m sure you appreciate, the main aim of our study was to clarify unambiguously that the simplest and strongest formulations of single-gene models are simply untenable in the face of the data; there are ways we could have squeezed more power out the data if we wanted to really give ourselves the best chance of finding even a quite feeble locus, but the absence of a strong determinant was really the main outcome from our point of view.


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    2. On 2014 Jan 24, Dorothy V M Bishop commented:

      I wondered if the authors could do more with their data, given that the sample consists of twin pairs. The most plausible genetic models are ones in which there is a genotype with no bias to left or right, vs one with a bias to right-handedness. A right-hander could come from either group. However, a right-hander with a left-handed MZ twin is likely to come from the no-bias group. Thus by focusing on MZ twins and reclassifying the phenotype on the basis of the twin pair (RR, RL and LL) one would be able to conduct a better test of association with a realistic phenotype. I suspect this study does not have big enough sample size to do this with adequate power, but I think that, in principle, it ought to work, and so might be a way forward for future studies.


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    1. On 2016 Nov 30, Graham Walker commented:

      We've made an interactive medical calculator for the Ottawa SAH Rule on MDCalc — it also includes additional supplemental content on how to use the rule, next steps, additional references, and details about the creators.


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    2. On 2014 Aug 30, Michelle Lin commented:

      Great publication discussing the high sensitivity of the Ottawa SAH Rule. A week-long ALiEM-Annals of EM journal club discussion was held, along with a videocast with Drs. Perry and Stiell.

      http://www.aliem.com/journal-club-clinical-decision-rule-subarachnoid-hemorrhage/

      Furthermore, the curated discussion has been published in Annals of EM at: http://www.ncbi.nlm.nih.gov/pubmed/24951414


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    1. On 2013 Oct 31, John Cannell commented:

      The authors found markers oxidative stress is present in ASD. I wonder if the authors are aware that the genes for the antioxidants superoxide dismutase and thioredoxin reductase are directly up-regulated by the secosteroid 1,25 di-hydroxy vitamin D3 (calcitriol). I believe both genes also harbor a vitamin D response element.

      Peehl DM, Shinghal R, Nonn L, Seto E, Krishnan AV, Brooks JD, Feldman D. Molecular activity of 1,25‐dihydroxyvitamin D3 in primary cultures of human prostatic epithelial cells revealed by cDNA microarray analysis. J. Steroid Biochem Mol. Biol 2004;92:131–141. PMID:15555907>

      Calcitriol also directly up-regulates glutathione reductase and increases glutathione levels.

      Jain SK, et alo. Vitamin D upregulates glutamate cysteine ligase and glutathione reductase, and GSH formation, and decreases ROS and MCP-1 and IL-8 secretion in high-glucose exposed U937 monocytes. Biochem Biophys Res Commun. 2013 Jul 19;437(1):7-11. doi: 10.1016/j.bbrc.2013.06.004. Jain SK, 2013

      Also, supplemental vitamin D significantly reduces oxidative stress in humans.

      Nikooyeh B, et al. Daily intake of vitamin D- or calcium-vitamin D-fortified Persian yogurt drink (doogh) attenuates diabetes-induced oxidative stress: evidence for antioxidative properties of vitamin D.J Hum Nutr Diet. 2013 Jul 5. doi: 10.1111/jhn.12142. Nikooyeh B, 2014

      Asemi Z, et al. Vitamin D supplementation affects serum high-sensitivity C-reactive protein, insulin resistance, and biomarkers of oxidative stress in pregnant women. J Nutr. 2013 Sep;143(9):1432-8. doi: 10.3945/jn.113.177550. Asemi Z, 2013

      Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

      Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

      Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

      Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

      Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

      DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

      Eyles DW, Burne TH, McGrath JJ. Vitamin D, effects on brain development, adult brain function and the links between low levels of vitamin D and neuropsychiatric disease. Front Neuroendocrinol. 2013 Jan;34(1):47-64. doi: 10.1016/j.yfrne.2012.07.001. Epub 2012 Jul 11. Review. Eyles DW, 2013

      Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

      Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

      Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's


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    1. On 2013 Nov 15, Lillian Kenner commented:

      The cytohesin family of of GEFs have been well established as having homologous structural organization. Here, the GRAB2 GEF clearly shows a divergence from the typical GEF. GRAB2, though comprised of the same domains as other GEFs, has a unique conformationally static native state. Variance in this GEF structure have caused markedly different downstream regulation. The lack of specificity in cellular membranes observed here allow BRAG2 to be readily available for signaling in cells. This allows it to regulate signaling from many cellular membranes, such as the plasma membrane, and endosomes. This does lead to the question of how the GRAB2 activity is modulated as there appears to be no auto-inhibition.


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    1. On 2015 Aug 27, Bernard Friedenson commented:

      For more information please see the article entitled "Mutations in Breast Cancer Exome Sequences Predict Susceptibility to Infection and Converge on the Same Signaling Pathways" This article is available at http://la-press.com/article.php?article_id=5029


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    1. On 2017 May 18, Misha Koksharov commented:

      It's better to read the following pdf version: http://koksharov83.narod.ru/docs/lab/Koksharov_PPS-2013_final.pdf

      It contains a few small corrections (e.g. of a duplicated pdb code in the table, wrong doi for one of the references, etc).


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    1. On 2014 Jan 07, Brett Snodgrass commented:

      Dear Author,

      Thank you for the astute observation regarding the distinction between Grant's findings and those of isolated left ventricular noncompaction.

      I think Dr. Lurie's article is also relevant to isolated noncompaction. Grant's case occurred in the setting of pulmonary atresia and was therefore not “isolated,” but secondary to the abnormal hemodynamics. http://www.ncbi.nlm.nih.gov/pubmed/22176755

      Grant did report a case of pulmonary atresia with intact ventricular septum. Examination of figures four and five exhibit a vessel of Wearn.

      Grant RT. An unusual anomaly of the coronary vessels in the malformed heart of a child. Heart 1926;13:273–283 https://twitter.com/BrettSnodgrass1/status/420281076070637568

      The sphincter was an area of secondary intimal fibroplasia. Vessels of Wearn 1. http://bit.ly/JTWearn 2. http://www.ncbi.nlm.nih.gov/pubmed/22704295 3. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933738/

      Relationship of pulmonary atresia with intact ventricular septum to the vessels of Wearn, similar to Grant's work: 1. http://www.ncbi.nlm.nih.gov/pubmed/23332812

      Aortic atresia with mitral stenosis has also been associated with the vessels of Wearn: Comparable to the hypertensive right ventricle of PAIVS, the hypertensive left ventricle of AA/MS likely resulted in more prominent sinusoids and vessels of Wearn as in the following case. 1. http://www.ncbi.nlm.nih.gov/pubmed/22498086<br> 2. https://twitter.com/BrettSnodgrass1/status/418829863609331712

      Comments and suggestions are always welcome. Thank you kindly.


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    1. On 2013 Dec 13, David Schindel commented:

      Marques, Maronna and Collins (1) rightly call on the biodiversity research community to include latitude/longitude data in database and published records of natural history specimens. However, they have overlooked an important signal that the community is moving in the right direction. The Consortium for the Barcode of Life (CBOL) developed a data standard for DNA barcoding (2) that was approved and implemented in 2005 by the International Nucleotide Sequence Database Collaboration (INSDC; GenBank, ENA and DDBJ) and revised in 2009. . All data records that meet the requirements of the data standard include the reserved keyword 'BARCODE'. The required elements include: (a) information about the voucher specimen from which the DNA barcode sequence was derived (e.g., species name, unique identifier in a specimen repository, country/ocean of origin); (b) a sequence from an approved gene region with minimum length and quality; and (c) primer sequences and the forward and reverse trace files. Participants in the workshops that developed the data standard decided to include latitude and longitude as strongly recommended elements but not as strict requirements for two reasons. First, many voucher specimens from which BARCODE records are generated may have been collected before GPS devices were available. Second, barcoding projects such as the Barcode of Wildlife Project (4) are concentrating on rare and endangered species. Publishing the GPS coordinates of collecting localities would facilitate illegal collecting and trafficking that could contribute to biodiversity loss. The BARCODE data standard is promoting precisely the trend toward georeferencing called for by Marques, Marrona and Collins. Table 1 shows that there are currently 346,994 BARCODE records in INSDC (3). Of these BARCODE records, 83% include latitude/longitude data. Despite not being a required element in the data standard, this level of georeferencing is much higher than for all cytochrome c oxidase I gene (COI), the BARCODE region, 16S rRNA, and cytochrome b (cytb), another mitochondrial region that was used used for species identification prior to the growth of barcoding. Data are also presented on the numbers and percentages of data records that include information on the voucher specimen from which the nucleotide sequence was obtained. In an increasing number of cases, these voucher specimen identifiers in INSDC are hyperlinked to the online specimen data records in museums, herbaria and other biorepositories. Table 2 provides these same data for the time interval used in the Marques et al. letter (1). These tables indicate the clear effect that the BARCODE data standard is having on the community’s willingness to provide more complete data documentation.

      See Tables 1 & 2

      The DNA barcoding community's data standard is demonstrating two positive trends: better documentation of specimens in natural history collections, and new connectivity between databases of species occurrences and DNA sequences. We believe that these trends will become standard practices in the coming years as more researchers, funders, publishers and reviewers acknowledge the value of, and begin to enforce compliance with the BARCODE data standard and related minimum information standards for marker genes (5).

      DAVID E. SCHINDEL(A), MICHAEL TRIZNA(A), SCOTT E. MILLER(A), ROBERT HANNER(B), PAUL D. N. HEBERT(B), SCOTT FEDERHEN(C), ILENE MIZRACHI(C)

      (A) National Museum of Natural History, Smithsonian Institution Smithsonian Institution, Washington, DC 20013–7012, USA. (B) University of Guelph, Ontario, Canada (C) National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA

      1. A.C. Marques, M.M. Maronna, A.G. Collins, Science 341, 1341 (2013)
      2. Consortium for the Barcode of Life, http://www.barcodeoflife.org/sites/default/files/DWG_data_standards-Final.pdf (2009)
      3. Data in Tables 1 and 2 were drawn from GenBank (www.ncbi.nlm.nih.gov/genbank/) [data as of 1 October 2013]
      4. Barcode of Wildlife Project, www.barcodeofwildlife.org (2013)
      5. Yilmaz, P., Kottmann, R., Field, D., Knight, R., Cole, J. R., Amaral-Zettler, L., et al. (2011). Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nature Biotechnology, 29(5), 415–420. doi:10.1038/nbt.1823


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    1. On date unavailable, commented:

      None


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    2. On 2016 Jan 10, Paul Harch commented:

      The response by Dr. Cifu is non-responsive to the scientific points raised in my Comment. In keeping with the purpose of PubMed Commons, an open, non-personal scientific exchange, the request is repeated to respond to the scientific points raised, specifically: 1. Cifu, et al,<sup>1</sup> and all of the DoD HBOT TBI studies,<sup>2</sup> are dose-finding non-controlled studies, according to a physiologic scientific definition of HBOT. None of them are sham controlled. 2. Cifu, et al,<sup>1</sup> showed no effect of 3 combination doses of hyperbaric therapy on mTBI PPCS and PTSD except in the 2.0 ATA 100% oxygen group which demonstrated a statistically significant improvement in PTSD symptoms. 3. Cifu, et al,<sup>1</sup> attributes the positive outcomes of civilian and other DoD-sponsored HBOT TBI studies to non-treatment effects such as placebo, relocation to a subtropical environment, Hawthorne Effect, etc., yet 5 of 6 outcomes for Cifu, et al,<sup>1</sup> are not positive. 4. This author is requesting that Dr. Cifu and co-investigators reconcile their neutral results with the positive and negative results of other studies on the same subject population. The maximal salutary environment of Pensacola, FL should have generated the most positive results of all studies, if in fact the outcomes are due to the non-treatment effects enumerated by Cifu, et al,<sup>1</sup> yet it did not. The major differences in all of these studies were the doses of hyperbaric therapy employed. The doses in Cifu, et al<sup>1</sup> were ineffective. 5. The claim that the results of HBOT in acute severe TBI are “inconclusive” is contrary to the results of multiple randomized trials.

      The points raised in the previous Comment and this Rebuttal are not “…any of a shifting number or false arguments…” They are the same points raised in the peer-reviewed published Letter to the Editor (LTE),<sup>3</sup> of the Wolf/Cifu, et al,<sup>4</sup> paper which informed the data of Wolf/Cifu, ,<sup>4</sup> et al, and invalidated their conclusions. To this date, the authors have not responded to this Letter to the Editor. I would ask Dr. Cifu again to review the referenced sampling in that LTE<sup>3</sup> and the plethora of scientific literature accumulated over the past 70 years showing that small increases in ambient pressure are bioactive across the entire phylogenetic spectrum, including humans.<sup>5</sup> This is old science just recently brought to the fore<sup>3</sup> in the clinical hyperbaric medicine community and is best described as an inconvenient truth, rather than “ridiculous and embarrassing.” Instead of addressing this science Dr. Cifu has lodged the convenient claim of financial incentive to dismiss my Comment: “…the clinicians and lobbyists who make their livings using HBOT for a wide range of neurologic disorders…” This evasive charge was previously lodged by VA researchers in a critique<sup>6</sup> of this author’s report<sup>7</sup> and addressed by this author.<sup>8</sup> The charge is inconsistent with nearly three decades of basic science and clinical research and more consistent with the conflict of interest of VA researchers.<sup>8</sup> A final point: in no publication has the claim regarding effectiveness of HBOT in mTBI PPCS been predicated on an exclusive or even dominant anti-inflammatory effect of HBOT. Rather, the argument is based on the known micro-wounding of brain white matter in mTBI,<sup>9</sup> and the known gene-modulatory,<sup>10</sup> trophic wound-healing effects of HBOT in chronic wounding.<sup>11</sup> The preponderance of literature in HBOT-treated chronic wound conditions,<sup>11</sup> is contrary to Dr. Cifu’s statement of HBOT as a “useless technology.”<br> The implications of getting this science correct and clarifying the confusion in the medical and lay community caused by the confounding DoD studies’ conclusions are enormous. Millions of civilians and brain-injured military service personnel with PPCS or residual neurocognitive sequelae of moderate and severe TBI can be helped by this biological repair therapy. The only “false hope” by patients would be in Cifu, et al,<sup>1</sup> where the patients, by and large, did not improve. In nearly all other studies where proper doses of hyperbaric therapy were employed the “false hope” resulted in positive outcomes.

      References:

      1. Cifu DX, et al. J Head Trauma Rehabil. 2013 Sep 18. [Epub ahead of print]. DOI: 10.1097/HTR.0b013e3182a6aaf0.<br>
      2. Weaver LK, et al. Undersea Hyper Med. 2012;39(4):807–814.
      3. Harch PG. J Neurotrauma. 2013 Oct 11. [Epub ahead of print]. doi:10.1089/neu.2012.2799.
      4. Wolf G,et al. J Neurotrauma. 2012;29:1–7.
      5. Macdonald AG, Fraser PJ. Comparative Biochemistry and Physiology Part A. 1999;122:13-36.
      6. Wortzel HS, et al. J Neurotrauma. 2012;29(14):2421-4.
      7. Harch PG, et al. J Neurotrauma. 2012;29:168–185.
      8. Harch PG, et al. J Neurotrauma. 2012;29:2425-2430.
      9. Ryu J, et al. (2014). Acta Neuropathologica Communications. 2014;2:153.
      10. Godman CA, et al. Cell Stress Chaperones. 2010;15:431–442.
      11. Gesell LB, ed. Hyperbaric Oxygen Therapy Indications. The Hyperbaric Oxygen Therapy Committee Committee Report. 12th ed. Durham, NC: Undersea and Hyperbaric Medical Society;2008.


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    3. On 2016 Jan 03, David X Cifu commented:

      Mild Traumatic Brain Injury ("Concussion") of any etiology is a complex injury that typically (>95%) has an excellent and rapid recovery. Individuals who have persistent symptoms for more than 3 months after a concussion will commonly have a number of number of factors (related and not related to the initial mTBI) contributing to the chronicity of their symptoms, which makes further improvement challenging. Multimodal interventions, delivered by knowledgeable and experienced individuals who work in an interdisciplinary fashion, emphasize progressive increases in physical and cognitive activity, stress the importance of a return to normal and full pre-injury activity, de-emphasize the need for diagnostics, encourage self-management to enhance resiliency, avoid unproven and fringe treatments, and utilize psychological techniques (e.g. CBT) to ameliorate behavioral and cognitive dysfunction, are the only proven effective strategies. While current research has identified a potential role for chronic inflammation contributing to neurodegeneration in the miniscule subset of individuals who develop early onset dementia (chronic traumatic encephalopathy), persistent inflammation has not been identified in the vast majority of individuals and has not been associated with the persistence of symptoms. There is no reason to believe that an intervention like HBOT that purports to decrease inflammation would have any meaningful effect on the persistence of symptoms after concussion. Three well-controlled, independent studies (funded by the Department of Defense and published in a range of peer reviewed journals) involving more than 200 active duty servicemen subjects have demonstrated no durable or clinically meaningful effects of HBOT on the persistent (>3 months) symptoms of individuals who have sustained one or more concussions. Despite these scientifically rigorous studies, the clinicians and lobbyists who make their livings using HBOT for a wide range of neurologic disorders (without scientific support) have continued to advocate the use of HBOT for concussion. They purport that either the elevated pressures or the slightly higher than room oxygen content (1.2 vs 1.0) of the sham procedures used as part of the scientific control are confounding the research trials. These claims are ridiculous and embarrassing. These distractors would rather attack highly controlled and peer supported research publications by any of a shifting number or false arguments than admit they are advocating a useless technology. HBOT does not work on any level for the persistent symptoms seen after concussion. As a clinician and an academician, I would never recommend its usage and would advise any patient or clinician to avoid this inappropriate intervention. We have evidence-based and clinically sound treatments for post-concussive symptoms (as noted above). Let's employ these proven tools, help our patients, and cease with purveying false hopes.


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    4. On 2016 Jan 02, Paul Harch commented:

      Cifu, et al<sup>1</sup> characterize the Department of Defense HBOT TBI studies<sup>1-3</sup> as sham-placebo controlled clinical investigations. A sham group “omits a key therapeutic element of the treatment or procedure under investigation”<sup>4</sup> and a placebo must be inert.<sup>5</sup> The key therapeutic elements in hyperbaric therapy are pressure and hyperoxia, neither of which are inert.<sup>6</sup> Therefore, Cifu et al<sup>1</sup> is neither sham, placebo, nor controlled; all groups contain either increased pressure, hyperoxia, or both.<sup>6,7</sup><br> Cifu, et al<sup>1</sup> define HBOT as involving “…breathing high levels of oxygen…at… at least 1.4 times greater than …(1 atmosphere absolute…ATA)…. <sup>1</sup> This non-physiologic definition sets an arbitrary threshold for HBOT that excludes the contribution of lesser elevated pressures and degrees of hyperoxia (e.g. 1.39999 ATA hyperbaric oxygen is not HBOT?). Hyperbaric oxygen therapy is a combination intervention of increased pressure and hyperoxia,<sup>6,7</sup> that up- and down-regulates both independent and overlapping pressure and oxygen-sensitive genes<sup>6,8-10</sup> to produce well-known clinical effects.<sup>11</sup> Cifu et al<sup>1</sup> purported to test the doses of HBOT in previous publications.<sup>12-14.</sup> It did not. Cifu et al<sup>1</sup> studied 3 composite doses of hyperbaric therapy by using different doses of oxygen, a single dose of pressure (2.0 ATA), and changing doses of oxygen and pressure during compression and decompression that have not been previously tested in mTBI/PPCS and PTSD. Cifu, et al<sup>1</sup> stands in contrast to Wolf, et al<sup>2,</sup> which initially showed statistically significant beneficial effects of two different composite doses of hyperbaric therapy in mTBI/PPCS and PTSD (1.3 ATA air and 2.4 ATA 100% oxygen), and other studies using 1.5 ATA 100% oxygen.<sup>12,15-17</sup> (Wolf, et al’s<sup>2</sup> findings have been qualified in a subset analysis that demonstrated a trend toward harm with 2.4 ATA oxygen in PPCS).<sup>18</sup> According to Cifu, et al<sup>1,</sup> the results of Wolf, et al<sup>2</sup> and “…prior case reports<sup>14,19-22</sup> are explained by factors other than the effect of HBO2 on PPCS,” i.e., placebo, relocation, reduced duty schedules, Hawthorne Effect, leisure time and activities in a noncombat, semitropical beach environment, and other non-biologic effects of the hyperbaric chamber experience. This explanation has merit if Cifu, et al’s<sup>1</sup> data were uniformly positive. However, it is not, despite the maximal salutary environment of Pensacola, FL. The most logical explanation for Cifu, et al’s<sup>1</sup> data is the independent and differing bioactivity of different combination doses of pressure and hyperoxia on gene expression. <sup>9,10</sup> Cifu, et al<sup>1</sup> have demonstrated the ineffectiveness of 2 new composite doses of hyperbaric therapy on PTSD and 3 new doses on PPCS, and the effectiveness of one dose on PTSD. The PPCS findings are consistent with the literature on HBOT in chronic traumatic brain injury cited by Cifu and others<sup>1-3,6,7,12-16,23</sup> that reveal no evidence for the effectiveness of 2.0 ATA of pressure or oxygen on chronic TBI, and negative/toxic effects ≥ 2.0 ATA in acute severe TBI.<sup>24,25</sup> Cifu, et al<sup>1</sup> finish with a claim that the results of HBOT in acute severe TBI are “inconclusive.” There are five randomized clinical trials on HBOT in acute severe TBI,<sup>26-30</sup> a comparative dosing study,<sup>25</sup> and two Cochrane reviews<sup>21,31</sup> demonstrating a significant reduction in mortality<sup>26,28-31</sup> (~60%) and improvement in outcome.<sup>25-27,29,30</sup> There is nothing inconclusive about this data, however it’s inclusion in a report on mTBI PPCS is inappropriate. In summary, Cifu, et al<sup>1</sup> is mis-described as a sham placebo controlled study based on a non-physiologic definition of hyperbaric therapy that omits the bioactivity of increased pressure. On this foundation Cifu, et al<sup>1</sup> combine their data with Wolf, et al<sup>2</sup> and offer sweeping erroneous conclusions about the effectiveness of hyperbaric therapy in PPCS of mTBI and acute severe TBI. Cifu, et al<sup>1</sup> is a 3 dose study of different combinations of pressure and oxygen that demonstrates the ineffectiveness of two doses of hyperbaric therapy in patients with PPCS and PTSD and the effectiveness of a third dose in PTSD and possibly PPCS. Their data complement the effectiveness of multiple other doses of hyperbaric therapy in mTBI PPCS<sup>2,12,15-17,23</sup> and PTSD<sup>2,12,15,17</sup> which they refer to incorrectly as showing “no symptom relief with HBO2,” and an animal model of HBOT in chronic mTBI.<sup>32</sup> The Cifu,<sup>1</sup> Wolf,<sup>2</sup> and civilian studies<sup>12,15,16</sup> must be appreciated In terms of the effects of different doses of hyperbaric therapy (increased pressure and hyperoxia) on PPCS and PTSD whose doses have different physiologic and gene profiles. Some of these doses are effective while others are not. Conflict of Interest: The author is the co-owner of Harch Hyperbarics, Inc., a C-corporation that provides expert witness testimony and hyperbaric consulting. References: 1. Cifu DX, et al. J Head Trauma Rehabil. 2013 Sep 18. [Epub ahead of print]. DOI: 10.1097/HTR.0b013e3182a6aaf0.<br> 2. Wolf G, et al.. J Neurotrauma. 2012;29:1–7. 3. Weaver LK, et al. Undersea Hyper Med. 2012;39(4):807–814 4. Sham. Available at: http://www.merriam-webster.com/medical/sham. 5. Placebo. Available at: http://medical-dictionary.thefreedictionary.com/placebo+effect. 6. Harch PG. J Neurotrauma. 2013 Oct 11. [Epub ahead of print]. doi:10.1089/neu.2012.2799. 7. Harch P. Undersea Hyper Med. 2013;40(5):469-70. 8. Godman CA, et al. Cell Stress Chaperones. 2010;15:431–442. 9. Chen Y, et al. Neurochem. Res. 2009; 34:1047–1056. 10. Oh S, et al. Cell Stress and Chaperones. 2008;13:447-458. 11. Gesell LB, ed. Hyperbaric Oxygen Therapy Indications. The Hyperbaric Oxygen Therapy Committee Committee Report. 12th ed. Durham, NC: Undersea and Hyperbaric Medical Society;2008. 12. Harch PG, et al. J Neurotrauma. 2012;29:168–185. 13. Rockswold SB, et al. J Neurosurg. 2010;112:1080–1094. 14. Harch PG. In: Joiner JT, ed. Proceedings of the 2nd International Symposium on Hyperbaric Oxygenation for Cerebral Palsy and the Brain-Injured Child. Flagstaff, AZ: Best Publishing Co;2012:31–56. 15. Harch, PG, et al. Cases Journal. 2009;2:6538. http://casesjournal.com/casesjournal/article/view/6538. 16. Wright JK, et al. Undersea Hyper Med. 2009;36:391–399. 17. Data on Cifu, et al1, Wolf, et al3, and HOPPS Army study presented at the 46th Annual UHMS Scientific Meeting in Orlando, FL 6/15/2013 in a special symposium. 18. Scorza KA, et al. Abstract C27, Friday, 6/14/2013, 8:12 a.m. Undersea and Hyperbaric Medical Society Annual Meeting, Orlando, FL. 19. Rockswold SB, et al. Neurol Res. 2007;29(2):162–172. 20. Bennett MH. Extrem Physiol Med. 2012;1(1):14.<br> 21. Bennett MH, et al. Cochrane Database Syst Rev. 2004;(4):CD004609. 22. McDonaugh M, et al. Arch Phys Med Rehabil. 2004;85(7):1198-1204. 23. Harch PG, et al. Hyperbaric oxygen therapy in global cerebral ischemia/anoxia and coma. In: Jain KK, ed. Textbook of Hyperbaric Medicine, 5th revised edition Chapter 19. Seattle, WA: Hogrefe and Huber Publishers;2009:235–274. 24. Holbach KH, et al. J Neurol. 1977;217:17-30. 25. Holbach, KH. In: Schurmann K, ed. Advances in Neurosurgery, Vol. 1. Berlin: Springer;1973:158-163. 26. Holbach KH, et al. Acta Neurochir (Wien). 1974;30:247–256, (Ger) 27. Artru F., et al. Eur Neurol. 1976;14:310-318. 28. Rockswold GL, et al. J Neurosurg. 1992;76:929–934. 29. Ren H, et al. Chinese Journal of Traumatology (English Edition). 2001;4(4):239-241. 30. Rockswold SB, et al. J Neurosurg. 2013;118(6):1317-28. 31. Bennett MH, et al. Cochrane Database Syst Rev. 2012;12:CD004609. doi: 10.1002/14651858.CD004609.pub3. Review. 32. Harch, PG, et al. Brain Res. 2007. 1174, 120–129.


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    1. On 2015 Jan 17, Jacob H. Hanna commented:

      None


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    2. On 2015 Jan 17, Jacob H. Hanna commented:

      1) Hanna group response can be found on bioRxiv: http://dx.doi.org/10.1101/013961 It should be noted that the above speculative critique by Bertone & co. has been rejected by Nature editors and reviewers following, among other things, our response indicated above.

      2) 11/09/2017 - Follow-up papers from Hanna group further dismissing these critiques and substantiating our initial discoveries are now available: http://www.biorxiv.org/content/early/2017/09/07/184135


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    3. On 2015 Jan 17, Jacob H. Hanna commented:

      None


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    4. On 2015 Jan 16, Paul Bertone commented:

      A critique of this paper is available on bioRxiv: dx.doi.org/10.1101/013904


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    1. On 2014 Jul 22, Jim Woodgett commented:

      Appears that this paper is in the process of being retracted. The authors posted this note: http://atlas.bx.psu.edu/project/human.html There were apparently issues with data analysis. Kudos to them for making this information available. Would be good to know what the mistake was so others might not repeat it.


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    1. On 2014 Jul 09, Chandan Kumar commented:

      Same paper is available as PMID:23623766, with link to the journal site for access to full paper. Prob'ly a mistake at Pubmed providing two links to the same paper.

      Molecular lipidomics of exosomes released by PC-3 prostate cancer cells.

      Llorente A, Skotland T, Sylvänne T, Kauhanen D, Róg T, Orłowski A, Vattulainen I, Ekroos K, Sandvig K.

      Biochim Biophys Acta. 2012 Jul;1831(7):1302-9. doi: 10.1016/j.bbalip.2013.04.011. Epub 2013 Apr 24.

      PMID: 23623766 [PubMed - in process]

      Free Article

      Related citations


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    1. On 2013 Oct 24, Karim N'Diaye commented:

      A very interesting perspective, but it overlooks that deep-brain stimulation is another option towards neuromodulation in psychiatry. Though, I agree that DBS is highly invasive and thus limited to the most severe resistant cases. I don't clearly see why their argument should be limited to non-invasive approaches such as rTMS (which are not devoid of any risk, hence better called low-risk rather than non-invasive).

      In fact, closed-loop/neurofeedback systems are a real trend in the field of DBS, with strong proponents in the context of psychiatric disorders (eg. Ward MP, 2010 in depression), finding support with the promising results obtained in neurological conditions (eg. Parkinson's disease: Rosin B, 2011) and the advent of novel tools combining not only electric field potentials measures but also voltammetry within a minimal volume (Chang SY, 2013). And indeed, the field is burgeoning with discussions regarding the concrete ethical issue raised by these technologies (Vaadia E, 2009) as well as the broader anthropological changes they may convey (Moutaud, B, « C'est un problème neurologique ou psychiatrique?» , Les Cahiers du Centre Georges Canguilhem, 2008).


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    1. On 2014 Sep 09, David J Volkman commented:

      The following letter was sent to the NEJM and rejected after internal review after one day.

      Under-diagnosis of Lyme Borreliosis It was recently estimated that of the more than 300,000 annual borrelia infections (Lyme disease (LD)) in the US, the CDC reports only 30,000 (1). The two-tier serology criterion recommended by the CDC, derived from the 1994 Dearborn Conference (2), requires 5-10 antibody reactivities to confirm a case, resulting in many positive Lyme disease (LD) titers with fewer reactivities being ignored and untreated. In contrast, a single reactivity against a crude flagella antigen or a positive IgG ELISA against a whole cell borrelia sonicate (WCS) is often sufficient to detect new infection (3). In 1999 Felz reported 22/22 people with an erythema migrans rash in Georgia and South Carolina, areas the CDC insist is devoid of LD, had IgG antibody against the flagella (3). The WCS from the inexpensive, widely available B31 Long Island borrelia isolate has enough ubiquitous p41 flagella epitopes to detect borrelia infections across the US, Europe, and China (4). As shown in Table 1 specific antibodies may take more than 5 weeks to develop and if assayed too early may be absent. Table 1 shows the serology of a woman with a negative LD serology hospitalized with a diagnosis of aseptic meningitis. A week after discharge she had a highly positive ELISA, a strong anti-41 kd IgG band, and 3 IgM bands. She was treated with 4 weeks of oral doxycycline, recovered fully, and remains well 2 years later. Anti-borrelia antibodies can take 5 weeks to develop and may have reactivity only to the p41 flagella; obtained too early or requiring restrictive criteria, serology may be falsely reported as negative. Since Congress is considering closer oversight of FDA approved LD testing (5); it is imperative testing becomes evidence-based, sensitive, and reflects biomedical reality. The CDC’s current 20 year old criteria for LD testing leave many infected people with spurious false negative tests, undiagnosed, and untreated.   Table 1: Serologic Response to EM

      Date IgG/IgM EIA IgG bands IgM bands

      Early June noted 5 mm light brown bump on thigh June 27 negative none none negative July 8 5.49* P41 + p23,39,41 + IgM positive/WB negative < 5 bands

      August 1 month 100mg BID PO doxycycline Next year 4.79 p41, p23 + none negative

      • relative optical density (1.00 = 3 Standard Deviations greater than mean of negative controls)
      • present

      References 1. Kuehn BM. CDC Estimates 300000 US Cases of Lyme Disease Annually. JAMA.18, 2013. 310, 1110.

      1. CDC (1995) Recommendations for test performance and interpretation from the second national conference on serologic diagnosis of Lyme disease. Morbidity and Mortality Weekly Report 44, 590–591.
      2. Felz MW, Chandler FW Jr, Oliver JH Jr, Rahn DW, Schriefer ME. Solitary erythema migrans in Georgia and South Carolina. Arch Dermatol. 1999; 135:1317-26.

      3. Chao LL, Chen YJ, Shih CM. First isolation and molecular identification of Borrelia burgdorferi sensu stricto andBorrelia afzelii from skin biopsies of patients in Taiwan. Int J Infect Dis. 2011 Mar; 15:e182-7.

      4. Nelson C, Hojvat S, Johnson B, Petersen J, Schriefer M, Beard CB, Petersen L, Mead P. Concerns regarding a new culture method for Borrelia burgdorferi not approved for the diagnosis of Lyme disease. Centers for Disease Control and Prevention (CDC). MMWR Mor


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    1. On 2013 Oct 29, John Cannell commented:

      As the authors suggest, micronutrient deficiencies may explain their findings. One micronutrient that is depleted in multiparous women is vitamin D.

      Andersen LB, Abrahamsen B, Dalgård C, Kyhl HB, Beck-Nielsen SS, Frost-Nielsen M, Jørgensen JS, Barington T, Christesen HT. Parity and tanned white skin as novel predictors of vitamin D status in early pregnancy: a population-based cohort study. Clin Endocrinol (Oxf). 2013 Sep;79(3):333-41. doi: 10.1111/cen.12147. Epub 2013 Jul 2. Andersen LB, 2013

      Furthermore, the states with the highest participants in the Women's and Infant and Child program, which includes prenatal as well as postnatal vitamin D supplements, have significantly lower autism rates.

      Shamberger RJ. Autism rates associated with nutrition and the WIC program. Jn Am Coll Nutr. 2011 Oct;30(5):348-53. Shamberger RJ, 2011

      Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with autism. Two of the studies below (Mostafa et al and Gong et al) also found autism severity, as rated on standard autism rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with autism severity.

      Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

      Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

      Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

      There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

      DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

      Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

      Furthermore, the vitamin D theory of autism explains many of the epidemiological facts of autism.

      Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

      Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

      70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day.

      Cannell JJ. Autism, will vitamin D treat core symptoms? Medical Hypotheses. 2013 Aug;81(2):195-8. Cannell JJ, 2013

      A group of well-known European autism researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into the theory of vitamin D deficiency and autism.

      Kočovská E, Fernell E, Billstedt E, Minnis H, Gillberg C. Vitamin D and autism: clinical review. Res Dev Disabil. 2012 Sep-Oct;33(5):1541-50. doi: 10.1016/j.ridd.2012.02.015. Epub 2012 Apr 21.Kočovská E, 2012

      The author's important finding of higher autism rates with lower inter-pregnancy intervals is entirely consistent with the vitamin D theory of autism.

      John J Cannell, MD

      Vitamin D Council

      http://www.vitamindcouncil.org


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    1. On 2013 Dec 22, William Brieger commented:

      Since this study was conducted, WHO's Global Malaria Program has updated its recommendations about intermittent preventive treatment in pregnancy (IPTp). The guideline and briefing paper can be found at http://www.who.int/malaria/areas/high_risk_groups/pregnancy/en/index.html - in short IPTp is now recommended for every antenatal care visit after quickening (doses one month apart), meaning up to 4 doses if countries are practicing focused antenatal care.


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    1. On 2014 Jan 01, Qian Liu commented:

      This is an official government file for Chinese thoracic surgeons.


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    1. On 2015 Nov 13, University of Kansas School of Nursing Journal Club commented:

      Reviewers: (Team 10) Lucy Bush, Sydney Jordan, Elijah Penny, Alex Noller, Parwana Noori, Cassidy Playter, Brittany Winter (Senior Nursing Students – Class of 2016)

      Background:

      This article was chosen based on how it directly correlates with the transformational leadership section we recently covered in lecture. This study explores how transformational leadership effects nursing innovation and the role of an organizational climate. This article bridges the gap in knowledge present between transformational leadership of management and the behavior of employees subjected to this leadership style. As discussed by Marquis and Huston (2015), transformational leadership by definition is designed to encourage nurses to be innovative, compassionate, and caring; however, this definition does not cover what kinds of innovative behaviors nurses under transformational management exhibit. The purpose of us analyzing this article was to discover what specific behaviors that could be evoked by the consistent support of a manager with a transformational leadership style. The authors of the article conducted the study in three regional hospitals in Taiwan that yielded a different cultural perspective of nursing and leadership, (Weng, Huang, Chen, & Chang, 2013, p. 427). Much effort and resources are focused on nurses’ performance in the clinical setting, and transformational leadership has its proper place in the drive to improve nursing innovation.

      Methods:

      The databases used to retrieve this article were The Biosemantics Group, CINAHL, and PubMed. The article we choose was originally not found when using the following Boolean search: “transformational leadership” AND “nursing.” Even though the subject heading being searched was adjusted from title to abstract, CINAHL revealed no articles of interest. When PubMed was searched for: “the impact of transformational leadership,” the article we decided upon was found. The study employed a cross-sectional research design that used personal reporting from nursing professionals. Data was collected using a questionnaire survey consisting of a 5-point Likert scale sent out to 150 selected nurses from three separate Taiwan hospitals (Weng et al., 2013, p. 431). The questionnaires were sent out anonymously to nurses in the selected hospitals. A total of 450 questionnaires were sent out from 11 April to 15 May 2011 and the research team obtained a total of 439 questionnaires with viable data (Weng et al., 2013, p. 431). The target population of nurses was selected primarily based upon their age, educational background, role in the clinical ladder, marital status, department of employment, and hospital experience in order to eliminate extraneous factors that could have affected the implication of the results on nursing practice (Weng et al., 2013, p. 431). The study also recognized that inspirational motivation, idealized influence, and a patient safety climate could also positively influence the innovation of staff nurses in Taiwan hospitals. After removing all potentially compromising variables, the research team analyzed the impact of transformational leadership on nurse innovation.

      Findings:

      The key findings of this study showed that their initial hypothesis one was correct: transformational leadership has a significantly positive influence on nurse innovation behavior. The questionnaires would go on to reveal that nurse managers can indirectly, positively influence nurse innovative behaviors through the establishment of a culture of patient safety and innovation (Weng et al., 2013). In other words, organizational climate directed by transformational leadership could impacts innovative behavior. A large limitation is that the study was only carried out in three Taiwanese hospitals; therefore, it would be hard to say that the results are externally valid or applicable to all nursing care across the world. Further research will need to be carried out in U.S. hospital settings to determine if the effects seen in Taiwanese hospitals were not influenced by other factors such as geography, culture or traditions not evident in the U.S. care settings. Another difference noted in this study was the time frame of data collection. The questionnaires were only sent out for a little over a month-long period in 2011; therefore, the data collected only represents a time-limited analysis of the effects of transformational leadership on nurse innovative behaviors. In the future, it would be recommended that the study be carried out over a considerably longer time frame to ensure data collection evidenced sustained nursing innovative behaviors. On a macro-system level, this problem impacts nearly all nursing units across the world because nursing innovations in patient care could be applicable to all scenarios in which nursing care is needed. From a microsystem perspective, nurse managers interested in boosting creativity and innovation among their unit staff should understand the indirect influence transformation leadership and organizational climate can have on nursing innovative behaviors. The importance of innovation is highly applicable to all hospital development and especially nursing care development, as nurses are deeply involved in direct patient care and the practice of healthcare.

      Implications:

      The study reports the significance of transformational leadership. This implies that hospitals should develop and encourage transformational leadership approach by designing and implementing leadership training programs aimed at developing cultures of patient safety and innovation. On the microsystems level, the findings of this study demonstrate that nurse managers can foster innovation by involving nurses in team projects to develop and implement creative ideas. Throughout the implementation and evaluation phases of nurse innovative projects, nurse manager should recognize success and encourage behaviors attributed to the success in an effort to sustain such innovation. Weng (2013) also stated the importance of establishing a culture of patient safety through development of a patient safety problem-reporting network. Not only does patient safety reporting make nurse managers aware of threats to patient safety, but it also supports development of innovations through staff involvement. This literature is important to our group because it allows us to explore what transformational leadership can look like at the microsystems level. Only through continual reflection on our own practices, can we accomplish changes in our leadership behaviors in the clinical setting. This article models the important affects that we as future nurse leaders can have on the safety of the patients we are caring for. Personal empowerment exercises like the discovery of these cultures of innovation have proved to be inspirational to us throughout our learning process.

      References

      Weng, R. H., Huang, C. Y., Chen, L. M., & Chang, L. Y. (2013). Exploring the impact of transformational leadership on nurse innovation behavior: a cross‐sectional study. Journal of nursing management. 23,4. doi:10.1111/jonm.12149

      Marquis, B., & Huston, C. (2015). Leadership Roles and Management functions in Nursing: Theory and Application. (8th ed). Wolster & Kluwer. Philadelphia. Chapter 3: Twenty-First Century Thinking about Leadership and Management, pp. 60-61.


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    1. On 2014 Mar 09, Gyanshankar Mishra commented:

      This is an excellent study on pulmonary function tests in diabetes with/without COPD.

      We had done a similar study on pulmonary function tests in Diabetics with obstructive airway diseases like Asthma or COPD. Available online at http://www.applied-cardiopulmonary-pathophysiology.com/05_mishra.html

      In fact our prior study was on Pulmonary functions in Diabetes. http://www.ncbi.nlm.nih.gov/pubmed/21302598


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    1. On 2014 Mar 02, Andrea Messori commented:

      The systematic review by Adam and co-workers [1] is probably the most comprehensive analysis currently available on the comparative effectiveness of new oral anticoagulants for thromboprophylaxis in patients subjected to orthopaedic surgery. One problem for readers who are interested in this issue is that PubMed now includes at least 20 meta-analyses or systematic reviews focused on this issue [1-20]. This confirms that a problem exists with multiple overlapping meta-analyses that study the same randomized trials published on the same topic[21-22]. However, there seems to be no straightforward solution to this problem.

      Andrea Messori HTA Unit, Regional Health Service 50100 Firenze ITALY

      References

      1: Adam SS, McDuffie JR, Lachiewicz PF, Ortel TL, Williams JW Jr. Comparative effectiveness of new oral anticoagulants and standard thromboprophylaxis in patients having total hip or knee replacement: a systematic review. Ann Intern Med. 2013 Aug 20;159(4):275-84. doi: 10.7326/0003-4819-159-4-201308200-00008.Review. PubMed PMID: 24026260.

      2: New Oral Anticoagulants for the Prevention of Thromboembolic Events in Patients with Atrial Fibrillation [Internet]. Ottawa (ON): Canadian Agency forDrugs and Technologies in Health; 2012. Available from http://www.ncbi.nlm.nih.gov/books/NBK169793/ PubMed PMID: 24279001.

      3: Hull RD, Liang J, Bergqvist D, Yusen RD. Benefit-to-harm ratio of thromboprophylaxis for patients undergoing major orthopaedic surgery. A systematic review. Thromb Haemost. 2014 Jan 29;111(2):199-212. doi: 10.1160/TH13-08-0654. Epub 2013 Oct 24. PubMed PMID: 24154501.

      4: Castellucci LA, Cameron C, Le Gal G, Rodger MA, Coyle D, Wells PS, Clifford T, Gandara E, Wells G, Carrier M. Efficacy and safety outcomes of oral anticoagulants and antiplatelet drugs in the secondary prevention of venous thromboembolism: systematic review and network meta-analysis. BMJ. 2013 Aug 30;347:f5133. doi: 10.1136/bmj.f5133. Review. PubMed PMID: 23996149; PubMed Central PMCID: PMC3758108.

      5: Hamidi V, Ringerike T, Hagen G, Reikvam Å, Klemp M. New anticoagulants as thromboprophylaxis after total hip or knee replacement. Int J Technol Assess Health Care. 2013 Jul;29(3):234-43. doi: 10.1017/S0266462313000251. Epub 2013 Jun 17. PubMed PMID: 23768996.

      6: Mahmoudi M, Sobieraj DM. The cost-effectiveness of oral direct factor Xa inhibitors compared with low-molecular-weight heparin for the prevention of venous thromboembolism prophylaxis in total hip or knee replacement surgery. Pharmacotherapy. 2013 Dec;33(12):1333-40. doi: 10.1002/phar.1269. Epub 2013 Apr 26. PubMed PMID: 23625693.

      7: Pebanco GD, Kaiser SA, Haines ST. New pharmacologic methods to prevent venous thromboembolism in older adults: a meta-analysis. Ann Pharmacother. 2013 May;47(5):605-16. doi: 10.1345/aph.1R247. Epub 2013 Apr 19. PubMed PMID:23606553.

      8: Kwok CS, Pradhan S, Yeong JK, Loke YK. Relative effects of two different enoxaparin regimens as comparators against newer oral anticoagulants: meta-analysis and adjusted indirect comparison. Chest. 2013 Aug;144(2):593-600. doi: 10.1378/chest.12-2634. PubMed PMID: 23519234.

      9: Yoshida Rde A, Yoshida WB, Maffei FH, El Dib R, Nunes R, Rollo HA. Systematic review of randomized controlled trials of new anticoagulants for venous thromboembolism prophylaxis in major orthopedic surgeries, compared with enoxaparin. Ann Vasc Surg. 2013 Apr;27(3):355-69. doi:10.1016/j.avsg.2012.06.010. Epub 2013 Jan 23. Review. PubMed PMID: 23351997.

      10: Hellwig T, Gulseth M. New oral therapies for the prevention and treatment of venous thromboembolism. Am J Health Syst Pharm. 2013 Jan 15;70(2):113-25. doi:10.2146/ajhp110601. Review. PubMed PMID: 23292264.

      11: John M. Eisenberg Center for Clinical Decisions and Communications Science. Venous Thromboembolism Prophylaxis in Orthopedic Surgery. 2012 Aug 30. Comparative Effectiveness Review Summary Guides for Clinicians [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2007-. Available from http://www.ncbi.nlm.nih.gov/books/NBK107166/ PubMed PMID: 23035277.

      12: Harenberg J, Marx S, Dahl OE, Marder VJ, Schulze A, Wehling M, Weiss C. Interpretation of endpoints in a network meta-analysis of new oral anticoagulants following total hip or total knee replacement surgery. Thromb Haemost. 2012 Nov;108(5):903-12. doi: 10.1160/TH12-07-0482. Epub 2012 Sep 26. PubMed PMID: 23014668.

      13: Gómez-Outes A, Terleira-Fernández AI, Suárez-Gea ML, Vargas-Castrillón E. Dabigatran, rivaroxaban, or apixaban versus enoxaparin for thromboprophylaxis after total hip or knee replacement: systematic review, meta-analysis, and indirect treatment comparisons. BMJ. 2012 Jun 14;344:e3675. doi:10.1136/bmj.e3675. Review. PubMed PMID: 22700784; PubMed Central PMCID:PMC3375207.

      14: Bozzato S, Galli L, Ageno W. Thromboprophylaxis in surgical and medical patients. Semin Respir Crit Care Med. 2012 Apr;33(2):163-75. doi:10.1055/s-0032-1311795. Epub 2012 May 30. Review. PubMed PMID: 22648489.

      15: Thirugnanam S, Pinto R, Cook DJ, Geerts WH, Fowler RA. Economic analyses of venous thromboembolism prevention strategies in hospitalized patients: a systematic review. Crit Care. 2012 Mar 9;16(2):R43. [Epub ahead of print] PubMed PMID: 22405349.

      16: Cohen A, Drost P, Marchant N, Mitchell S, Orme M, Rublee D, Simon TA, Sutton A. The efficacy and safety of pharmacological prophylaxis of venous thromboembolism following elective knee or hip replacement: systematic review and network meta-analysis. Clin Appl Thromb Hemost. 2012 Nov;18(6):611-27. doi:10.1177/1076029612437579. Epub 2012 Mar 2. Review. PubMed PMID: 22387582.

      17: Falck-Ytter Y, Francis CW, Johanson NA, Curley C, Dahl OE, Schulman S, Ortel TL, Pauker SG, Colwell CW Jr; American College of Chest Physicians. Prevention of VTE in orthopedic surgery patients: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012 Feb;141(2 Suppl):e278S-325S. doi:10.1378/chest.11-2404. PubMed PMID: 22315265; PubMed Central PMCID: PMC3278063.

      18: Raskob GE, Gallus AS, Pineo GF, Chen D, Ramirez LM, Wright RT, Lassen MR. Apixaban versus enoxaparin for thromboprophylaxis after hip or knee replacement: pooled analysis of major venous thromboembolism and bleeding in 8464 patients from the ADVANCE-2 and ADVANCE-3 trials. J Bone Joint Surg Br. 2012 Feb;94(2):257-64. doi: 10.1302/0301-620X.94B2.27850. PubMed PMID: 22323697.

      19: Kwong LM. Therapeutic potential of rivaroxaban in the prevention of venous thromboembolism following hip and knee replacement surgery: a review of clinical trial data. Vasc Health Risk Manag. 2011;7:461-6. doi: 10.2147/VHRM.S4441. Epub 2011 Jul 18. Review. PubMed PMID: 21822393; PubMed Central PMCID: PMC3148419.

      20: Maratea D, Fadda V, Trippoli S, Messori A. Prevention of venous thromboembolism after major orthopedic surgery: indirect comparison of three new oral anticoagulants. J Thromb Haemost. 2011 Sep;9(9):1868-70. doi:10.1111/j.1538-7836.2011.04421.x. PubMed PMID: 21711443.

      21: Moher D. The problem of duplicate systematic reviews. BMJ. 2013 Aug 14;347:f5040. doi: 10.1136/bmj.f5040. PubMed PMID: 23945367.

      22: Siontis KC, Hernandez-Boussard T, Ioannidis JP. Overlapping meta-analyses on the same topic: survey of published studies. BMJ. 2013 Jul 19;347:f4501. doi: 10.1136/bmj.f4501. PubMed PMID: 23873947; PubMed Central PMCID: PMC3716360.


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    1. On 2014 Jan 07, Robert Badgett commented:

      This review includes the important trial comparing acupuncture to simulated acupuncture by Cherkin in 2009 and noted this trial was one of the 7 trials with low risk of bias.(1) However, this trial, which has an unfavorable conclusion when comparing acupuncture to simulated acupuncture, is not included in the analyses within this review.

      Reference:

      Cherkin CD et al. A randomized trial comparing acupuncture, simulated acupuncture, and usual care for chronic low back pain. Arch Intern Med. 2009. doi:10.1001/archinternmed.2009.65. PMID: 19433697


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    1. On 2014 Jan 30, Vivian McAlister commented:

      Some concepts of normal anatomy come from study of diseased cadavers. This paper describes an erroneous concept, perpetuated for 200 years through plagiarism. See final draft here.


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    1. On 2014 Nov 17, Raphael Levy commented:

      Comments available at my blog, authored by 1) Mathias Brust, Liverpool, 2) Quanmin Guo, Birmingham and, 3) Philip Moriarty, Nottingham.

      A detailed analysis of this article, and more broadly of this body of work is published today in PloS One by Stirling et al; from the abstract: “through a combination of an exhaustive re-analysis of the original data with new experimental measurements of a simple control sample comprising entirely unfunctionalised particles, we conclusively show that all of the STM evidence for striped nanoparticles published to date can instead be explained by a combination of well-known instrumental artefacts, strong observer bias, and/or improper data acquisition/analysis protocols.


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    1. On 2014 Mar 02, Daniel Schwartz commented:

      This review is exceptionally thorough and provides nice insights into the therapeutic options in this uncommon but serious complication of hepatitis C infection. http://qxmd.com/r/24024840


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    1. On 2015 Feb 07, Jayaprakash Sahoo commented:

      Current existing literature supports the association of serum testosterone with decreased adiposity and estradiol with increased adiposity in men.Finkelstein et al in their original article have introduced a new paradigm of estrogen deficiency contributing to increases in body fat in men. However, the conclusions of this study are not supported by some plausible pathophysiology.

      The sex steroids (total) are not the only determinants of the fat mass. Alterations in fat mass in study subjects could be contributed by concomitant changes in GH-IGF-1, thyroid, cortisol axes and free sex steroid levels.Local conversion of androgen to estradiol at pituitary level is required for adequate production of GH in a normal adult male. Aromatase inhibitors may lead to adult GH deficiency resulting increased fat mass in them. Additionally, probable GnRH analogue induced hypothyroidism and estradiol induced thyroxine binding globulin changes can also contribute to fat mass alterations by disturbing the thyroid axis. Alteration of free cortisol due to estradiol induced change in cortisol binding globulin levels may be another significant contributor. Hence, a similar study incorporating all hormonal determinants of fat mass is required for clearing uncertainty in the pathophysiology.


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    1. On 2014 Dec 10, Kath Wright commented:

      Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home


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    1. On 2014 Jan 10, Christopher Sampson commented:

      And who would the 'heroes' be? Those for whom the compensation is most likely to compensate them for the loss of their organ (i.e. the poor).

      Here in the UK, when one mentions a hero it is usually in reference to a soldier. The hero narrative is rampant. So who joins the army? In a cursory glance at the literature I find few data for the UK, but plenty for the US. For one, it seems that people are less likely to enlist if they have college educated parents. Why else would the British Army choose to focus its recruitment efforts in the poorest of schools? One wonders whether the (largely) privately educated graduates of Sandhurst will face the same danger to life as their soldier counterparts. Are we really comfortable with our heroes being less well educated than the beneficiaries of their heroism? I, for one, am not.

      There is every reason to suspect that the same would apply to living organ donation. The hero narrative is only "appropriate and useful" as a means of dispelling guilt.


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    1. On 2014 May 26, Marc Girard commented:

      As a drug specialist with a more than 30-year experience in safety, I was often missioned as a medical expert witness in criminal or civil inquiries on vaccine litigations, where I repeatedly pointed out the worrying lack of knowledge of most vaccine experts regarding the basic scientific and regulatory requirements normally applicable to pharmaceutical products – esp. as far as adverse reactions were concerned: this represents a tragic shortcoming for such preventive drugs, targeted towards people in perfect health with the problematic aim of protecting them against diseases the occurrence of which in a severe form is often an unlikely event, and for which therefore the risk of side-effects should not go beyond extremely narrow limits… Amongst many others examples, this paper by Tozzi et al. is an impressive illustration of this lack of expertise a far as drug safety is concerned.

      Whatever the authors’ views on the matter, the primary tool to assess drug safety is not “epidemiological studies” but double-blind investigations versus placebo (a genuine placebo, namely a completely inert product and not another vaccine…) performed during development on a sufficient duration: as everybody knows, vaccine makers have managed the exploit to get exempted of this otherwise inescapable step. Additional indicators of amateurism in vaccine development include “fast track” procedures (whose consequences have been recently illustrated by the narcoleptic risk of Pandemrix), as well as the striking poverty of the dose-ranging studies (which account for regular turmoil in “experts” recommendations regarding the scheme of immunization as well as the timing of boosters).

      As far as “epidemiological studies” are concerned, their main default is of being inextricably polluted by major conflicts of interests, as in most cases, they are performed either by the manufacturers or, even more frequently, by national or international health agencies (or their “experts”) whose most obvious interest is to hide the – sometimes tragic – drama they may have triggered by their irresponsible campaigns to promote some vaccines: this is the reason why, amongst a dozen of such studies performed on the neurological risks of hepatitis B vaccination, the only one showing a clear increase was also the sole whose financing was independent of any promoters of this immunization…

      To come now to the assessment of causality of individual adverse reactions, the first remark is that the methodological inspiration of Tozzi et al. is regrettably obsolete. The use of algorithms has been almost completely abandoned by most regulatory bodies, for one reason which was pointed out more than 25 years ago [1]: namely, that use of algorithms (or decision table) is a tool for clinical decisions (e.g. to perform a laparotomy in view of such and such signs or symptoms), whereas assessing causality in drug toxicity is a process of knowledge, and not of decision (there is not the slightest signification in “deciding” whether a drug is, or not, the cause of an effect – and the reader has just to consider that this incredible way of reasoning is never used to assess drug efficacy, yet another pharmacological effect…). Lack of validation regarding the inter-raters agreement is an additional indicator of the methodological amateurism of the authors: this step should have been a strong prerequisite, taking account the vague of some items (e.g. that concerning an “appropriate time window after vaccine administration”, when experience of such an assessment with academic vaccine “experts” shows that it is almost invariably assessed as too short or too delayed… The same holds true for the item of “biological plausibility”, when experience, once again, teaches the fanatical obstinacy of most vaccine experts to challenge even the biological mechanisms which are most probable or convincing [2]).

      Jacob Puliyel has listed a number of cases where Tozzi et al.’s algorithm would miss obvious vaccine causality. Let’s suggest another, that I witnessed in a number of sad instances: 3 weeks after a first injection, a person develops unexplained asthenia associated with paresthesia; one week after the second immunization, he/she develops motor symptoms, dysuria and visual disturbances; the day following the third injection, he/she is admitted to hospital where the diagnosis of multiple sclerosis is rapidly established. For any specialist in drug safety, the causal role of the vaccination would be highly probable: but not for Tozzi et al.…

      Actually, amongst the 20 items of their checklist, no less than 15 (75%) are devoted to refute a vaccine-induced causality: no need to have read the Complete Psychological Works of Sigmund Freud to recognize the “resurfacing of the repressed” in such a bias. After all and as the authors confess with an astonishing ingenuousness, the main point is it not to “maintain public confidence in immunization programs”? Tell me: in any of the “immunization programs” – including those devised by vaccine makers [3]?...

      REFERENCES

      [1] Girard M. Quality of ADRs. Adv Drug React Ac Pois Rev 1987;4:231-232

      [2] Comenge Y, Girard M. Multiple sclerosis and hepatitis B vaccination: adding the credibility of molecular biology to an unusual level of clinical and epidemiological evidence. Med Hypotheses 2006; 66: 84-86

      [3] Cohen D, Carter P. WHO and the pandemic flu "conspiracies". BMJ 2010; 340:c2912


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    2. On 2014 Apr 18, Amitav Banerjee commented:

      When death is the outcome temporally associated with an intervention such as immunization, it is better to err on the side of safety by presuming all deaths as probably AEFI unless other etiology is established beyond reasonable doubt. Establishing the cause of adverse event or death may not always be possible in developing countries as health facilities are lacking in rural and remote areas. In such situations, "Counting" without "Classifying" would be a more appropriate strategy to establish any AEFI by comparing with baseline data which can again be established by "Counting." Frequent exercises of classification of AEFI, though conceptually sound will not be sensitive enough to detect all cases of AEFI, without the backup facilities required to establish the correct cause of all deaths or adverse events following immunization in remote areas of developing countries. In such resource poor settings better penetration and more equitable distribution of health services and attention to under five malnutrition, in which we fare very badly, would prevent more cases of deaths due to pneumonia in children rather than adding on more and more vaccines. After promoting the pentavalent vaccine in developing countries, one would expect the same experts to promote the pneumococcus vaccine in these countries. One would wish that the policy makers concentrate more on "Health Promotion" which implies better sanitation, nutrition and education rather than on "Vaccine Promotion" which is a piecemeal solution to the problem of communicable diseases at an exorbitant cost. Amitav Banerjee, Professor Community Medicine, Dr D Y Patil Medical College, Pune, India


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    3. On 2014 Apr 09, B M Hegde commented:

      "Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius and a lot of courage to move in the opposite direction,” wrote E. F. SCHUMACHER some time ago. We have many such expert groups in science and, more so, in medicine. “The algorithm should provide countries and health officials at the global level with an instrument to respond to vaccine safety alerts, and support the education, research and policy decisions on immunization safety.” This statement in the last part of the abstract tells the whole story. With the new instrument the response to every ‘vaccine safety alert’ will be denial. The new AEFI algorithm makes it possible to declare almost every vaccine related death as ‘unrelated to the vaccine’ based on the fact that deaths were not attributed to vaccine in the pre licensure studies.

      It was Charles Sherrington, a Nobel Laureate in physiology, who wrote in 1899 when he became the professor of Physiology at the age of 42 in Liverpool University that “positive sciences can never answer the question “why”. They can, at best, answer “how or how much” but NOT “why?” As a physiologist I can say how the heart contracts, but not “why” the heart contracts. In reductionist science of medicine we take shelter under this wisdom to bury all the inconvenient questions. No one can for sure say “why” the child died after vaccination, new AEFI notwithstanding. Common sense, circumstantial evidence, emotional and spiritual quotients in our rounded education to be doctors should help us to answer such questions of cause-effect most of the time. Now even if a healthy child dies within minutes following vaccination and there is no alternate explanation for the AEFI, even then the powers that be could easily declare that death as coincidental and not due to the vaccine, thanks to the new AEFI. This is dangerous ‘science’.

      B. M. Hegde MD, FRCP(Lond.), FRCP(Edin.), FRCP(Glas.), FRCP(Dub.), FACC(U.S.A.). Formerly Vice Chancellor, Manipal Academy of Higher Education, Manipal India


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    4. On 2014 Mar 26, J Stone commented:

      None


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    5. On 2014 Mar 24, Toni Bark commented:

      None


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    6. On 2014 Mar 12, Lokesh Tiwari commented:

      There is conceptual flaw in the ‘Assessment of causality of individual adverse events following immunization (AEFI): A WHO tool for global use’ developed by Tozzi et al. If we apply common sense, fundamental safety rule is to identify threats to safety and fix them. Having so many deaths reported after immunization, particularly following pentavalent vaccine in the developing countries, it is important to develop a more sensitive tool to identify AEFI and classify them according to severity of threat they impose to human life and thoroughly investigate them. As pointed out by Puliyel J and Madhvi Y, Tool developed by Tozzi et al will under report AEFI. Considering sequence of events in the world pertaining to development of vaccines, their business, conflict of interests of health agencies and members of guideline committees, it seems that huge business in vaccine industry is affecting science of vaccines and we are developing various ways to promote the business at the cost of human lives. Compared to Brighton classification, tool developed by Tozzi et al has much less sensitivity to detect adverse events following immunization as it masks probable and possible reactions related to immunization and classifies them as inconsistent or indeterminant categories, giving ways to continue the use of potential risky vaccines. Going for a less sensitive tool for safety concerns is not only illogical but risky for the children of the world.


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    7. On 2014 Feb 20, Jacob Puliyel commented:

      None


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    8. On 2014 Apr 26, Meenakshi Girish commented:

      The admonition "be scientific" - whenever one does not back one's argument by scientific data - now sounds so hollow! Every scientific 'fact', it seems, has two sides. Of late this has become truer for medical science. And if, I as a clinician can get confused, imagine the plight of the lay public for whom it is confusion confounded. While preparing for a debate recently on vaccinations, I was perplexed that the IAP Committee on Immunisation states "The committee reviewed studies on the distribution and prevalence of different pneumococcal serotypes in the country, including some recent studies done by vaccine manufacturers in India like Pneumonet by M/s Pfizer and Alliance for Surveillance of Invasive Pneumococci (ASIP) by M/s GSK (unpublished). The committee concluded that the data on prevalence of different pneumococcal serotypes in the country was sparse and limited to few hospital based studies. On the basis of available data, it is difficult to evaluate the coverage of serotypes included in the existing Pneumococcal conjugate vaccine (PCV) formulations" [Indian Pediatrics July,2012]. Despite this the vaccine has been included in the IAP immunisation recommendations. Is the IAP justified in doing so? On the other hand, would they be wrong if they were to withold the recommendations till large scale studies are carried out.


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    9. On 2014 Mar 24, Paul King commented:

      Dear Jacob Puliyel,

       The points you have raised are excellent.
      
       However, from the scientists' point of view, the reality is that all adverse events following inoculation (AEFIns) should be reported and, unless a causal relationship has been proven or unequivocally disproved, no attempt should be made to classify such AEFIns as they occur.
      
       Instead, a centralized open database system, like the U.S. Vaccine Adverse-Events Reporting System (VAERS), but one which has meaningful penalties for any healthcare provider's failure to report any possible AEFIn to those maintaining this AEFIn database, who after confirming the source of the report, its general validity, the vaccine's identity and lot identifier, and, in as much detail as possible, the temporal and symptoms information associated with that AEFIn, will post it to the database where an open search tool is provided for anyone to examine the data as they see fit (e.g., a search engine like the one available at <http://www.medalerts.org>).
      
       Then, on  vaccine type and specific vaccine source, temporal clustering and, for multiple-dose vaccines, the dose effect should be continually assessed for evidence of a signal (temporal clustering or associated much more with one manufacturer's vaccine than another manufacturer's comparable vaccine or a disproportionate number of AEFIns after the first dose as compared to the second dose when dosing occurs within a several weeks pattern). 
      
      For new vaccines, all observed AEFIns following vaccination, regardless of the events found in the clinical trials used to get the vaccine approved for use, should be treated as possibly causally related UNLESS an in-depth autopsy clearly establishes that the vaccine could not possibly have been a causal or aggravating factor.
      
       In addition, for new vaccines, the government should require the manufacturer to distribute each lot in a suitable small contiguous population segment such that, if there is any possible "lot" effect, the "lot" effect should be more easily ascertained.
      
       Furthermore, before any vaccine is administered to a child, the child' temperature, pulse rate, weight, apparent health and the child's general health history should be recorded and, 30 to 60 minutes after the inoculations given, the child's temperature and pulse rate should be again recorded along with any apparent inoculation-site effects (e.g., redness and swelling) and inoculation-triggered reactions (e.g., fainting).
      
       Finally, absent unequivocal proof that a vaccine inoculation could not have caused conditions that led to a vaccinated individual's death or been a contributing factor thereto, all AEFIns that have death as an outcome should be labeled as probably vaccination related.
      
       From the viewpoint of the scientific method, any classification that establishes artificial barriers and criteria to the inclusion of observed events into the body of knowledge (as the WHO's proposed system so clearly does) should be REJECTED because it interferes with the scientific method's ability to observe all of the data and to generate testable hypotheses and draw inferences from the entire body of post-inoculation AEFIn information that has been generated by the actual events that have transpired. 
      
       Finally, in speaking of post-inoculation adverse events, term "immunization" should be replaced by "inoculation" because, as others have noted, it takes some time (weeks to months) for any significant level of protection to be generated after an inoculation; not all who are inoculated will develop that protection; and many, if not most, AEFIn events occur shortly after inoculation.
      
       The sooner all start being honest about the realities surrounding vaccine inoculation, the more likely it will be that the public will rely on the information provided.
      
       However, if, as the WHO seems to be doing and, in the USA, the U.S. Centers for Disease Control and Prevention (CDC) has been doing for years, public health officials continue to inflate the benefits of vaccination (by at least a factor of 10) and minimize the risks associated with vaccine inoculation (by a factor of 100), then, as is increasingly being observed in the USA and other developed countries, the public will become increasingly wary of vaccination.
      
       In much of the world, people understand that there are no true coincidences -- only events that have been made to appear to be coincidental by either a genuine lack of understand of the overall facts leading to the "coincidence" reported or by the deliberate suppression of the facts, including when, for example, AEFIns that result in death are made to "disappear". 
      
       Hopefully, the WHO will realize the scientific falsity of its current approach to classifying AEFIns in a manner that, in essence, pretends that the death did not occur after the vaccination or that it was a "coincidence" or "is unclassifiable", and abandon that approach.
      
       If the WHO does not recognize the preceding reality, then all of the scientists who study AEFIns in a given country need to demand that their governments reject the WHO scheme as vigorously as they are able!
      


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    10. On 2014 Mar 18, Jacob Puliyel commented:

      Dr Malik, as part of the India Government Ministry of Health, has information on the AEFIs with Pentavalent vaccine and their investigation. I mention individual instances because Dr Malik is familiar with them and it best illustrates the harm done by the new system of AEFI classification.

      Of the 54 deaths reported to the Government of India some have been investigated and the AEFI reports are available here

      The deaths as described below could well have been caused by ‘multisystem generalized reaction to one or more vaccine components’ (page 50 of the CIOMS/WHO report). But a case definition for this entity has not been developed as yet by the Brighton group. When such multisystem reactions occur they appear like the multiple organ dysfunction syndrome (MODS) that follow sepsis but it must not be confused with it. The AEFI committee assumes that all MODS are due to due to sepsis or, if it is associated with unconsciousness, it must be meningitis/encephalitis. The new AEFI algorithm seems to promote and propagate this confusion.

      1) The manner in which the deaths are declared as unrelated to the vaccine is instructive. The first of these deaths was in a child who was vaccinated at 11 AM. That evening at 5 PM the child had fever for which she was given paracetamol. The baby woke up several times that night crying. She was found dead in her bed next morning. There was blood around the nostrils.

      On postmortem examination a large swelling around the injection site 9.8 x 7.9 x 4.7 cm with edema and infiltration involving muscle and subcutaneous tissue was noted. The internal organs including brain, kidneys and lungs were congested. There were petechiae on the surface of the lungs and bilateral adrenal bleeds. The report said the autopsy findings were consistent with death due to hypersensitivity reaction.

      The AEFI report however says the death is unlikely to be a programme error or ‘due to vaccine associated to the vaccination’ (sic)

      2) The central team looked at the 15 deaths in Kerala . One death in Pathanamthitta is reported in detail. The healthy 6 week baby was vaccinated on 26 December 2012 at 12 noon. The mother noted swelling of legs and the baby was ‘grunting’ and reluctant to feed. She was given 4 drops of paracetamol syrup for 'fever and crying' at 5 PM and 2 times on the next day. The baby was found dead with blood stained discharge from the nose at 4-30 AM on the morning of the 28th. No postmortem examination was performed.

      The AEFI report classified this death as “Unknown unclassifiable category” in spite of the fact that the parents are available and gave a detailed history as part of the verbal autopsy.

      3) The AEFI report has more interesting details that I quote verbatim: “Temporality of vaccination with death cannot be established as a causal relationship since it may also be possible that in the child had a subclinical infection (therefore no obvious signs and symptoms) and it aggravated in cold conditions, led to Bronchiolitis and death. This may be the reason for death due to pulmonary edema (manifesting as blood from the nose and in some postmortem findings of blood in respiratory tract).”

      The cold conditions reported as leading to pulmonary edema and death is intriguing. Kerala has a climate that borders between a tropical savanna climate and a tropical monsoon climate. As a result it does not experience distinct seasons. The mean maximum temperature is 34 °C mean minimum temperature is 21 °C and the lowest temp recorded in December in Thiruvanthapuram was 20 °C..

      The death in babies in Kerala who were apparently completely well in the morning when they went for immunization but who became unwell soon after vaccination and deteriorated rapidly to death cannot rationally be attributed to ‘subclinical bronchiolitis infection aggravated by cold conditions’ leading rapidly to pulmonary edema and death.

      Any explanation no matter how outlandish seems adequate but the likelihood of there being a causative association with the vaccination, which is obvious, is not considered.

      This is akin to a person found dead under the rubble after a house collapse. The house-insurance-company may refuse to pay the next of kin, saying the house collapse could have been coincidental and cannot be blamed for the death till it is proved that the deceased had not suffered a heart attack just before the house collapsed.

      4) 8 deaths in Kashmir were investigated by the AEFI team.

      There had been 1 death each in June September and December 2013, but in October there were 11 deaths according to a RTI response (AD/FW/K/RTI/822-24).

      Many local newspapers reported the deaths in October were associated with use of a brand of Pentavalent vaccine called Easyfive which vaccine had previously been disqualified because of quality concerns but had just been reintroduced. Easyfive is not being used in the Kashmir Government immunization programme currently.

      Like in Kerala, the deaths in Kashmir were attributed blithely to sepsis with metabolic disorder (in Aisha who had convulsions and normal CSF and no blood culture evidence of sepsis), meningitis (in Mozim based on persistent vomiting, metabolic acidosis, convulsions and crying excessively), pneumonia with aspiration (in Nida with fast breathing and gasping respiration with a family history of sibling death following pneumonia), liver disorder with metabolic acidosis (in Karneez with fever followed by repeated seizures but no CSF examination), sepsis with metabolic acidosis (in Shaistha crying excessively and irritable for 3 days after vaccination, convulsions on the third day, put on ventilator till death on 9th day). It is paradoxical, these diagnoses were reached on the clinical symptoms and laboratory findings of MODS without specific blood culture evidence of sepsis or CSF evidence of meningitis, suggesting the criteria for making these diagnoses are not strict like the algorithm needed to arrive at a diagnosis of death caused by vaccine. No death was attributed to MODS due to ‘multisystem generalized reaction to one or more vaccine components’. The most obvious possibility is not even mentioned in the differential diagnosis.

      5) The doctors in the Kashmir hospital who noted the sudden increase in cases of deaths in October (11 cases in one month against the previous rate of 1 case in 2 months) sent telephonic text messages to senior government officials in the central government and state government to appraise them of these events but the AEFI team comes down heavily on them for sending these messages "as if to report 'breaking news'". Apparently they were expected not to take notice of these deaths and continue with business as usual and perhaps not to alert anyone.

      It seems that after the October spike in incidence of AEFI deaths, the brand of vaccine was changed and the numbers of death have come down but the Government AEFI report does not mention it. It appears that although all brands of the vaccine have been associated with AEFI deaths in different countries, some brands may be particularly lethal.

      A good AEFI reporting system must have picked up all these linkages which the new algorithm makes studious efforts to avoid.


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    11. On 2014 Mar 13, Jacob Puliyel commented:

      6500 PENTAVALENT-VACCINE AEFI-DEATHS IN INDIA EACH YEAR CANNOT BE ACCEPTABLE

      I thank Dr Malik for endorsing the opinion that the AEFI guidelines need to be revised. Unfortunately neither Tozzi and colleagues, nor Bonhoeffer et al (Bonhoeffer J, 2009) have responded and we do not know if the authors agree with us.

      Dr Malik’s comment points out that India lacks a strong system of AEFI surveillance and investigation. This is undisputable. The fact of this poor surveillance in some States is clearly illustrated by the data obtained under the Right to Information from the Government of India, published by the Center for Science and Environment in their magazine – Down to Earth. Goa - a State with good surveillance and a low infant mortality rate (IMR 10/1000 live births) reported 26 AEFI deaths per 100,000 infants vaccinated with the Pentavalent vaccine whereas Gujarat, with poorer health infrastructure and high IMR, reported only 0.4 deaths per 100,000 infants vaccinated (Gujarat IMR is 50/1000 live births). The correlation between reported AEFI rate and IMR is illustrated here (R2 = 0.458).

      Clearly AEFI deaths (following Pentavalent vaccination) in States like Goa and Kerala is much higher than previously (with the older DPT vaccine). If the Goa 'AEFI-death-rate' (reliable data from the state with the lowest IMR and presumably the best health infrastructure and surveillance systems) is projected nationwide and 26 babies are to die among every 100,000 babies vaccinated, 6500 AEFI deaths can be anticipated when the year’s birth cohort of 25 million babies in India are vaccinated. This cannot be acceptable.


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    12. On 2014 Feb 21, Akash Malik commented:

      In total agreement to my worthy colleagues, the AEFI guidelines do need a revision, but citing an example from India (pentavalent) for this is inappropriate, because India lacks a strong system of AEFI surveillance and investigation.

      It has to be taken into account that deaths after pentavalent (2.0 per lakh 1st doses of pentavalent vaccine),is less than the expected number of deaths (3.56 deaths per lakh live births)in the state of Kerala (Best performing state in India in terms of IMR )and this rate of 2.0 per lakh 1st doses of pentavalent vaccine is still less than the expected number of adverse events due to DPT alone.

      It is important not only to report and highlight numbers, but also to correctly analyse them.


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    13. On 2014 Feb 20, Jacob Puliyel commented:

      Tozzi and colleagues state that their article describes the new tool for causality assessment of AEFI as set out in the User Manual for the Revised WHO Classification

      1) However this manual it seems has been developed without adequate care and without thinking through the consequences of the changes.

      a) One pointer to this is how the manual cites an example of vaccines being wrongly blamed for events unrelated to its administration (Page 13). It says that vaccines were wrongly blamed for deaths resulting from consumption of the Cassia occidentalis beans causing a syndrome of acute hepato-myoencephalopathy. However the article they quote describes Japanese B encephalitis being blamed for the deaths – not the vaccine Panwar RS, 2008

      b) Dr Madhavi put the new classification to a simple test. She tested how the system would have responded if the revised AEFI classification been in place in 1999. She suggests that the intusussceptions following use of RotaShield would have been classified as ‘inconsistent with causal association’ because:

      i) other qualifying factors like previous similar reaction (re-challenge equivalent) were not available

      ii) nor was biological plausibility demonstrated at that time

      iii) and background rate, other exposures etc were not ruled out.

      Under this category ‘inconsistent with causal association’ it would never activate the analysis reserved for ‘indeterminate’ reactions – “Information on AEFIs that are classified as indeterminate should be pooled and analyzed by time and place, in order to understand if the AEFI represents a new signal of an unrecognized event. Should this be the case, a more comprehensive epidemiological investigation should be performed.” Tozzi AE, 2013

      These intusussceptions would have continued for years before the vaccine was pulled off the shelves.

      2) In my previous comment I had pointed out that the experts investigating the Sri Lanka deaths from Pentavalent vaccine deleted the categories ‘Probable’ and ‘Possible’ from the Brighton classification and reported that although they found no alternate explanation for the deaths, the deaths were unlikely to be related to the vaccine. An apologist for the distorted Brighton Classification told me at that time that it was ‘experts’ who developed the Brighton Classification and it is alright for other experts to alter the classification. That was prescient. The new system makes a virtue of this ability to disregard the algorithm when it suits any expert. It says “Finally, instead of assigning a final category through an automatic classification process, the final outcome of the case investigation depends on the personal judgment of the assessor.” Tozzi AE, 2013

      3) Post marketing surveillance is used to monitor the safety of a drug. Since drugs are approved on the basis of clinical trials which involve a relatively small numbers of people who have been selected for this purpose - meaning that they normally do not have other medical conditions which may exist in the general population - post marketing surveillance can further refine, or confirm or deny, the safety of a drug after it is used in the general population by large numbers of people who have a wide variety of medical conditions. (Abridged from Wikipedia)

      The effort of the revised WHO Causality assessment of an AEFI is to deny adverse events noticed on post marketing surveillance, are caused by the vaccine (unless they had been observed in the original small clinical trials).

      Events that occur 1 in 10,000, for example the intussusceptions with RotaShield will be noticed only in post marketing surveillance.

      The AEFI in individuals was responsible for the ‘signal’. Evidence of causality in the individual provided evidence of causality in the population. The new system stands this logic on its head when it says on Page 5 that causality in the population must be known before causality in the individual can be ascribed.

      “Causality assessment of AEFI should be performed at several different levels. The first is the population level, where it is necessary to test if there is a causal association between the use of a vaccine and a particular AEFI in the population. Secondly, at the level of the individual AEFI case report, one should review previous evidence and make a logical deduction to determine if an AEFI in a specific individual is causally related to the use of the vaccine. The third level of assessment is in the context of the investigation of signals.”

      I am not stating that there is something sacrosanct about the original Brighton Classification but one has to evaluate the two schemes (Brighton vs CIOMS) from the point of view of patient safety to see which scheme would react to rare RotaShield-like-reactions first. The causality scheme that insists on calling all reactions as ‘indeterminate’ or ‘inconsistent/coincidental’ just because they were not noticed in the original small clinical trials, undermines the very raison d'être of post marketing surveillance. Patient safety (meaning protecting patients) rather than vaccine safety (protecting vaccines) is what is important.


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    14. On 2014 Feb 15, Y. Madhavi commented:

      The above responses have raised very pertinent and highly contentious issues regarding CIOMS/WHO tool for the causality assessment of AEFI presented in Tozzi et al paper. This tool has negative implications in resource poor settings with poor surveillance systems and inadequate infrastructure.

      Tozzi et al’s model claim to establish the causality between vaccine and AEFI referring to the general and cause-specific definitions of CIOMS (2012), (pages 39-40). However, it is not that simple nor is it really helpful. For instance, intussusception is a known adverse event with rota virus vaccine. But intussusception can also happen without Rotavirus vaccination. Suppose, if it happens in the week after immunization, it is possible that it is caused either by vaccine or it could be that the child was to get it any way and vaccination was coincidence. Yet the CIOMS scheme will classify this as 2A Consistent causal association to immunization [http://www.who.int/vaccine safety/initiative/tools/vaccinfosheets/en/index.html].

      On the other hand had the CIOMS scheme been in use since1999, it is interesting to speculate how these intussusceptions would have been classified given that there was no known causal association. The fact that the event could take place independently of vaccination and no clear biologically plausible explanation linking it to the vaccine, it would be classified as 1A or 4C ‘Inconsistent causal association to immunization’ or ‘C. Coincidental’ [http://www.who.int/vaccine safety/initiative/tools/vaccinfosheets/en/index.html].

      Reactions classified as ‘Indeterminate’ may at some point be evaluated if similar events are reported to identify a signal of a new potential causal association. Reactions classified as ‘Inconsistent causal association to immunization’ are not even reviewed later.

      Dr. Puliyel is correct in suggesting that, a child who develops high fever within 2 hours, has convulsions, then lapsed into a coma and dies within 10 hours following immunization will be classified as ‘unclassifiable’ because ‘encephalitis’ as cause of the event cannot be ruled out.

      Tozzi et al, argue that in the case of ‘events with a consistent temporal relationship but with insufficient evidence for the vaccine as a cause according to well designed epidemiologic studies… further studies are encouraged if other similar events are identified......’. This can be used to defer discontinuation of the vaccine despite adverse effect. Moreover, the requirement for ‘other similar events’ is vague, as it does not specify how many events are needed to suspend vaccination.

      In a recent controversy on AEFI causality report on pentavalent vaccine in India, deaths following vaccination were attributed to sudden infant deaths (SIDS) without doing proper investigation. In the causality assessment of 15/2/13, the AEFI committee reported eight infant deaths as SIDS. However, in a new causality report, which is now available with the health ministry, only one death due to SIDS, three deaths with causal association with immunisation and seven deaths as 'unclassifiable' including those previously reported as SIDS [http://www.pharmabiz.com/NewsDetails.aspx?aid=79591&sid=1]. It is interesting that where sufficient information was previously available to arrive at the ‘diagnosis by exclusion’ of SIDS the information was later considered insufficient enough to merit the new classification as ‘unclassifiable’. “The final classification should be based on the personal judgment of the assessor”, according to Tozzi et al, (page no 5043, under 3.3 Algorithm), and this will result in numerous similar discrepancies in the classification directly related to the number of people whose ‘personal judgment’ is sought.

      In India, there have been around 21 deaths and 83 adverse events reported following pentavalent vaccination which was introduced in a few states last year. Rather than halting the vaccination till its safety is proven, India extended its vaccination to the rest of the states under international pressure.

      If the sole purpose of CIOMS/WHO tool of causality for AEFI is to ensure vaccine safety in the population, the pentavalent vaccination would have been halted in India, as it was done in countries like USA (rotavirus vaccine), till the vaccine safety is established.

      The main emphasis of Causality assessment of AEFI approach seems to be to cite either the lack of strong evidence for causal association or the presence of strong evidence against causal association, to classify an adverse event as “Not an AEFI”.


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    15. On 2014 Feb 05, Brandon Horn commented:

      Drs. Puliyel and King,

      Thank you for the insightful observations. Just wanted to add that antibody response time is quite variable. Theoretically, we would see adverse events also happening weeks to months after introduction to an antigen. Varicella for example produces symptoms typically 10-21 days after exposure. Antibody detection for HIV occurs between 3 and 6 months. Therefore, we could expect some serious adverse events, for example related to autoimmune disease, to show signs up to 6 months+ post-inoculation. This is one of the reason it is so hard to study vaccine adverse events in the United States, because the vaccine schedule makes any pediatric autoimmune disease temporally associated with a vaccination. Animal studies have indicated that this indeed can occur.


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    16. On 2014 Feb 05, Paul King commented:

      In general, as a scientist who studies vaccine safety, effectiveness, and cost-effectiveness issues, I support Dr. Puliyel's observations and suggestions.

      Moreover, the use of the term "coincidental" should be limited to those instances where a full autopsy, including appropriate tissue section examinations fails to find any potential causal or contributory factor that may be related to a preceding vaccination. In science, while it is a reality that the relationship between a specific vaccination and a subsequent serious adverse event MAY be "coincidental", proof is required that all of the other scientifically plausible linkages between the vaccination and the AEFI have been properly considered and ruled out by scientifically sound and appropriate medical evidence BEFORE that AEFI should be labeled as "a coincidence".

      Furthermore, intervening events between the vaccination and the adverse reaction reported should NOT preclude the possibility of the vaccines' given being a possible or probable causal factor UNLESS the intervening event completely accounts for "100%" of the symptoms and findings that may be attributable to the suspected vaccination/vaccinations.

      In addition, when an adverse events occur after vaccination/vaccinations, such events should still be classified as "possibly" or "probably" associated with the suspected vaccine when other probable or possible causal factors are identified UNLESS the other factor(s) completely preclude the vaccine from being a causal factor.

      Finally, when looking at a possible adverse event and a suspect antecedent vaccination set, one should consider ALL of the case's antecedent and concomitantly administered vaccines in light of the their possible contributions to the adverse outcome observed before attempting to assign a possible or probable linkage between a given vaccine and and the adverse-event observed.

      Thus, UNLESS there is definitive proof that some intervening non-vaccine event caused the adverse outcome that was reported, an Adverse-Event Following Inoculation (AEFI) should always remain an AEFI [Note: As an example, a child's death is reported 2 weeks after as the child received an AEFI but the causal event is found to be that an appliance (e.g., a television) was knocked off onto the child while the child was sleeping -- causing the child's death. Only in such instances, should an initial AEFI could be reclassified as a not an AEFI.

      In addition, whenever a "new" vaccination program is introduced, since the goal is to ensure the vaccine being introduced is "safe" and there is no real-world experience in the population as to what serious adverse events may occur or their rate of occurrence in that population, AEFIs that are serious should be presumed to be linked to the "new" vaccination program in question UNLESS there is definitive evidence that only other factors were causal -- especially in instances of deaths shortly after inoculation.

      Furthermore, since most serious adverse events occur shortly after inoculation, the term "AEFI" should be redefined as "Adverse-Event Following INOCULATION" because the vaccine has not had time to generate any effective level of disease protection in the inoculee and, in some instances, the children having the adverse reaction do not develop any level of disease protection -- especially in those instances where the adverse-event is "death" shortly after inoculation.

      Clearly, if the choice is between the Brighton criteria and those being proposed in the WHO "tool", obviously the Brighton criteria should be retained and the scientifically challenged criteria proposed by the WHO should be rejected.


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    17. On 2014 Feb 04, Jacob Puliyel commented:

      DEATHS IN DEVELOPING COUNTRIES WILL COUNT FOR LESS

      Tozzi et al describe causality assessment for AEFI using criteria from the CIOMS/WHO working group on pharmacovigilence . AEFI is any untoward medical occurrence following immunization. A causal relationship is not implied. The Brighton collaboration classified reactions as very likely/certain; probable; possible; unlikely; unrelated; unclassifiable, based on temporal criteria and evidence of alternate etiological explanation. Deaths soon after immunization without an alternate explanation were classified as ‘probably related to vaccine’.

      THE NEED FOR A NEW CLASSIFICATION

      With use of Pentavalent vaccine (Diphtheria, Tetanus, Pertussis, Hib and Hepatitis B) in developing countries, there have been many AEFI deaths. WHO experts investigated these deaths in Sri Lanka. They could find no alternate explanation for 3 deaths. The experts write in the report that they deleted the categories ‘probable’ and ‘possible’ from the Brighton classification and after that, although they could not attribute deaths to another cause, they were declared unlikely to be related to the vaccine. The association to vaccine should have been classified as ‘probable’. The BMJ published a letter about this Saxena KB, 2010

      1. The CIOMS/WHO report came after the BMJ letter. The committee, composed of 40 members (19 were vaccine-industry representatives), proposed changes to how AEFI are investigated and reported. The 194-page document has serious implications for developing countries.

      2. Case definitions for different adverse events were developed. Illogically, the inclusion criteria for the proposed case definitions are too strict to be of scientific value in most countries. For example, to diagnose ‘encephalitis’ one needs the child with fever and encephalopathy to live at least 24 hours after AEFI onset, and have a CSF examination, an EEG or neuro-imaging and one of these investigations must be positive, to reach a level 2 diagnosis (page 73).

      3. Presume that a healthy child is vaccinated. Suppose she develops high fever within 2 hours, has convulsions, then lapsed into a coma and dies within 10 hours. (Variations of this scenario have been enacted repeatedly with Pentavalent vaccine). Using CIOMS/WHO definitions, as the encephalopathy lasted less than 24 hours, it cannot be classified as encephalitis. In many countries, the facilities for a lumbar puncture may be unavailable, much less those for an EEG and CT/MRI. Under the report’s scheme, this would be labeled, “Insufficient information to distinguish both acute encephalitis and ADEM; Case unable to be definitely classified”.

      4. Further, on page 170 (i) (in very small print), the report says, “Such a case must be classified as 'Not an AEFI'”. This last step, which classifies an “AEFI” as “Not an AEFI”, is patently unscientific, illogical and Orwellian.

      5. The scenario described could well have been caused by ‘multisystem generalized reaction to one or more vaccine components’ (page 50). The encephalopathy, fever and convulsions could follow systemic inflammatory response but CIOSM does not have case definition for this, and inability to exclude causes of encephalopathy, is sufficient to classify the reaction as ‘not an AEFI’.

      6. The risk is not merely theoretical. In March 2013 WHO investigated 12 deaths in Viet Nam from the same Pentavalent vaccine. The Viet Nam report stated, “no fatal AEFI has ever been associated with this vaccine”. The 2008 WHO experts had earlier classified the Sri Lanka deaths as AEFI unlikely to be related to vaccine. The Viet Nam report stating ‘no fatal AEFI has ever been associated with this vaccine’ suggests the Sri Lanka AEFI is now reclassified as “Not an AEFI”.

      7. Tossi et al suggest that ‘events with a consistent temporal relationship but with insufficient evidence for vaccine as a cause, according to well designated epidemiological studies – in such cases, further studies are encouraged if other similar events are identified’. There have been 54 deaths temporally related to the vaccine in India. Instead of taking them as a group the new system looks at ‘individual adverse events’ and then labels them as ‘not an AEFI’ making way for many more deaths.

      8. Tossi and colleagues report different clinical scenarios (Supplementary material). The scenario in Asia is also worth considering. Pentavalent vaccine is selectively promoted in developing countries with poor surveillance systems. Eighty three deaths following Pentavalent inoculation have been reported from Asian countries Puliyel J, 2013. There is no plausible alternate explanation. Most deaths occurred after the first vaccine dose, fewer after the second, and hardly any after the third. This pattern argues against the deaths being random events. Yet, the WHO to maintains that a cause and effect relationship has not been established.

      9. This contrasts with what happened in 1998 when RotaShield was approved in the US. When intussusceptions were reported to the Vaccine Adverse Event Reporting System (VAERS) and only 12 children were affected the vaccine was withdrawn. No one needed to be ‘certain’.

      10. A public health expert in India, Dr Y Jain has filed a public interest petition in the Supreme Court asking for these deaths to be investigated. The petition states that in the first six months, when the 40,000 doses were administered to children in the southern state of Kerala, at least five children died. Extrapolated to the 25 million babies born in India each year, 3,125 deaths can be expected from the vaccine each year. Using the best evidence from the Minz study Minz S, 2008 the incidence of Haemophilus influenzae type b meningitis in India is 7/100,000 children under 5. Using the Unicef rapid method to estimate Hib Pneumonia 350 deaths from Hib disease will be prevented over 5 years by vaccinating one birth cohort of 25 million. 3125 deaths from AEFI cannot be acceptable to prevent 350 Hib deaths.

      11. The Infant Mortality Rate (IMR) in Kerala is 14. Seven of these deaths occur in the first month. The other seven deaths occur in the remaining 11 months of the infant’s first year. Pentavalent vaccine is administered six weeks after birth to babies who have survived neonatal life. Of the first five deaths from the vaccine, four occurred within 24 to 48 hours of the first dose of this vaccine. The death rate of babies in the first days after vaccination works out to be two to four times higher than Kerala’s post neonatal IMR.

      12. The first 14 deaths in Kerala were investigated by AEFI experts. They reported 6 children had co-morbid conditions and the other 8 died of sudden infant death syndrome (SIDS). This SIDS rate on day after vaccination is higher than the all-cause IMR.

      13. Under the new scheme, fatal AEFI in developing countries will be falsely recorded as ‘Not an AEFI’, simply because some time or test criterion was not met. Death is the worst AEFI possible. Continued use of the CIOMS/WHO scheme will result in missing an important opportunity to pick up signals that could save lives. This is dangerous. Perhaps we need to get back to the Brighton Classification.


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    1. On 2013 Sep 26, Markus Meissner commented:

      Dr Clare Harding (Meissner group):

      This study by Farrell and Gubbels continues this group’s work in understanding the unusual method of cell division in Toxoplasma gondii, specifically the role of the kinetochore, a complex of proteins used to attach the centromere to the spindle fibres in mitosis. In Toxoplasma, unlike in mammalian systems, there is now convincing evidence that chromosomes remain attached to the spindle core throughout the cell cycle. This suggests that the kinetochore could be dispensable in Toxoplasma replication. The authors demonstrate that two conserved kinetochore proteins, TgNuf2 and TgNdc80, remain associated with the spindle core throughout the cell cycle in Toxoplasma. Although ablation of microtubules resulted in a partial disruption of kinetochore clustering, microtubules were not absolutely required for this localisation. Interestingly, conditional knock-down of TgNuf2 resulted in a complete inability of the parasites to grow. As predicted from other organisms, a reduction of TgNuf2 resulted in chromosome miss-segregation.<br> Knock-down of TgNuf2 resulted in simultaneous depletion of TgNdc80. This suggests these proteins form a stable dimer, which has been demonstrated using human proteins however remains to be confirmed in Toxoplasma. However, depletion of both proteins complicates the picture with regards to the phenotype observed. The authors were unable to identify any other components of the kinetochore through homology to other organisms and several key components of these pathways appear to be missing in Toxoplasma. In order to fully understand the role of the kinetochore in Toxoplasma cell division, more components of the kinetochore need to be identified, potentially using a pull-down approach. The identification of a putative novel nuclear localisation signal (NLS) for apicomplexan parasites is potentially interesting and the authors have demonstrated that this sequence is important for the localisation of TgNuf2. However, as the authors mention, it is possible that this domain is required for the structural integrity of the protein; hopefully future studies will address this issue in more depth.<br> Overall, this is a very interesting paper which significantly adds to our knowledge of the molecular mechanisms of cell division in this apicomplexan parasite.


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    1. On 2014 Mar 01, David Mage commented:

      The author is correct that infant asphyxia of overlaying by a co-sleeper has an equal risk for both males and females Williams FL, 2001. However, he is incorrect that the ratio of male to female infant deaths by SIDS is usually 2:1. When all SIDS studies are combined the male fraction goes to 0.61 corresponding to a male:female ratio of 3:2, not 2:1 Mage DT, 2004, Mage DT, 2014.


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    1. On 2014 Nov 17, Denis Lebel commented:

      The administration process is a complex one. The authors of this paper did a very good job of identifying drug administration sub-steps. This paper should be read by anyone planning the implementation of a computerized medication administration record.


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    1. On 2013 Oct 30, Edurne Zabaleta-del-Olmo commented:

      It is an interesting review article which highlights the barriers to collaborative work between nurses and physicians practitioners in primary care health. The most common barrier is the lack of awareness by physicians of the scope of nursing practice. Working in partnership is essential so it is necessary to build the strategies intended to promote it. Congratulations to the authors.


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    1. On 2014 Mar 11, Harsha Radhakrishnan commented:

      For someone like me with a limited understanding of how MRI works, this is an amazing paper.


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    1. On 2013 Oct 05, Daniel J Simons commented:

      The paper implies that game training allows adults to perform as well as 20 year olds when multitasking. What it actually shows is that after training on the game, older adults perform as well as younger adults who are playing that same game for the first time. It does not show that training allows the older adults can multitask as well as the younger subjects in any other context. For example, the training did not lead to differential improvements on an a dual-task outcome measure.

      The study had a small sample size (about 15/condition), and the analysis did not correct for multiple tests, meaning that it is not clear whether training led to any reliable improvements on the outcome measures.

      The paper also did not control for expectations in the training and control group, meaning that any differential improvements upon re-testing could be due to differential placebo effects.

      I have posted an extensive post-publication review of the paper here: http://blog.dansimons.com/2013/09/19-questions-about-video-games.html


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    1. On 2015 Feb 12, Tamás Ferenci commented:

      EDIT (2015 Feb 13): I removed my comment for reasons of elegance, as Dr. Miller's original comment - to which I was solely replying - was also removed.


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    2. On 2015 Feb 12, Clifford Miller commented:

      None


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    3. On 2015 Feb 11, Tamás Ferenci commented:

      Dear Dr. Puliyel,

      re: the TOKEN study. You quote Table 31, which (a) pertains not to the hexavalent vaccine, but rather hexa- and pentavalent combined (I'll return to the significance of this shortly), and (b) presents the results of the unweighted analysis.

      Let us first examine what weighting means. It is possible to compensate for the preferential enrollment of those who were recently vaccinated (which is not only a theoretical possibility, rather, its existence has been empirically demonstrated in the study), by a method called inverse-probability weighting, thus providing better estimates. Not only I'm saying this, but the authors of the study themselves (p. 13):

      The results obtained from these weighted analyses are regarded as more valid and are therefore presented in this summary. For reasons of completeness, the unweighted analyses are reported in the full study report in addition to the weighted risks estimated.

      So, you were quoting the less valid results, which were only presented for the sake of completeness. Let us now go to your other source, Table 36. It is at least a weighted analysis, but the first problem still lingers: it is again not pertaining to hexavalent vaccine, but hexa- and pentavalent combined. The problem is, that the results are dominated by the effect of pentavalent vaccine (cf. Table 41), which is on the one hand not the issue discussed here, and on the other hand, it was also the more error-prone part of the study, given the fact that only 14 pentavalently vaccinated subjects were included (as compared to the almost hundred hexavalently vaccinated). For objectivity, I once again quote the authors of the study (p. 14):

      In addition, response rate was especially high for parents whose deceased child was recently vaccinated with a pentavalent vaccine. This self-selection and the very low number of cases substantially limits interpretation of these findings.

      Now let's move on to the issue that is actually discussed for this article, the hexavalent vaccine. Table 27 presents the results with the weighted analysis in the 1st and 2nd life-year combined: there is no increased risk neither with Model 1, nor with Model 2 (just to refer to your remark...), Table 28 shows the results for 1st year alone: there is no increased risk neither with Model 1, nor with Model 2. Tables 29 and 30 presents the results of the stratified analyses, none of which shows increased risk.

      I also note that there was a case-control part in addition to the SCCS, which found no increased risk in any of the investigated scenarios.

      re: reporting bias. I believe we have discussed everything here, just one very minor addition, which cropped up when I was browsing the comments. At another point, Dr. Miller is quite strongly arguing that 90% (!!!) of the adverse events, even serious adverse events, he specifically added (and used in the calculations for SIDS), don't get reported. Now 90% is not reported or these events are "investigated thoroughly" and thus "ascertainment bias is not likely to play a major role"...? You should decide..


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    4. On 2015 Feb 06, Jacob Puliyel commented:

      None


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    5. On 2015 Feb 05, Tamás Ferenci commented:

      Dear Dr. Puliyel,

      Thanks for your response. Let me have a few comment on it.

      If the reporting is so bad the clusters aren't real, then the data can't/shouldn't be used to defend its safety.

      Or to question it... Actually, I very much do hope that it is not used, at least in itself, to "defend" its safety: like I already discussed, this data simply can't be used for such purposes, the sole application is to warrant the performing of active safety studies (which have been done).

      3A data is self-reported. It is no crime if a parent does not report to the doctor that their child developed leg pain a few days after being administered Infanrix.

      For the record, 3A includes only serious adverse events, ranging from ITP through haematochezia to anaphylaxis, and yes, it even includes deaths. While I agree that reports made by parents can not be compared to reports made by physicians, comparing such adverse events to "leg pain" is not too fair, either.

      Forensic experts are unlikely to ‘forget’ to mention immunization, simply because it was not given on the day of death but on the previous day.

      By this, we get back to the first half of the 1st remark in my original comment (which you have not addressed). Under the circumstances you described, we could very well argue that such "professional forensic experts" are also unlikely to forget a vaccination a week ago as well, yet, it can be easily demonstrated that in reality this needs to be the case, see my original comment.

      But it is difficult to argue convincingly that higher under-reporting is likely on the day just after a vaccine is administered, compared to the day of vaccination.

      Actually, we don't need to: Day 1 is not significantly different from Day 0, Day 2 is the same as Day 1, so the first point where the number of reports truly drops is at the third day.

      Tables 31 and 36 show significantly increased risk of unexplained sudden unexpected death in the first 3 days after hexa- or pentavalent vaccination (1st and 2nd year of life).

      While I am not specifically familiar with the TOKEN study, it is immediately clear that you only cited half of the results: those tables also reveal that while there is indeed a period of increased risk on day 0-3, but this is followed by a period (day 4-7) of decreased risk, the net effect of which is an unchanged risk...

      So it appears that active studies have confirmed that there are two vaccines which cause 'sudden deaths'.

      OK, so we have a range of studies cited by Dr. Franco (none of which you have addressed), all having negative result, a SINGLE study which you cited, whose results are summarized by its own authors as "[t]he main study analysis showed no increased risk of sudden death within one week after hexavalent vaccination [...] multivariate case-control analysis [...] was in accordance with this finding and did not suggest a risk increase within one week after hexavalent vaccination", and you described this situation as "active studies have confirmed that there are two vaccines which cause 'sudden deaths'". Well...


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    6. On 2015 Feb 04, Jacob Puliyel commented:

      I thank Ferenci and Miller for their responses. I will address the three points made by Dr Ferenci

      1) The data I have quoted (from Table 36) was made available by the manufacturers GSK, to defend the safety record of Infanrix Hexa to the regulatory authority (- the EMA). The data suggests a cluster on and following the day of vaccination. If the reporting is so bad the clusters aren't real, then the data can't/shouldn't be used to defend its safety. If the reporting is good, then the clusters are real too, and the vaccine looks unsafe.

      2) Dr Ferenci writes “ ..it is immediately obvious from 3A appendices (pp. 301-522, pp. 857-1064) that no matter which disease-group we look at, the vast majority of spontaneous reports with known time are definitely coming from the first few days!”

      The sources for the the reports in the 3A appendices are different. 3A data is self-reported. It is no crime if a parent does not report to the doctor that their child developed leg pain a few days after being administered Infanrix.

      But SIDS deaths are different and have to be reported mandatorily to those like coroners who must determine the cause of death. They are investigated by professional forensic experts. SIDS are ‘deaths under suspicious circumstances’ - unexplained death that could be infanticide unless proved otherwise. Forensic experts are unlikely to ‘forget’ to mention immunization, simply because it was not given on the day of death but on the previous day. Reporting bias is less likely to be an issue with such forensic reports. Under-reporting on all days will of course still occur for all the reasons it occurs for other serious adverse events. But it is difficult to argue convincingly that higher under-reporting is likely on the day just after a vaccine is administered, compared to the day of vaccination.

      3) Finally, Dr Ferenci says that active vaccine safety studies are better than passively acquired data. For well designed, managed and executed studies I wholeheartedly agree with him.

      The TOKEN study aimed to assess comprehensively a possible causal relationship between vaccination and unexplained sudden unexpected death of children between their 2nd and 24th month of life. The study was supported and sponsored by the Paul-Ehrlich-Institute (PEI) and the Federal Ministry of Health (Bundesministerium für Gesundheit). Unfortunately this large study with a wealth of data has not been published in an indexed peer reviewed journal as yet. It is available here: http://www.rki.de/DE/Content/Gesundheitsmonitoring/Studien/Weitere_Studien/TOKEN_Studie/Studyreport.pdf?__blob=publicationFile

      Parents of children who had died of SIDS were requested to participate in the study. 37.6% (254 cases) could be included in the study, where parental consent was obtained. Tables 31 and 36 show significantly increased risk of unexplained sudden unexpected death in the first 3 days after hexa- or pentavalent vaccination (1st and 2nd year of life).

      So it appears that active studies have confirmed that there are two vaccines which cause 'sudden deaths'. I am grateful that the Italian Court has allowed public scrutiny of GSK's PSUR reports held as confidential by the EMA.

      Jacob Puliyel


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    7. On 2015 Feb 08, Clifford Miller commented:

      There is a matter to add to my above comments concerning the Observed/Expected analysis provided by GSK to the European Medicines Agency [EMA] and to my exchanges with Dr Ferenci here: http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8920

      Where death and vaccination occurred on the same day, unlike any death occurring after the day of vaccination, only half the children who would have been expected to die by chance alone would have been vaccinated.

      As vaccination appointments can take place at any time during the daytime, one has to adjust for the expected number of deaths by chance where the child died without being vaccinated.

      Neither GSK nor the EMA appear to have considered that point judging by the information in GSK's PSUR's 15 and 16.

      SIDS cases are often found in the early hours of the morning and can also die in their sleep at any time during daytime.

      This would mean that half the number deaths expected by chance on Day 0 would have been of vaccinated children. So only half the number of spontaneous reports would be expected.

      Spontaneous reports of adverse events cannot be relied upon to state the exact times of death nor of vaccination. The detailed narrative accounts of cases in GSK's PSURs 15 and 16 support this. So it seems unlikely that Day 0 means a period of 24 hours commencing from the time of vaccination but merely means the calendar day starting from and ending at midnight.

      On such a basis, if all deaths occurred on the first dose the number expected by chance to die regardless of vaccination would be 162 and not GSK's 54. The data suggests one must weight the expected deaths as it seems more deaths were on the day of the first dose - namely on the same day as vaccination. So one would expect by chance alone a lower number than 162 deaths, but a higher number than 54.

      Adjusting for underreporting running at 90% in a country, the UK, with better reporting rates than most other countries this brings us to expect no more than 16 spontaneous reports of sudden deaths to occur by chance on the day of first vaccination if all 162 deaths expected by chance were vaccinated.

      But if only half the number of children who might be expected by chance to die are vaccinated [81] then one expects no more than 8 spontaneous reports of deaths associated with contemporaneous vaccination to be by chance compared to the 16 actual reports.

      What is remarkable about that is 16 deaths were observed. This is in close correspondence within the same order of magnitude with a crude estimation of the number of spontaneous reports one might expect by chance to coincide with vaccination [ie. 8].

      In addition, the healthy vaccinee effect being greatest on the first day of vaccination [1] indicates a low likelihood these are spurious mere coincidences. And as Dr Puliyel has observed, sudden deaths of children are investigated as potential cases of infanticide, unlike other kinds of deaths. And ~90% of the spontaneous reports were by medical professionals.

      So one has a greater degree of confidence such reports are more reliable and that the reports are of children who died because they were vaccinated and not because it is mere coincidence. The numbers do not support the latter conclusion.

      As noted previously, the proper comparison is not what GSK submitted to the EMA but between the number of spontaneous reports to be "Expected" by chance and those "Observed".

      I note Dr Puliyel asked for peer review of his observations. I too ask the authors of this paper to do the same for those I have set out.

      [1] https://www.ruor.uottawa.ca/bitstream/10393/31774/1/Hawken_Steven_2014_thesis.pdf

      EDITED FOR GREATER CLARITY @ 14:30 GMT 8th Feb 2015


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    8. On 2015 Feb 05, Clifford Miller commented:

      Whichever way one looks at this problem, the reports of sudden death do not look like they should be considered in any way coincidental.

      Ignoring the observed clustering of reports on the day of and days following vaccination, if the GSK figure of 54 is not the number of deaths to be expected on any day but the number of deaths to be expected to coincide with any one of the three vaccinations in a 180 day vaccination period: 1) without correcting for underreporting; 2) assuming the rate of sudden death GSK used is applicable for the periods concerned; 3) the healthy vaccinee correction of 0.8 is applicable; and 4) this is not confounded by co-administration the same day with any other vaccine, then one would expect 54 deaths to coincide with the day of vaccination over the course of three vaccines.

      It is not however the correct calculation for the number of deaths to be expected to be reported. And that is what GSK and the EMA should have compared.

      Ignoring 2), 3) and 4), underreporting of serious adverse events to safety regulators is high. Correcting for underreporting using the rate observed in a country with good rates of reporting, then GSK's 54 figure becomes 5.4 expected reports [90% underreporting of serious adverse events] compared to 16 reports of observed actual deaths:

      "Compared to other countries the number of spontaneous reports submitted in the UK is relatively high and reporting rates in relation to prescription volumes are also among the best in Europe.2 It is estimated, however, that only 10 per cent of serious reactions and between 2 and 4 per cent of non-serious reactions are reported.2 Such a high level of under-reporting will necessarily lead to bias in the data collected via the Yellow Card Scheme." BMA Board of Science Reporting adverse drug reactions A guide for healthcare professionals May 2006

      Even if we assume a highly conservative figure for underreporting namely that 2/3 of serious adverse events are not reported, the GSK figure becomes 18 compared to the observed 16.

      And the healthy vaccinee correction may be optimistic. A 2014 thesis published by the University of Ottawa shows that on the day of vaccination serious ill health in children is 1/3rd of that on any other day, so one would expect spurious reports of merely coincidental ill-health to be 1/3rd of those on any other day including being lower than on the day following vaccination:

      https://www.ruor.uottawa.ca/bitstream/10393/31774/1/Hawken_Steven_2014_thesis.pdf

      The position is confounded by Infanrix Hexa being co-administered with two other vaccines on the same day - so it is not the only vaccine to be considered. According to Wyeth's [now Pfizer] PSUR 4 for Prevenar 13 the rate of reported neurological complications is highest when co-administered with Infanrix Hexa, lowest when administered alone and when administered with any other vaccine the figure lies between the two. [1]

      [1] Prevenar 13 : PSUR 04 – Response to RSI MA numbers: EU/1/09/590/001-006


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    9. On 2015 Feb 04, Clifford Miller commented:

      My reply to Dr Ferenci [2015 Feb 03 2:20 p.m.] now appears beneath his comment [2015 Feb 02 09:30 a.m.]. The EMA's failure to notice GSK's error in calculating the number of sudden deaths per day predicted to be expected by chance as three times too high [54] instead of what it should be [18] is addressed. The population to a reasonable approximation for these purposes is not 54.7 million doses but 54.7m doses / 3 administered per child.


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    10. On 2015 Feb 03, Clifford Miller commented:

      None


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    11. On 2015 Feb 06, Clifford Miller commented:

      Dear Dr Ferenci,

      Thank you. I am not repeating what you said. My comments are in the context of my overall comments to which I made express reference here:

      http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8956

      Perhaps you might like to summarise your responses to all the observations made in the context in which they were made. By such means we can see what is common ground.


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    12. On 2015 Feb 05, Tamás Ferenci commented:

      Dear Dr. Clifford,

      I believe you are practically repeating, almost literally, what I said in my very first reply. Let me quote myself:

      [S]trictly speaking "all of which can result in an SIDS" is only true if these events are independent, which might not be the case, but assuming that such event can only and exclusively occur after the first vaccination (and the probability at the further vaccinations is zero, conditional on surviving the first), which would give rise to your calculation, is no less irrealistic in my opinion.

      Thus, my conclusion is unchanged: Nevertheless, I agree with you that this issue would have worthed at least a discussion in the PSUR, it'd have been elegant to discuss it, but at this point, I don't see that it is "plain wrong", as suggested by your comment.

      Let me also add that even if you are correct that most deaths happened after the first dose, this is still not a conclusive evidence per se: SIDS has a decreasing age-specific incidence curve at this age range, so higher dose repetition numbers coincide with higher age which is in turn associated with lower risk itself. I.e. these two are confounded.


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    13. On 2015 Feb 05, Clifford Miller commented:

      Dear Dr Ferenci,

      Thank you. If one assumes an equal probability of death per dose then exposure is more relevant. If death is more likely on the first dose then the population is more relevant.

      See also my comment above: http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8956

      GSK's 54 expected deaths figure is based on an equal likelihood on each exposure. This ignores the likelihood of death on the first dose. The data GSK provided to the EMA appears misleading. The figure for deaths expected by chance should be much much closer to 18 than to 54.

      GSK's individual case report data in PSUR's 15 and 16 shows the following distribution of deaths for those reports which included the information:

      7 @ 2 months, 8 @ 3 months, 1 @ 4 months, 2 @ 5 months, 1 @ 6 months 1 @ 11 months.

      Some of the deaths aged 3 months may be first dose vaccinations given at 2 months or could also be late first doses at three months. The age at vaccination is not given.

      The interval between vaccination and death for these deaths was between 0 and up to 14 days [with one at 24 days].

      The EMA SPC dosage schedule for these ages states:

      The primary vaccination schedule consists of three doses of 0.5 ml (such as 2, 3, 4 months; 3, 4, 5 months; 2, 4, 6 months) or two doses (such as 3, 5 months). There should be an interval of at least 1 month between doses.

      The Expanded Program on Immunisation schedule (at 6, 10, 14 weeks of age) may only be used if a dose of hepatitis B vaccine has been given at birth.


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    14. On 2015 Feb 05, Tamás Ferenci commented:

      Dear Dr. Miller,

      cited in your comment 54 million as the population figure when the maximum upper limit is 18 million to a good approximation.

      Like I have discussed in my comment, the question is not the size of population, but the exposure. These are different concepts; this was just the main point of my discussion.


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    15. On 2015 Feb 04, Clifford Miller commented:

      Dr Ferenci,

      Thank you for your response.

      GSK and the EMA appear to have made the issue of an Observed/Expected analysis central to the matter. That appears the main point - what to a reasonable approximation is the Expected figure to compare to the Observed 16 real spontaneous reports of real deaths of real children occurring on Day 0 [the day of vaccination].

      The correction required to the approach used by GSK is to use a realistic figure to a good approximation for the maximum population.

      At the moment the position with that correction appears to be 18[E]:16[O] to a good approximation for these purposes [albeit without yet making a correction for underreporting].

      I put the issue of the population to you because your comment states you are a senior lecturer in biostatistics and because of course you chose to comment on the matter and cited in your comment 54 million as the population figure when the maximum upper limit is 18 million to a good approximation.

      As for your other points, in the light of the foregoing, in my view it is the GSK O/E analysis which needs to be addressed - all else at this time being surplusage.

      It is of course open to any of the authors or others who have commented who also used the figure of 54 million as representing the size of the population to comment.


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    16. On 2015 Feb 04, Tamás Ferenci commented:

      Dear Dr. Miller,

      Thanks for your remark.

      Let me note, however (as you submitted your comment as a reply to mine), that my 2nd comment and the second half of my 1st comment is in no way dependent on the size of the background population, so they remain completely intact, even if your criticism is correct. The first half of my first comment indeed depends on the background size, but - as I have pointed out - the discrepancy is in excess to two magnitudes, so a factor of 3, even if you are correct, doesn't affect qualitatively my conclusion.

      As a side note, I also can't completely agree with your logic. You are correct that this way, the same child is counted several times in the background population, but don't forget that the same child - save for those who die, but their number is of course negligible even compared to 18 million - is also exposed several times! (All of which can result in an SIDS and those results are counted together in Table 36.) Well, strictly speaking "all of which can result in an SIDS" is only true if these events are independent, which might not be the case, but assuming that such event can only and exclusively occur after the first vaccination (and the probability at the further vaccinations is zero, conditional on surviving the first), which would give rise to your calculation, is no less irrealistic in my opinion.

      Nevertheless, I agree with you that this issue would have worthed at least a discussion in the PSUR, it'd have been elegant to discuss it, but at this point, I don't see that it is "plain wrong", as suggested by your comment.


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    17. On 2015 Feb 03, Clifford Miller commented:

      Dr Ferenci,

      The number of daily sudden deaths to be expected by chance is just in excess of 18 and not the number GSK reported to the EMA. One must not equate the number of doses sold [54.7 million] with the size of the population. The maximum vaccinated population is 18 million.

      This means the number of sudden deaths predicted by chance using GSK's proposed annual rate of .454 per 1000 and healthy vaccinee factor of 0.8 is 18.

      To that you must compare the number reported in spontaneous reports. That number according to GSK is 16 dead children, [and that is without correcting for underreporting].

      Of the number of doses sold GSK estimate the number used for Year 1 is 54.7 million. Each child historically was to receive three doses according to the EMA Schedule. The authors of this paper suggest a 4 dose schedule is being adopted so 18 million is an upper boundary and that ignores over-vaccination, spoils and other wastage.

      It is therefore a little troubling that the report to the regulator was so far in error and that the EMA appears to have failed to have noticed.


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    18. On 2015 Feb 02, Tamás Ferenci commented:

      Dr. Puliyel’s comment raises important questions about the time clustering of adverse events observed in passive vaccine safety data, i.e. the pattern of temporal association of adverse events with vaccination – which is the only thing that can be investigated using such data –, however his approach neglects an important aspect thus leading to unfounded conclusions in my opinion.

      The major issue was raised by Dr. Franco, but let me add two further remarks.

      1) While it is obviously clear for everyone that we will never be able to surely tell the exact role of reporting bias (and thus the real effect of the vaccine on SIDS, if there is any), there are two points that worth mentioning in my opinion, which were not raised by Dr. Franco:

      • The fact that Dr. Puliyel’s calculation is flawed can be simply demonstrated using his own data. Let’s have a look at the method where he calculated excess deaths using “the second 10-day-window-period as the baseline SIDS rate”. Using the data from the <1 year old, his method would result in 2 deaths in 10 days, which means 73 deaths in a year (assuming linear rate within the first life-year, as in the PSUR), which means – using a background population of the size of 54.7 million – an SIDS rate of 0.00133 per 1000 which is two magnitudes (!) smaller than what is actually reported in the literature. As SIDS rate simply can’t be that low, we can conclude that Dr. Puliyel’s assertion on ascertainment bias “not playing a major role” is definitely wrong.
      • In his second comment, Dr. Puliyel referred to the fact that there is a substantial drop even after the first three days. Although at first glance it is tempting to agree with Dr. Puliyel that “[i]t is difficult to imagine that reporting bias is responsible for this big a change, in so short a time”, actual data shows otherwise. While I have not compiled a comprehensive statistics, it is immediately obvious from 3A appendices (pp. 301-522, pp. 857-1064) that no matter which disease-group we look at, the vast majority of spontaneous reports with known time are definitely coming from the first few days! And these can be used for comparison, because 3A also only includes – by definition – serious events. Now either the vaccine is causing everything from “Blood and lymphatic system disorders” to “Vascular disorders” (which is perhaps not something that Dr. Puliyel suggests…) or there is in fact a dramatic drop in reporting rate just after a few days.

      2) Finally, let me note that I have a feeling that Dr. Puliyel misunderstands the applicability of passive data. Due to the inherent bias outlined above, such data simply can not be used alone to make conclusions on causality. Rather, their aim – among others – is to detect “suspicious” cases, which can be then specifically investigated with appropriately designed active vaccine safety methods, which are capable – as opposed to what we can do from passive data – to draw causal conclusions. There is no point in claiming that by applying “better” methods, we detected causality from passive data, because this is simply impossible, the only thing that can be meaningfully asked for if we detect something suspicious (using any method, including Dr. Puliyel’s) is to perform an active study. But these have been conducted (as pointed out by Dr. Franco)! Now Dr. Puliyel either accepts their results, or questions their methodology (which is a separate issue), the only thing he can’t do is to question the results of an active study based on passive data.

      Conflict of interest: None.

      Tamás Ferenci PhD

      Senior lecturer (biostatistics), Óbuda University, Budapest, Hungary

      John von Neumann Faculty of Informatics, Physiological Controls Group


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    19. On 2015 Jan 22, Jacob Puliyel commented:

      I thank the authors for their response to my comment.

      I was presuming that in the countries from where this data was gathered, sudden infant death or SIDS is considered 'unnatural death'. If that is so, these deaths will have been investigated by a competent forensic team and the immunization records will have been examined to check if the infant was up to date with its vaccinations or whether there was an element of neglect. Reporting bias (based on parents perception that vaccine was the trigger for events that lead to the death of their child) would have little or no role under these circumstances.

      The authors quote from the 'Guidelines for good pharmacovigilance practices'; that events that are expected, common and mild, or occur late after vaccination, are less likely to be reported. That is not applicable here, as SIDS is completely unexpected and a catastrophic event.

      Further, the analysis in Table 2 of the linked article http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version) shows that there were 42 deaths in the first 3 days and only 16 in the next 3 days. It is difficult to imagine that reporting bias is responsible for this big a change, in so short a time.

      We will need to find a more plausible explanation. Otherwise we have to accept that the deaths were caused by the vaccine and the diagnosis of SIDS was wrong.

      Jacob Puliyel


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    20. On 2015 Jan 21, Elisabetta Franco commented:

      Dr Puliyel’s analysis uses the period of 10-19 days post-vaccination as a control for the period of 0-9 days post-vaccination to determine whether there is an excess of Sudden Infant Deaths (SIDS) in the first ten days following administration of Infanrix-hexa. The opinion of all the Authors is that the suggested imbalance in reported SIDS between 0-9 days and 10-19 days periods represents a well recognised bias in spontaneous report reporting, where the shorter the time that has elapsed between the vaccination procedure and the event, the more likely it is to be perceived as a trigger and subsequently be reported. Conversely, events that are expected, common and mild, or occur late after vaccination, are less likely to be reported [1]. Many studies have demonstrated an absence of causal association between vaccination and SIDS [2,3]. Post marketing data are shared on a regular basis with regulatory authorities worldwide [1,4], who support this position [2,3].

      1. Guideline on good pharmacovigilance practices (GVP) Product- or Population-Specific Considerations I: Vaccines for prophylaxis against infectious diseases (9 December 2013) (OE analyses section) http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2013/12/WC500157839.pdf [Accessed on 13JAN2015])
      2. World Health Organization http://www.who.int/features/qa/84/en/
      3. Center for Disease Control and prevention, Atlanta, USA http://www.cdc.gov/vaccinesafety/Concerns/sids.html
      4. ENCePP Guide on Methodological Standards in Pharmacoepidemiology, http://www.encepp.eu/standards_and_guidances/methodologicalGuide9_2.shtml


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    21. On 2015 Jan 19, Jacob Puliyel commented:

      Apropos the earlier posting there are a couple of other facts that we must consider when looking at the incidence of sudden unexplained deaths immediately following vaccination with Infanrix.

      a) The safety assessment document has used the number of doses of vaccine distributed as the denominator. The report acknowledges that all the doses of the vaccine distributed, need not have been utilized.

      There can be another argument against using this denominator. As each child is given up to 5 doses (https://www.gsksource.com/gskprm/htdocs/documents/INFANRIX.PDF) and they could die after any one of the doses (and you can die only once), perhaps it would be more appropriate to look at the number of deaths against the number of babies vaccinated (rather than the number of units of vaccine distributed). The appropriate denominator would be about one fifth the denominator used in the report.

      b) Appendix 5A in the document sent to the regulator gives the International Event Report in 13 fatal cases. It can be seen in this sample that there were more deaths after the first dose than after the second and more after the second than after the third dose. This is a pattern seen with adverse events following immunization (AEFI) that are causatively related.

      c) In May 2005, Zinka and colleagues have reported six cases of sudden infant deaths caused by another hexavalent vaccine (similar to Infanrix), called Hexavac Zinka B, 2006. Marketing authorization in the European Union was withdrawn in August 2005 (Doc.Ref.EMEA/207369/2005).

      d) The CIOMS /WHO have revised the widely used Brighton Protocol for assessment of AEFI. The new scheme facilitates misclassification of vaccine related deaths as [Not an AEFI] and this has been discussed on PubMed Commons earlier. (http://www.ncbi.nlm.nih.gov/pubmed/19061929 ) (http://www.ncbi.nlm.nih.gov/pubmed/23452584 ) (http://www.ncbi.nlm.nih.gov/pubmed/24021304 ).

      e) In some ways the deaths with Infanrix is similar to deaths seen with the use in Asia of Pentavalent vaccine against 5 disease ( DPT, hepatitis B, Hib) Puliyel J, 2013. Some of these deaths have been investigated by the WHO using this revised method and the vaccine had been declared safe. http://www.who.int/vaccine_safety/committee/topics/hpv/GACVSstatement_pentavalent_June2013.pdf

      f) The deaths are completely unnecessary as the vaccines could have been given separately, and separately they have a long track record of safety. One hopes that the findings will result in an honest assessment of the harms being done by these new combined vaccines.

      Conclusion

      As mentioned earlier there is nothing sacrosanct about the original Brighton Classification (http://www.who.int/vaccine_safety/publications/AEFI_aide_memoire.pdf) but one has to evaluate the two schemes (Brighton vs CIOMS) from the point of view of patient safety to see which scheme would react to rare vaccine related adverse reaction signals early. “The causality scheme that insists on calling all reactions as ‘indeterminate’ or ‘inconsistent/coincidental’ just because they were not noticed in the original small clinical trials, undermines the very raison d'être of post marketing surveillance. Patient safety (meaning protecting patients) rather than vaccine safety (protecting vaccines) should be more important.”


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    22. On 2015 Jan 13, Jacob Puliyel commented:

      Baldo and colleagues quote 2 references to suggest that in Germany, a population-based evaluation demonstrated a possible safety signal for DTPa-HBV-IPV-Hib-SP but failed to show an imbalance between observed and expected SUD cases for DTPa-HBV-IPV/Hib von Kries R, 2005 von Kries R, 2006. However this seems to be contradicted by the data that was submitted by the manufacturer to the regulatory authority and the analysis below.

      The GlaxoSmithKline Biological Clinical Safety and Pharmacovigilance’s confidential report to the Regulatory Authority on Infanrix hexa (combined Diptheria Tetanus and Acelluar Pertusis, Hepatitis B, inactivated Poliomyelitis and Haemophilus influenza type B vaccine for the period 23 October 2009 to 22 October 2011 (the 15th and 16th Periodic Safety Update Report (PSUR)) has been made available to the public by the Italian Court of Justice Nicola Di Leo and is now available on the internet (http://autismoevaccini.files.wordpress.com/2012/12/vaccin-dc3a9cc3a8s.pdf)

      Section 9.3.1.1 on pages 246-249 documents an evaluation of whether the number of ‘sudden deaths’ reported, exceeded the number one could expect to occur by coincidence - that is from the natural background incidence of sudden death. The background incidence of 0.454/1000 live births in the first year and 0.062/1000 live births is used, with a healthy vaccine correlation factor of 0.8 applied. Table 36 on page 249 tabulates the number of sudden death that would be expected to occur by chance within a range of days post vaccination.

      Table 1 Cumulative number of observed and expected cases of Sudden Death following Infanrix hexa in children in their first or second year of life

      This is available here: http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version)

      ( Source: Table 36 The GlaxoSmithKline Biological Clinical Safety and Pharmacovigilance report to Regulatory Authority )

      According to this analysis, the number of sudden death cases reported after vaccination with Infantrix hexa is below the number of cases expected in children in the first year of life. It is equal or below the number of cases expected in children in the 2nd year of life.

      However if one analyses the data looking at deaths in first 10 days after administration of vaccine and compares it to the deaths in the next 10 days, it is clear that 97% of deaths (65 deaths) in the infants below 1 year, occur in the first 10 days and 3% (2 deaths) occur in the next 10 days. Had the deaths been coincidental SIDS deaths unrelated to vaccination, the numbers of deaths in the two 10 day periods should have been the same.

      Similarly in children older than 1 year, 87.5% deaths (7 deaths) occurred in the first 10 days and 12.5% (1 death) occurred in the next 10 days.

      If we consider the number of deaths in the second 10-day-window-period as the baseline SIDS rate in these healthy children coming for immunization, we can see that there was an excess of 63 (65 – 2 = 63) deaths in the first year and excess of 6 deaths (7 – 1 = 6) among those vaccinated between 1 and 2 years.

      In the reporting period, one must conclude that Infanrix hexa vaccine could have been responsible for at least 69 deaths.These are all deaths within a small window period (of 3 weeks) after a catastrophic event which has been investigated thoroughly (forensic investigation of sudden unexpected deaths - SIDS/SUDS), therefor ascertainment bias is unlikely to have played a major role.

      Table 2 The daily increment in Sudden Death following Infanrix hexa in children ' is tabulated and made available here: http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version)

      The decelerating incremental-deaths further supports the contention that there is a clear relationship of ‘sudden death’ to the vaccination episode. 42 deaths had taken place in the first three days after vaccination, 16 deaths in the next 3 days between day 3 and day 5, 3 deaths between day 6 and day 8, 2 deaths between day 9 and day 11, and there were only 2 deaths in all of the remaining 10 days. The fact that rate of deaths decreases rapidly and continuously as time elapses after immunization, makes it clear that the deaths are related to the vaccination episode.

      This is being posted on PubMed Commons to put it up for open review by the scientific community, on account of its urgency, as this is a matter that involves the lives of children and there is a continuing risk to children.

      As the authors of this article are best qualified to peer review this submission, I am inviting each of the authors castrom@wustl.edu paolo.bonanni@unifi.it mclaudia@fei.edu.br giovanni.gabutti@unife.it franco@med.uniroma2.it fem75838@gsk.com r.prato@unifg.it fvitale@igiene.unipa.it to review it and to post their review on PubMed Commons.

      Jacob Puliyel MD MRCP M Phil

      puliyel@gmail.com


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    1. On 2013 Nov 04, Allison Stelling commented:

      This was a good read. The authors do a good job going over the present body of literature about using Raman and IR for medical diagnostics. I particularly liked the fact that they defined "sensitivity" and "specificity" in their Introduction, and kept the statistics and processing algorithms reasonably straightforward in their analysis. I also admire the fact that they used two different spectral methods (florescence and Raman spectroscopy) to investigate the tissue; combining the two increases the likelihood of accurate and reliable diagnostic results.

      I wonder, though, if it would be more effective to individualize the diagnosis even further- that is, take a background spectra on a "healthy" section, and take a huge number of acquisitions. The disease phenotype might pop out in the difference spectra as the instrument scans over the tissue area. (More likely, many things will. But, you might be able to train it on the disease's signature, and detect it within the subtraction spectra.) This could possibly avert the issue of training sets with misclassified (misdiagnosed) spectra in the training set for "healthy" (or vice versa). With tumors, there can be quite of lot of inter-individual variance within different tumor classifications and subtypes. Raman could really help with more tailored, individualized diagnostics.


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    1. On 2014 Jan 27, William Hollingworth commented:

      I'd like to reinforce Dr Coyne's point about the advantages of PubMed Commons over the much slower, traditional method of communication still used by journals like the Journal of Clinical Oncology.

      5th September 2013: Our online paper and the accompanying editorial were published on the JCO website. The editorial, which we had not previously seen, was quite critical and contained several points that we wanted to respond to.

      10th Sept 2013: We submitted our letter of response to JCO. After a couple of enquiries, I was told that our letter couldn't be published for several months.

      17th Dec 2013: Our letter was accepted.

      14th Jan 2014: Proofs, conflict of interest, authorship statement for the letter received and returned.

      I'm still not sure when our letter will appear in the journal or on its website.

      The 4+ month delay clearly stifles debate and favours the editorialist (who has immediate right of reply) over the authors (who have to wait). Next time I'll respond through PubMed Commons.


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    2. On 2013 Nov 14, James C Coyne commented:

      This is an exceptionally transparent report of a clinical trial that was intended to improve cancer patients' level of distress by introducing routine screening. The results were that screen patients did not have lower levels of distress and did not appreciably increase their use of specialized psychosocial and mental health services. Cost data suggest that it took about $28 to screen one patient, the screening was not cost-effective.

      This kind of data is sorely needed to evaluate implementation of screening versus other possible uses of the same resources. Unfortunately, when this article came out in Journal of Clincal Oncology, it was accompanied by a negative editorial commentary. Apparently the authors of the study had no forewarning or opportunity to respond. Moreover, this article is behind a pay wall, but the attack on it in the same journal is freely available.

      Here's the attack on it Carlson LE, 2013 and here's a link to my blog post <http://blogs.plos.org/mindthebrain/2013/11/08/wheres-the-evidence-that-screening-for-distress-benefits-cancer-patients/

      discussing all the implications of such a use use of invited commentaries by advocacy groups to discredit negative findings would contradict their claims of benefit from accepting their practice recommendations. It's good that we have PubMed Commons so that such invited commentaries do not become the last word in evaluating studies.


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    1. On 2013 Nov 14, James C Coyne commented:

      Although not identified as such in PubMed, this article is an invited commentary on another article Hollingworth W, 2013.

      The targeted article involved a reasonably conducted randomized trial that found that implementing routine screening for distress failed to reduce the distress of cancer patients and only minimally increased referrals to specialty psychosocial and mental health services. The article also concluded that screening was not cost-effective.

      There is a paucity of such data available, even though crucial to evaluating the value of implementing screening versus alternative uses of resources. See http://blogs.plos.org/mindthebrain/2013/11/08/wheres-the-evidence-that-screening-for-distress-benefits-cancer-patients/

      The commentary is quite negative, unfairly so, especially because the authors of the targeted article were not forewarned or given a chance to respond. The author of the commentary is a key proponent of routine screening for distress and took the occasion of an invited commentary to trash negative findings from a relatively well done study.

      The commentary represents a post publication enforcement of the confirmatory bias generally required for screening articles to be published. The targeted article nonetheless got through peer review, but obviously the author of the invited commentary was forewarned and given an opportunity to neutralize its impact.

      Eight of the 16 citations are to the author or a close collaborator’s work. Many do not present relevant data was seem relevant at all. I would consider some of them gratuitous self citations. And others seem to represent simply advocacy pieces, that are not evidence based.

      Although this commentary appears in a paywalled journal, it can be freely accessed, whereas the targeted article is securely behind a paywall. This substantially adds to the unfairness of this commentary. You can readily access the commentary from PubMed, but cannot directly access the article that it harshly criticizes.

      I have commented more extensively on this invited commentary and the target article in a PLOS Mind the Brain blog post < http://blogs.plos.org/mindthebrain/2013/11/13/2127/> The publishing of this invited commentary demonstrates a failure of prepublication peer review of the kind that post publication comments in PubMed Commons can remedy.


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    1. On 2015 Oct 05, Siddharudha Shivalli commented:

      I read this article with a great interest. Authors’ efforts are praiseworthy. It highlights the key factors associated with the risk of malaria in the study area and provides evidence for fine tuning of malaria control activities. However, following issues need to be addressed.

      The prevalence of malaria should have been reported with 95% confidence intervals (n=83/1084, 7.7%; 95% CI: 6.2-9.4). Authors have mentioned in the abstract that the multivariate logistic regression analysis was used to compare the factors associated with malaria in pregnant women. However, the same is missing in ‘Data analysis’ part of methods. Moreover, authors mention that after adjusting for possible confounders, the use of insecticide spray (p<0.001) and young maternal age (p = 0.020) were the main factors associated with a reduced and an increased risk of malaria infection among pregnant women in Lagos, respectively [Table 5]. It is advisable to explicitly mention all the confounders used in the regression model to avoid ambiguity. Although the study sample was large (n=1084), a word about R2 (explaining the variance in the risk of malaria) of the applied regression model would have been more affirmative. Although bed net, ITN and Insecticide sprays are the major preventive measures, others like avoiding water logging and clean surroundings, proper covering of stored water, screening of the houses with wire mesh, clothes covering maximum body surface etc. are overlooked in this study.

      None the less, I must congratulate the authors for investigating an important public health problem in the study area.

      Competing interests

      The author declares that there is no conflict of interest about this publication.


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