6,062 Matching Annotations
  1. May 2026
    1. On 2026-03-27 14:32:15, user Peter Ellis wrote:

      If you can validate this finding by some other method then this would be a truly remarkable finding. The Y chromosome contains numerous genes that are essential for spermatogenesis - it should not be possible for any cell lineage lacking the Y to give rise to mature sperm. The only possible point at which the Y could be lost (or Y-bearing cells could be lost) would be post-meiotic.

      Is it possible instead that there is some alteration in chromatin packaging which somehow selectively affects the extraction efficiency of Y chromosomal DNA sequences?

      Alternatively, how exactly is the calculation of Y content being done? If this is an aggregate measurement from bulk DNA, is it possible that rather than there being cells that have fully lost the Y, there is a mix of cell lineages present, each of which has a range of different Y microdeletions present?

      Given the known essentiality of the Y for sperm production, I think you will find it challenging to get this past peer review without some kind of per-cell analysis, which could be FISH-based or single-cell genotyping. In either case you'd need very high throughput to have statistical power to detect 1% of cells with LOY

    1. On 2026-03-26 15:44:14, user Peter J. Wolf wrote:

      As both a researcher and community cat caregiver, I’m very pleased to see this work being conducted!

      I was rather surprised to see the relatively low instances of secondary traumatic stress (i.e., 47% moderate, 10% high) reported in this study. I imagine this is the result of using the thresholds proposed by Stamm (2010). You might consider repeating your analysis using the revised thresholds proposed by De La Rosa et al. (2018).

      Literature cited<br /> De La Rosa, G. M., Webb-Murphy, J. A., Fesperman, S. F., & Johnston, S. L. (2018). Professional quality of life normative benchmarks. Psychological Trauma: Theory, Research, Practice, and Policy, 10, 225–228. https://doi.org/10.1037/tra0000263

      Stamm, B. H. (2010). The Concise ProQOL Manual (2nd ed.). https://proqol.org/proqol-manual

    1. On 2026-01-12 13:02:28, user Ryan wrote:

      The plot in figure 2 is great. However, providing a supplemental with the actual HR of testing would be helpful for others to do a tipping point analysis of your results and confirm the testing effect is or is not strong enough to nullify your results. This would greatly enhance the reproducibility of your research.

    2. On 2026-01-12 13:11:20, user Ryan wrote:

      I recommend leaving an HR for testing positivity or adding the positivity rate as adjusted variable, this will allow testing level to be compared and not just testing timing on the results. From the look of it hin the log ratios over time, it does not look like it will completely wash out the signal, however, it is hard to tell with giving the actual values.

    3. On 2025-12-12 17:45:56, user Ceejay wrote:

      Line 293: "This study’s inability to find a protective influence of influenza..." I think what is meant is protective influence *of vaccination* on influenza

    4. On 2025-10-09 02:52:59, user sid moose wrote:

      I can’t tell, not a scientists here.. but did they test for whether or not the participants had the flue before the start of the study?

    1. On 2026-03-30 13:27:10, user Sverre wrote:

      This is a very cool article, thanks for sharing it! Currently planning a kinda similar analysis. I just want to point out that Norwegian middle school GPA is not a 10-year cumulative measure: it just contains grades from year 10 (and a few from year 9).

    1. On 2026-03-29 15:01:54, user Ian Buller wrote:

      Quick note that your citation of the abstract by Brown & Vo et al. (2022; DOI: 10.1158/1538-7755.DISP21-PO-192) is now published as a manuscript in JNCI by Vo & Brown et al. (2025; DOI: 10.1093/jnci/djaf066). I am a co-author on both.

    1. On 2026-03-25 06:58:19, user Eugenio Forbes wrote:

      As part of the methodology, did anyone diagnose equipment and cables, plot the recordings to verify that it's not mostly noise?

    1. On 2026-03-25 02:47:47, user Tin Pham wrote:

      This paper could have been ameliorated by specifying the target trial specifications (eg. eligibility criteria, treatment and outcome, follow-up, causal contrasts) and the emulated analogues, according to the TARGET guideline (Cashin et al, 2025). Also, I suggest some sensitivity analyses be done (e.g. varying the lag time, different model specifications for calculating the propensity score, ITT vs PP treatment estimates) to verify the robustness of the findings.<br /> _____<br /> References: <br /> Cashin AG, Hansford HJ, Hernán MA, et al. Transparent Reporting of Observational Studies Emulating a Target Trial—The TARGET Statement. JAMA. 2025;334(12):1084–1093. doi:10.1001/jama.2025.13350

    1. On 2026-03-23 19:50:14, user Neville Calleja wrote:

      There is clearly a number of confounders here and the way it is written and summarised in the abstract does not give enough credit to this. The link with pre-existing EBV infection, potential infection before the vaccine took full effect etc has not been well described. A number of subset analyses have been carried out, which may border on data dredging, rather than formal multivariate analyses. Also clearly the involvement of a major antivax advocate has meant that the study has been highjacked.

    1. On 2026-03-23 18:21:15, user Evolutionary Health Group wrote:

      We at the Evolutionary Health Group ( https://evoheal.github.io/ ) enjoyed this paper. Here are our highlights:

      The saliva-based work presented here shows convincing equivalence to blood tests across multiple pathogens, cohorts, and age groups. The attention to real-world validation shows that the method is platform-level, opening the possibility of applying this type of assay in other contexts.

      Because saliva samples are self-collected, non-invasive, and stable, the authors demonstrate that it's possible to capture the daily resolution of important pathogens, addressing a major limitation in epidemiology where true dynamics can't be captured due to infrequent sampling.

      Blood-based studies frequently under-sample children, older adults, rural populations, and low-resource populations. Saliva testing removes many of the cost, commute, and invasiveness barriers and helps create more representative datasets for use in epidemiological inference and public health policy.

      Professionally collected blood samples benefit from consistent quality. Self-collected samples are more likely to suffer a loss of quality due to improper collection techniques. We would be interested to know how sample quality compares when collections are truly independent of any professional guidance.

    1. On 2026-03-14 00:41:31, user Lisa DeTora wrote:

      What an interesting study! I'd be curious about your views on more open-ended questions users might ask of LLMs about specific vaccines. I also wonder if you have advice for public health agencies or healthcare providers on using LLMs in this setting

      One small point: the vaccine hesitancy reference is pre-COVID. My understanding is that this problem has been somewhat worse since the pandemic, making the problems you seek to address even more critical.

    1. On 2026-03-13 17:56:20, user NomosLogic wrote:

      Important preprint out of Johns Hopkins — LLMs evaluated as a diagnostic safety net for correcting physician errors.<br /> The right question to ask alongside it: for which clinical decisions is "better probabilistic reasoning" the correct architectural answer, and for which decisions is determinism required?<br /> Drug-gene interactions have correct answers. They are computable. An LLM that reasons well about a CYP2C19 finding is still approximating what a deterministic rules engine computes exactly — every time, auditably, without session-level variance.<br /> The safety net shouldn't be a better guesser. It should be a system that cannot get the answer wrong.

    1. On 2026-03-10 21:27:15, user Abdul Harif wrote:

      Training a 160-input multilayer perceptron on a cohort of only 35 unique participants is highly prone to overfitting, even with the inclusion of dropout layers and early stopping. Also, the control group only provided a single breath specimen at one time point, whereas the patient group provided breath specimens before treatment and again 6 to 8 weeks later. This introduces unmitigated temporal confounding variables, such as seasonal changes or device drift over the 8-week period, which the control group does not account for.

    1. On 2026-03-09 13:24:18, user David Glasser, MD wrote:

      All authors are equity owners of the system studied. Were these the same experts that reviewed discordant cases and sided with the system they owned almost 4 times as often as the board certified clinicians who made the initial assessments?

      Ethical review was by the company that markets the system studied.

      MAJOR sources of bias and conflicts of interest here. I give them credit for being forthright about disclosing them.

    2. On 2026-02-20 13:58:16, user Peer Reviewer wrote:

      We requested the materials needed to reproduce the main results in this preprint. Although the manuscript states that “all data produced in the present study are available upon reasonable request,” a request from our group did not receive a response, and the requested materials have not been made available for independent replication.

    1. On 2026-02-27 17:03:20, user Deepak Modi wrote:

      The NGS dataset in this study is available with IBDC Study Accession: INRP000591 and INSDC (SRA) Project Accession: PRJEB108860

    1. On 2026-02-22 17:29:44, user Sue Hewitt wrote:

      How is it possible to review the supplementary tables, which do not seem to be included in the preprint? Will this research be submitted for peer review?

    1. On 2026-02-21 03:18:58, user Naoki Watanabe wrote:

      We are pleased to announce that this preprint has undergone peer review and has been published in a formal journal. Please refer to the final version of the article.

      Watanabe N, Watari T, Otsuka Y. Desulfovibrio Bacteremia in Patients with Abdominal Infections, Japan, 2020–2025. Emerg Infect Dis. 2026 Feb [cited 2026 Feb 21];32(2). Available from: http://dx.doi.org/10.3201/eid3202.251581

    1. On 2026-02-02 05:15:23, user S. Miyamoto wrote:

      Now published in Commun Med.

      Miyamoto S, Numakura K, Kinoshita R, Arashiro T, Takahashi H, Hibino H, Hayakawa M, Kanno T, Sataka A, Sakamoto R, Ainai A, Arai S, Suzuki M, Yoneoka D, Wakita T, Suzuki T. Serum anti-nucleocapsid antibody correlates of protection from SARS-CoV-2 re-infection regardless of symptoms or immune history. Commun Med (Lond). 2025 May 15;5(1):172. doi: 10.1038/s43856-025-00894-8. PMID: 40374831; PMCID: PMC12081900.

    1. On 2026-01-31 09:06:49, user Chris Morgan wrote:

      I understand from the Methods that the background population were required to have at least 12 months registration prior to each observation year and that PD events prior to 2007 were excluded. I am therefore assuming PD patients had to have the first diagnosis after this 12 months as a wash-in to ascertain true incident cases. As this is not explicit in the text and noting the higher incidence in the early years of the study, could the author just confirm this please

    1. On 2026-01-29 02:57:44, user Vanessa Haase wrote:

      Correction to my previous comment: The HQ calculations for heart rate increase are scientifically invalid. Heart rate increase from nicotinic agonists is the intended pharmacological effect, not an adverse outcome. The authors use an ARfD based on heart rate increases, but HQ methodology is designed to assess adverse health effects. Pharmacological receptor activation that produces the desired stimulant effect cannot be characterized as a toxicological hazard. By this logic, caffeine would have unacceptable HQs for increased alertness.<br /> Valid cardiovascular risk assessment requires identifying doses causing actual adverse outcomes like sustained tachycardia leading to arrhythmias, hypertensive crises, or cardiovascular events in vulnerable populations. The physiological response that constitutes the purpose of product use is not a safety threshold exceedance.<br /> The conclusions about exceeding safety thresholds rest on this fundamental mischaracterization of pharmacology as toxicity. This undermines legitimate regulatory concerns about unregulated nicotine analogues. Meaningful risk assessment requires identification of true adverse cardiovascular outcomes, not normal receptor-mediated responses.

    1. On 2026-01-26 18:38:43, user Johanna Karla Lehmann wrote:

      No single factor that could be associated with a deterioration in post-COVID-19 symptoms after a SARS-CoV2 vaccine dose was investigated (objectives, title, primary outcome). Factors that could have been considered include quantitative changes in spike production, ACE2 expression, Ang II and Ang 1-7 levels, immunological/ inflammatory markers or changes in the severity/extent of comorbidity (blood pressure behaviour, changes in blood circulation, glucose/lipid metabolism, blood clotting, etc.) and smoking habits.<br /> A deterioration and/or increase in symptoms comes as no surprise. Both the infection and the desired acquired immunity through a COVID-19 vaccination (vaccine indication) require SARS-CoV2 spike antigens (RBD of the spike S1 subunit). These are known to react with ACE2 and trigger pathophysiologically undesirable specific organ dysfunctions and symptoms via an Ang II increase and other reactions (bradykinin increase, etc.). For long Covid, an influence of spikes on nicotinic acetylcholine receptor reactions in the periphery and in the CNS is also being discussed. This was evident in the symptoms of coughing (probably dry cough!) and concentration problems, both of which increased significantly after vaccination.<br /> Vaccination (inclusion criterion) and coughing (a symptom!) were named as the ‘identified only factors’ for a worsening of post-COVID-19 symptoms. Neither of these can be described as factors underlying the worsening. The different risks associated with specific vaccines (mRNA, adenovirus, protein-based, attenuated) should be carefully examined in a representative, controlled, comprehensive clinical study.

    1. On 2026-01-26 15:25:00, user Veronica Ruiz wrote:

      In response to the question Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? I believe that use of fourth-generation rapid tests should continue and be encouraged simply because reduce the window period, and it always should be incorporated into a complete diagnostic and confirmatory algorithm. Like other HIV diagnostic tools, its true usefulness lies in the interpretation framed within an algorithm, and I believe that the vast majority of people who work in the field of diagnosis understand this, and it is clearly outlined in all the guides or recommendations on the subject. In other words, fourth-generation rapid tests alone do not guarantee the detection of acute infection, but in combination of counseling applied to high-risk populations including continuous monitoring and application of other tests including NAT and Ac/Agp24 combo for the detection of the acute viremia phase and the information provided to users can considerably improve the chance of early detection.<br /> As has already been expressed in other comments, there is a huge bias in comparing studies that use different tests, including some that were not approved for use and whose sensitivity increased in updated versions, as well as including mixed populations of very different types in which the percentage of incidence of HIV infection is not comparable.<br /> However, I believe that the greatest bias in the sensitivity calculation is the failure to take into account the appearance of different markers throughout the evolution of the infection, a topic already described by Fiebig in Fiebig EW, Wright DJ, Rawal BD, et al. Dynamics of HIV viremia and antibody seroconversion in plasma donors: implications for diagnosis and staging of primary HIV infection. AIDS 2003; 17(13):1871–1879. <br /> This review conflates detection methods using tests that detect different markers (Table I) related to the time of infection. For example when compared to a NAT test, which has a shorter window period, a fourth-rate rapid test won't have the same diagnostic scope, just like tests that exclusively detect the p24 antigen, whose detection threshold is well-proven to be much lower than any rapid test.<br /> Is also a well-known and reported fact that fourth-generation rapid tests do not perform as well as instrumental methods, but is an inherent limitation of method. Therefore, comparisons should be made using methods with at least a similar detection threshold and window period.The discussion is always interesting and enriching, and I will seek to contact the authors to continue it.

    2. On 2026-01-23 13:21:44, user Dr Ali Johnson Onoja wrote:

      The analysis aggregates performance data from a heterogeneous mix of fourth-generation HIV rapid tests, including research-use-only products (e.g., SD Bioline HIV Ag/Ab Combo), discontinued devices (Combo RT, D4G, E4G, Geenius HIV-1/2, Bio-Rad GS HIV Combo), the FDA-approved U.S. version of Determine HIV-1/2 Ag/Ab Combo, and the WHO-prequalified Alere HIV Combo/Determine HIV Early Detect. In the Nigerian context, where national HIV testing algorithms approved by the Federal Ministry of Health (FMoH) and NACA restrict use to WHO-prequalified assays, pooling data from obsolete or non-programmatic tests without stratification by brand, version, or regulatory status may misrepresent the true performance of diagnostics currently available or deployable in Nigeria.<br /> Assumption of Class-Dependent Performance and Its Programmatic Implications in Nigeria<br /> The review assumes that diagnostic performance is determined primarily by test class (i.e., fourth-generation Ag/Ab RDTs), without sufficient consideration of infection kinetics, targeted biomarkers, assay technology, or specimen type. In Nigeria—where HIV testing is predominantly conducted using finger-prick whole blood in community, primary healthcare, and outreach settings—test performance during acute HIV infection (AHI) is heavily influenced by the timing of presentation and the biological stage of infection. Failure to account for Fiebig stage–specific detectability risks overgeneralizing performance expectations and may undermine rational decisions about where and how fourth-generation RDTs could add value within Nigerian testing strategies.<br /> Non-Standard Definitions of Acute HIV Infection and Relevance to Nigerian Epidemiology<br /> Definitions of AHI vary widely across included studies, spanning multiple Fiebig stages (I–III or I–IV), each characterised by distinct biomarker kinetics (HIV RNA -> p24 antigen -> antibody). In the Nigerian epidemic—where individuals often present late for testing but key populations and high-incidence sub-groups may test during early infection—averaging sensitivity across biologically heterogeneous stages obscures the specific window (notably p24-positive Fiebig II–III) in which Ag/Ab RDTs are theoretically expected to improve case detection. This limits the applicability of pooled sensitivity estimates for informing targeted AHI screening strategies in Nigeria, including among key populations, STI clinics, and PrEP entry points.<br /> Influence of Older Devices and Study Design on Applicability to Nigeria<br /> Lower pooled sensitivity estimates are largely driven by evaluations of older diagnostic devices and laboratory-based case–control studies. Approximately two-thirds of included studies rely on non-consecutive sampling, small AHI sample sizes (<100), and archived specimens—designs known to introduce spectrum and selection bias. For Nigeria, where HIV testing occurs primarily in real-world service delivery settings with operational constraints, such estimates may understate the potential performance of newer WHO-prequalified fourth-generation RDTs when integrated appropriately into national algorithms. Consequently, these findings should be interpreted cautiously when informing policy decisions, guideline updates, or pilot implementation of AHI screening in Nigeria.

    3. On 2025-12-24 04:25:36, user Dr Micah Matiang'i wrote:

      If the role of Ag/ab RDTs is not well understood in resource limited settings , then there is need to do more population based studies before WHO reaches a conclusion

    4. On 2025-12-19 17:14:16, user Cesar Ugarte wrote:

      The preprint by Fajardo et al. addresses an important evidence gap regarding the utility of combined antigen–antibody tests for detecting acute HIV infection. Although the authors adopt a valuable global perspective, the interpretation and synthesis of the data would benefit from greater nuance to enhance clinical relevance. The authors' QUADAS-2 assessment shows High Risk of Bias regarding patient selection and Unclear Risk regarding the conduct of the index test. In diagnostic epidemiology, such findings are not just descriptive but also signal a huge spectrum effect and possible threshold bias. Therefore, the summary estimates presented in Figures 3 and 4 may reflect a statistical average of disparate clinical realities rather than a reliable indicator of test performance (for example in Figure 3 there are 10 studies with a sensitivity less than 10%, including some with 0%, so the evaluation in detail of these studies should be done to see if these studies can be combined with the other ones). Another issue is the inclusion of "obsolete" diagnostic platforms that have been withdrawn due to suboptimal performance. A sensitivity analysis or subgroup stratification should be restricted to tests currently on the market. This would enable the reader to distinguish between the historical evolution of the technology and the expected performance in contemporary clinical practice.

      The interpretation of diagnostic performance also should be addressed in detail. Whereas sensitivity and specificity have usually been considered "intrinsic" to a test (so doesn´t depends on disease prevalence), evidence suggests significant variation across clinical settings. The underlying epidemiological status and operator expertise can affect the test’s accuracy. Finally, I agree with the authors that real-world evidence on cost-effectiveness and implementation barriers is lacking. However, we should be very careful to avoid having a biased meta-analytic estimate that leads to the premature abandonment of "imperfect" but viable diagnostic solutions. In the case of acute HIV infection, for which early detection is critical to ART initiation and reduction of secondary transmission, interpretation of this evidence needs to balance statistical rigor against the urgent public health need for early diagnosis.

    5. On 2025-12-17 21:30:43, user Norman Moore wrote:

      We have contacted the authors of the article Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? A systematic review and meta-analysis of diagnostic performance by Fajardo et al. ( https://doi.org/10.1101/2025.10.14.25338004) . The primary limitation of this article is that it conflates the performance of 4th generation HIV tests that (1) were never launched, (2) that were earlier versions of tests that are no longer available in most parts of the world, and (3) tests that have received WHO pre-qualification (PQ), in a single analysis despite the known and significant differences in performance among them. This has resulted in lower performance representation of certain products over others. It would be more beneficial to the medical community to have a meta-analysis that includes HIV diagnostic tests that are both CE marked and have WHO PQ to maximize the real-world applicability of this systematic review.

    6. On 2025-12-13 03:02:23, user Missiani wrote:

      Title: Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? A systematic review and meta-analysis of diagnostic performance<br /> Authors: Emmanuel Fajardo, Céline Lastrucci1, Pascal Jolivet1, Magdalena DiChiara1, Carlota Baptista da Silva1, Busi Msimanga1, Anita Sands2, Cheryl Johnson1

      The authors systematically searched six databases for studies evaluating Ag/Ab RDTs vs laboratory reference standards in individuals aged >=18 months. Out of 53 studies from 24 countries, they documented a pooled sensitivity of Ag/Ab RDTs for AHI to be 48% (95% CI: 34–62) with specificity of 97% (95% CI: 84–100). They concluded that Ag/Ab RDTs appear to have limited ability to detect AHI, missing more than half of AHI cases<br /> They also documented analytical sensitivity (detection of p24 antigen) at 31%, and antibody detection at 15% which was too low.

      I have three main comments that can improve the programmatic application of this manuscript <br /> 1. The study is presented negatively and concludes “Detection of AHI using Ag/Ab RDTs remains a challenge” despite the effort made and resources used. The study oversimplifies highly variable diagnostic data and assumes similarity between the studies, ignoring that a sensitivity of 48% and a specificity of 97% means that half of the kits performed better and almost all were specific. In Table 2, the authors examined region, study settings, and design, population, specimen, etc., but did not examine the group of kits whose sensitivity and specificity exceeded the pooled values. By examining this group of kits, they will successfully address the title of the article (Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection). Omitting this subgroup analysis presents one dimension of the data. We recommend they include this analysis as a way to address the gaps.<br /> 2. The authors present the p24 and Ag/Ab as a standalone approach rather than a combined or multiplex kit to address early diagnosis during AHI, which will provide an opportunity in low-income countries to reduce transmission, improve linkage to care and clinical outcome. Based on their sensitivity of 48%, multiplexing the test would improve diagnosis by the same margin, which is a substantial gain. We recommend adding a paragraph on the impact of incorporating p24 into a multiplex platform. Because many diagnostic tests are now packaged as multiplex platforms, incorporating this perspective will give the title greater depth and better reflect current testing practices<br /> 3. Some test kits reviewed in the study are either obsolete, recalled, or never progressed beyond early pre-evaluation stages. This raises significant concerns about the validity and current use of the findings. Manufacturers may have already recognized the kits’ poor sensitivity and, as a result, chose not to move forward with full production. Without acknowledging the discontinued or preliminary status of these kits, the study’s conclusions risk being misleading since the kits are not on the market. Recognizing the actual status of these products is essential, as it directly affects how their findings should be interpreted and whether they can responsibly inform policy or implementation decisions.

    1. On 2026-01-26 09:10:28, user Gail Davey wrote:

      The Neglected Tropical Diseases considered by the 2021-25 Ethiopian National Strategic Plan ( https://espen.afro.who.int/sites/default/files/content/document/Third%20NTD%20national%20Strategic%20Plan%202021-2025_0.pdf ) include podoconiosis. This is also considered among the skin-NTDs by WHO. Extensive information is available on the distribution and impact of podoconiosis, which has a greater burden than LF in Ethiopia. It would be helpful to include mention of this conditon within the manuscript.

    1. On 2026-01-23 19:44:39, user David Laursen wrote:

      Thanks for an interesting preprint, which I hope to read more carefully soon. I am not particularly well versed within causal inference so apologies if the question is unclear.

      I noticed your warning against conditioning on post-treatment belief (since it is a collider). Just wondering, does this reservation extend more generally to cautioning against testing for success of blinding at all, regardless of doing a stratified analysis of treatment effects by belief (in an estimation setting, this would probably be estimating differences in beliefs between arms, either with conventional 2x2 measures, or blinding indices). This appears to be a central discussion in many fields, so would appreciate your reflections.

    1. On 2026-01-19 13:00:58, user Gene C Koh wrote:

      Gene Ching Chiek Koh, Serena Nik-Zainal

      Department of Genomic Medicine, University of Cambridge, CB2 0QQ, UK.

      We commend Kanwal et al. for their timely evaluation of the in vivo mutagenic potential of CX-5461. This follows our report that CX-5461 induces substantial mutagenesis in cultured mammalian cells1. The authors analysed samples from four patients treated with CX-5461, including marrow aspirates, trephine biopsies, PBMCs, and skin lesions collected at early treatment timepoints (baseline; days 1, 2, or 9; and end-of-treatment of a 21-/28-day cycle), and used error-corrected duplex sequencing to detect low-frequency mutations. They concluded that CX-5461 exposure did not increase single-/ double-base substitution or indel burdens, nor reproduced the mutational signatures reported in our in vitro study. While we welcome their contribution, several methodological and interpretive shortcomings limit the conclusions that can be drawn.

      1. Data presentation<br /> Figures 1–3 present absolute mutation counts instead of frequencies normalized to total informative duplex bases per sample. In duplex sequencing, normalization is a basic requirement to account for variability in sequencing depth and library complexity; without it, true mutation accrual or fold-change differences versus controls (if any) cannot be assessed reliably.

      2. Experimental controls, assay sensitivity, and performance<br /> The study lacks essential positive and negative controls making it impossible to evaluate whether the sequencing and analytical processes used by the authors have worked. Clinical samples with known mutational signatures detectable through this approach should have been included to confirm assay sensitivity and substantiate a true negative finding. This is fundamental. Samples from patients unexposed to CX-5461 were also required as negative controls to establish background variability, affording confidence intervals and statistical robustness.<br /> Moreover, the authors have not shown awareness of the assay’s limit of detection (LOD). What is the smallest measurable fold-change at the reported sequencing depth? Without this, one cannot determine the smallest mutational differences that could have been missed. The authors have not disclosed quality-control metrics required to understand whether sufficient data quality was achieved for detecting differential mutagenesis. P/S: TwinStrand kit has an error rate ~0.5e-7 to 1e-7 depending on the protocols, and this can be considerably higher if DNA quality is low or from fixed biopsies.

      3. Lack of curation, comparisons to literature<br /> The reported mutation counts did not make sense (baseline values exceeding treated samples, patient samples sometimes lower than kit control). The authors should perform some ‘sanity check’ comparisons with published mutation frequencies of respective normal adult tissues from other duplex-sequencing studies2,3. Analytical rigour would include, for example, examining whether detected variants represent driver mutations from clonal haematopoiesis or occurred in genes under post-treatment selection. Such analyses would have demonstrated critical evaluation of data quality and biological relevance.

      4. Cell-type considerations, sampling window<br /> Most analysed compartments—PBMCs, MACS-sorted marrow fractions—are dominated by mature, non-dividing cells that rarely fix new mutations. A more relevant population for assessing mutagenicity is the haematopoietic stem and progenitor cells (HSPCs), typically <0.5% of marrow cells. A null result in the analysed compartments could just mean no widespread mutation fixation in mature immune cells; it does not exclude the possibility of mutagenesis in progenitors below the detection threshold of the current assay.<br /> In addition, samples were taken at very early timepoints (days 1, 2, 9, or EOT) of the first treatment cycle. At such intervals, mutagenic events are unlikely to have become fixed, as mutagen-induced DNA damage will need time to become embedded through DNA repair and replication. Exposure in terminally-differentiated cells might yield no detectable mutations. If exposure occurs on dividing cells, mutational footprints may only become detectable months or years after exposure. The current dataset lacks the temporal window necessary to assess cumulative in vivo mutagenicity.

      5. Expected evidence of prior treatments <br /> All four patients reportedly had “measurable, relapsed, or refractory advanced haematologic malignancies without any standard therapeutic options available”4. Although treatment histories were not provided, these patients likely received multiple prior therapies (e.g., doxorubicin, cyclophosphamide, etc) that could induce characteristic mutational signatures in normal haematopoietic cells5. Were signatures of prior therapy detected by the authors? Their absence raises concerns regarding the overall assay sensitivity and/or suggests that sampling strategy was suboptimal for detecting mutagenic exposures.

      6. Interpretation of model data<br /> While critical of our findings in cultured human cells as “not adequately representative of physiological human tissue” – a limitation we explicitly acknowledged in our manuscript’s title and discussion – the authors cited a C. elegans study6 in support of their argument of “low non-selective mutagenic potential of CX-5461”. This interpretation is incorrect: the worm study reported high copy-number aberrations, high SNV burdens, and a distinct A>T/T>A-rich signature after CX-5461 exposure, with survival requiring multiple repair pathways (homology-directed repair, microhomology-mediated end joining, nucleotide excision repair, and translesion synthesis). If anything, these cross-species findings reinforce rather than contradict our observations that CX-5461 is highly mutagenic. The concentrations used in that study were chosen to promote viability in the worms, not to minimise mutagenicity. Selective viability does not equate to selective mutagenicity.

      7. Clinical mutagenicity testing<br /> We agree that clinical safety assessments must be rigorous and physiologically relevant. The authors dismissed our experiments as not rivalling the “GLP-compliant, non-mutagenic” results of the CX-5461 drug development pathway. However, those mutagenicity data are not available in the public domain and have neither been shared by the authors nor the company that distributes CX-5461.

      We urge the authors to reconsider and not simply dismiss our findings. First, the primary clinical quality mutagenicity assay (required by agencies such as the US Food and Drug Administration (FDA), European Medicines Agency, and UK Medicines and Healthcare Regulatory Agency (MHRA)) referred to by the authors comprises the Ames test – a reverse gene mutation test performed in prokaryotes (e.g., E.coli, Salmonella).

      Second, according to the FDA’s ICH S2(R1) guidance for a standard battery of mutagenicity assays (Safety Implementation Working Group of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use), additional genotoxic assays should be performed in mammalian cells in vitro (where some of the more common assays include metaphase chromosome aberration assays, the micronucleus assay, and the mouse lymphoma L5178Y cell Tk (thymidine kinase) gene mutation assay (MLA)) or in in vivo studies as necessary.

      Third, the FDA guidance acknowledges that “no single test is capable of detecting all genotoxic mechanisms relevant in tumorigenesis” and that the standard battery serves primarily for hazard identification rather than comprehensive assessment of mutagenic potential. For negative in vivo results, the ICH S2(R1) guidance requires evidence of adequate target-tissue exposure (e.g., toxicity in the tissue, TK/PK data, or direct tissue concentrations) to validate interpretability. Without such data, negative findings have limited meaning, especially where in vitro systems demonstrate strong mutagenicity.

      Fourth, while the Ames test served its purpose for decades, there are well-described problems including false positives, false negatives and critically, a lack of human metabolism that even supplementation with rodent S9 mix cannot always overcome.

      Finally, a point also raised by the accompanying commentary to our publication is that perhaps the time has come to re-evaluate how mutagenicity assays are performed. Current assays cannot capture the genome-wide mutation patterns revealed by whole-genome sequencing in human cells, and as a community we should consider using unbiased, agnostic, modern genomic approaches capable of detecting all classes of mutational changes in human cells. This is not an attack on CX-5461; rather, it is a call to the community to consider re-evaluation of mutagenicity assays in drug development.

      8. Unsubstantiated claims<br /> The claim of potential contaminants accounting for the mutagenic outcomes we and others have observed is speculative and unsupported. The fact that multiple studies1,6 observed the same mutagenic outcomes using CX-5461 from independent sources suggests that this is unlikely. The authors showed no analytic chemistry (LC-MS/MS) and/or spiking experiments to substantiate this claim.

      9. Inadequate supporting material throughout <br /> There were many gaps in the methods/supporting information, including adequate clinical annotation, precise sampling times/total treatment cycle, and basic quality-control metrics. Experimental details (e.g., antibodies used for MACS sorting, essential for interpreting analysed subpopulations) were not provided. These omissions limit transparency, reproducibility, and the interpretability of the findings.

      10. Beneficence, non-maleficence, autonomy, justice<br /> First, in academia and medicine, we are guided by the principle of doing no harm. In identifying mutagenesis in experimental systems (an incidental finding), we acted in the best interest of the community – reporting an observation that could have an impact on patients and acknowledging the limitations of our system. We have no role in the (dis)continuation of clinical trials; we simply presented our data transparently and highlighted potential risk. <br /> Second, while the authors chose to discontinue their trial, several others remained active (e.g., NCT04890613, NCT06606990, NCT07069699, NCT07147231, NCT07137416). Their decision was conservative, and in our view, scientifically prudent. We commend their caution. However, it does not justify criticism of those of us reporting safety concerns in good faith.<br /> Third, as a community, we serve society better by being aware of issues, addressing the problems with robust experiments rather than polarising into groups “for” or “against” a compound, so that truly beneficial compounds can get to patients as quickly as possible. <br /> Finally, safety concerns may extend beyond mutagenesis and include tumour promotion effects. CX-5461’s interaction with TOP2B, for example, has been linked to serious, late-emerging toxicities, including therapy-induced leukaemia and cardiotoxicity7-10.

      Concluding remarks<br /> Given the experimental and analytical shortcomings outlined above, definitive conclusions regarding CX-5461’s in vivo mutagenicity cannot yet be drawn. The absence of evidence should not be taken as evidence of absence. Rigorous, longitudinal studies with appropriate controls and independent oversight are required to assess true medium- to long-term risks.

      We share the authors’ view that thorough, transparent evaluation of anticancer agents is essential. Given the authors’ vested interest in finding a negative result, we suggest independent individuals be involved in performing the analysis/interpretation of their studies to negate potential conflicts of interest. We remain open to collaboration in this effort, in the shared interest of patient safety and scientific integrity.

      1. Koh, G.C.C., Boushaki, S., Zhao, S.J., Pregnall, A.M., Sadiyah, F., Badja, C., Memari, Y., Georgakopoulos-Soares, I., and Nik-Zainal, S. (2024). The chemotherapeutic drug CX-5461 is a potent mutagen in cultured human cells. Nat Genet 56, 23-26. 10.1038/s41588-023-01602-9.
      2. Abascal, F., Harvey, L.M.R., Mitchell, E., Lawson, A.R.J., Lensing, S.V., Ellis, P., Russell, A.J.C., Alcantara, R.E., Baez-Ortega, A., Wang, Y., et al. (2021). Somatic mutation landscapes at single-molecule resolution. Nature 593, 405-410. 10.1038/s41586-021-03477-4.
      3. Machado, H.E., Mitchell, E., Obro, N.F., Kubler, K., Davies, M., Leongamornlert, D., Cull, A., Maura, F., Sanders, M.A., Cagan, A.T.J., et al. (2022). Diverse mutational landscapes in human lymphocytes. Nature 608, 724-732. 10.1038/s41586-022-05072-7.
      4. Khot, A., Brajanovski, N., Cameron, D.P., Hein, N., Maclachlan, K.H., Sanij, E., Lim, J., Soong, J., Link, E., Blombery, P., et al. (2019). First-in-Human RNA Polymerase I Transcription Inhibitor CX-5461 in Patients with Advanced Hematologic Cancers: Results of a Phase I Dose-Escalation Study. Cancer Discov 9, 1036-1049. 10.1158/2159-8290.CD-18-1455.
      5. Mitchell, E., Pham, M.H., Clay, A., Sanghvi, R., Williams, N., Pietsch, S., Hsu, J.I., Obro, N.F., Jung, H., Vedi, A., et al. (2025). The long-term effects of chemotherapy on normal blood cells. Nat Genet 57, 1684-1694. 10.1038/s41588-025-02234-x.
      6. Ye, F.B., Hamza, A., Singh, T., Flibotte, S., Hieter, P., and O'Neil, N.J. (2020). A Multimodal Genotoxic Anticancer Drug Characterized by Pharmacogenetic Analysis in Caenorhabditis elegans. Genetics 215, 609-621. 10.1534/genetics.120.303169.
      7. Pan, M., Wright, W.C., Chapple, R.H., Zubair, A., Sandhu, M., Batchelder, J.E., Huddle, B.C., Low, J., Blankenship, K.B., Wang, Y., et al. (2021). The chemotherapeutic CX-5461 primarily targets TOP2B and exhibits selective activity in high-risk neuroblastoma. Nat Commun 12, 6468. 10.1038/s41467-021-26640-x.
      8. Zhang, W., Gou, P., Dupret, J.M., Chomienne, C., and Rodrigues-Lima, F. (2021). Etoposide, an anticancer drug involved in therapy-related secondary leukemia: Enzymes at play. Transl Oncol 14, 101169. 10.1016/j.tranon.2021.101169.
      9. Cowell, I.G., Sondka, Z., Smith, K., Lee, K.C., Manville, C.M., Sidorczuk-Lesthuruge, M., Rance, H.A., Padget, K., Jackson, G.H., Adachi, N., and Austin, C.A. (2012). Model for MLL translocations in therapy-related leukemia involving topoisomerase IIbeta-mediated DNA strand breaks and gene proximity. Proc Natl Acad Sci U S A 109, 8989-8994. 10.1073/pnas.1204406109.
      10. Zhang, S., Liu, X., Bawa-Khalfe, T., Lu, L.S., Lyu, Y.L., Liu, L.F., and Yeh, E.T. (2012). Identification of the molecular basis of doxorubicin-induced cardiotoxicity. Nat Med 18, 1639-1642. 10.1038/nm.2919.
    1. On 2026-01-14 16:06:13, user Charles Tritt wrote:

      This is interesting and important work. However, the flaw I see in this study is that it included only 40 episodes of hypoxia (defined as a SpO2 of < 90%) out of 1760 measurements. Arterial saturation measurements are only clinically significant when they are significantly low, so the approach used doesn’t seem to answer the important question – are there systematic pulse ox errors that make a clinical difference?

      The linked protocols show induced hypoxia (I assume by subjects breathing air diluted with nitrogen). Of course, this couldn’t be done with critically ill patients. But I don’t see that the state of the patients being particularly important to the question of systematic pulse ox errors. Would it not be a better approach to test healthy individuals an induce hypoxia so their data set contains the clinically important information.

    1. On 2026-01-13 16:13:38, user Christine Stabell Benn wrote:

      Comment on “Non-specific effects of vaccines on all-cause mortality: a meta-analysis of randomized controlled trials (RCTs) 2012–2025”<br /> Christine Stabell Benn, Frederik Schaltz-Buchholzer, Sebastian Nielsen, Peter Aaby<br /> We commend the authors for addressing the important and contentious question of non-specific effects (NSEs) of vaccines on all-cause mortality. However, we have several major concerns regarding the framing, completeness, methodology, and interpretation of the preprint. Collectively, these issues undermine the conclusions drawn.

      1. Restricted research question and dismissal of large parts of the evidence baseThe authors explicitly restrict their review to randomized controlled trials (RCTs) published after the WHO review of non-specific effects(1). If the stated objective is to assess the evidence for NSEs on all-cause mortality in randomized trials, an updated meta-analysis incorporating all relevant RCTs, rather than an arbitrarily time-limited subset, would be more informative. The decision to exclude pre-2012 RCTs from the main analysis appears methodological rather than substantive and risks answering a narrow procedural question rather than addressing the broader scientific question.

      More importantly, NSEs represent a research area in which randomized trials are inherently difficult or impossible to conduct at scale, because the vaccines in question are already part of routine immunization schedules. As in other areas of public health - such as smoking, breastfeeding, or nutrition - causal inference therefore relies on triangulation across multiple study designs, including observational studies and natural experiments, supported by biological and immunological evidence.<br /> If the intention is to provide a meaningful update on the state of the evidence for NSEs, a comprehensive synthesis that acknowledges the strengths and limitations of all relevant study designs - or at minimum a clear and balanced justification for excluding them - is required.

      2. Incomplete identification of relevant randomized trialsDespite claiming a comprehensive search, the review misses several important randomized controlled trials that are directly relevant to NSEs, including recent RCTs published well within the stated search window (e.g. PubMed IDs: 39357573, 38350670, 33893799, 30256314). The omission of these trials raises concerns about the sensitivity of the search strategy and undermines confidence in the completeness of the evidence base.

      3. Extreme clinical and methodological heterogeneity invalidates the pooled meta-analysis<br /> The meta-analysis combines trials of three different vaccines (BCG, measles vaccine, and OPV) administered at vastly different ages (birth to 59 months), with follow-up periods ranging from days to five years, and using different randomization schemes and outcomes structures. This is not merely “heterogeneity,” but fundamentally different interventions addressing different biological hypotheses.

      Pooling these studies is not equivalent to combining “apples and bananas,” but rather apples and cars. The resulting pooled estimate does not correspond to a coherent causal treatment effect and is therefore not interpretable.

      4. Non-adherence with the WHO meta-analysis methodologyBy pooling all vaccines together, and furthermore by not focusing on the time window where a given vaccine is the most recent, the authors of the new meta-analysis violates the principles set out in the WHO meta-analysis, which emphasized vaccine-specific analyses and the importance of the most recent vaccine exposure.

      5. Overreliance on conservative confidence interval methods without adequate justificationThe authors emphasize the use of the Hartung-Knapp-Sidik-Jonkman (HKSJ) method as providing “more reliable and conservative control of type I error.” While HKSJ can be appropriate when few studies estimate the same underlying effect, its application here - given the very marked heterogeneity and conceptual incoherence of the pooled treatment effect - adds statistical conservatism without resolving the more fundamental problem of model misspecification. The resulting wide confidence intervals should not be interpreted as robust evidence against NSEs.

      6. Misinterpretation of heterogeneity statistics (I²)The statement that an I² of ~44% indicates that “approximately half the differences in the results are due to actual variations between studies” is misleading in this context. I² is meaningful only when studies estimate the same underlying causal association. When fundamentally different interventions are pooled, I² no longer has the interpretation implied by the authors.

      7. Speculation that early BCG effects are due to bias is unsubstantiatedThe manuscript repeatedly suggests that observed mortality reductions within the first 1–3 days after BCG vaccination may reflect bias due to lack of blinding. This speculation appears inconsistent with the design and reporting of the original trials. In Guinea-Bissau randomization occurred at discharge, and post-randomization care was not provided by study staff(2). In the Indian trial, the authors explicitly state that it is unlikely that the lack of blinding influenced the result. In previous open label randomized trials of BCG Russian strain in the same sites, no difference in neonatal mortality was found, which suggests that the lack of blinding did not bias the findings(3).

      Given these safeguards, attributing early effects to bias is unsupported by trial evidence and suggests that the original studies were not carefully read or adequately considered.

      8. Ignoring extensive mechanistic evidence for rapid BCG effectsThe authors further imply that effects within days are biologically implausible. This overlooks a substantial body of experimental and clinical evidence demonstrating that BCG induces trained innate immunity, including rapid functional reprogramming of myeloid cells and emergency granulopoiesis, which can occur within days and protect against severe infections such as sepsis(4, 5). These mechanisms provide a biologically coherent explanation for early effects and should have been discussed as plausible alternatives to bias.

      9. Failure to engage with established explanations for heterogeneous measles vaccine effectsThe manuscript notes heterogeneity across measles vaccine trials but does not engage with recent work offering compelling explanations for these differences, including interactions with OPV campaigns and vaccination sequence effects(6). Ignoring this literature leads to an oversimplified interpretation in which heterogeneity is treated primarily as noise rather than as potentially informative signal.

      10. Introduction of an a posteriori unifying hypothesisLate in the discussion, the authors invoke a new hypothesis that all live-attenuated vaccines should yield similar NSEs on all-cause mortality. This hypothesis appears post hoc and is not clearly justified biologically. It has never been a hypothesis within the NSE field and is biologically implausible, not least because baseline mortality differs substantially by age. Introducing this assumption only after the pooled analysis further weakens the inferential logic of the paper.

      Overall assessmentThe manuscript raises an important question, but its conclusions are undermined by:<br /> • an artificially restricted scope,<br /> • incomplete inclusion of relevant RCTs,<br /> • inappropriate pooling across fundamentally different interventions,<br /> • speculative dismissal of biologically plausible findings,<br /> • and inconsistent use of hypotheses introduced after the analysis.<br /> As currently written, the preprint does not provide a reliable basis for concluding that NSEs of vaccines on all-cause mortality are absent or unimportant. A substantially revised analysis - grounded in a comprehensive evidence base, clearer causal questions, and vaccine-specific syntheses - would be required to support such claims.

      References1. Higgins JP, Soares-Weiser K, Lopez-Lopez JA, Kakourou A, Chaplin K, Christensen H, et al. Association of BCG, DTP, and measles containing vaccines with childhood mortality: systematic review. BMJ. 2016;355:i5170.<br /> 2. Biering-Sorensen S, Aaby P, Lund N, Monteiro I, Jensen KJ, Eriksen HB, et al. Early BCG-Denmark and Neonatal Mortality Among Infants Weighing <2500 g: A Randomized Controlled Trial. Clin Infect Dis. 2017;65(7):1183-90.<br /> 3. Adhisivam B, Kamalarathnam C, Bhat BV, Jayaraman K, Namachivayam SP, Shann F, et al. Effect of BCG Danish and oral polio vaccine on neonatal mortality in newborn babies weighing less than 2000 g in India: multicentre open label randomised controlled trial (BLOW2). BMJ. 2025;390:e084745.<br /> 4. Kleinnijenhuis J, Quintin J, Preijers F, Joosten LA, Ifrim DC, Saeed S, et al. Bacille Calmette-Guerin induces NOD2-dependent nonspecific protection from reinfection via epigenetic reprogramming of monocytes. Proc Natl Acad Sci U S A. 2012;109(43):17537-42.<br /> 5. Brook B, Harbeson DJ, Shannon CP, Cai B, He D, Ben-Othman R, et al. BCG vaccination-induced emergency granulopoiesis provides rapid protection from neonatal sepsis. Sci Transl Med. 2020;12(542):eaax4517.<br /> 6. Nielsen S, Fisker AB, da Silva I, Byberg S, Biering-Sørensen S, Balé C, et al. Effect of early two-dose measles vaccination on childhood mortality and modification by maternal measles antibody in Guinea-Bissau, West Africa: A single-centre open-label randomised controlled trial. EClinicalMedicine. 2022;49:101467.

    1. On 2026-01-10 20:05:34, user Sequoia wrote:

      I'm interested in seeing if replacing the UPFs near the checkout with non-UPFs would result in an increase in non-UPFs consumption, especially if they were easy to eat with no preparation required (e.g. an apple or energy balls), and if so, by how much.<br /> I am delighted to know that research is being done on this critical subject.

    1. On 2026-01-09 08:47:36, user Janne Ruotsalainen wrote:

      The MVA vector is highly immunogenic as it has been used as a small pox vaccine. The ex vivo ELISPOT responses against MVA are pretty high raising the question whether the anti-vector T cell responses became immunodominant and thus suppressed some neoantigen specific T cell responses?

    1. On 2025-12-30 06:02:44, user James P wrote:

      Really nice, timely methods paper. It puts clear names and concrete examples on two ways biomarker studies can look better than they truly are in practice: (1) enrichment/range restriction, where you study a highly selected group and results don’t transport to typical patients, and (2) “double dipping,” where the same biomarker data influence who gets included and how performance is judged, which can inflate accuracy.

      I also appreciated how the audit plus the simple simulation experiments make the problems intuitive rather than abstract. The recommendations are practical (be explicit about the intended target population/estimand, and separate discovery from confirmation or prespecify analyses) and feel immediately useful for trial-ready cohorts and clinical workflows.

    1. On 2025-12-27 04:25:05, user Anjum wrote:

      Hi <br /> This manuscript has been published at <br /> John A, V R Reshma, El-Hazimy K. Bridging the Nutrition Education Gap: From Theory to Practice- A Scalable Model for Nutrition Practicums in Medical Training. Journal of Teaching Innovation and Reform. 2025;1:11-25.

    1. On 2026-03-25 16:26:02, user Kristina Jakobsson wrote:

      The outcome of this interesting study was the absolute change in eGFR from the start of the work shift to the end of the work shift.

      Cross-shift fluctuations of biomarkers are valuable for group-level evaluation of work-related kidney strain. S-Cr and S Cystatin C can rise significantly during a hot, labor-intensive shift and normalize overnight (1,2)

      However, eGFR should not be used for cross-shift comparisons, since eGFR assumes a stable level of creatinine over days (i.e., steady-state) (3) Hence, conventional eGFR calculations are not valid if creatinine is rapidly changing. S-Cr change is the preferred metric for cross-shift evaluations.

      An alternative for estimation of rapid functional changes during clinical AKI has also been suggested; the “Kinetic eGFR” (4).

      REFERENCES: <br /> 1. Lucas RAI, Hansson E, Skinner BD, Arias-Monge E, Wesseling C, Ekström U, Weiss I, Castellón ZE, Poveda S, Cerda-Granados FI, Martinez-Cuadra WJ, Glaser J, Wegman DH, Jakobsson K. The work-recovery cycle of kidney strain and inflammation in sugarcane workers following repeat heat exposure at work and at home. Eur J Appl Physiol. 2025 Mar;125(3):639-652. doi:10.1007/s00421-024-05610-3. Epub 2024 Oct 5. PMID: 39369140; PMCID: PMC11889006<br /> 2. Hansson E, Lucas RAI, Glaser JR, Weiss U, Ekström U, Abrahamson M, Wesseling C, Wegman DH, Jakobsson K. Understanding changes in serum creatinine during work in heat. Kidn Int Report vol 10 issue 8, p2860-63, Aug 2025. <br /> 3. Waikar SS, Bonventre JV. Creatinine kinetics and the definition of acute kidney injury. J Am Soc Nephrol. 2009;20: 672–679. doi: 10.1681/ASN.2008070669<br /> 4. Chen S (2013). Retooling the creatinine clearance equation to estimate kinetic GFR when the plasma creatinine is changing acutely. Journal of the American Society of Nephrology DOI: 10.1681/ASN.2012070653

    1. On 2025-12-05 05:35:16, user Evolutionary Health Group wrote:

      We at Evolutionary Health Group ( https://evoheal.github.io/ ) really enjoyed this paper.

      Here are our highlights:

      One of the strongest contributions is the introduction of a nonlinear null model of covariates that outputs a single scaler, which can be inserted into existing linear frameworks while adding the power of nonlinear modeling.

      The authors demonstrate that nonlinear covariate modeling consistently helps more than it harms: adding the null prediction rarely interferes with genetic inference and the gains are substantial for many traits, giving the method an encouraging risk-benefit profile.

      Instead of attempting to model exposures explicitly, the authors show that spatiotemporal information can capture complex environmental influences. Even though these features are non-causal, researchers can use such data to hypothesize environmental drivers without having to specify them individually in models.

      Using TreeSHAP-IQ, the authors show that nonlinear models find age-sex, seasonality-sex, and birth-home location interactions. These patterns are biologically credible and validated by external literature but cannot be captured by standard linear covariate adjustments. This shows that nonlinear covariate modeling doesn't just improve predictions, it produces interpretable biological insights.

    1. On 2020-05-26 22:31:23, user guost wrote:

      Unfortunately there is absolutely no info about what kind immunoassay this LIAISON XL platform is. The company Diasorin website for is totally useless in that regard.

    1. On 2020-04-24 07:57:39, user Sinai Immunol Review Project wrote:

      Repurposing Therapeutics for COVID-19: Rapid Prediction of Commercially available drugs through Machine Learning and Docking <br /> Mahapatra et al. MedRXiv [@doi:10.1101/2020.04.05.20054254v1]

      Keywords<br /> • Drug prediction<br /> • Machine learning<br /> • Docking

      Main Findings<br /> The COVID-19 pandemic has ravaged hospitals: the disease can present severe complications (acute respiratory failure in particular), and yet no specific drug exists to date. Time being of the essence, it is therefore essential to explore drugs already on the market for other indications. These drugs, however, must be tested in COVID-19 patients and thus selection of limited candidates is important. The authors argue that an important step in accelerating the selection of promising drugs can be done in silico.<br /> The authors use machine learning (ML), training their algorithm on a dataset obtained from in vitro targeting of SARS Coronavirus 3C-like Protease with existing drugs. The trained algorithm was then used to screen drugs available in the Food and Drug Administration’s Drug Bank. Using the Drug Bank dataset, the authors also performed a docking study -a process used to predict in silico the orientation and conformation of a molecule when bound to its receptor. Since SARS-CoV-2 spike protein is considered to play an important role in infection by binding ACE-2, docking was also applied to study the stability of drug-spike protein complexes. The results of the ML and docking were aligned, and antiretroviral Saquinavir was identified as a potentially promising therapy for COVID-19.

      Limitations<br /> The authors train their algorithm on SARS Coronavirus 3C-like Protease, as inhibitors of this protein should prevent the virus from replicating in the host. However, the authors note that the most promising target seems to be SARS-CoV-2 spike protein. Moreover, the training dataset is the result of in vitro studies, and may have limited relevance in vivo.<br /> Overall, preclinical studies and then potential clinical trials would need to be performed before administering this drug to COVID-19 patients though, admittedly, clinical validation of an existing drug could happen faster than the development of new drugs entirely. Saquinavir has been studied in vitro by Yamamoto et al.[1], and shown little promise in SARS-CoV-2 treatment so far.

      Significance<br /> Repurposing of existing drugs is can be advantageous to develop treatment strategies. An in silico approach could help identify potential therapies, although they must be confirmed in clinical trials before being administered on a large scale.

      References<br /> Yamamoto et al. Nelfinavir inhibits replication of severe acute respiratory syndrome coronavirus 2 in vitro. BioRXiV preprint, 2020

      Credit<br /> Reviewed by Maria Kuksin as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

    1. On 2024-04-27 18:42:07, user Kim Brumfield wrote:

      Thank you to Dr. Myles and his team for doing this research. My daughter has 20 years of prescribed steroid use for eczema without informed consent of the risk of topical steroid addiction and withdrawal. The dermatologists she saw used step therapy which eventually resulted in tachyphylaxis. The topical steroids stopped working after reaching hichest potency and now she is suffering from "eczema on steroids" which is really topical steroid withdrawal. Please help us find the cure for this horrible iatrogenic disease.

    2. On 2024-04-27 19:07:49, user Toby wrote:

      So glad to see that this problem is being taken seriously. I have suffered from eczema all my life and from TSW as described here for many years. I hope this research will result in new treatments for this awful condition.

    3. On 2024-04-27 19:50:44, user Eve Benson wrote:

      I am starting my 8th year of TSW. The first five years were torture, the last few have been manageable. I can identify with every symptom listed in this study. I can also identify with the stress of seeing several "well-meaning" doctors whose only choice of treatment was putting me back on steroids, which I refused thanks to the education I received from online communities of thousands of people who were suffering like myself. More studies like this one are needed. TSW is real. Sufferers of TSW deserve appropriate medical care and care from practitioners who understand the disease and thus provide appropriate treatment. It is time for medical institutions to step up and address TSW.

    4. On 2024-05-02 15:45:09, user Kelly Barta wrote:

      This is such an important and groundbreaking study in its showing a differentiation between Atopic Dermatitis and Topical Steroid Withdrawal Syndrome, which has been one of the big debates within the medical community. Patients need and deserve acknowledgement and support from their health care providers, but understandably, this is unable to happen without the science to back up what we are seeing anecdotally in the eczema patient population.

      More research is needed to determine how and when topical steroids are creating these dysfunctions in patients in order to better understand their proper use and prescribing guidelines. This research is CRITICAL to the over 31 million Americans living with eczema and over 300 million worldwide (not to mention the countless other dermatology patients), who are prescribed topical steroids to manage a skin condition.

    1. On 2020-02-13 21:52:14, user reuns wrote:

      I deduce from "case 13: no viral RNAs were detected until the fourth upper respiratory samples" that in the graphic U means negative

    1. On 2020-03-25 19:31:48, user Charles Haas wrote:

      My concern with their disinfection experiments is that there is no indication that they neutralized the disinfectant prior to culturing. This is an absolute necessity.

    1. On 2020-05-28 08:18:17, user Philippe Brouqui wrote:

      The paper of KIM et all reports on the response to treatment of hydroxychloroquine or<br /> lopinavir-ritonavir with or without antibiotic in a retrospective cohort study<br /> with comparison with standard of care. The evaluation has been carried out on<br /> moderate case only and no death were reported. They assume that HCQ and ATB is superior to both SCO and LR plus ATB in time to viral clearance, length of hospital<br /> stay, duration of fever and cough. Adverse event been significantly different<br /> from SOC but not different between the two arms of treatment and only<br /> mild. <br /> Methodology: Is appropriate for the aim<br /> -The study is relevant to the aims: treat patient early (non-severe disease) at the time to diagnosis to avoid complication and death<br /> - The study is relevant toward bringing new data in time to outbreak by using repurposing of drugs HCQ and LR <br /> -The study is relevant toward bias related to heterogeneity of care as a single center study.<br /> - Classification of patients referred to NIH Guidelines (NEWS Score) as mild, moderate and severe COVID<br /> - Definition of negative PCR and viral clearance is in adequation to previous published literature.<br /> -Treatment was done within the range of recommended dosage ; HCQ 200mg/ twice a day as well as for lopinavir/ritonavir 200/50 mg, however higher doses are generally used for HCQ (600mg/d). For antibiotics there were given as recommended

      Ethics

      -Data were collected through the patient medical file of the hospital blinded and using patient dataprotection

      Outcome measures<br /> -Correspond to aims delay between treatment initiation and viral clearance, discharge from hospital and symptoms resolution

      Statistical analysis

      This is classical analysis methods relevant to aim

      Confounding bias/ Limitation:<br /> -Those relative to retrospective study but well a posteriori controlled <br /> -As a retrospective study of the 358 patients (270) 173 mild and 97 moderate covid-19 cases were analyzable for completion of treatment and data availability. <br /> - 3/270 patients were still ongoing treatment at time of release (1%)<br /> - 97 moderate Covid-19 patients were categorized HCQ ATB SOC (22) LR ATB Soc (35), SoC (40) and analyzed for treatment and outcomes<br /> -A posteriori comparative analysis shows that the two groups HCQ and LR were identical in terms of comorbidity and other known factors that may weigh on the outcome.<br /> -Comparison with the Soc group alone showed that this last was less severely ill<br /> (significantly less pneumonia), and factor associated with poor outcomes, such<br /> as low lymphocytes count, and elevated CRP were associated with the treated<br /> groups. Interestingly dyspnea was more prevalent in this SOC group but we know<br /> that absence of dyspnea (silent hypoxemia) is rather than dyspnea linked to<br /> outcome. This suggest that if a difference in treatment exist it will probably<br /> be under evaluated. <br /> - Retinopathy to HCQ as never been reported in such short treatment and HCQ in serum returns to negative in 15 days after end of treatment (unpublished) <br /> The limitation of the study as been well reported

      Interpretation of results: adequate except comparison LR/LR and ATB<br /> Time to clearance are shorter particularly in the HCQ and ATB group for which time to PCR > 35CTis 12 days in what is published elsewhere<br /> -Cough resolve significantly better in the HCQ ATB and fever in the two treated groups compare to SOC.

      Adverse events were more frequent but only mild

      The subgroup analysis LR versus LR ATB should be interpreted carefully as we don’t know interval time to onset of the LR only arm which may interfere with viral clearance of this subgroup.

      Conclusion<br /> This study appropriately show that HCQ & ATB is better than LR & ATB than to SOC<br /> to shorten viral clearance, resolution of symptoms, and to shorten hospitalization duration in moderate form of COVID-19. The role of ATB alone to shorten viral clearance is overestimated

      Note : P BROUQUI , has no conflict of interest with the industry concerning this review<br /> but has already published study supporting the efficiency of HCQ and azithromycin in COVID-19.

    1. On 2020-04-26 13:59:26, user Italian_in_london wrote:

      There is an important element of this research widely mentioned in Italian TV interviews and on Italian generalist press: the isolation of all positive cases caused a sharp drop (60%) in intensive care cases, as if the high viral load of people exposed to multiple contacts with positive cases is the main cause as to why some people end up I intensive care. I am interested to understand why information allegedly coming from this research does not seem to appear here. It is obvious what the implications are for medical staff being asked to go back to work despite being still contagious.

    1. On 2021-12-05 11:00:28, user Professor Ritual wrote:

      I actually like the modelling idea, a noble effort - but as things move fast the data used in the study is now outdated. Please remodel for the current data: 71% senior breakthrus and 50% adult breakthrus.

    1. On 2020-04-07 01:06:33, user Cristian Reyes P. wrote:

      In Chile BCG vaccine has been mandatory since 1949. Everybody is vaccinated. Over 90% of the population. You can study us. We still have the lowest mortality in the region.

    1. On 2020-07-24 16:43:50, user Kamran Kadkhoda wrote:

      The correlate of protection is not inferred this way it is typically inferred through prospective vaccine trials in SARS-CoV-2-native volunteers.

    1. On 2020-04-08 01:57:26, user Eliot Abrams wrote:

      This just fits a gaussian curve. Absurd. Among other reasons, there is a second wave as soon as the current shelter in place restrictions are lifted.

    1. On 2021-12-22 14:03:31, user Simone Davies wrote:

      I had these symptoms (vibrations for months, muscle twitching for days) after my all 3 of my vaccine shots. I had not had covid before I was vaccinated. Would be interested to know if this is true in others?

    1. On 2020-06-09 17:41:58, user Hamid Reza Marateb wrote:

      This is a hospital-based cohort whose results could not be generalized to the population. Moreover, these patients usually have commorbidity, and thus avoid smoking. Here are justifications.

    1. On 2020-08-08 06:57:06, user Dr-Beesan Maraqa wrote:

      Thank you for this study. I am struggling to find studies assessed the associations between stress and demographic factors, job title, and relation to social life.

    1. On 2022-01-01 05:17:59, user Ardiana wrote:

      N501Y and E484K signals high spread ability and original vaccine antibody evasion. But there were many variants like this and that couldn't beat Delta.

    1. On 2020-04-15 11:57:26, user Renato Prandina wrote:

      Duration and extent of immune protection will be critical to the novel betacoronavirus SARS-CoV-2 and will unfold in coming years. Some speculative scenarios...

    1. On 2020-04-16 12:20:10, user Marlowe Fox wrote:

      The tests on the efficacy of HCQ are confounded by multiple variables, including comorbidities, symptom onset, prescription drugs (RAAS inhibitors appear to play a key role in viral intensity), and testosterone/estrogen level, to name only a few.

      Geneticists, epidemiologists, and other scientists have long used casual diagrams to clearly show variables that may potentially confound their results (1). The Wuhan study at the very least would need to account for the following:

      HCQ <— comorbidities —> recovery<br /> HCQ <— symptom onset —> recovery<br /> HCQ <— drug prescriptions —> recovery

      Adjusting for the confounding variable would essentially smooth out the flow of information between the treatment (HCQ) and the outcome (recovery), allowing for the inference of causal effects.

      Assuming observable data is not available to adjust for confounding variables, a casual mechanism (mediator) could smooth out the flow of information from the treatment to the outcome (so long as the mediator is not influenced by confounder).

      Luckily, multiple in vitro studies have been performed. One study posits that HCQ lowers endosomal pH which ultimately inhibits COVID from binding to ACE 2 and decreasing viral intensity (3).

      HCQ —> endosomal pH —>glycosylation of COVID cellular receptor —> ACE 2 binding —> viral intensity —> acute lung injury

      Another in-silico study posits that HCQ blocks specific protein sites on the host ACE2 cell, thereby thwarting its attempt to infect it and preventing the cytokine storm (over-reaction of the lymphatic system) that some posit is responsible for Acute Lung Injury (3). So here we have an entirely different causal mechanism:

      HCQ —> BRD-2 receptor sites —> cytokine storm —> acute lung injury

      Despite these problems, some believe that the p-values obviate the need to control for potentially lurking variables. However, they are subject to myriad influences, known as p-hacking. Whether it is the number of tests performed or the number of comparisons made, it increases the chance of finding a statistically significant p-value (4). Three professional statisticians co-authored a paper reviewing the validity of the Wuhan study (5). There were several issues with the data upon which the two significant p-values were based.

      I suppose there is also a pragmatic argument: The p-values, along with existing studies and reports, are sufficient enough evidence to offset any concern for lurking variables in these urgent times. In other words, how much evidence is sufficient to warrant large scale roll-out of a low-cost treatment that may have a beneficial effect, from saving individuals who would have otherwise died to curbing its spread?

      The consequences of large roll-out: manufacturing, scaling, distribution chains, and so forth could result in a tremendous diversion of resources. How many pharmaceutical manufacturers even have the capacity to roll out production of this magnitude? What if they all start scaling their labor to produce this particular drug. You can’t just put this genie back into the bottle. Not to mention the scientific energy/intellectual capital that would go to proving or disproving this proposed treatment. And why? Because scientific evidence demanded it? No because a tortured p-value and unpublished/unsubstantiated anecdotal evidence caught the attention of some in the media, and it has been over-popularized as a panacea. What about the risk that HCQ is not an effective treatment despite large investments in cash and resources that have been invested? Do you think the wheels of capitalism turn so easily? Investors will want a return and if that means continually touting an ineffective drug through spurious science, they will continue to do so. What about individuals taking HCQ as a prophylactic, believing themselves to be protected against COVID? Or COVID+ individuals taking HCQ and believing themselves to be cured? Or individuals who think: Well, if I get it—I’ll just take HCQ and be fine. This would increase the spread of COVID. From my perspective, the ignorance to viral transmission and the required precautions is widespread. This is just one more reason not to acquiesce to the new social norms of wearing face masks, social distancing, and abiding by shelter-in-place rules. Here, I think an understanding of cognitive psychology is important to anticipate the future behavior of a society in which a cheap and easy-to-manufacture cure is published in the media.

      To sum up, HCQ's efficacy is not sufficiently proven to warrant a widespread roll-out, because it could result in several downstream consequences, from the diversion of resources (both manufacturing capabilities and intellectual capital) to increasing the risk threshold of individuals--who spurious believe in an easy and cheap treatment--thereby increasing the infection rate. One of two things needs to happen. Clinical trials that properly adjust for all potential comorbidities. Or the discovery of a causal mechanism (in vivo), which would obviate the need to control/adjust for confounders. For me, this would tip the utilitarian scales in regard to the potential benefits versus the risks.

      References

      1. Judea Pearl and Dana Mackenzie. 2018. The Book of Why: The New Science of Cause and Effect (1st. ed.). Basic Books, Inc., USA.
      2. https://www.ncbi.nlm.nih.go...
      3. https://papers.ssrn.com/sol...
      4. https://www.scientificameri....
      5. https://zenodo.org/record/3....
    1. On 2019-10-30 08:25:55, user Marema wrote:

      This paper is done to investigate how acute financial problems affect undergraduate students' clinical learning.The study used qualitative method to explore their experiences. I here for further information.

    1. On 2020-05-06 06:53:53, user Hossein Mirzaei wrote:

      Dear Georg<br /> i cant find table 1 in your article, Which you refereed to that for Main characteristics of patient.<br /> can you help me to find that?<br /> Thanks<br /> Hossein

    1. On 2020-02-17 08:52:17, user Ellie_K wrote:

      Once this paper has been peer-reviewed, could someone post here in the comments where (i.e. in which scholarly journal) it is published? Thank you!

    1. On 2020-03-04 13:30:42, user Bìtao Qiu wrote:

      I think there are some wrongly put numbers on Table 3 (page 35), e.g. n = 59 for Immunodeficiency patients. It should be 3 according to the abstract and n = 3 on page 36.

    1. On 2020-09-19 14:10:12, user kdrl nakle wrote:

      Given the low infection rates you most likely have many false positives and the adjustment is probably of uncertain quality. Basically, it is not very accurate to use serosurveys in low infection areas.

    1. On 2020-03-24 19:18:13, user Luis Cabrera wrote:

      In the Extended Data 2, there is another standard curve, instead of "Primer, reporter molecules, target gene fragments, and guide RNAs used in this study. "

    1. On 2020-03-26 15:11:11, user Sinai Immunol Review Project wrote:

      Study description: Plasma cytokine analysis (48 cytokines) was performed on COVID-19 patient plasma samples, who were sub-stratified as severe (N=34), moderate (N=19), and compared to healthy controls (N=8). Patients were monitored for up to 24 days after illness onset: viral load (qRT-PCR), cytokine (multiplex on subset of patients), lab tests, and epidemiological/clinical characteristics of patients were reported.

      Key Findings:<br /> • Many elevated cytokines with COVID-19 onset compared to healthy controls <br /> (IFNy, IL-1Ra, IL-2Ra, IL-6, IL-10, IL-18, HGF, MCP-3, MIG, M-CSF, G-CSF, MIG-1a, and IP-10).<br /> • IP-10, IL-1Ra, and MCP-3 (esp. together) were associated with disease severity and fatal outcome. <br /> • IP-10 was correlated to patient viral load (r=0.3006, p=0.0075).<br /> • IP-10, IL-1Ra, and MCP-3 were correlated to loss of lung function (PaO2/FaO2 (arterial/atmospheric O2) and Murray Score (lung injury) with MCP-3 being the most correlated (r=0.4104 p<0.0001 and r=0.5107 p<0.0001 respectively).<br /> • Viral load (Lower Ct Value from qRT-PCR) was associated with upregulated IP-10 only (not IL-1Ra or MCP-3) and was mildly correlated with decreased lung function: PaO2/FaO2 (arterial/atmospheric O2) and Murray Score (lung injury).<br /> • Lymphopenia (decreased CD4 and CD8 T cells) and increased neutrophil correlated w/ severe patients.<br /> • Complications were associated with COVID severity (ARDS, hepatic insufficiency, renal insufficiency).

      Importance: Outline of pathological time course (implicating innate immunity esp.) and identification key cytokines associated with disease severity and prognosis (+ comorbidities). Anti-IP-10 as a possible therapeutic intervention (ex: Eldelumab).

      Critical Analysis: Collection time of clinical data and lab results not reported directly (likely 4 days (2,6) after illness onset), making it very difficult to determine if cytokines were predictive of patient outcome or reflective of patient compensatory immune response (likely the latter). Small N for cytokine analysis (N=2 fatal and N=5 severe/critical, and N=7 moderate or discharged). Viral treatment strategy not clearly outlined.

    1. On 2020-05-18 12:43:08, user Sinai Immunol Review Project wrote:

      Long period dynamics of viral load and antibodies for SARS-CoV-2 infection: an observational cohort study<br /> Huang et al. medRxiv [@doi.org/10.1101/2020.04.22.20071258]<br /> Main Findings<br /> The presence of serum IgM and IgG against SARS-CoV2 has been shown in several studies, however, a limited number of studies have shown the longitudinal relationship between viral RNA levels and antibody titers. This retrospective, observational study evaluated the dynamics of viral RNA, IgM and IgG specific for SARS-CoV2 proteins in patients with confirmed SARS-CoV-2 pneumonia over an 8-week period. <br /> Throat swabs, sputum, stool and blood samples from 33 patients with laboratory confirmed SARS-CoV-2 pneumonia were collected to analyze viral load and specific IgM and IgG against spike protein (S), spike protein receptor binding domain (RBD), and nucleocapsid (N). The demographics of the patients showed that 24 had respiratory symptom, two had symptoms in both the respiratory and the gastrointestinal tracts, one had gastrointestinal symptoms and six were asymptomatic. Chest CT revealed 27 patients had bilateral infiltrates and six had unilateral infiltrates. All the patients received antiviral treatment and atomized interferon during hospitalization. <br /> While viral load in throat swabs and sputum was higher at the symptom onset and undetectable by three weeks and five weeks respectively, viral load in stool started low but remained detectable for more than five weeks in many patients. The viral loads in sputum declined significantly slower compare to throat, so that the patients were divided into two groups based on load in sputum: short-persistence (viral RNA undetectable within 22 days, n=17) and long-persistence (viral RNA persists more than 22 days, n=16). The relationship between the persistence of sputum viral RNA and antibodies showed that short-persistence group had higher anti-S IgM, anti-RBD IgM and anti-RBD IgG levels compare to long-persistence group suggesting a potential protection by anti-RBD antibodies. The length of time from symptom onset to hospital admission was also associated with SARS-CoV-2 viral clearance. In addition, the higher seropositive rate for anti-S and anti-RBD IgM was seen in long-persistence patients. They suggest that delayed admission to the hospital resulted in higher seropositive and longer infection in patients with COVID-19.<br /> Limitations<br /> The separation of ‘low persistence’ vs ‘high persistence’ groups seems quite arbitrary, as only virus RNA levels for in sputum were considered, and viral loads in throat swabs and stool were not considered (these were no significant difference between the low vs high groups. The manuscript needs better and more detailed description of methods and figure legends. The same color codes for each patient could be used in figure 1, so that the readers could see if there was a trend in viral load between specimens in a same patient, and graphics for each patient will be useful to understand viral dinamics in the three types of samples for each person. The graphs on figure 5 seemed to correspond to one time point data, but there was no explanation which time point was used. In the results section, it was not clear which figures or tables were related to the text. The correlation between severity, viral load and persistency, and antibody titers could be analyzed.<br /> Significance<br /> It is important to understand the relationship between viral loads, disease progression and viral-specific antibodies in COVID-19 disease. More studies are necessary.

      Reviewed by Miyo Ota as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

    1. On 2020-10-30 23:23:26, user Leonidas Palaiodimos wrote:

      This article has been reviewed by peers and published at Hormones-the International Journal of Endocrinology and Metabolism

    1. On 2020-04-22 04:36:02, user Paul Hue wrote:

      Has Covid19 been truly isolated? Have its purported surface proteins been linked to genetic sequences in recovered genetic material from a true isolation?

    1. On 2020-04-23 17:39:53, user Patrick wrote:

      "Rates of ventilation in the HC, HC+AZ, and no HC groups were 13.3%, 6.9%, 14.1%, respectively."

      "The risk of ventilation was similar in the HC group [...] and in the HC+AZ group [...], compared to the no HC group."

      Is there a mistake in one of these sentences, or am I reading this right?

    2. On 2020-04-24 20:55:11, user wangkon936 wrote:

      The issue with a "retrospective" study is that populations cannot be randomized. It is clear just looking at the data that the vitals and the biochemistry of the hydroxlchloroquine ("HC") or hydroxlchloroquine and azithromycin group ("HC + AZ") was inferior vs. the non HC or HC + AZ group. In other words the HC and HC + AZ groups were significantly unhealthier vs. the the non HC or HC + AZ groups. A randomized true clinical trial would have filtered this bias out, but a retrospective study structurally solidified this bias in. Thus, this study has a structurally solid bias that render's its ultimate conclusions suspect and of limited use.

    3. On 2020-04-25 08:48:51, user Huan Mo wrote:

      Of course the patients who were treated with hydroxychloroquine were sicker at the baseline. The no-hydroxychlroquie patients have tons of missing values in basic labs and apparently they are mostly mild and outpatients.

      This study is like saying pneumonia treated in tertiary medical center has worse outcome than treated in an outpatient clinic.

    1. On 2020-11-18 21:50:14, user Hamid Merchant wrote:

      Very interesting findings. Can you post the Ct values of all individual patients at different time points in a table as a supplementary data file please?

    1. On 2022-10-24 19:47:27, user Camille Sawosik wrote:

      The main goal of this study was to create a new model in order to diagnose brain disorders as they are often complex and get misdiagnosed. It seems that the researchers here have created a base computer model in order to diagnose brain disorders. The main critique here, as even the researchers point out, is that the model needs greater development and study before it can be applied in a clinical setting. At this point in development of the model, I would say that this paper has moderate significance, but could provide a breakthrough in the field if further development occurs. For now, the brain samples looked at all came from a limited number at the NBB. In the future, perhaps applying this model in other populations would continue to develop its significance within the field. The large majority of this paper relied on methods based in computer design. Coming from someone with a smaller background in these methods, I would have liked to see greater description of what they did. For example, at one point the FuzzyWuzzy library is referenced, and it would have been helpful to include some explanation of what this is. At some points as well, I found that the methods were essentially repeated in the results. The concept was interesting, but it was often hard to follow exactly what was done as this study seemed much more programing and computing based. In some sections, as well, tables or figures were referenced, but then those tables did not exist within the paper. Moving forward, other researchers should definitely use this as a building block for the future in order to build off of and develop a more advanced model. The findings here are interesting and provide a good framework for future extrapolation of the model. I found this paper interesting and hope for future development to get this idea into a clinical setting!

    1. On 2022-11-17 03:39:53, user M. Cunningham wrote:

      The FDA EUA specifies that Paxlovid's window of availability requires the patient to be within both 5 days of symptom onset and the first positive test, whichever comes first. Is this not the VA's protocol? I only saw the testing aspect mentioned. I would think that this would further narrow the margins of error (eg: confirming early treatment). Additionally, Paxlovid is nirmatrelvir and the co-drug ritonavir. Since the press is already reporting this the same as a peer-reviewed finding, IMHO it's important to correct these omissions so that the public is not confused about the use of this medication. But I am enthusiastic to re-read the study when it has been evaluated and reviewed! Thank you for your research.

    1. On 2022-12-02 16:36:24, user Mark Czeisler wrote:

      Note from the authors:

      A revised version of this paper was published in Annals of Internal Medicine on 29 November 2022 following peer review. Below is a link to the article, along with the PubMed citation.

      https://www.acpjournals.org...

      Czeisler MÉ, Czeisler CA. Shifting Mortality Dynamics in the United States During the COVID-19 Pandemic as Measured by Years of Life Lost. Ann Intern Med. 2022 Nov 29. doi: 10.7326/M22-2226. Epub ahead of print. PMID: 36442062.

    1. On 2022-12-26 13:26:47, user y wang wrote:

      You did not indicate the method of calculating the chi-squre.<br /> Actually, your method does not seem correct. <br /> One can google "Comparing Two Independent Population Proportions" and find the formula and calculator.<br /> Using the calculator, I found z=6.00, i.e., chi-squre=36 (not your 35.67).

    1. On 2023-04-21 12:49:03, user antonia peros wrote:

      I believe that the topic of your research is very important and current, however, I have several methodological objections. <br /> Although the authors pointed out the limitations, they made quite strong conclusions and recommendations despite too small, non-randomized sample and a cross-sectional design without a control group.<br /> The use of the used instruments is very questionable when it comes to recalling satisfaction, self-esteem, and reduction in depression from 6 months ago. I also think that the fact that the respondents were familiar with the purpose of the research could have contributed to the recall bias.<br /> An important factor in your research could be how long the subjects exercised, and you did not collect that data. What their target is in the research is also vaguely defined. I recommend including some more objective criteria for that.

    1. On 2023-05-18 19:00:12, user Dave Fuller wrote:

      Please add final peer-reviewed citation as:

      Lin D, Wahid KA, Nelms BE, He R, Naser MA, Duke S, Sherer MV, Christodouleas JP, Mohamed ASR, Cislo M, Murphy JD, Fuller CD, Gillespie EF. E pluribus unum: prospective acceptability benchmarking from the Contouring Collaborative for Consensus in Radiation Oncology crowdsourced initiative for multiobserver segmentation. J Med Imaging (Bellingham). 2023 Feb;10(Suppl 1):S11903. doi: 10.1117/1.JMI.10.S1.S11903. Epub 2023 Feb 8. PMID: 36761036; PMCID: PMC9907021.

      Thanks!!

      CDF

    1. On 2023-06-01 01:20:57, user Edmund Seto wrote:

      This paper has been accepted for publication in the journal Science of the Total Environment under the title "Assessing the effectiveness of portable HEPA air cleaners for reducing particulate matter exposure in King County, Washington homeless shelters: Implications for community congregate settings"

    1. On 2023-09-20 17:48:48, user ASH wrote:

      Why did the authors investigate the associations between poultry fecal matters and E.coli, instead of other more poultry-specific zoonosis, like Salmonella? E. coli is commonly found in the lower intestine of warm-blooded organisms, of which most are harmless...<br /> Why didn't the authors check the DHS data? Similar data can be found in the DHS data which is publicly available.

    1. On 2023-11-04 15:16:53, user Clive Bates wrote:

      Two problems here.

      First is scalability. This doesn't sound like an intervention that would engage many veterans, nor does it seem likely to be affordable or practical at the scale necessary to achieve a turnaround in the aggregate burdens arising from smoking.

      Tobacco-related deaths exceed those resulting from homicides, suicides, motor vehicle accidence, alcohol consumption, illicit substance use, and acquired immunodeficiency syndrome (AIDS), combined.

      Almost all of that excess mortality is attributable to smoking not nicotine. Tobacco harm reduction approaches may deliver more and sooner - e.g. encouraging migration to smoke-free alternative forms of nicotine use such as vaping.

      Second, it is quite possible that veterans with forms of PTSD are benefiting in some way from the functional and therapeutic properties of nicotine. Again, an approach to smoking cessation that does not demand nicotine cessation may achieve nearly all the health benefits of quitting smoking without demanding withdrawal from nicotine use.

      The trial could at least consider an additional arm to assess the utility of encouraging vaping for smoking cessation. It might achieve more for less.

    1. On 2023-11-13 10:04:59, user Theo Peterbroers wrote:

      "The duration from the day of index vaccination to the day of the survey completion was a median of 595 days (Interquartile Range<br /> (IQR): 417 to 661 days; range: 40 to 1058 days)."<br /> That is at least one participant vaccinated before the start of the pandemic.<br /> EDIT Make that one person from early in the vaccine trials. How time flies.

    1. On 2023-11-15 16:42:12, user jhick059 wrote:

      This article was published in the peer-reviewed journal PLoS One on October 30, 2023 (citation below), but the medRxiv page has not yet been updated to reflect the PLoS One publication.

      Citation: Hickey J, Rancourt DG (2023) Predictions from standard epidemiological models of consequences of segregating and isolating vulnerable people into care facilities. PLoS ONE 18(10): e0293556. https://doi.org/10.1371/jou...

    1. On 2023-11-27 21:08:47, user Judith Mowry wrote:

      The recent paper on peripheral vasopressors by Yerke doi.org/10.1016/j.chest.202... is an important reference for your research. It is vital to note that they changed their protocol to add very specific protocols and rules regarding IV site inspection, defined who was responsible. Also note that an antecubital site (or any joint) is avoided to minimize movement and extravasation risk. I wish you success with your research.

    1. On 2024-02-20 21:32:15, user Wally Wilson wrote:

      It would be handy if the authors could get the abbreviations for Borderline Personality Disorder (BPD) and Bipolar Disorder (BD) corrected

    1. On 2024-04-25 03:20:17, user Lena Palaniyappan wrote:

      Very interesting work. We observed a similar 'amelioration' effect using a cross-sectional design a few years ago (Guo et al., 2016). Since then we made several cross-sectional and a few longitudinal observations supporting the possibility of compensation and reorganisation after first episode psychosis (Palaniyappan et al., 2019a; 2019b), including one with the largest untreated sample we could access at that time (Li et al., 2022). These observations compel us to spare more efforts to understand the compensatory processes in psychosis (Palaniyappan et al, 2017, Palaniyappan & Sukumar 2020, Palaniyappan, 2021; 2023).

      Guo S, Palaniyappan L, Liddle PF, Feng J. Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study. Psychological medicine. 2016 Jul;46(10):2201-14.

      Li M, Deng W, Li Y, Zhao L, Ma X, Yu H, Li X, Meng Y, Wang Q, Du X, Sham PC. Ameliorative patterns of grey matter in patients with first-episode and treatment-naïve schizophrenia. Psychological Medicine. 2023 Jun;53(8):3500-10.

      Palaniyappan L. Progressive cortical reorganisation: a framework for investigating structural changes in schizophrenia. Neuroscience & Biobehavioral Reviews. 2017 Aug 1;79:1-3.

      Palaniyappan L, Das TK, Winmill L, Hough M, James A, Palaniyappan L. Progressive post-onset reorganisation of MRI-derived cortical thickness in adolescents with schizophrenia. Schizophr Res. 2019a Jun 1;208:477-8.

      Palaniyappan L, Hodgson O, Balain V, Iwabuchi S, Gowland P, Liddle P. Structural covariance and cortical reorganisation in schizophrenia: a MRI-based morphometric study. Psychological Medicine. 2019b Feb;49(3):412-20.

      Palaniyappan L, Sukumar N. Reconsidering brain tissue changes as a mechanistic focus for early intervention in psychiatry. Journal of psychiatry & neuroscience: JPN. 2020 Nov;45(6):373.

      Palaniyappan L. The neuroscience of early intervention: Moving beyond our appeals to fear. Australian & New Zealand Journal of Psychiatry. 2021;55(10):942-943.

    1. On 2024-04-26 17:02:43, user Gary Goldman wrote:

      We broadened our analyses (of IMRs) to explore potential relationships between childhood vaccine doses and NMRs (neonatal mortality rates) and U5MRs (under age 5-year mortality rates). Using 2019 and 2021 data, 17 of 18 analyses (12 linear regressions and six ANOVA and Tukey-Kramer tests) achieved statistical significance and corroborated the trend reported in our original study, demonstrating that as developed nations require more vaccine doses for their young children, mortality rates worsen. Please see https://pubmed.ncbi.nlm.nih...

    1. On 2024-05-02 18:11:05, user Keith Robison wrote:

      There is a great degree of interest in this preprint due to it being the first extended description of using the iCLR technology.

      It would be very valuable to have details on how much Illumina short read data was generated from iCLR libraries and how much of that data contributed to the iCLR reads vs. what could not be used

      It would also be valuable to report the read length distribution of the iCLR reads in greater detail - particularly since many interested parties cannot perform that analysis themselves on the clinical data sets

    1. On 2024-11-08 19:59:59, user Andre Boca Ribas Freitas wrote:

      Important Observations on Underreported Chikungunya Mortality in Light of Global Burden Analysis

      Dear Authors,

      I thoroughly appreciated your recent preprint on the global burden of chikungunya and the potential benefits of vaccination. Your work provides critical insights into the widespread impact of this disease and emphasizes the significant potential of vaccine interventions.

      However, I wanted to highlight a critical issue that our research and that of others in the field have identified: the substantial underreporting of chikungunya-related mortality across many regions. While chikungunya is often categorized as a non-fatal disease, a growing body of evidence reveals severe and sometimes fatal cases that frequently go unrecorded by epidemiological systems. Our recent studies in Brazil documented excess mortality rates from chikungunya far surpassing those officially reported, with mortality rates up to 60 times higher than recorded by standard surveillance systems?Freitas et al., 2024?. Additionally, studies like those by Mavalankar et al. (2008) in India and Beesoon et al. (2008) in Mauritius underscore the elevated mortality associated with chikungunya during epidemic outbreaks, further reinforcing this critical gap in mortality surveillance.<br /> This growing evidence highlights the critical need for increased investment in molecular diagnostics, integrated surveillance, and more comprehensive mortality tracking for chikungunya. These measures are essential for aligning public health responses with the true impact of the disease and ensuring the full scope of chikungunya’s burden is addressed.

      Thank you for advancing this essential conversation. Through improved surveillance and research collaboration, we can work toward effective strategies to mitigate the severe impact of chikungunya globally.

      Best regards,

      Dr. André Ricardo Ribas Freitas<br /> Faculty of Medicine, São Leopoldo Mandic, Campinas-SP, Brasil

      Freitas ARR, et al. Excess Mortality Associated with the 2023 Chikungunya Epidemic in Minas Gerais, Brazil. Front Trop Dis. 2024. doi: 10.3389/fitd.2024.1466207.

      Mavalankar D, Shastri P, Bandyopadhyay T, Parmar J, Ramani KV. Increased mortality rate associated with chikungunya epidemic, Ahmedabad, India. Emerg Infect Dis. 2008 Mar;14(3):412-5. doi: 10.3201/eid1403.070720. PMID: 18325255; PMCID: PMC2570824.

      Beesoon S, Funkhouser E, Kotea N, Spielman A, Robich RM. Chikungunya fever, Mauritius, 2006. Emerg Infect Dis. 2008 Feb;14(2):337-8. doi: 10.3201/eid1402.071024. PMID: 18258136; PMCID: PMC2630048.

      Manimunda SP, Mavalankar D, Bandyopadhyay T, Sugunan AP. Chikungunya epidemic-related mortality. Epidemiol Infect. 2011 Sep;139(9):1410-2. doi: 10.1017/S0950268810002542. Epub 2010 Nov 15. PMID: 21073766.

      Freitas ARR, Donalisio MR, Alarcón-Elbal PM. Excess Mortality and Causes Associated with Chikungunya, Puerto Rico, 2014-2015. Emerg Infect Dis. 2018 Dec;24(12):2352-2355. doi: 10.3201/eid2412.170639. Epub 2018 Dec 17. PMID: 30277456; PMCID: PMC6256393.

      Freitas ARR, Gérardin P, Kassar L, Donalisio MR. Excess deaths associated with the 2014 chikungunya epidemic in Jamaica. Pathog Glob Health. 2019 Feb;113(1):27-31. doi: 10.1080/20477724.2019.1574111. Epub 2019 Feb 4. PMID: 30714498; PMCID: PMC6427614.

    1. On 2024-12-03 21:03:36, user xPeer wrote:

      Courtesy review from xPeerd.com

      This manuscript introduces DeepEnsembleEncodeNet (DEEN), an innovative polygenic risk score (PRS) model integrating autoencoders and fully connected neural networks (FCNNs) to address limitations of existing PRS methods. By disentangling dimensionality reduction and predictive modeling, DEEN enables the capture of both linear and non-linear SNP effects, improving prediction accuracy and risk stratification for binary (e.g., hypertension, type 2 diabetes) and continuous traits (e.g., BMI, cholesterol). Evaluation using UK Biobank and All of Us datasets highlights superior performance over established methods. While conceptually and methodologically compelling, areas such as interpretability, generalizability across diverse populations, and computational efficiency warrant further refinement.

      Major Revisions<br /> 1. Interpretability and Practicality<br /> Black-Box Concerns: The complexity of the DEEN model limits its interpretability compared to simpler PRS methods like Lasso or PRSice. While the manuscript acknowledges this limitation, incorporating efforts to visualize model predictions (e.g., feature importance maps or SNP clustering analysis) would enhance its usability (Section: Discussion, p.16).<br /> Clinical Translation: The manuscript emphasizes the potential of DEEN for clinical utility but lacks discussion on the challenges of implementing deep learning models in healthcare. Addressing regulatory barriers and clinician engagement would add value (Section: Discussion, p.17).<br /> 2. Population Generalizability<br /> Demographic Bias: Both datasets used (UK Biobank, All of Us) consist predominantly of European-ancestry individuals. This limits the model's applicability to global populations. Expanding the discussion on efforts to improve DEEN’s cross-ancestry generalizability is essential (Section: Results, p.11).<br /> Validation Across Diverse Cohorts: While DEEN is validated on two datasets, additional external validations across non-European populations would strengthen claims of generalizability and reliability.<br /> 3. Comparative Analyses<br /> Missing Baseline Methods: Although DEEN is compared with multiple PRS methods, inclusion of additional machine learning benchmarks (e.g., gradient boosting models, convolutional neural networks for SNP effects) would better contextualize DEEN’s advantages (Section: Results, p.8).<br /> Risk Stratification Assessment: The risk stratification results are promising but need more rigorous evaluation metrics beyond odds ratios, such as net reclassification improvement (NRI) or integrated discrimination improvement (IDI).<br /> 4. Computational Efficiency<br /> Resource Requirements: DEEN’s reliance on high-performance computing resources (e.g., GPU usage) is noted but not sufficiently quantified. Providing benchmarks of computational costs and runtime against alternative methods is crucial for practical implementation (Section: Methods, p.19).<br /> Optimization: While grid search was used for hyperparameter tuning, exploring automated optimization frameworks (e.g., Bayesian optimization) could reduce computational overhead.<br /> 5. Data Filtering and Variant Selection<br /> Potential Bias from Variant Filtering: The preselection of SNPs based on p-values may exclude rare variants or those with small effects. A sensitivity analysis on SNP filtering thresholds would clarify the robustness of DEEN’s predictive power (Section: Methods, p.20).<br /> Minor Revisions<br /> 1. Typos and Formatting<br /> Figure Legends: Some figures (e.g., Figure 5) lack clear explanations of axes and statistical methods.<br /> Grammar: Line 124: Replace "similarly drive CRC progression" with "similarly drive progression."<br /> 2. AI Content Analysis<br /> Estimated AI-Generated Content: ~20-25%.<br /> Implications: Repetitive phrasing in methodological descriptions and literature summaries suggests potential AI assistance. While the technical content appears valid, manual rephrasing can enhance originality and scientific depth.<br /> 3. Statistical Reporting<br /> Insufficient Confidence Intervals: Odds ratio enrichment results lack 95% confidence intervals in several places, undermining statistical rigor (Section: Results, p.9).<br /> Inconsistent Metric Definitions: Terms like “improved R²” and “higher AUC” are used loosely. Precise numerical values and effect size comparisons would improve clarity.<br /> 4. Terminology Consistency<br /> Key terms like "dimensionality reduction" and "risk stratification" should be consistently defined and applied across sections to avoid ambiguity.<br /> Recommendations<br /> Enhance Model Interpretability:

      Integrate explainability tools (e.g., SHAP values, visualization of autoencoder layers) to clarify how SNPs influence predictions.<br /> Discuss the potential for hybrid models balancing interpretability and performance.<br /> Address Demographic Bias:

      Validate DEEN using datasets from underrepresented populations (e.g., African, Asian ancestries).<br /> Incorporate transfer learning techniques to enhance generalizability.<br /> Benchmarking and Evaluation:

      Compare DEEN against additional advanced machine learning models for PRS.<br /> Introduce advanced evaluation metrics like NRI and IDI to strengthen claims.<br /> Refine Computational Analysis:

      Provide detailed resource utilization benchmarks.<br /> Explore alternative hyperparameter optimization methods to improve training efficiency.<br /> Expand Data Analysis:

      Perform a sensitivity analysis on variant filtering thresholds.<br /> Investigate the inclusion of rare variants to improve model robustness.

    1. On 2024-12-20 20:46:20, user Jakub wrote:

      You have stated: "We performed targeted metabolomics to quantify the absolute abundance of known uremic toxins, including (...) 4-ethylphenyl sulfate (4-EPS) (...) in plasma of this cohort. As expected, CKD and PAD+CKD groups had significantly higher levels of all these uremic toxins (Figure 3A)." Unfortunately, Figure 3A does not provide data on 4-ethylphenyl sulfate. May you add data on this solute?

    1. On 2025-01-10 21:50:46, user Harold Bien wrote:

      Fascinating article. Given that each individual VOC in Fig 1 appears to have significant overlap between each group and wide distributions, it would be interesting to learn how the various machine learning algorithms used each VOC and the resulting model. Could the authors provide more information on the ML algorithms used, how it was trained, and how the ROCs were constructed?

    1. On 2022-05-24 20:25:23, user Carol Taccetta, MD, FCAP wrote:

      If a subject was still on immunotherapy at time of "recovery," the outcome of the adverse event cannot be considered as "resolved." It will also be important to follow these subject for relapse after therapy discontinuation, as immune-mediated conditions can sometimes relapse months, even years, after immunotherapy discontinuation.

    1. On 2022-06-14 12:41:29, user Robert Clark wrote:

      I was puzzled in Fig. 3 that the numbers for the severe cases was 39 for placebo and 51 for IVM. I thought this was measuring the comparative effect of ivermectin for the severe cases. But I see in the Supplementary appendix in eTable 1 that this is just giving the numbers in this category on entrance to the study.

      But this raises another problem. For a randomized trial the number of severe cases assigned to the placebo and treatment groups should be close. Yet the IVM group got 24% greater number of severe cases. That’s a discomfortingly large difference for a randomized trial. Clearly this could create a bias against the treatment regimen.

      Reviewing the further eTable 1of baseline symptoms, we see several categories of symptoms that would be key indicators of severe disease such as dypsnea, difficulty breathing, were assigned significantly more severe cases to the IVM group compared to the placebo group.

      That shouldn’t happen in a randomized trial. I suspect something went wrong with the randomization. This could create such a serious bias against the treatment that a disclaimer should be placed on this study that its randomization procedure is being reviewed.

      Robert Clark

    1. On 2022-07-10 23:39:20, user Charles Warden wrote:

      Hi,

      Thank you very much for posting this preprint.

      I consider the topics raised by this study to be important and interesting.

      However, I have some comments and questions:

      1) I agree that confirmation bias can be a contributing factor. However, I think true limitations in utility are also important. So, I am not sure if I completely agree with the statement "When results were not consistent with participant’s personal or family history, many participants found reasons to dismiss or discredit these results. This indicates a role for confirmation bias in responses to [self-initiated] PRS." For example, I might really want to understand the genetic basis for a disease, but the percent heritability explained by the PRS may be low and I could therefore be disappointed with the usefulness of a PRS due to a discordant result.

      I have a blog post where I share my impute.me scores (along with others):

      https://cdwscience.blogspot.com/2019/12/prs-results-from-my-genomics-data.html

      I don't know if I would exactly say my response was "negative," but I certainly got the impression the PRS that I saw may have limited utility. In that sense, my view of the method was not positive, even if it did not evoke a strong emotional "negative" response.

      Within that blog post, “ulcerative colitis” would be an example where there were different PRS for the same disease but very different percentiles (for the same SNP chip). So, I would consider that an example of the reaction that is described being due to something other than confirmation bias.

      2) Did the interviewers respond when there were possible points of misunderstanding during the interview process?

      It was acknowledged as a limitation in the discussion: "the researchers did not have access to participant’s PRS results and were unable to evaluate people’s understanding of their results".

      However, it seems like that could be important. For example, there is a quote "Unfortunately, I do regret getting a PRS… I would have rather not known. I like uncertainty". Assuming that there were appropriate limitations to communicate, I believe a response from the interviewer might cause that quote to no longer reflect the subject’s opinion.

      In general, there appears to be a noticeable emphasis on mental health in the article. My opinion is that this is an area where limitations are particularly important. If it helps, I think there are some additional details in this blog post for the book Blueprint.

      In terms of my own impute.me results, I thought the "anxiety" PRS seemed reasonable (to the best of my ability to assess that). However, I also thought changes in conditions over time were important, and I thought there was potential for misuse.

      3a) I think it is a minor point, but I don't remember receiving an invite to join a Zoom meeting for a discussion about my impute.me results.

      I hope that I was one of the 209 candidates, but I was not sure if I could confirm that. I also noticed mention of categories like “medium” or “low” for one quote referencing a z-score of 2.5, but I only saw the continuous score distribution in the screenshots from my blog post.

      3b) Perhaps more importantly, I tried to go back to sign in to check if I missed something.

      In the Folkersen et al. 2020 paper, the link provided is for https://www.impute.me/. However, that link currently re-directs to a Nucleus website (https://mynucleus.com/).

      Can you please provide some more information about the re-direction of the impute.me link?

      For example, I submitted an e-mail to register on the new website, but I don't think I can see my earlier results anymore?

      Additionally, I was confused when I couldn’t find the GitHub code provided with that paper: https://github.com/lassefolkersen/impute-me

      4) Finally, but I don't think either of the 2 models that I see ("dismissed medical concerns" and "medical distrust") are a great description for myself. I think something like "curiosity" and "critical assessment" would be more appropriate for myself.

      For example, I wouldn't say I distrust the healthcare system or medical research broadly, but I do think feedback and engagement is important. Thus, when I encounter problems, I submit reports to FDA MedWatch. Likewise, I contribute data/experience to projects like PatientsLikeMe.

      Thanks Again,<br /> Charles

    1. On 2022-07-11 04:26:35, user E Hansen wrote:

      It would be useful if the authors could clarify if "unvaccinated" means "never injected", or if this group also includes subjects not yet defined as vaccinated, but who has received a vaccine within the last week/14 days. <br /> The same goes for the vaccinated group; does it include everyone who received a shot from the day injected, or only those who have passed the first 14 days after injection and then being consideres "vaccinated"? This was not entirely clear to me, anyway. <br /> Thank you

    1. On 2022-07-29 09:25:01, user Dr. D. Miyazawa MD wrote:

      Please also refer to previous studies.

      Hypothesis that hepatitis of unknown cause in children is caused by adeno-associated virus type 2 (08 May 2022)<br /> https://www.bmj.com/content...

      Daisuke Miyazawa. Possible mechanisms for the hypothesis that acute hepatitis of unknown origin in children is caused by adeno-associated virus type 2. Authorea. May 16, 2022.<br /> DOI: 10.22541/au.165271065.53550386/v2

    1. On 2022-08-06 10:16:33, user Jef Baelen wrote:

      No inclusion/exclusion criteria are mentioned? It includes a study from 2004, long before SARS-CoV-2 emerged. The Caruhel study was not performed on COVID-19 patients. The çelebi study used a cycle treshold cut-off of 38 and evaluated 20 parameters of which masks was only 1. The results of this study were wrongly extrapolated in table 1. Very dubious studies included in this meta-analysis!

    1. On 2022-08-09 12:40:13, user PhillyPharmaBoy wrote:

      The authors conducted a thorough evaluation of the impact of ivermectin on SARS-CoV-2 clearance. On the surface their results differ from those of Krolewiecki, et al. (below). In a post hoc analysis these investigators found that ivermectin accelerated viral decay when drug concentration (4 hr) exceeded 160 ng/ml. It would be useful for the PLATCOV Group to mention this study and discuss potential reason(s) for the discrepancy.

      https://www.sciencedirect.c...

    1. On 2022-09-14 16:05:23, user Roy Miller wrote:

      There may be more evidence for this immunity than previously thought, Since Queen Elizabeth's death on September 8, 2022 the half-dozen British Royals have mingled with countless people, shaking hands, touching random surfaces, and breathing air all over the Scotland, England, and northern Ireland. I assume the Royals all have had their COVID injections and I have to assume that they have come in contact with the COVID virus on numerous occasions. Current thinking would lead me to assume the crowds gathered to see them would make transmission of the virus more likely.

      So why hasn't COVID spread like wildfire over the grieving population? Perhaps it is too soon to tell. But since COVID symptoms appear 2 to 14 days after infection, at least a large uptick in the COVID infections should be noticeable by now But no such event has occurred according to the British Press. So I have to conclude that there are additional factors to consider such as the one postulated by this article.

      PS: I have no medical training although my job involves helping the medical community take advantage of high technology.

    1. On 2022-09-22 09:16:27, user Wera Pustlauk wrote:

      Dear authors,

      thanks for the valuable effort to set up a new assay for the determination of PPi.

      Regarding table III samples remained somewhat vague to me. Clarification in the table header including the unit of the determined PPi might be helpful. Calculation of the standard deviation in addition to the average would make the data more roboust and would establish a more substantial link to the variability discussed in the paragraph before. Moreover, time differences in the addition of EDTA to the CTAD tubes as discussed in the text should be clearly stated for each sample in the table III as well.

      In addition, a hands on protocol (stored in a repository or as supplement) allowing the direct usage of the assay based on the optimized procedure would make the usage more accessible.

      Best regards,<br /> Wera Pustlauk

    1. On 2020-04-24 15:03:58, user Iba net wrote:

      I am Masum Billa from Bangladesh. Now situation going to volcano speed, we don't know what will be happen in the next but our government cannot control all of us meanwhile how is it possible to serve them. We are trying our best to serve them in camp. If anybody wants research or visit Rohinga Camp. Please contact me billaasia@gmail.com

    1. On 2020-04-24 16:08:53, user Rajendra Kings Rayudoo wrote:

      To<br /> Prof.Dankmar Boehning<br /> I'm.from india and IAM f glad to hear a realistic approach to realtime infectious cases including asymptomatic and presymptomatic.and interested to know how it works<br /> Please explain how can I calculate the cases in india through your model .<br /> Regards <br /> Rajendra

    1. On 2020-04-25 22:54:50, user wbgrant wrote:

      This open access article supports the present modeling study and should be cited in the final version:<br /> Low Temperature and Low UV Indexes Correlated with Peaks of Influenza Virus Activity in Northern Europe during 2010?2018.<br /> Ianevski A, Zusinaite E, Shtaida N, Kallio-Kokko H, Valkonen M, Kantele A, Telling K, Lutsar I, Letjuka P, Metelitsa N, Oksenych V, Dumpis U, Vitkauskiene A, Stašaitis K, Öhrmalm C, Bondeson K, Bergqvist A, Cox RJ, Tenson T, Merits A, Kainov DE.<br /> Viruses. 2019 Mar 1;11(3). pii: E207. doi: 10.3390/v11030207.<br /> http://www.mdpi.com/resolve...

    2. On 2020-04-25 23:09:56, user wbgrant wrote:

      One more publication in support<br /> Environmental predictors of seasonal influenza epidemics across temperate and tropical climates.<br /> Tamerius JD, Shaman J, Alonso WJ, Bloom-Feshbach K, Uejio CK, Comrie A, Viboud C.<br /> PLoS Pathog. 2013 Mar;9(3):e1003194. doi: 10.1371/journal.ppat.1003194. Epub 2013 Mar 7. Erratum in: PLoS Pathog. 2013 Nov;9(11). doi:10.1371/annotation/df689228-603f-4a40-bfbf-a38b13f88147.

    1. On 2020-04-27 04:52:01, user Krishna Undela wrote:

      It is the first information on knowledge and beliefs of general public of India on COVID-19. In this article we can understand the false beliefs / myths circulating among the general public of India about transmission of novel coronavirus and prevention and treatment of COVID-19.

    1. On 2020-04-27 10:34:04, user Elena Sharova wrote:

      They don't randomize health care workers to find an effect in comparable conditions (hospital, patients management, patient burden). Jan21 to Feb23 - incubation period before pneumonia detection is approximately 1-2 weeks. So how to compare pneumonias in the 1st week in control group with abcence in test group starting interferon - regurding the 1st week test group DO NOT infect a 1-2 week ago, not during the research. Are these groups equal?

    1. On 2020-04-27 16:44:44, user Dr. Amy wrote:

      Obesity increases the density and upregulates ACE2 receptors. I couldn't figure out how women were protected given the higher incidence of obesity, but a Japanese researcher in this area shared this with me (which I do not fully understand.) "ACE2 is not only an entry receptor for the SARS-CoV-2 virus, but also protects against the pathogenic effects of RAS and the ACE/AngII/AT1R axis. I believe the balance between ACE/AngII/AT1R axis and ACE2/Ang1-7/MasR axis is important. Higher expression of ACE2 in old female rats than male represents protective effects. That's why women would have lower morbidity and mortality. This is my speculation."

    1. On 2020-04-27 19:52:19, user eldhose poulose wrote:

      You mentioned that you colllected the airline data, I see only airline data for the year 2017, February. can you provide the latest data? Also can you give more details on the data that you used for the study?

    1. On 2020-04-27 23:05:18, user Jink wrote:

      Hope the higher Ct's are due to low yield from filters. Having a synthetic standard/control would have justified the Ct numbers. Think about it if expanding the sample size.

    1. On 2020-04-30 02:42:13, user Tyler Chen wrote:

      I appreciate the authors’ urgency in addressing SARS-CoV-2 decontamination for reuse of N95 filtering facepiece respirators (FFRs). In the spirit of that urgency and health impacts, I note two concerns with the current preprint that could accidentally cause confusion: (1) The paper claims N95 filtration is preserved after microwave-generated steam, whereas the test listed in the methods was a TSI quantitative fit test, which is primarily designed to test fit, not necessarily filtration. (2) The paper’s claim of a universally accessible N95 decontamination protocol may accidentally overstate the N95 models for which this protocol is verified. N95 models vary widely in their construction and resistance to steam heat, so any models other than the one used in this experiment will likely require thorough testing before this method is applied.

      I would suggest that the authors make the following changes:<br /> (1) Clarify whether or not filtration is verified at larger particle sizes and charge (e.g. 0.26 microns, uncharged). If filtration is not yet verified at larger particle sizes, this test may be important to verify N95 performance following microwave steam treatment.<br /> To provide some background: The TSI 8026 Particle Generator generates 0.04 micron particles [1] that are intended to be readily filtered by the N95, and are assumed to only enter the N95 through gaps in the face seal and not through the mask material itself [2]. It is possible for N95 FFRs to pass quantitative fit tests while still failing filtration tests at different particle sizes--one study “observed [protection factors] <100 even for subjects who passed fit testing (fit factor > 100)” [3]. Therefore, fit testing using the 8026 particle generator does not imply that N95 filtration is necessarily preserved at larger particle sizes which are most relevant for filtration effectiveness in the SARS-CoV-2 pandemic, especially given the fact that the decontamination treatment may shift what particle size is most penetrating for the N95. Recent non-peer-reviewed research shows N95 material suffering a decrease in filtration of 0.26 micron particles after 4-5 cycles of 10min stovetop steam treatment [4], though it is unclear from this manuscript if the MGS treatment did not reach this limit, or that the limit was not observed due to the different particle size used. Therefore, testing for quantitative fit should perhaps be supplemented by filtration tests at larger particle diameters (whether from this study or by citing others), especially when a decontamination process is involved such as steam heat that has an unknown effect on the most penetrating particle size for the N95. Given the potential for widespread implementation of this protocol it seems important that this point be clarified.

      (2) Secondly, it may be important to notify readers that the performance of the N95 model in this paper likely cannot be generalized to all N95 models without further testing. N95 models vary widely in construction and resistance to steam, and each model should be individually verified to maintain both fit and filtration by this protocol before use. This is supported by the fact that N95 models can vary widely with respect to the most penetrating particle size, and each country may only have access to certain N95 models [3,4,5]. Furthermore, there is literature evidence that the mask performance in response to steam and heat also varies across N95 models (see the table of results in Appendix B https://www.n95decon.org/fi... "https://www.n95decon.org/files/heat-humidity-technical-report)"). Therefore, it is important to clarify in the text that this method is not yet universally-validated -- N95 fit has only been verified for the 3M 1860 molded N95 in particular, and other models are likely to have significantly different behavior. Independent verification of both fit and filtration may be needed for other N95 models.

    1. On 2020-04-30 04:49:44, user Aaron wrote:

      It would be a useful addition to show the % positive of tests performed in the same range as Fig 1C. If a greater proportion of tests are coming back positive following April 7, that could suggest that testing is occurring more and more frequently among those most likely to be positive. This is problematic as it can obscure mild cases that may not appear to be positives. In general, this information would help contextualize what types of cases are being captured by these data in Wisconsin, mostly severe cases, or mild and severe cases alike.