6,062 Matching Annotations
  1. May 2026
    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 2026-03-27 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 2026-01-12 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

    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 2022-10-24 11:51:28, user Indi Trehan wrote:

      This article has now been published after peer review: The Journal of Pediatrics 2022; 247: 147-149. doi: 10.1016/j.jpeds.2022.05.006.

    1. On 2020-04-06 19:55:46, user Sinai Immunol Review Project wrote:

      Clinical Characteristics of 2019 Novel Infected Coronavirus Pneumonia:A Systemic Review and Meta-analysis

      The authors performed a meta analysis of literature on clinical, laboratory and radiologic characteristics of patients presenting with pneumonia related to SARSCoV2 infection, published up to Feb 6 2020. They found that symptoms that were mostly consistent among studies were sore throat, headache, diarrhea and rhinorrhea. Fever, cough, malaise and muscle pain were highly variable across studies. Leukopenia (mostly lymphocytopenia) and increased white blood cells were highly variable across studies. They identified three most common patterns seen on CT scan, but there was high variability across studies. Consistently across the studies examined, the authors found that about 75% of patients need supplemental oxygen therapy, about 23% mechanical ventilation and about 5% extracorporeal membrane oxygenation (ECMO). The authors calculated a staggering pooled mortality incidence of 78% for these patients.

      Critical analysis:<br /> The authors mention that the total number of studies included in this meta analysis is nine, however they also mentioned that only three studies reported individual patient data. It is overall unclear how many patients in total were included in their analysis. This is mostly relevant as they reported an incredibly high mortality (78%) and mention an absolute number of deaths of 26 cases overall. It is not clear from their report how the mortality rate was calculated. <br /> The data is based on reports from China and mostly from the Wuhan area, which somewhat limits the overall generalizability and applicability of these results.

      Importance and implications of these findings in the context of the current epidemics:<br /> This meta analysis offers some important data for clinicians to refer to when dealing with patients with COVID-19 and specifically with pneumonia. It is very helpful to set expectations about the course of the disease.

    1. On 2023-12-12 14:56:15, user Tanmoy Sarkar Pias wrote:

      This paper has been accepted to an IEEE conference. A link (& DOI) to the IEEE Xplore will be added when this article is published. Please see the following copy right details of IEEE.

      2023 26th International Conference on Computer and Information Technology (ICCIT), 13-15 December, Cox’s Bazar, Bangladesh

      979-8-3503-5901-5/23/$31.00 ©2023 IEEE

    1. On 2023-12-19 12:39:03, user Christos Proukakis wrote:

      Response to: “Is Gauchian genotyping of GBA1 variants reliable?”

      Marco Toffoli1,2, Anthony HV Schapira1,2, Fritz J Sedlazeck2,3,4, Christos Proukakis1,2 *

      1. Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, UK
      2. Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
      3. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
      4. Department of Molecular and Human Genetics, Baylor College of Medicine, TX, USA

      * To whom correspondence should be addressed: c.proukakis@ucl.ac.uk

      We recently described two methods for GBA1 analysis, which is hampered by the adjacent highly homologous pseudogene: Gauchian, a novel algorithm for analysis of short-read WGS, and targeted long-read sequencing 1. Tayebi et al have applied the former to WGS from 95 individuals, and compared it to Sanger sequencing 2. They report concordant genotypes in 85, while 11 had discrepant calls (we note that this leads to a total of 96). In addition, they report 28 false Gauchian calls in 1000 Genomes Project (1kGP) samples. Gauchian was developed because the homology of the GBA region requires a short read variant caller that does not rely solely on read alignments, and can identify specific variants known to be pathogenic. To understand the cause of these discrepancies, we reviewed their data, and conclude that they are mis-interpreting Gauchian results in 8 of the 11 discrepant samples, and incorrectly using Gauchian to analyze low-coverage 1kGP samples.

      Among the 11 (11.5%) samples with inconsistent calls with Sanger (Table 1), four (Pat_08, Pat_26, Pat_28 and Pat_58) were not called as the variants are not on Gauchian’s target list, which includes all ClinVar variants in December 2021. These variants, and any others, can be easily added (see Supplementary Information). Three other samples (Pat_75, Pat_76 and Pat_79) had low data quality resulting in large variation in sequencing depth across the genome, as shown by the median absolute deviation (MAD) of genome coverage: 0.269, 0.128 and 0.127 (three highest values among all samples). Gauchian recommends trusting calls in samples with MAD values <0.11, and produces a warning message if this is exceeded. In all three samples, the GBA1+GBAP1 copy number was a no-call (marked as “None” in the output file), indicating that Gauchian could not determine the copy number due to high coverage variation. Variants were not called because no further analysis was done beyond copy number calling. These should not be viewed as false negatives, as the warning message and the report of no-calls should prompt the user to obtain higher quality data or consider alternative sequencing. Among the remaining 4 samples with inconsistent results: Pat_03 had a Gauchian call of heterozygosity for p.Asn409Ser, while Sanger reports this as homozygous. Review of the IGV trace (Tayebi et al. Supp Figure 1) shows that at least 10 reads (around a fifth of the total) have the reference base, and therefore it is hard to conclude this is homozygous. Review of the Sanger trace (not provided) could determine whether there is a low peak representing the reference allele. We cannot provide a conclusion, and additional analysis is recommended. Mosaicism could be a plausible explanation, and this has been reported in GBA1 3,4, albeit not at this position. Pat_47 had a false negative p.Leu483Pro call. Pat_16 was indeed wrongly genotyped as homozygous for p.Asn409Ser, related to the adjacent c.1263del+RecTL deletion. Pat_92 had all expected variants called, but the heterozygous p.Asp448His was mis-genotyped as homozygous. In summary, there is one false negative and two wrongly genotyped variants (heterozygous variants called homozygous). Gauchian’s precision is therefore 98.9% (175 out of 177 calls are correct). Its allele-level recall/sensitivity is 99.4% after excluding alleles not on Gauchian’s target list, and samples which could not be analyzed due to high coverage variation. Alternatively, it can be calculated as 97.2% if only samples with high coverage variation are excluded, 96.2% if only alleles not on the target list are excluded, and 94.1% if all these samples are considered .

      Tayebi et al. concluded that Gauchian is not able to call recombinant variants without providing orthogonal evidence. In Pat_95, Pat_71 and Pat_16, they examined alignments in IGV and reported absence of supporting reads for Gauchian calls, but all recombinant alleles called by Gauchian were consistent with Sanger. This highlights that read mapping in this region is unreliable (variant supporting reads may align to the pseudogene), making interpretation of alignments in IGV very challenging. Gauchian is designed to untangle ambiguous alignments, locally phase haplotypes and make correct calls. Particularly, in Pat_95, they claimed that Gauchian called the expected RecNciI variant but got the mechanism of the recombinant allele wrong (gene conversion vs. gene fusion). This claim appears to be based on incorrect interpretation of IGV alignments, i.e. seeing 3’ UTR mismatches associated with GBAP1 does not necessarily indicate gene fusion, as they can be misalignments, or even part of the gene conversion. The RecNciI in Pat_95 is a gene conversion, as indicated by the normal copy number between GBAP1 and GBA1. Tayebi et al. claimed that this is a gene fusion without orthogonal evidence. In addition, they claimed that Gauchian misreported copy numbers in Pat_92, Pat_42 and Pat_72, again without orthogonal evidence. We validated Gauchian copy number gains by digital PCR in four cases 1. While particular recombinants could be prone to erroneous copy number calling, we do not know what “other techniques'' identified a different copy number in Pat_92. Orthogonal validation using digital PCR would resolve this. Finally, it is true that Gauchian does not have all possible recombinants on its target list, as it is designed to focus on recombinant variants in exons 9-11, because others are rare and detectable with standard callers.

      Tayebi et al. reported 4 samples where Gauchian missed variants in GRCh38 compared to GRCh37. Among these, two (Pat_35, Pat_75) were due to incorrect alignment settings that resulted in abnormally low mapping quality throughout the region. It is likely that ALT-aware alignment was on for all samples except these two. The remaining two (Pat_16, Pat_78) reflected an area of improvement for Gauchian to better call p.Asn409Ser, which is not a GBAP1-like variant, and can thus be called well by standard callers.

      We reported Gauchian calls of 1000 Genomes Project (1kGP) samples, validating some by targeted long reads 1. Gauchian called zero samples with biallelic variant in exons 9-11. However, Tayebi et al. reported a completely different set of Gauchian calls in the same samples (in their Table 4). This was caused by incorrect use of Gauchian on old low coverage WGS (median coverage <10X, https://ftp.1000genomes.ebi... "https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase3/data/)"), rather than 30X (https://ftp-trace.ncbi.nlm.... "https://ftp-trace.ncbi.nlm.nih.gov/1000genomes/ftp/1000G_2504_high_coverage/data/)").

      We are grateful to Tayebi et al for assessing Gauchian analysis of this very challenging gene 2, but note that most discrepancies were due to incorrect use or misinterpretation of results. “No call” samples due to inadequate data quality cannot be considered false negative, as no calls are provided, and warnings of noisy coverage are given where applicable. Samples with inadequate coverage should obviously be avoided, as Gauchian is expected to perform at coverage >30X. Gauchian does not call variants not on its target list, which can be expanded. We provide updated recall (99.4%) and precision (98.9%) values. We have not seen any evidence of the alleged inability of Gauchian to call recombinant variants, and would welcome orthogonal copy number assessment of discrepancies. We show that Gauchian can be used for GBA1 assessment when coverage and data quality are adequate. We do note a limitation in genotyping p.Asn409Ser, a non-recombinant variant that can be called by standard variant callers, which we recommend running together with Gauchian for a complete call set. Finally, in clinical cases where absolute certainty is required, Sanger sequencing could be considered, with targeted long read sequencing another option 1,5–7.

      Table 1. Details on the 11 samples where Gauchian and Sanger are inconsistent.

      Gauchian calls Sanger Assessment,Tayebi et al. Our assessmentSample Copy Number of GBA1 and GBAP1 GBAP1-like variant in exons 9-11 Other unphased variants Genotype Prediction

      Pat_08 4 None p.Asn409Ser p.Asn409Ser/p.Gln389Ter False Negative Missed variant is not on Gauchian's target list

      Pat_28 4 None p.Arg535His p.Arg535His/Cys381Tyr False Negative Missed variant is not on Gauchian's target list

      Pat_58 4 None p.Asn409Ser, p.Arg296Ter p.Asn409Ser, p.Arg296Ter, c.203delC False Negative Missed variant is not on Gauchian's target list

      Pat_26 4 None p.Asn409Ser p.Asn409Ser/p.Arg502Cys False Negative Missed variant is not on Gauchian's target list.

      Tayebi et al.’s Supplementary Figure 1 shows no variant at p.Arg502Cys (c.1504C>T), but a different variant at the neighboring position, p.Arg502His (c.1505G>A), which is not on Gauchian's target list.

      Pat_75 None (No Call) NA NA p.Arg502Cys/p.Arg159Trp Missed Copy number is a no-calldue to high variation in depth so no further variant calling was performed. Coverage MAD 0.269

      Pat_76 None (No Call) NA NA p.Asn409Ser/p.Asn409Ser Missed Copy number is a no-call due to high variation in depth so no further variant calling was performed. Coverage MAD 0.128

      Pat_79 None (No Call) NA NA p.Leu483Pro/p.Arg502Cys Missed Copy number is a no-call due to high variation in depth so no further variant calling was performed. Coverage MAD 0.127

      Pat_03 4 None p.Asn409Ser p.Asn409Ser/p.Asn409Ser False Negative Gauchian call is supported by reads, see Tayebi et al.’s Supplementary Figure 1.

      Pat_47 4 None p.Asn409Ser p.Asn409Ser/p.Leu483Pro False Negative True false negative

      Pat_16 3 c.1263del+RecTL/ p.Asn409Ser, p.Asn409Ser p.Asn409Ser, c.1263del+RecTL False Positive Heterozygous p.Asn409Ser misgenotyped as homozygous as Gauchian did not know the exact breakpoint of the c.1263del+RecTL deletion, which is very close to p.Asn409Ser.

      Pat_92 7 p.Asp448His/p.Leu483Pro,p.Asp448His p.Asp448His/ p.Leu483Pro+Rec7 False Negative There is no false negative. Rec7 is reflected in the copy number call (copy number gain). This GBAP1 duplication does not have any functional impact on GBA, so Gauchian does not report it as a GBA variant. Heterozygous p.Asp448His misgenotyped as homozygous.

      Acknowledgements

      We are grateful to Xiao Chen and Michael Eberle for helpful comments. They are former employees of Illumina and current employees of Pacific Biosciences. This research was funded in in part by Aligning Science Across Parkinson's [Grant numbers 000430 and 000420] through the Michael J. Fox Foundation for Parkinson's Research (MJFF).

      Competing interests

      FJS receives research support from PacBio and Oxford Nanopore. AHVS has received consulting fees from AvroBio, Auxilius, Coave, Destin, Enterin, Escape Bio, Genilac, and Sanofi and speaking fees from Prada Foundation.

      Supplementary Information

      Add new variants to Gauchian’s config file

      The four new variants can be added to Gauchian’s config file as follows.

      For hg38, add the following lines to gauchian/data/GBA_target_variant_38.txt

      chr1 155236304 A GBAP G c.1165C>T(p.Gln389Ter)<br /> chr1 155236327 T GBAP C c.1142G>A(p.Cys381Tyr)<br /> chr1 155239989 CGGGGGT GBAP CGGGGGGT c.203delC(p.Thr69fs)

      Add the following line to gauchian/data/GBA_target_variant_homology_region_38.txt<br /> chr1 155235195 T 155214568 C c.1505G>A(p.Arg502His)

      For GRCh37, add the following lines to gauchian/data/GBA_target_variant_37.txt<br /> 1 155206095 A GBAP G c.1165C>T(p.Gln389Ter)<br /> 1 155206118 T GBAP C c.1142G>A(p.Cys381Tyr)<br /> 1 155209780 CGGGGGT GBAP CGGGGGGT c.203delC(p.Thr69fs)

      Add the following line to gauchian/data/GBA_target_variant_homology_region_37.txt<br /> 1 155204986 T 155184359 C c.1505G>A(p.Arg502His)

      Bibliography

      1. Toffoli, M. et al. Comprehensive short and long read sequencing analysis for the Gaucher and Parkinson’s disease-associated GBA gene. Commun. Biol. 5, 670 (2022).

      2. Tayebi, N., Lichtenberg, J., Hertz, E. & Sidransky, E. Is Gauchian genotyping of GBA1 variants reliable? medRxiv (2023) doi:10.1101/2023.10.26.23297627.

      3. Filocamo, M. et al. Somatic mosaicism in a patient with Gaucher disease type 2: implication for genetic counseling and therapeutic decision-making. Blood Cells Mol. Dis. 26, 611–612 (2000).

      4. Hagege, E. et al. Type 2 Gaucher disease in an infant despite a normal maternal glucocerebrosidase gene. Am. J. Med. Genet. A 173, 3211–3215 (2017).

      5. Pachchek, S. et al. Accurate long-read sequencing identified GBA1 as major risk factor in the Luxembourgish Parkinson’s study. npj Parkinsons Disease 9, 156 (2023).

      6. Graham, O. E. E. et al. Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort. Parkinsonism Relat. Disord. 70, 36–41 (2020).

      7. Leija-Salazar, M. et al. Evaluation of the detection of GBA missense mutations and other variants using the Oxford Nanopore MinION. Mol. Genet. Genomic Med. 7, e564 (2019)

    1. On 2024-04-11 17:53:00, user eysen wrote:

      JMIR Publications and PREreview are pleased to announce our next Preprint Live Review on Friday, April 19 at 9am PT / 12pm ET / 4pm UTC which discusses this preprint

      Register Now at https://docs.google.com/for...

      The Live Review is hosted by two facilitators from the PREreview team with experience in moderating virtual collaborative review discussions. They will guide participants through a constructive discussion of the following preprint: Assessing the Incidence of Postoperative Diabetes in Gastric Cancer Patients: A Comparative Study of Roux-en-Y Gastrectomy and Other Surgical Reconstruction Techniques - by Tatsuki Onishi

      Live Review Details:

      WHEN: Friday, April 19 at 9am PT / 12pm ET / 4pm UTC

      WHO: The Live Review is hosted by two facilitators from the PREreview team with experience in moderating virtual collaborative review discussions.

      WHAT: The participants will be guided through a constructive discussion of the following preprint: Assessing the Incidence of Postoperative Diabetes in Gastric Cancer Patients: A Comparative Study of Roux-en-Y Gastrectomy and Other Surgical Reconstruction Techniques - by Tatsuki Onishi medRxiv: https://doi.org/10.1101/202...

      A review will be then written and published on PREreview.org within the following 2 weeks. Participants will have the chance to help compose the final review and be recognized as reviewing authors.

      HOW: To participate, please complete the following registration form. You will receive an email from PREReview with a link to a Zoom room and a passcode.

      More information on JMIRx-Med, the first pubmed-indexed preprint overlay journal: https://xmed.jmir.org/annou...<br /> https://xmed.jmir.org/announcements/457

    1. On 2024-05-03 15:04:37, user Tamy wrote:

      I am happy to see someone taking an interest in this horrific condition. My daughter has suffered for over 9 years and the mental toll, as well as, the physical toll it has taken on her overall well being has been life changing! Thank you for giving these sufferers some validation!

    1. On 2025-05-01 12:48:20, user Ravi Sharma wrote:

      Ladies and Gentlemen,

      in loving memory of my late, beloved mother, a type 2 diabetic since my birth, I dedicate this research to harnessing the beneficial power of gen-AI to banish GDM from the face of the earth.

      I salute my industrious and loyal research group for their dedication in this journey.

      Until our work is published and linked to this DoI, kindly cite this preprint as ...

      Edmund Evangelistaa, Fathima Rubab, Syed M. Salman Bukhari, Amril Nazir and Ravishankar Sharma. (2025). "Developing a GraphRAG-enabled local-LLM for Gestational Diabetes Mellitus." medRxiv preprint doi: https://medrxiv.org/cgi/content/short/2025.04.28.25326568v1

      With kind regards and best wishes, Ravi

    1. On 2022-01-27 21:10:24, user Siguna Mueller, PhD, PhD wrote:

      I find it difficult to see how many individuals were in each group. I may, or may not, be able to guess some proportions. For instance, Fig. 4 suggests that there were not many in the booster group, if any at all. (This is because boosters obviously were only rolled out not too long ago). Is the small peak at approx. 35 days since injection attributable to the booster group? If so, this makes me wonder if they were sufficiently many to be statistically relevant. Again, I find it hard to infer exact numbers of participants in the different groups. This info would really be helpful. Thanks.

    2. On 2022-02-14 04:09:55, user RBNZ wrote:

      "The estimates are furthermore adjusted for vaccine status of the potential secondary case interacted with the household variant, and the vaccine status of the primary case. "

      There is no information included as to how vaccination status adjusts the odds ratio.

    1. On 2022-02-03 14:15:23, user Matt Thrun-Nowicki wrote:

      Given previous studies’ evidence of a poor association between RAT results and viral culturability based on # of days after symptom onset, you guys might wanna wait to publish this paper until after those viral cultures result.

      In addition, your explanation of why booster’d HCW had higher positive RAT’s is a little baffling. If your explanation was correct, wouldn’t you expect to see the percentage of positive RAT’s among booster’d HCWers drop over time, and those of unbooster’d go up? What about confounders (like demographics of the booster’d vs unbooster’d)?

    1. On 2025-09-07 20:13:12, user S S Young wrote:

      Milojevic et al. 2014 had access to all emergency room visits for all of England and Wales for the years 2003 to 2008, over 400,000 myocardial infarction (MI) events, and over 2 million CVD emergency hospital admissions. They found no effect of CO, NO2, Ozone, PM10, PM2.5, or SO2 on heart attacks, hospital admissions, or mortality, their Figures 1 and 2.

      Milojevic, A., Wilkinson, P., Armstrong, B., Bhaskaran, K., Smeeth, L., Hajat, S. 2014. Short-term effects of air pollution on a range of cardiovascular events in England and Wales: Case-crossover analysis of the MINAP database, hospital admissions and mortality. Heart (British Cardiac Society) 100, 14: 1093-98. https://doi.org/10.1136/heartjnl-2013-304963 .

    1. On 2020-04-19 16:51:41, user Sinai Immunol Review Project wrote:

      Neutralizing antibody responses to SARS-CoV-2 in a COVID-19 recovered patient cohort and their implications

      Fan Wu et al.; medRxiv 2020.03.30.20047365; doi:https://doi.org/10.1101/202...

      Keywords

      • Neutralizing antibodies<br /> • SARS-CoV-2<br /> • pseudotype neutralization assay

      Main findings

      In this study, plasma obtained from 175 convalescent patients with laboratory-confirmed mild COVID-19 was screened for SARS-CoV-2-specific neutralizing antibodies (nABs) by pseudotype-lentiviral-vector-based neutralization assay as well as for binding antibodies (Abs) against SARS-CoV-2 RBD, S1 and S2 proteins by ELISA. Kinetics of neutralizing and binding Ab titers were assessed during the acute and convalescent phase in the context of patient age as well as in relation to clinical markers of inflammation (CRP and lymphocyte count at the time of hospitalization). Across all age groups, SARS-CoV-2-specific nAbs titers were low within the first 10 days of symptom onset, peaked between days 10-15, and persisted for at least two weeks post discharge. In contrast to spike protein binding Abs, nAbs were not cross-reactive to SARS-CoV-1. Moreover, nAb titers moderately correlated with the amount of spike protein binding antibodies. Both neutralizing and binding Ab titers varied across patient subsets of all ages, but were significantly higher in middle-aged (40-59 yrs) and elderly (60-85) vs. younger patients (15-39 yrs). However, plasma nAb titers were found to be below detection level in 5.7% (10/175) of patients, i.e. a small number of patients recovered without developing a robust nAb response. Conversely, 1.14% (2/175) of patients had substantially higher titers than the rest. Notably, in addition to patient age, nAb titers correlated moderately with serum CRP levels but were inversely related to lymphocyte count on admission. In summary, the authors show that patients with clinically mild COVID-19 disease mount a strong humoral response against the SARS-CoV-2 spike protein. Compared to younger patients, middle-aged and elderly patients had both higher neutralizing and binding Ab titers, accompanied by increased CRP levels and lower lymphocyte counts. These patients are usually considered at higher risk of severe disease. Therefore, robust neutralizing and binding Ab responses may be particularly important for recovery in this patient subset. Conversely, patients who failed to produce high nAb/binding Ab titers against spike protein did not progress to severe disease, indicating that binding Abs against other viral epitopes as well as cellular immune responses are equally important.

      Limitations

      This study provides valuable information on the kinetics of spike protein-specific nAb as well as binding Ab titers in a cohort of convalescent mild COVID-19 patients of all ages. However, similar studies enrolling larger patient numbers, including those diagnosed with moderate and severe disease as well as survivors and non-survivors, especially in the elderly group (to rule out potential bias for more favorable outcome), are warranted for reliable assumptions on the potentially protective role of Abs and nAbs in COVID-19. Moreover, longitudinal observation beyond the acute and convalescent phase in addition to stringent clinical and immunological characterization is urgently needed. <br /> In their study, Wu et al. did not measure binding Abs against non-S viral proteins, which are also induced in COVID-19 and therefore could have added valuable diagnostic information with regard to patients who seemingly failed to mount both binding and neutralizing Ab responses against the SARS-CoV-2 spike protein. Likewise, while this study excluded cross-reactivity of nAbs against SARS-CoV-1, no other coronaviruses were tested. Of additional note, neutralizing activity of plasma Abs was only assessed by pseudotype neutralization assay, not against live SARS-CoV-2. Generally, while these are widely used and reproducible assays, in vitro neutralization of pseudotyped viruses does not necessarily translate to effective protection against the respective live virus in vivo (cf. review by Burton, D. Antibodies, viruses and vaccines. Nat Rev Immunol 2, 706–713 (2002)). Further studies are therefore needed to assess the specificity and neutralizing characteristics of these Abs to test whether they could be candidates for prophylactic and therapeutic interventions. In this context, setting arbitrary cut-off values (ID50<500 vs. a detection limit of ID50 < 40) and thus classifying up to 30% of patients in this study as “weak” responders does not take into account our currently limited knowledge regarding protective capacity of these nAbs and should therefore have been avoided by the authors.

      Significance

      This preprint is arguably the first report on neutralizing and binding Ab titers in a larger cohort of mild COVID-19 patients. Assessing Ab titers in these patients is not only important in order to confirm whether mild COVID-19 elicits robust nAb responses, but also adds further information regarding the use of plasma from mild disease patients for convalescent plasma therapy as well as vaccine design in general. Future studies will need to address now whether the nAb responses generated in mild disease will be protective or (functionally) different from nAbs generated in moderate and severe disease. The findings in this study are therefore of great relevance and should be further explored in ongoing research on potential coronavirus therapies and prevention strategies.

      This review was undertaken as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2025-11-30 23:44:45, user Cyril Burke wrote:

      [Note: This is the second of several rounds of review of an earlier version of our combined manuscript, aiming to reduce ‘racial’ disparity in kidney disease. The comments were kindly offered by nephrologists, through a medical journal, and we remain grateful to them for the time and care they gave to improve our manuscript.

      We removed identifying features and included our responses, at the end of this comment. The changing title and line numbers refer to earlier versions.]

      August 3, 2022<br /> Dear Dr. Burke III,

      REDACTED.

      Reviewer #1: Cyril O Burke III et al submit a revised version of their intriguing , unusual paper.

      Overall, the paper remains extremely lengthy (the total , including clean and track versions and reply to reviewers is close to 200 pages !!) , whereas it contains relatively little original data.

      The authors speculate and comment a lot (and most of these speculations/comments will hardly be understandable by the expected audience, primary care physicians), and this will in addition distract the reader from the main key message (which is right in the opinion of this reviewer (see first round of review) and warrants more attention and studies.

      The race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted in the opinion of this reviewer. In this respect, I completely agree with the comment of reviewer 2 in the first round.

      I can not resist quoting here the reply of the authors to reviewer 2. “This manuscript could be divided into three or four short papers, increasing the likelihood that any one of them would be read. However, different groups tend to read papers about screening for kidney impairment, racial disparities, cofactors in modeling physiologic parameters, or policy proposals to encourage best practices. Despite the appeal of perhaps three or four publications, we decided to tell a complete story in a single paper, but we are open to suggestions.”

      My reply to their reply: nobody would read the current paper , even partially. Shorten, shorten, shorten please and focus on the key message.

      Reviewer #2: Thank-you, once again, for the opportunity to review this lengthy “thesis-style” manuscript which discusses some important often over-looked topics. The under-use of serial creatinine measurements and over-reliance on often erroneous eGFR measurements is an important point which is easily missed by healthcare workers with potentially serious consequences. Likewise, the misuse of racial constructs in medicine (and elsewhere) is an important point.

      I am satisfied with this re-submission and the changes which have been made to the original manuscript.

      Minor points:<br /> 431: “creatinine inhibits several membrane transporters”. = Cimetidine

      502: “Because mGFRs have population variation as wide as sCr, with much greater physiologic variability compared to the relatively stable sCr and serum cystatin C”<br /> As mentioned previously the cited article compares the variability of sCr and cystatin C with CrCl, I agree with the authors that CrCl is a form of mGFR, however, probably one of the poorer forms and not what a reader will think of when mGFR is mentioned. In our current age of medicine when we talk about mGFR CrCl is seldom included, studies reviewing methods of mGFR will seldom include CrCl, however CrCl may be compared to one of the mGFR methods. Likewise, if a patient is sent for a mGFR, a CrCl will not be performed. In our current age of medicine mGFR refers to methods such as the clearance of iohexol, iothalamate, Cr-EDTA, inulin, DTPA, etc; the authors themselves mention this (line 539 – 540). I fully agree with the authors that mGFR is FAR from perfect and has many inaccuracies and imprecisions (which are often overlooked)- these are well published, some of which are cited in this manuscript. If the authors wish to use the current study as a source they should state the findings in a way that cannot be misinterpreted. For example: “CrCl has much greater physiologic variability than sCr and cystatin C …” – in this case the reader can determine for themselves whether they would use CrCl as a surrogate for mGFR. Alternatively, adjust the statement and use another source which has shown the variability that exists with what we currently refer to as mGFR method.

      670 – 719: As the authors specifically discuss age it would be prudent to briefly mention the short-comings, or considerations for interpretation, of serial creatinine measurements at a very young age which generally rise until late adolescence when steady muscle mass is achieved. Also note changes in creatinine and GFR from birth till 2 – 3 years.

      783 – 784: Consider re-wording the grammar makes this sentence difficult to read

      959 – 968: Note, editing has not been accepted (tracked changes still shown)

      1116 - 1121: “Using the opioid crisis as an example…. in, for example, the opioid crisis” – same sentence

      RESPONSE TO REVIEWERS:<br /> September 17, 2022<br /> Longitudinal creatinine, not ‘race’, signals pre-chronic kidney disease and decline in glomerular filtration rate

      We again greatly appreciate the reviewers for offering detailed comments and guidance, which we have endeavored to incorporate as best we could.

      Comments to the Author<br /> Reviewer #1: Cyril O Burke III et al submit a revised version of their intriguing, unusual paper.<br /> 1. Overall, the paper remains extremely lengthy (the total, including clean and track versions and reply to reviewers is close to 200 pages !!), whereas it contains relatively little original data.<br /> The authors speculate and comment a lot (and most of these speculations/comments will hardly be understandable by the expected audience, primary care physicians), and this will in addition distract the reader from the main key message (which is right in the opinion of this reviewer (see first round of review) and warrants more attention and studies.<br /> The race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted in the opinion of this reviewer. In this respect, I completely agree with the comment of reviewer 2 in the first round.<br /> I can not resist quoting here the reply of the authors to reviewer 2.<br /> "This manuscript could be divided into three or four short papers, increasing the likelihood that any one of them would be read. However, different groups tend to read papers about screening for kidney impairment, racial disparities, cofactors in modeling physiologic parameters, or policy proposals to encourage best practices. Despite the appeal of perhaps three or four publications, we decided to tell a complete story in a single paper, but we are open to suggestions."<br /> My reply to their reply: nobody would read the current paper, even partially. Shorten, shorten, shorten please, and focus on the key message.<br /> We fundamentally agree and have worked to shorten the text; to clarify our understanding that ‘race’ may change with time, location, and self-identification; and to add a Table of Contents to make the Parts more accessible to interested readers. We comment a lot because, in highly racialized societies, like the US [1,2], it can be difficult to see beyond ‘race’ without explicit speculation about other possible explanations for difference, which we understand, may or may not pan out under investigation. One hope is that all clinicians will pursue explanations other than ‘race’, but this seems unlikely. Busy medical researchers have little time to develop expertise outside their area of interest, which may explain why ‘Commentary’ and ‘Perspective’ articles have failed to inspire an ethical ban on the misuse of ‘race’ in medical research, journals, clinics, and elsewhere [3]. We do not know whether a suite of articles can meaningfully contribute to ending misuse of ‘race’, where so many scholarly articles have failed, but after perceiving little change over four decades, trying something completely different seemed (almost) rational.

      1. Nunez-Smith M, Curry LA, Bigby J, Berg D, Krumholz HM, Bradley EH. Impact of race on the professional lives of physicians of African descent. Ann Intern Med. 2007 Jan 2;146(1):45-51. doi: 10.7326/0003-4819-146-1-200701020-00008. PMID: 17200221.

      2. Betancourt JR, Reid AE. Black physicians' experience with race: should we be surprised? Ann Intern Med. 2007 Jan 2;146(1):68-9. doi: 10.7326/0003-4819-146-1-200701020-00013. PMID: 17200226.

      3. McFarling UL. Troubling podcast puts JAMA, the ‘voice of medicine,’ under fire for its mishandling of race. Stat News. 2021 April 6 [Cited 2022 August 31]. Available from: https://www.statnews.com/2021/04/06/podcast-puts-jama-under-fire-for-mishandling-of-race/ <br /> Reviewer #2: Thank-you, once again, for the opportunity to review this lengthy “thesis-style” manuscript which discusses some important often over-looked topics. The under-use of serial creatinine measurements and over-reliance on often erroneous eGFR measurements is an important point which is easily missed by healthcare workers with potentially serious consequences. Likewise, the misuse of racial constructs in medicine (and elsewhere) is an important point.<br /> Thank you for again giving time for helpful criticism and comments on our manuscript.

      A. I am satisfied with this re-submission and the changes which have been made to the original manuscript.<br /> Minor points:<br /> B. 431: “creatinine inhibits several membrane transporters”. = Cimetidine<br /> Corrected.

      C. 502: “Because mGFRs have population variation as wide as sCr, with much greater physiologic variability compared to the relatively stable sCr and serum cystatin C”<br /> As mentioned previously the cited article compares the variability of sCr and cystatin C with CrCl, I agree with the authors that CrCl is a form of mGFR, however, probably one of the poorer forms and not what a reader will think of when mGFR is mentioned. In our current age of medicine when we talk about mGFR CrCl is seldom included, studies reviewing methods of mGFR will seldom include CrCl, however CrCl may be compared to one of the mGFR methods. Likewise, if a patient is sent for a mGFR, a CrCl will not be performed. In our current age of medicine mGFR refers to methods such as the clearance of iohexol, iothalamate, Cr-EDTA, inulin, DTPA, etc; the authors themselves mention this (line 539 – 540). I fully agree with the authors that mGFR is FAR from perfect and has many inaccuracies and imprecisions (which are often overlooked)- these are well published, some of which are cited in this manuscript. If the authors wish to use the current study as a source they should state the findings in a way that cannot be misinterpreted. For example: “CrCl has much greater physiologic variability than sCr and cystatin C …” – in this case the reader can determine for themselves whether they would use CrCl as a surrogate for mGFR. Alternatively, adjust the statement and use another source which has shown the variability that exists with what we currently refer to as mGFR method.<br /> We appreciate this comment and have both added another reference and added to the text an argument for reconsidering creatinine clearance. Many hospitals and some countries lack the resources for advanced mGFR filtration markers, which are only used for research or for screening related to kidney transplants. However, most laboratories have the tools for ‘quick-creatinine clearance’ (quick-CrCl), which may be an acceptable alternative to the classic mGFRs. If confirmed, a simple and affordable quick-CrCl might allow hospitals and laboratories worldwide an alternative measurement requiring fewer assumptions for another aspect of glomerular filtration.

      D. 670 – 719: As the authors specifically discuss age it would be prudent to briefly mention the short-comings, or considerations for interpretation, of serial creatinine measurements at a very young age which generally rise until late adolescence when steady muscle mass is achieved. Also note changes in creatinine and GFR from birth till 2 – 3 years.<br /> We have added a brief discussion of the diagnosis of CKD in infants, children, and adolescents.

      E. 783 – 784: Consider re-wording, the grammar makes this sentence difficult to read<br /> Done.

      F. 959 – 968: Note, editing has not been accepted (tracked changes still shown).<br /> Done.

      G. 1116 - 1121: “Using the opioid crisis as an example…. in, for example, the opioid crisis” – same sentence.<br /> Rewritten.

      We thank you.

    1. On 2022-03-01 05:15:31, user Nun Daled Yud wrote:

      clearly serial daily or twice daily testing is needed for patients who would benefit from the early antiviral treatments particularly aged care facilities .

    1. On 2022-03-09 02:39:17, user Peter J. Yim wrote:

      Vaccine efficacy based on vaccination registries is dependent on the completeness of the registries. Any missing or improperly registered data contributes to misclassification bias: https://drive.google.com/fi...<br /> This study relies on the Citywide Immunization Registry (CIR) and the NYS Immunization Information System (NYSIIS). However, no evidence is presented for the accuracy of those registries. As such, the VE estimates from this study should be regarded as uncertain.

    2. On 2022-05-05 12:39:51, user Robert Clark wrote:

      The data shows efficacy against infection becomes NEGATIVE after one month. Imperative to found out if at longer times this also happens for hosp./deaths. Review the data to found out.

      Robert Clark

    1. On 2022-03-23 02:12:03, user Guest wrote:

      Hello authors,<br /> Thank you for submitting a preprint of this interesting study on the virome to a public domain. I have a few questions regarding your methods and materials.<br /> First, the detailed description of sample collection was great, but I could not find any internal standards for the PCR steps, DNA extraction, or isolation of VLP. These might have been stated, somewhere else perhaps, but I could not identify them. However, for sample collection, how did you determine the location and type of wounds that would be tested? Was there a specific location or depth for chosen wounds or just all types stated that were within the frames of the criteria?<br /> Secondly, the methods for sample processing and DNA extraction are excellent, but I cannot seem to find any information regarding the primers used or the number of cycles performed while analyzing 16S rRNA. I could not find the total number of sequences obtained per sample, however, the quality reading for the viral reads was in-depth and well covered. I did not find any profile or 16S normalization or a total quantification of bacterial or bacterial numbers (like qPCR).<br /> Thirdly, I did not find anything about OTU abundance corrected for variance in copy numbers or variance in genome size. I also could not find any method details regarding coverage of communities measured or if there was any comparison to the dominate to rare. One last question, what do you define as ‘deep sequencing’ regarding this study?<br /> Overall, I found this article very interesting and a good read. Thank you for providing such excellent work with the virome. I have not seen many studies regarding the effects of the virome on human healing, host interactions, or composition until recent years, but this article provides a great starting point for these types of studies.

      SHSU5394

    1. On 2022-04-07 15:07:03, user Addi Romero wrote:

      A revised, updated version has been published as a correspondence in The Lancet Infectious Diseases. A link will be forthcoming. Meanwhile, feel free to have a look at the In Press, Corrected Proof: <br /> https://www.sciencedirect.c...

      Dynamics of humoral and T-cell immunity after three BNT162b2 vaccinations in adults older than 80 years

    1. On 2022-04-29 17:03:47, user Madhava Setty, MD wrote:

      Very interesting study. From where did the data on viral copies come from? Also, the odds of seroconversion in placebo vs treatment, stated as 13.67 at a given viral copy level, doesn't seem to be reflected in the corresponding plot (B).

    1. On 2022-05-21 01:10:31, user Fritz Stumpges wrote:

      You need to provide ground level readings for this test, for your group (1) without masks. Without this base, we don't know if your methods are just producing extremely high readings across the board!

    1. On 2022-05-30 22:36:58, user Stuart Turville wrote:

      Now published within this manuscript here:

      Congratulations<br /> Dear Stuart G. Turville

      We are pleased to inform you that your article has just been published:

      Title<br /> Platform for isolation and characterization of SARS-CoV-2 variants enables rapid characterization of Omicron in Australia

      Journal<br /> Nature Microbiology

      DOI<br /> 10.1038/s41564-022-01135-7

      Publication Date<br /> 2022-05-30

      Your article is available online here https://doi.org/10.1038/s41... or as a PDF here https://www.nature.com/arti....

    1. On 2020-05-20 00:33:44, user SizzMo wrote:

      It appears that the methods of administration of hydroxychloroquine were doomed to fail before even being undertaken. A review of the full study reveals NO mention of zinc, and suggests that hydroxychloroquine was administered alone or sometimes in tandem with azithromycin, and primarily to hospitalized patients in very late stages of illness. The omission of zinc and administration only in late stages of disease defeat the mechanism of action by which the hydroxychloroquine protocol works

      The primary mechanism of action in the hydroxychloroquine+zinc+azithromycin protocol uses hydroxychloroquine primarily as an ionophore for zinc, which then inhibits viral replication in the cell cytoplasm. Zinc is an essential component of this protocol, and omitting zinc appears to be a fatal flaw in all of the reviewed studies and case reports in this analysis. Furthermore, this paper repeatedly refers to hydroxychloroquine being administered to hospitalized patients. The mechanism of action is the inhibition of viral replication, which reduces viral load at early stages of disease. Giving this protocol in late stages of disease when viral load is already heavy and patients are already severely ill defeats the purpose of the protocol and practically guarantees that it will not be effective. The methods reviewed in this study overlook what is known about both the mechanism of action of viral inibitors, and the synergistic function of hydroxychloroquine and zinc in viral RNA replication, making it appear that these "studies" were designed to fail.

      Clinicians employing the complete hydroxychloroquine+zinc+azithromycin protocol at early stages of disease (mild to moderate illness) are universally reporting high levels of efficacy. <br /> Additionally, researchers in an NYU Langone retrospective analysis of more than 900 patients with mild-to-moderate illness who received the protocol with or without zinc also reported significant improvements in patients who received zinc. The NYU Langone study is currently undergoing peer review, and is available at this link: https://www.medrxiv.org/con...

    2. On 2020-05-23 22:06:14, user CKComments wrote:

      The authors dismiss the finding regarding the improvement in lung health in their summary. It's messed up lungs that kill patients, so it seems worth emphasizing.

    1. On 2022-07-18 12:29:27, user Loretta Lorenz wrote:

      Quite likely many person are vaccinated and infected in various sequences. My question is, if the SARS-CoV 2 Spike protein measurement differentiated beetween spike proteins originating from a vaccine against COVID-19 and the different Spike Proteins of the various SARS-CoV-2 mutations.

    1. On 2022-07-20 16:59:17, user Tania Watts wrote:

      The authors may want to note similar findings in our paper, Dayam et al. Accelerated waning of immunity to SARS-CoV-2 mRNA vaccines in patients with immune-mediated inflammatory diseases, JCI Insight, 10.1172/jci.insight.159721 April 2022. We show anti-TNF treated patients have lower Ab responses, no neutralization of Omicron and enhanced waning of T and Ab responses to SARS-CoV-2 mRNA vaccines after 2 doses.

    1. On 2022-07-25 16:31:06, 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 2022-07-29 13:52:30, user Stuart MacGowan wrote:

      This is great work! A few years ago I worked on something similar - mapping missense variants to Pfams and defining constrained positions https://doi.org/10.1101/127050 . We also saw enrichment of pathogenic variants at constrained positions. Great to see this area moving forward!

    1. On 2022-08-04 17:25:32, user Paul Hunter wrote:

      Did you include date or week number in your model? During the study period there was a dramatic shift in the proportion of tests positive in Portugal from about 1 in 4.5 to 1 in 2 and that could explain your findings of a 3 x greater risk of hospitalisation associated with BA.5 infection irrespective of the actual risk . If you did not include week number then I think your conclusions are probably flawed.

    1. On 2022-10-05 13:49:05, user Merja Rantala wrote:

      Congrats for this preprint, it is an important summary what we know about protection of hybrid immunity and prior infection against cov19. However, I think that references and claims in the discussion should be checked. There was a sentence on page 13, first paragraph, claiming that covid survivors would have higher risk for dementia in addition to some other conditions. The reference cited was 36, which is not at all about risks for diseases after covid, but the other way around: risk factors for a severe covid outcome. So the ref need to be replaced. Moreover, we really don''t know at this stage whether risk for dementia is increased after covid or not, although has been under heavy speculation.

    1. On 2020-05-26 09:28:09, user David Sbabo wrote:

      5 counfounding factors with a p-value under 0.05, all in the same direction "higher chance of mortality for the no zinc group".

    1. On 2020-05-26 17:03:03, user Sinai Immunol Review Project wrote:

      The main finding of the article: <br /> Recent studies have diverged as to weather conditions are allied or not with the spreading of Covid-19. Through random-effects meta-regression analysis, this work aimed was to determine if elements linked to meteorology can influence SARS-CoV-2 incidence and the speed of its propagation. The number of Covid-19 patients and meteorological conditions at each Japanese prefectural capital city from January to April 2020 were collected. <br /> The results demonstrated a negative association between Covid-19 incidence and monthly mean air temperature (C) (coefficient -0.351), sea level air pressure (hPa) (coefficient -0.001) and the monthly mean daily maximum UV index (UV) (coefficient -0.001).

      Critical analysis of the study: <br /> The manuscript would benefit from a more thorough introduction and discussion of the results in the context of previous studies. The authors could explore more the results of the supplementary table 1 (wind speed, relative humidity and sunshine). The figure caption should be better detailed, explaining the characteristics of each graph.

      The importance and implications for the current epidemics: <br /> The transmission dynamics of SARS-CoV-2 depends on different factors, such as population density, demographic and clinical characteristics of the population, hygiene, local ventilation, etc., and the seasonality of SARS-CoV-2 is not yet known.<br /> The data of this manuscript suggest that higher air temperature, air pressure, and ultraviolet are associated with a lower incidence of Covid-19. Certainly, this study is a step in identifying which environmental factors can favor viral transmission.

      Reviewed by Bruna Gazzi de Lima Seolin.

    1. On 2020-05-27 02:34:42, user Aaron wrote:

      It would be a good addition to show the breakdown of patient demographics for those samples included in Figure 4 to show whether there are differences in the samples collected for each clade thus far. If there are any significant differences, those could be just as important as the viral sequence, if not more so. While I see that authors tried to control for these variables, it'd still be a good idea to show this information in a table in the main figures.

      Additionally, the differences in the rate of spread for each clade are probably much more attributable to the cities themselves that each clade is primarily associated with rather than any differences in the virus; there are major differences in the infrastructure and movement of individuals depending on the metropolitan area. I don't find it particularly surprising that any viral sequence(s) associated with NYC would spread faster than those found in Washington or Chicago. The differing responses of each city in shutting down public movement will also play a big role here.

    1. On 2020-05-28 12:04:39, user Mike Nova wrote:

      M.N.: Good study. It would be good to trace also the correlations with 1) Degree of Rat Infestations and 2) Centralised air conditioning and high power flush public toilets, producing the infectious aerosoles in these places.

    1. On 2020-05-28 16:48:14, user Megan Toohey wrote:

      So I had an antibody test that came back negative but I did have trace amounts apparently. The range was 1.4 and my result was 0.2. I did get sick for a week with severe migraine, dizzy, light headed, nausea, fever runny, nose (off and on but not bad) not really congested, no sob, or cough. Got tested twice for covid which came back negative each time. I work in a hospital so i am around covid a lot. I'm just looking for some insight on that 0.2 result. And if they mostly doing detected/not detected type testing doesn't that technically mean if its my system its been detected? I'm not a scientist, doctor, or nurse so I apologize if my question is dumb.

    1. On 2020-05-28 20:40:28, user Esmeralda R. wrote:

      Once accepted, this paper will be very important. <br /> This is a data that still in need in the community. Diabetes has been associated in many studies, but this work with 18.5K patient, from which 3.7K diabetic patients was/is in need. <br /> Real Gramas

    1. On 2020-05-29 03:44:38, user TE de la Belle wrote:

      It seems to me that there is no actual evidence that Covid-19 was ever more prevalent in the elderly than in any other age group. When testing subjects are chosen by self-selection, surely it is those suffering from the most severe symptoms who will be most likely to self-select and be tested. It is the elderly who are more likely to develop more severe symptoms to this disease. So, it is the elderly with Covid-19, suffering from symptoms, that were being tested early on, more frequently than younger people, who were more likely to have mild or no symptoms. As testing has become more prevalent and contact tracing has begun, we are testing more people with mild or no symptoms. So more young people appear in the statistics. Surely that is the most likely explanation for the shift in frequency between age groups.

    1. On 2020-05-29 06:53:23, user Chris Valle-Riestra wrote:

      This is a great contribution to our knowledge of the epidemic. It's not an ideal way of determining the IFR, obviously, and the underlying serological studies had their shortcomings, but it's a well-reasoned effort to draw conclusions based upon the best available data. From what I've been able to learn, previous highly-publicized estimates of IFR by public health authorities have mostly been based on very thin data or been no better than educated guesses.

      Critiques just point up the great need for large scale rigorously-designed programs to gather far more data empirically. If that data leads to considerably different conclusions, so be it, but right now we don't have it.

    2. On 2020-05-21 23:33:25, user Jack A Syage wrote:

      Very interesting analysis, but I have a counter argument to this. Most of these studies were conducted before the death rate peak. Deaths represent infections from about 2.5 weeks before whereas antibody measurements are current. So cases have grown by multiples by then. As a check I see the following trend in Table 3: the earliest dates show the lowest IFR's (since growing cases run way ahead of deaths) and latest dates show the highest IFR's (as cases are subsiding and catching up to deaths). So I plotted this and there is a distinct upward dependence for IFR vs. date with a Pearson coeff of 0.61 (pretty strong) and a 2-tailed, paired t-value of a staggering p = 0.00003.

      I suspect continued antibody tests for populations well past the death rate peak will start to converge on a higher value of IFR, e.g., about 1%.

      I have been doing modeling and interested in views: please check out:

      https://www.medrxiv.org/con...

      and

      syage-covid19-assessment.com

      @jacksyage<br /> https://twitter.com/jacksyage<br /> https://twitter.com/medrxiv...

    1. On 2020-05-29 18:32:49, user Sinai Immunol Review Project wrote:

      Main Findings<br /> The authors analyzed and compared the stability of viable SARS-COV-2 and SARS-CoV-1 inoculums in five environmental conditions (aerosol, copper, cardboard, steel, and plastic) by using Bayesian regression model. It was reported that SARS-COV-2 was still detected in aerosols at 3 hours, with an exponential reduction in infectious titer that was similarly observed for SARS-CoV-1. The study also concluded that both SARS-COV-2 and SARS-CoV-1 are more stable on stainless steel and plastic than cardboard and copper. Viable SARS-CoV-2 was detected up to 72 hours on stainless steel and plastic. On copper and cardboard, SARS-COV-2 was viable up to 4 hours and 24 hours, respectively, compared to SARS-CoV-1 which could be detected up to 8 hours on both material types. The half-lives between both viruses are similar, except for on cardboard.

      Limitation of the study<br /> The strain used in the study was SARS-COV-2 nCoV-WA1-2020 (MN985325.1) from the first case of 2019 novel coronavirus in the US. However, mutation throughout the course of the pandemic is inevitable and may cause unpredictable consequences on its transmissibility and disease severity. Thus, follow-up on samples from various patients in different geographic and temporal time points should be conducted.

      Significance<br /> The results support that modes of SARS-COV-2 transmission can be attributed to both aerosol and fomites, due to extended viability for hours in aerosol and up to 72 hours on stainless steel surfaces. The types of plastic, cardboard, copper, and stainless materials were selected to reflect typical hospital and household situations. It is important to compare with the SARS-CoV-1 as similarities between the two suggests methods of mitigating the pandemic by abrogating transmission both in the community and hospital.

      Review by Joan Shang as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of medicine, Mount Sinai.

    1. On 2020-05-30 02:04:01, user jeff wrote:

      Has anyone correlated the asymptomatic people to those on a low dose aspirin regiment? Are these people who have contracted and recuperated on blood thinners and low dose aspirin? Is this virus really a virus and not a bacterium? These autopsies site thrombosis! Is anyone looking into this any further?

    1. On 2020-05-30 09:02:50, user Alberto 97 wrote:

      These data should be completed and submitted to a peer reviewed journal in the field, otherwise results reported in the Table cannot be trusted as experimentally sound, even without a thorough description of the methods used in the paper. Did you address the hypothesis to expand your evidence to be reported in a full publication in a specialized journal?

      Prof A. Manzini (Roma III)

    1. On 2020-06-01 12:41:21, user Ron Conte wrote:

      SARS-CoV-1 (causes SARS) is more similar to SARS-CoV-2 (causes Covid-19) than these cold coronaviruses used in the study. SARS antibodies last 2 to 3 years ("Duration of Antibody Responses after Severe Acute<br /> Respiratory Syndrome", Emerging Infections Diseases, 13:10, 2007), and "Memory T cell responses targeting the SARS coronavirus persist up to 11 years post-infection" (dx.doi.org/10.1016/j.vaccin... "dx.doi.org/10.1016/j.vaccine.2016.02.063)").

    1. On 2020-06-01 19:37:39, user Marcelo Fernandes wrote:

      The prediction model has several problems, and there are several wrong assumptions. At the moment, the number of cases and depths in Brazil is growing very fast. The results of this paper created a false feeling about Pandemic in Brazil.

    1. On 2020-06-04 15:25:54, user Andy Loveman wrote:

      what other factors were considered: prevalence of O-type, A-type in the population at large; and underlying health factors compared in both groups?

    2. On 2020-06-08 16:44:40, user Georg Mumelter wrote:

      Thank you! Would it be possible and interesting to further analyze the risk difference by patient age and maybe gender - is the difference especially prevalent in younger or older age, male female? Should be a farily quick and easy analysis (cluster or regression) and plot.

    3. On 2020-06-12 19:34:13, user Amr Sawalha, MD wrote:

      Nice work. The lack of association in the HLA region is very interesting given the perceived exaggerated immune-mediated response in patients with severe COVID-19. Genetic studies looking at patients with confirmed cytokine storm will be of interest in this regard, and of course a closer look at the epigenetics of immune-response genes will be of interest.

    1. On 2020-06-05 10:23:43, user Alberto M. Borobia wrote:

      This manuscript has been published in "Journal of Clinical Medicine" https://www.mdpi.com/2077-0...

      Borobia, A.M.; Carcas, A.J.; Arnalich, F.; Álvarez-Sala, R.; Monserrat-Villatoro, J.; Quintana, M.; Figueira, J.C.; Torres Santos-Olmo, R.M.; García-Rodríguez, J.; Martín-Vega, A.; Buño, A.; Ramírez, E.; Martínez-Alés, G.; García-Arenzana, N.; Núñez, M.C.; Martí-de-Gracia, M.; Moreno Ramos, F.; Reinoso-Barbero, F.; Martin-Quiros, A.; Rivera Núñez, A.; Mingorance, J.; Carpio Segura, C.J.; Prieto Arribas, D.; Rey Cuevas, E.; Prados Sánchez, C.; Rios, J.J.; Hernán, M.A.; Frías, J.; Arribas, J.R.; on behalf of the COVID@HULP Working Group. A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe. J. Clin. Med. 2020, 9, 1733.

    1. On 2020-06-05 23:05:25, user Amy E. Herr wrote:

      *WARNING to READER*: Essential technical information is missing from this PDF which prohibits accurate interpretation and repeatability of the results.There is (1) insufficient evidence substantiating successful 'decontamination', (2) insufficient information on UV-C source and detector, and (3) insufficient information on UV-C dosing. We urge the authors to add these critical details which are represent the bare-minimum for accurate reporting and reproducibility, as further described below:

      1. Claims of “decontamination” do not align with FDA EUA guidance/terminology. FDA guidance on requesting EUAs for respirator decontamination systems define “decontamination” and “bioburden reduction” in terms of specific log-reduction values for specific classes of microorganisms. Because 6-log or 3-log reduction was not always observed or possible to be measured in this study, and no non-enveloped viruses or bacteria were tested, the results do not fall within the FDA definitions for decontamination and bioburden reduction. We suggest adjusting terminology to align with FDA EUA guidance.

      2. Critical information on UV-C source and detector is not provided. Make, model, wavelength emission spectrum, type of UV-C source (e.g., low pressure mercury lamp, LED, etc.), and dimensions of any UV-C bulbs should be reported for the source; make, model, and wavelengths detected are key parameters to report for any radiometer/dosimeter. Because UV-C decontamination equipment is not standardized and measured UV-C dose depends critically on the details of the UV-C source and detector (e.g., whether emitted and detected wavelengths match), reporting these details is critical for accuracy and reproducibility.

      3. Missing details on UV-C dose distribution across the N95. For example, where was the N95 placed within the UVGI device, relative to the UV-C source? Was the ~10% dose permeation observed across all locations on all N95 models? Providing details on characterization of UV-C dose distribution across the N95 is requisite for readers to understand whether a ‘worst-case’ scenario is being modeled.

      We thank the authors for their important research efforts on N95 decontamination during this COVID-19 pandemic & look forward to an updated/revised PDF posting.

    1. On 2020-06-06 13:55:03, user Jürgen Heuser wrote:

      Thx very much for this very helpful work!!

      I'm afraid I do not understand the term <br /> "Comorbidities marked by * are defined by hospital discharge diagnoses in combination with drug redemptions (i.e. filled prescription within 6 months prior to the test date. Of note, there is a lag of 15 days on prescription data)" <br /> when applied to diagnoses like alcohol abuse, overweight or dementia. What kind of medication prescribed would qualify a patient into those categories?

      Best <br /> Jürgen Heuser

    1. On 2020-06-06 15:50:28, user Alberto M. Borobia wrote:

      Dear Authors, congratulations for your publication. Your reference Borobia et al. is now published in JCM.

      Borobia, A.M.; Carcas, A.J.; Arnalich, F.; Álvarez-Sala, R.; Monserrat-Villatoro, J.; Quintana, M.; Figueira, J.C.; Torres Santos-Olmo, R.M.; García-Rodríguez, J.; Martín-Vega, A.; Buño, A.; Ramírez, E.; Martínez-Alés, G.; García-Arenzana, N.; Núñez, M.C.; Martí-de-Gracia, M.; Moreno Ramos, F.; Reinoso-Barbero, F.; Martin-Quiros, A.; Rivera Núñez, A.; Mingorance, J.; Carpio Segura, C.J.; Prieto Arribas, D.; Rey Cuevas, E.; Prados Sánchez, C.; Rios, J.J.; Hernán, M.A.; Frías, J.; Arribas, J.R.; on behalf of the COVID@HULP Working Group. A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe. J. Clin. Med. 2020, 9, 1733.

      Best regards,

    1. On 2020-06-07 11:11:53, user peter kilmarx wrote:

      Great work! Why not use both in a pool of two specimens? You missed 8 positives with NP only and 3 positives with saliva only.

    1. On 2020-06-08 17:06:04, user Johann Holzmann wrote:

      Dear authors,<br /> Thank you for making the pre-print accessible, I read it with great interest.

      How do your findings regarding the presumptive false-positive rate of SARS CoV2 detection using RT-PCR relate with the very low RT-PCR positive rate as currently seen in many countries or regions with a very low prevalence of SARS CoV2?<br /> For example Australia runs between 30.000 to 35.000 PCR test daily for the last month and only gets around 10 positive assays per day. <br /> Other examples with a ratio of PCR assays per day to posiive assays of around 600-2000:1 are Iceland, Greece, Croatia, Thailand and certain parts of Germany (eg Sachsen-Anhalt, Mecklenburg Vorpommern) or Austria (eg Tirol).<br /> Wouldn't these data indicate a much lower false-positive rate than the one suggested in your manuscript?<br /> Thank you again for making your research accessible<br /> kind regards

    1. On 2020-06-30 12:50:48, user Dude Dujmovic wrote:

      "Secondary cases"? I think you need to precisely define what do you mean by that. The whole paper is extremely vague in what the numbers are about.

    1. On 2020-06-09 20:59:34, user Brenner Silva wrote:

      Comment:<br /> Well explained and valid analysis.<br /> Suggestions: <br /> line 203. please indicate the formula variables in the text.<br /> Possible corrections:<br /> line 147. please name the app as in "we used the COVID-19 app to"<br /> line 210. "where each is"<br /> line 213. "is defined by the"<br /> line 325. "and future work to better understand"

    1. On 2020-06-10 01:57:51, user Sinai Immunol Review Project wrote:

      Main findings<br /> To improve understanding of the cellular changes in the T and B cell compartments of COVID-19 patients, both during and after disease, Fan et al. analyzed lymphocytes isolated from the PBMCs of 4 severe COVID-19 patients (n=4), 6 COVID-19 recovered patients (n=6), and 3 healthy controls (n=3). Of note, 3 recovered patients' samples were collected 7 days after a negative SARS-CoV-2 test (recovery-early stage; RE) and absence of clinical symptoms, whereas the other 3 samples were collected 20 days after these criteria (recovery-late stage; RL). The authors used single-cell RNA sequencing and single-cell V(D)J sequencing to perform their analysis.

      The authors identified 9 classes of T cells, which included 4 sub-classes of CD4+ T cells and 5 sub-classes of CD8+ T cells. Not surprisingly, across severe COVID-19 patients, the proportion of T cells was reduced, compared to healthy controls. However, differential gene expression analysis revealed that T cells from severe COVID-19 patients highly expressed inflammatory markers, including IFNG and GZMA. Interestingly, when compared to these patients with active disease, RE samples showed significant enrichment of ICOS+ TH2-like follicular helper T cells (TFH), whereas RL samples showed a reportedly significant enrichment of a cluster identified as TH1 cells, though this result should be revisited for review (See biological limitations). These cell types were, in fact, reduced in severe COVID-19 patients. Generally, these T cells from recovering patients continued to indicate persistent activation and counter-regulation, based on expression of TCR activation-associated genes, including RNF125 and PELI1. Subsequent trajectory analyses of transcriptional dynamics indicated transition of effector CD8+ T cells to central memory T cells in RL patients. Ligand-receptor analysis revealed potential interactions between TH1 cells and CD14+ monocytes in severe COVID-19 patients. Finally, TCR sequencing identified several VJ combinations in high frequencies in severe COVID-19 patients, but not others.

      Within the B cell compartments across patients, the authors identified 9 clusters of naive B cells, 2 clusters of memory B cells, 2 clusters of plasma B cells, and a cluster of plasmablasts. Of these clusters, one, in particular, expressed genes characteristic of FCRL5+ atypical memory B cells, which have been described to be induced by viral infections. Interestingly, ligand-receptor analyses of the clusters in each group of patient samples identified different degrees of TFH cell and B cell interactions, suggesting different stages of T cell help for B cell activation. Subsequent BCR characterizations revealed the presence of homogenous monoclonal and heterogeneous clonally expanded B cell populations; the latter population exhibited an enrichment of B cell activation genes. The authors, then, compare across patients to evaluate T and B cell clonality based on V(D)J recombination analyses of RE and RL patient samples (See technical limitations).

      Interestingly, cytokine expression analysis revealed IL-6 expression by B cells. In contrast, B cells expressed IL12A in RE patients, while effector memory CD8, proliferative CD8, and CD4 T cells and plasma B cells highly expressed IL16 in RL patients. The authors report additional cytokine (and cellular) characteristics that distinguish severe COVID-19 patients and recovering patients.

      Limitations<br /> Technical<br /> A primary technical limitation is the sample size of this study for each group. There is little clinical information about the patients and no details about disease severity in patients recruited after viral clearance. For example, age and CMV status have a huge impact on the TCR repertoire, therefore clinical data on the different groups should be presented. Moreover, without additional information on the clinical management of the severe COVID-19 patients and what therapies were given to the recovering COVID-19 patients, it is difficult to compare the cellular changes in the immune landscapes of the COVID-19 patients across samples. Longitudinal analysis would have been more informative especially with regards to repertoire analysis and how expanded clones during active infections might differentiate into particular phenotypes after viral clearance.CD8 expression should have been included in the violin plots, as it is usually more robust and reliable than CD4 expression.

      Biological<br /> An immediate concern is whether the authors mis-characterized cluster 13 as a TH1 cell cluster. The cluster exhibits a low expression of CD3G and CD4. It’s neighboring clusters within the hierarchy belong to monocyte groups, so it is unexpected that a T cell subtype would be belong to their branch of the hierarchy tree. Consider also cluster 38, which shows more robust expression of CD3G and NKG7 and is arranged with the B cell group.

      In addition, the authors did not highlight or discuss expression of co-inhibitory receptors that could elucidate the heterogeneity of T cell differentiation during COVID-19. As a result, it is difficult to truly assess the activation status of the CD8+ cytotoxic T cells and whether there are features of T cell exhaustion.

      Finally, the distinction between naïve and some subsets of memory T cells by scRNA analysis can be challenging. It would be important for the authors to explore whether cluster 26, classified as a naïve CD8 T cell cluster predominant in RL group could be actually memory cells. It would have been important to show clonal diversity of the different clusters.

      Significance<br /> In summary, Fan et al. provide a comparative analysis of lymphocyte changes between PBMCs of patients with ongoing COVID-19 progression and of patients recovering from the disease. Using a combination of single-cell RNA sequencing and V(D)J recombination sequencing, the authors describe specific changes in T and B cell subpopulations over the course of early and late-stage recovery.

      This review was undertaken by Matthew D. Park as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-06-10 09:22:39, user alanarchibald wrote:

      Am I correct in understanding that your definition of (European) travel in the context of this study is limited to travel by persons who are normally resident in the UK and that travel by visitors to Scotland/UK is not addressed, presumably as you did not have access to the necessary samples and medical records.

    1. On 2020-06-15 01:10:48, user Serge wrote:

      There are many inaccuracies in the report that may significantly affect the conclusions.<br /> 1. Diamond Princess analysis: the mortality data (in single digits) is not sufficient for a confident estimate of the mortality per jurisdiction (for some nations there was only a single case). Moreover, most countries started universal BCG vaccination around 1950s plus the effect of WWII would likely compromise any earlier program to a significant extent. That means that regardless of the country of origin, large part of over 70 population would not be protected and thus shouldn't be considered in verification of the hypothesis.<br /> 2. Certainly there can be no expectation that the protection effect would extend equally into a very advanced age, 60 years and longer after vaccination.<br /> 3. What is meant by the statement "BCG was provided mostly in Europe"? This is plain incorrect, please check "BCG World Atlas".<br /> 4. Country analysis: was the population taken into account? It is not clear from the description of diagrams. I would advise to attempt to calculate mortality per capita, from the most current data and compare it between jurisdictions at a similar period of exposure. Note that all countries with the highest M.p.c. adjusted for the time of exposure, never had a BCG program (or equivalent as in Spain where it was provided for 18 years out of 70) there's simply not a single exception.

    1. On 2020-06-15 21:36:07, user Marm Kilpatrick wrote:

      Fantastic (but worrisome) work! <br /> Would it be possible to give the full details of the regression of infectious viral load via culturing (PFU/ml) vs RNA via qPCR? This relationship is robust and could be used as the basis for inferring infectious viral load from qPCR, but doing so in a way that explicitly incorporates uncertainty would require more details of the regression than you currently report. Specifically, if you could report the slope, intercept and residual standard error and sample size for this regression that would enable others to make maximal use of your results. Even better would be to make the individual data points from graph available and then the data could be used directly.<br /> Thank you very much for this important work!<br /> marm

    1. On 2020-06-17 13:21:18, user Jumana Haji wrote:

      Amazing experience working with this group to sort through guidelines and evaluate them for completeness while also developing a tool for future guidelines. The tool is ideal when keeping healthcare worker safety and wellbeing perspective as priorities.

    1. On 2020-06-17 20:11:26, user LB wrote:

      Zotero (a popular citation manager) says that this article has been retracted. If this is not the case, please ask Retraction Watch to correct the error.

    1. On 2020-06-18 01:00:02, user Alex Backer wrote:

      See https://ssrn.com/abstract=3... for a global study that shows case and death counts had significantly lower growth rates at higher temperatures (>14 °C) when aligned for stage in the epidemic. We then show irradiance and in particular solar elevation angle in combination with cloudopacity explain COVID-19 morbidity and mortality growth better than temperature: a reduction of mean solar elevation of 9 degrees led on average to a 2500% increase in COVID-19 case growth over the following two weeks. COVID-19 exploded during the darkest January in Wuhan in over a decade. Our results suggest transmission models should incorporate solar elevation and that the impact of UV irradiance on individual morbidity and mortality should be tested. We discuss implications for the best locations and optimal behaviors for high-risk individuals to weather the pandemic. --Alex Bäcker, Ph.D.

    1. On 2020-06-18 22:54:00, user RockyNBullwinkle wrote:

      would be nice to see just one large prospective randomized double blind study for hospitalized patients, one study for patients that don't meet criteria of hospitalization, and one for prevention. Zinc 50 mg daily and HCQ 200 mg twice daily.

    1. On 2020-06-19 18:24:34, user ChrisdeZilcho wrote:

      Apparently a new study from same team shows CoV2-positive samples from savage water stored in Dec last year. Would be interesting to see the phylogenetic sequence analysis. Did virus fizzle out in Dec/Jan or was there a "quiet" transmission activity? Have there been many independent intros into Italy? Looking forward to reading the publication.

    1. On 2020-06-19 22:15:27, user Michelle Kimple wrote:

      Have you thought of performing analyses of your data by city/county size and/or population density? In the abstract you state "We did not find an association between county level prevalence of COVID-19 cases and face covering use" but when I limited the data to only counties with the 5 most populous cities, there appears to be a strong correlation. I just tweeted my analysis of your data (the county populations may not be what you used, but the city and county population ranks are correct): https://twitter.com/KimpleL...

    1. On 2020-06-21 20:05:22, user Jørgen K. Kanters wrote:

      Please note that by some (yet) unknown reason one of the authors Claus Graff is omitted from the MedRxiv page, but correctly included in the pdf file. We will submit a revision tomorrov to correct it

    1. On 2020-03-26 13:52:15, user Sinai Immunol Review Project wrote:

      SUMMARY: This study aimed to find prognostic biomarkers of COVID-19 pneumonia severity. Sixty-one (61) patients with COVID-19 treated in January at a hospital in Beijing, China were included. On average, patients were seen within 5 days from illness onset. Samples were collected on admission; and then patients were monitored for the development of severe illness with a median follow-up of 10 days].

      Patients were grouped as “mild” (N=44) or “moderate/severe” (N=17) according to symptoms on admission and compared for different clinical/laboratory features. “Moderate/severe” patients were significantly older (median of 56 years old, compared to 41 years old). Whereas comorbidies rates were largely similar between the groups, except for hypertension, which was more frequent in the severe group (p= 0.056). ‘Severe’ patients had higher counts of neutrophils, and serum glucose levels; but lower lymphocyte counts, sodium and serum chlorine levels. The ratio of neutrophils to lymphocytes (NLR) was also higher for the ‘severe’ group. ‘Severe’ patients had a higher rate of bacterial infections (and antibiotic treatment) and received more intensive respiratory support and treatment.

      26 clinical/laboratory variables were used to select NLR and age as the best predictors of the severe disease. Predictive cutoffs for a severe illness as NLR >= 3.13 or age >= 50 years.

      Identification of early biomarkers is important for making clinical decisions, but large sample size and validation cohorts are necessary to confirm findings. It is worth noting that patients classified as “mild” showed pneumonia by imaging and fever, and in accordance with current classifications this would be consistent with “moderate” cases. Hence it would be more appropriate to refer to the groups as “moderate” vs “severe/critical”. Furthermore, there are several limitations that could impact the interpretation of the results: e.g. classification of patients was based on symptoms presented on admission and not based on disease progression, small sample size, especially the number of ‘severe’ cases (with no deaths among these patients). Given the small sample size, the proposed NLR and age cut offs might not hold for a slightly different set of patients. For example, in a study of >400 patients, ‘non-severe’ and ‘severe’ NLR were 3.2 and 5.5, respectively 1.

      References:<br /> 1. Chuan Qin, MD, PhD, Luoqi Zhou, MD, Ziwei Hu, MD, Shuoqi Zhang, MD, PhD, Sheng Yang, MD, Yu Tao, MD, PhD, Cuihong Xie, MD, PhD, Ke Ma, MD, PhD, Ke Shang, MD, PhD, Wei Wang, MD, PhD, Dai-Shi Tian, MD, PhD, Dysregulation of immune response in patients with COVID-19 in Wuhan, China, Clinical Infectious Diseases, , ciaa248, https://doi.org/10.1093/cid...

      This review was undertaken as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-05-22 16:23:27, user Jim Parfitt wrote:

      It is difficult to find any discussion on this issue. I am a person who has taken NO systemic antibiotics for over 40 years. And I basically never get sick. I have been wondering how many of the severe cases of Covid 19 are in people who regularly take systemic antibiotics, and so have messed up gut flora. This is what i suspect. I would like to read the whole study; if that is possible.

    1. On 2020-05-23 16:44:37, user Rosemary TATE wrote:

      Thank-you for this well-written and interesting paper. It's very puzzling s that ethnicity was not a factor for hospital mortality (either unadjusted or adjusted rr's). Statistics reported here in the UK suggest that ethnic minorities are at far higher risk. This recent preprint on US deaths suggests the same.(https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.05.21.20109116v1.full.pdf)")

      Do you have an explanation for these disparities. Could it be that non-whites are less likely to go to hospital in the US? Or is there another reason?

    1. On 2020-05-24 08:36:41, user Lauren wrote:

      Accidental death rates for my age group of 30 to 39 are roughly 1 in 1000 (white female) roughly the same as COVID. I get what others are saying but this specifically addresses percent of death compared to other fatality statistics. I do think though that thr 50 or 60 age range is more likely to die of COVID IF almost everyone were to be exposed, hopefully we will not see that. This however does not include impact of COVID on black and Hispanic populations which are much higher.

    1. On 2020-05-24 17:09:55, user Gary Kast wrote:

      Assuming that 1/3 of covid patients were taking the ace-I or arbs unless that is the percentage of the entire elderly pop taking them,( or at least the percentage of bp patients ) I would think that fact indicates a too high association of the meds and covid....I think general numbers should be discussed to support the conclusion. I see the math but question the assumptions and therefore conclusions without that additional number. If high bp is a comorbidity and patients takingbeta blockers and calcium channel and diuretics (b c d) are likewise or even higher numbers represented then clearly the type of bp meds is not too concerning. But if angiotensin drugs are only 20% of total bp meds consumed but 1/3 of patients in hospitals ...uh oh . Clearly not everyone who carries the virus ends up a patient .

    1. On 2020-05-26 23:26:41, user Sam Wheeler wrote:

      The medical staff can get the virus while commuting to work. Especially if you work place is the place where patients go for covid testing or treatment, so you share the bus or subway with sick patients.

    1. On 2020-05-27 01:37:02, user Keith wrote:

      Very exciting new and a likely game changer for dentists/ENTs or anyone who manipulates the mucosa of a potentially covid + patient

    1. On 2025-04-10 17:31:51, user SMR Hashemian wrote:

      At the peak of the COVID-19 crisis, when the world was gripped by fear and despair, Iran was not only battling a deadly virus but also grappling with brutal and inhumane sanctions. Economic sanctions severely restricted Iran's access to medicine, medical equipment, and vaccines, creating one of the biggest obstacles in the fight against this crisis. Yet, despite these unprecedented pressures, Iran did not surrender and, through relentless efforts, found ways to overcome these limitations.<br /> The Iranian government made every effort to bypass the sanctions through international negotiations and the creation of alternative financial channels to import the necessary medicines and equipment. These efforts, though fraught with difficulties, demonstrated Iran's resolve to save lives. Even as many countries refused to assist Iran, the nation relied on domestic capabilities and national solidarity to find solutions to the crisis.<br /> Amidst these challenges, Iran's healthcare workers stood on the front lines like unsung soldiers, making unparalleled sacrifices. Doctors, nurses, and all healthcare workers in hospitals not only played a critical role in saving countless lives but also faced significant personal risks, with many losing their lives in the process. These dedicated professionals demonstrated extraordinary commitment and selflessness, setting an example of resilience and dedication in the face of a global health crisis.<br /> But it was not just the healthcare workers who fought in this battle. Iran's scientific community also stepped up with full force. Iranian scientists and researchers, despite cruel sanctions and countless limitations, never stopped striving. They not only succeeded in producing domestic vaccines like Noora and SpikoGen, but also published numerous articles in prestigious international journals, showcasing Iran's role in advancing global science. These efforts are a testament to the fact that Iran, even under the toughest conditions, can rely on science and knowledge.<br /> The Iranian government, despite all limitations, spared no effort in controlling this crisis. From the very beginning, extensive education on health protocols was launched through the media. The public was continuously informed about health recommendations such as mask-wearing, social distancing, and hand hygiene. Even during Nowruz, one of the most important cultural events in Iran, the government encouraged people to reduce travel and celebrate at home. School and university closures, the shift to remote learning, and the reduction of workplace presence through teleworking all demonstrated the government's resolve to control the spread of the virus.<br /> These efforts, though accompanied by challenges, reflect Iran's national determination to confront this global crisis. Iran, despite all limitations, proved that it could stand firm against the toughest conditions by relying on science, sacrifice, and national solidarity. The accusations raised in this article are not only unfair but also overlook the relentless efforts of a nation. Iran fought with all its might to save lives, and that is something to be proud of.

      Seyed MohammadReza Hashemian<br /> Professor of Critical Care Medicine