Notes

Parental hatred states reduced cortical width in men.
Patients with influenza and SARS-CoV2/Coronavirus disease 2019 (COVID-19) infections have different clinical course and outcomes. We developed and validated a supervised machine learning pipeline to distinguish the two viral infections using the available vital signs and demographic dataset from the first hospital/emergency room encounters of 3,883 patients who had confirmed diagnoses of influenza A/B, COVID-19 or negative laboratory test results. The models were able to achieve an area under the receiver operating characteristic curve (ROC AUC) of at least 97% using our multiclass classifier. The predictive models were externally validated on 15,697 encounters in 3,125 patients available on TrinetX database that contains patient-level data from different healthcare organizations. The influenza vs. COVID-19-positive model had an AUC of 98%, and 92% on the internal and external test sets, respectively. Our study illustrates the potentials of machine-learning models for accurately distinguishing the two viral infections. The code is made available at https//github.com/ynaveena/COVID-19-vs-Influenza and may be have utility as a frontline diagnostic tool to aid healthcare workers in triaging patients once the two viral infections start cocirculating in the communities.
The SARS-CoV-2 virus has infected millions of people, overwhelming critical care resources in some regions. Many plans for rationing critical care resources during crises are based on the Sequential Organ Failure Assessment (SOFA) score. The COVID-19 pandemic created an emergent need to develop and validate a novel electronic health record (EHR)-computable tool to predict mortality.

To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon SOFA.

We conducted a prospective cohort study of a regional health system with 12 hospitals in Colorado between March 2020 and July 2020. All patients >14 years old hospitalized during the study period without a do not resuscitate order were included. Patients were stratified by the diagnosis of COVID-19. From this cohort, we developed and validated a model using stacked generalization to predict mortality using data widely available in the EHR by combining five previously validated scores and additio and SOFA scores predicted all-cause mortality with AUROCs of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94.Interpretation A novel EHR-based mortality score can be rapidly implemented to better predict patient outcomes during an evolving pandemic.Pandemic SARS-CoV-2 causes a mild to severe respiratory disease called Coronavirus Disease 2019 (COVID-19). Control of SARS-CoV-2 spread will depend on vaccine-induced or naturally acquired protective herd immunity. Until then, antiviral strategies are needed to manage COVID-19, but approved antiviral treatments, such as remdesivir, can only be delivered intravenously. Enisamium (laboratory code FAV00A, trade name Amizon®) is an orally active inhibitor of influenza A and B viruses in cell culture and clinically approved in countries of the Commonwealth of Independent States. Here we show that enisamium can inhibit SARS-CoV-2 infections in NHBE and Caco-2 cells. In vitro , the previously identified enisamium metabolite VR17-04 directly inhibits the activity of the SARS-CoV-2 RNA polymerase. Docking and molecular dynamics simulations suggest that VR17-04 prevents GTP and UTP incorporation. To confirm enisamium's antiviral properties, we conducted a double-blind, randomized, placebo-controlled trial in adult, hon prevent SARS-CoV-2 replication and that its metabolite VR17-04 can inhibit the SARS-CoV-2 RNA polymerase
. Moreover, we find that COVID-19 patients requiring supplementary oxygen, recover more quickly than patients treated with a placebo. Enisamium may therefore be an accessible treatment for COVID-19 patients.
SARS-CoV-2 is the causative agent of COVID-19. Although vaccines are now becoming available to prevent SARS-CoV-2 spread, the development of antivirals remains necessary for treating current COVID-19 patients and combating future coronavirus outbreaks. Here, we report that enisamium, which can be administered orally, can prevent SARS-CoV-2 replication and that its metabolite VR17-04 can inhibit the SARS-CoV-2 RNA polymerase in vitro . Moreover, we find that COVID-19 patients requiring supplementary oxygen, recover more quickly than patients treated with a placebo. Enisamium may therefore be an accessible treatment for COVID-19 patients.As three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find thang, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality -measured either by direct COVID-19 attributed deaths or excess deaths- and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.Multiple studies have demonstrated the negative impact of cancer care delays during the COVID-19 pandemic, and transmission mitigation techniques are imperative for continued cancer care delivery. To gauge the effectiveness of these measures at the University of Pennsylvania, we conducted a longitudinal study of SARS-CoV-2 antibody seropositivity and seroconversion in patients presenting to infusion centers for cancer-directed therapy between 5/21/2020 and 10/8/2020. Participants completed questionnaires and had up to five serial blood collections. Of 124 enrolled patients, only two (1.6%) had detectable SARS-CoV-2 antibodies on initial blood draw, and no initially seronegative patients developed newly detectable antibodies on subsequent blood draw(s), corresponding to a seroconversion rate of 0% (95%CI 0.0-4.1%) over 14.8 person-years of follow up, with a median of 13 healthcare visits per patient. These results suggest that cancer patients receiving in-person care at a facility with aggressive mitigation efforts have an extremely low likelihood of COVID-19 infection.
Neurological complications occur in COVID-19. We aimed to examine cerebrospinal fluid (CSF) of COVID-19 subjects with neurological complications and determine presence of neuroinflammatory changes implicated in pathogenesis.

Cross-sectional study of CSF neuroinflammatory profiles from 18 COVID-19 subjects with neurological complications categorized by diagnosis (stroke, encephalopathy, headache) and illness severity (critical, severe, moderate, mild). COVID-19 CSF was compared with CSF from healthy, infectious and neuroinflammatory disorders and stroke controls (n=82). Cytokines (IL-6, TNFα, IFNγ, IL-10, IL-12p70, IL-17A), inflammation and coagulation markers (high-sensitivity-C Reactive Protein [hsCRP], ferritin, fibrinogen, D-dimer, Factor VIII) and neurofilament light chain (NF-L), were quantified. SARS-CoV2 RNA and SARS-CoV2 IgG and IgA antibodies in CSF were tested with RT-PCR and ELISA.

CSF from COVID-19 subjects showed a paucity of neuroinflammatory changes, absence of pleocytosis or specific incnd for Neuroimmunology Research.
Thrombotic complications occur at high rates in hospitalized patients with COVID-19, yet the impact of intensive antithrombotic therapy on mortality is uncertain.

How does in-hospital mortality compare with intermediate-versus prophylactic-dose anticoagulation, and separately with in-hospital aspirin versus no antiplatelet therapy, in treatment of COVID-19?

Using data from 2785 hospitalized adult COVID-19 patients, we established two separate, nested cohorts of patients (1) who received intermediate- or prophylactic-dose anticoagulation ("anticoagulation cohort", N = 1624), or (2) who were not on home antiplatelet therapy and received either in-hospital aspirin or no antiplatelet therapy ("aspirin cohort", N = 1956). Propensity score matching utilizing various markers of illness severity and other patient-specific covariates yielded treatment groups with well-balanced covariates in each cohort. The primary outcome was cumulative incidence of in-hospital death.

Among propensity score-matched patients in the anticoagulation cohort (N = 382), in a multivariable regression model, intermediate-compared to prophylactic-dose anticoagulation was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.518 [0.308-0.872]). Among propensity-score matched patients in the aspirin cohort (N = 638), in a multivariable regression model, in-hospital aspirin compared to no antiplatelet therapy was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.522 [0.336-0.812]).

In this propensity score-matched, observational study of COVID-19, intermediate-dose anticoagulation and aspirin were each associated with a lower cumulative incidence of in-hospital death.

No conflict of interest exists for any author on this manuscript.
No conflict of interest exists for any author on this manuscript.Herein we measured CD4 + T cell responses against common cold corona (CCC) viruses and SARS-CoV-2 in high-risk health care workers (HCW) and community controls. We observed higher levels of CCC reactive T cells in SARS-CoV-2 seronegative HCW compared to community donors, consistent with potential higher occupational exposure of HCW to CCC. We further show that SARS-CoV-2 reactivity of seronegative HCW was higher than community controls and correlation between CCC and SARS-CoV-2 responses is consistent with cross-reactivity and not associated with recent in vivo activation. Surprisingly, CCC reactivity was decreased in SARS-CoV-2 infected HCW, suggesting that exposure to SARS-CoV-2 might interfere with CCC responses, either directly or indirectly. This result was unexpected, but consistently detected in independent cohorts derived from Miami and San Diego.
Severe community-acquired pneumonia secondary to SARS-CoV-2 is a leading cause of death. Current guidelines recommend patients with SARS-CoV-2 pneumonia receive empirical antibiotic therapy for suspected bacterial superinfection, but little evidence supports these recommendations.

We obtained bronchoscopic bronchoalveolar lavage (BAL) samples from patients with SARS-CoV-2 pneumonia requiring mechanical ventilation. We analyzed BAL samples with multiplex PCR and quantitative culture to determine the prevalence of superinfecting pathogens at the time of intubation and identify episodes of ventilator-associated pneumonia (VAP) over the course of mechanical ventilation. We compared antibiotic use with guideline-recommended care.

The 179 ventilated patients with severe SARS-CoV-2 pneumonia discharged from our hospital by June 30, 2020 were analyzed. 162 (90.5%) patients had at least one BAL procedure; 133 (74.3%) within 48 hours after intubation and 112 (62.6%) had at least one subsequent BAL during their hobstantial antibiotic overuse. The incidence rate of VAP in ventilated patients with SARS-CoV-2 pneumonia are higher than historically reported.
The majority of U.S. reports of COVID-19 clinical characteristics, disease course, and treatments are from single health systems or focused on one domain. Here we report the creation of the National COVID Cohort Collaborative (N3C), a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative U.S. cohort of COVID-19 cases and controls to date. This multi-center dataset supports robust evidence-based development of predictive and diagnostic tools and informs critical care and policy.

In a retrospective cohort study of 1,926,526 patients from 34 medical centers nationwide, we stratified patients using a World Health Organization COVID-19 severity scale and demographics; we then evaluated differences between groups over time using multivariable logistic regression. We established vital signs and laboratory values among COVID-19 patients with different severities, providing the foundation for predictive analytics. The cohort included 174,568 adults w disease.
This is the first description of an ongoing longitudinal observational study of patients seen in diverse clinical settings and geographical regions and is the largest COVID-19 cohort in the United States. Such data are the foundation for ML models that can be the basis for generalizable clinical decision support tools. The N3C Data Enclave is unique in providing transparent, reproducible, easily shared, versioned, and fully auditable data and analytic provenance for national-scale patient-level EHR data. The N3C is built for intensive ML analyses by academic, industry, and citizen scientists internationally. Many observational correlations can inform trial designs and care guidelines for this new disease.A fast-spreading SARS-CoV-2 variant identified in the United Kingdom in December 2020 has raised international alarm. We estimate that, in 16 out of 19 countries analyzed, there is at least a 50% chance the variant was imported by travelers from the United Kingdom byDecember 7th.
The new variant COVID-19 has likely been introduced by travelers from the UK and spreading undetected for months in many countries.
The new variant COVID-19 has likely been introduced by travelers from the UK and spreading undetected for months in many countries.Most COVID-19 vaccines require two doses, and current vaccine prioritization guidelines for COVID-19 vaccines assume full-dose vaccine deployment. However in the context of limited vaccine supply and an expanding pandemic, policymakers are considering single-dose vaccination as an alternative strategy. Using a mathematical model combined with optimization algorithms, we determined the optimal allocation with one and two doses of vaccine to minimize five metrics of disease burden under various degrees of viral transmission. Under low transmission, we show that the optimal allocation of vaccine critically depends on the level of single-dose efficacy (SDE). If the SDE is high, single-dose vaccination is optimal, preventing up to 36% more deaths than a strategy prioritizing full-dose vaccination for older adults first. With low or moderate SDE, mixed vaccination campaigns with coverage of all older adults with one dose are optimal. However, with modest or high transmission, vaccinating older adults first with two doses is best, preventing up to 41% more deaths than a single-dose vaccination given across all populations. Further, we show that maintaining social distancing interventions and speedy deployment are key for effective vaccination campaigns. Our work suggests that it is imperative to determine the efficacy and durability of single-dose vaccines, as mixed or single-dose vaccination campaigns may have the potential to contain the pandemic much more quickly.The COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G→U and C→U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e., they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. While previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite.SARS-CoV-2 entry into host cells is orchestrated by the spike (S) glycoprotein that contains an immunodominant receptor-binding domain (RBD) targeted by the largest fraction of neutralizing antibodies (Abs) in COVID-19 patient plasma. Little is known about neutralizing Abs binding to epitopes outside the RBD and their contribution to protection. Here, we describe 41 human monoclonal Abs (mAbs) derived from memory B cells, which recognize the SARS-CoV-2 S N-terminal domain (NTD) and show that a subset of them neutralize SARS-CoV-2 ultrapotently. We define an antigenic map of the SARS-CoV-2 NTD and identify a supersite recognized by all known NTD-specific neutralizing mAbs. These mAbs inhibit cell-to-cell fusion, activate effector functions, and protect Syrian hamsters from SARS-CoV-2 challenge. SARS-CoV-2 variants, including the 501Y.V2 and B.1.1.7 lineages, harbor frequent mutations localized in the NTD supersite suggesting ongoing selective pressure and the importance of NTD-specific neutralizing mAbs to protective immunity.SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) hospitalizations and deaths disportionally affect males and the elderly. Here we investigated the impact of male sex and age by infecting adult male, aged male, and adult female ferrets with SARS-CoV-2. Aged male ferrets had a decrease in temperature which was accompanied by prolonged viral replication with increased pathology in the upper respiratory tract after infection. Transcriptome analysis of the nasal turbinates and lungs indicated that female ferrets had significant increases in interferon response genes (OASL, MX1, ISG15, etc.) on day 2 post infection which was delayed in aged males. In addition, genes associated with taste and smell such as RTP1, CHGA, and CHGA1 at later time points were upregulated in males but not in females. These results provide insight into COVID-19 and suggests that older males may play a role in viral transmission due to decreased antiviral responses.Acute respiratory distress syndrome (ARDS) occurred in ~12% of hospitalized COVID-19 patients in a recent New York City cohort. Pulmonary endothelial dysfunction, characterized by increased expression of inflammatory genes and increased monolayer permeability, is a major component of ARDS. Vascular leak results in parenchymal accumulation of leukocytes, protein, and extravascular water, leading to pulmonary edema, ischemia, and activation of coagulation associated with COVID-19. Endothelial inflammation further contributes to uncontrolled cytokine storm in ARDS. We have recently demonstrated that Kruppel-like factor 2 (KLF2), a transcription factor which promotes endothelial quiescence and monolayer integrity, is significantly reduced in experimental models of ARDS. Lung inflammation and high-tidal volume ventilation result in reduced KLF2, leading to pulmonary endothelial dysfunction and acute lung injury. Mechanistically, we found that KLF2 is a potent transcriptional activator of Rap guanine nucleotide exchange factor 3 (RAPGEF3) which orchestrates and maintains vascular integrity. Moreover, KLF2 regulates multiple genome-wide association study (GWAS)-implicated ARDS genes. Whether lung KLF2 is regulated by SARS-CoV-2 infection is unknown. Here we report that endothelial KLF2 is significantly reduced in human lung autopsies from COVID-19 patients, which supports that ARDS due to SARS-CoV-2 is a vascular phenotype possibly attributed to KLF2 down-regulation. We provide additional data demonstrating that KLF2 is down-regulated in SARS-CoV infection in mice.The SARS-CoV-2 pandemic has spread at an unprecedented rate, and repurposing opportunities have been intensively studied with only limited success to date. If successful, repurposing will allow interventions to become more rapidly available than development of new chemical entities. Niclosamide has been proposed as a candidate for repurposing for SARS-CoV-2 based upon the observation that it is amongst the most potent antiviral molecules evaluated in vitro . To investigate the pharmacokinetics of niclosamide, reliable, reproducible and sensitive bioanalytical assays are required. Here, a liquid chromatography tandem mass spectrometry assay is presented which was linear from 31.25-2000 ng/mL (high dynamic range) and 0.78-100 ng/mL (low dynamic range). Accuracy and precision ranged between 97.2% and 112.5%, 100.4% and 110.0%, respectively. The presented assay should have utility in preclinical evaluation of the exposure-response relationship and may be adapted for later evaluation of niclosamide in clinical trials.Monoclonal antibodies (mAbs) are the basis of treatments and diagnostics for pathogens and other biological phenomena. We conducted a structural characterization of mAbs against the N-terminal domain of nucleocapsid protein (NP NTD ) from SARS-CoV-2 using small angle X-ray scattering (SAXS). Our solution-based results distinguished the mAbs' flexibility and how this flexibility impacts the assembly of multiple mAbs on an antigen. By pairing two mAbs that bind different epitopes on the NP NTD , we show that flexible mAbs form a closed sandwich-like complex. With rigid mAbs, a juxtaposition of the Fabs is prevented, enforcing a linear arrangement of the mAb pair, which facilitates further mAb polymerization. In a modified sandwich ELISA, we show the rigid mAb-pairings with linear polymerization led to increased NP NTD detection sensitivity. These enhancements can expedite the development of more sensitive and selective antigen-detecting point-of-care lateral flow devices (LFA), key for early diagnosis and epidemiological studies of SARS-CoV-2 and other pathogens.COVID-19 ARDS is associated with prolonged ventilator dependence and high mortality, but the underlying mechanisms are unknown. Critical to the pathogenesis of ARDS is injury to the alveolar epithelial cell (AEC) barrier; clinical recovery requires epithelial regeneration. We previously identified a KRT8 hi transitional state that regenerating AEC2s adopt during differentiation into AEC1s, the persistence of which may be pathogenic in pulmonary fibrosis. Here, we hypothesize that ineffectual differentiation of transitional cells into AEC1s without fibrosis may perpetuate barrier permeability and poor clinical outcomes in COVID-19 ARDS. To test this hypothesis, we examined postmortem lung tissue of COVID-19 ARDS patients. We observed extensive AEC1 injury, rare mature AEC2s, and abundant transitional cells. Transitional cells were cuboidal, partially spread or, rarely, flat but did not express AEC1 markers. They formed monolayers on alveolar septa denuded of AEC1s but structurally normal without fibrosis. We conclude that ineffectual AEC1 differentiation from transitional AECs may perpetuate barrier permeability and respiratory failure in COVID-19 ARDS. In contrast to fibrosis, transitional AECs may retain the capacity for physiologic AEC1 regeneration with restoration of normal alveolar architecture and function. Novel therapies to promote AEC1 differentiation from transitional cells may accelerate barrier restitution and clinical recovery in ARDS.Acute lung immunity to inhaled pathogens elicits defensive pneumonitis that may convert to the Acute Respiratory Distress Syndrome (ARDS), causing high mortality. Mechanisms underlying the conversion are not understood, but are of intense interest because of the ARDS-induced mortality in the ongoing Covid-19 pandemic. Here, by optical imaging of live lungs we show that key to the lethality is the functional status of mitochondrial Ca2+ buffering across the mitochondrial Ca2+ uniporter (MCU) in the alveolar type 2 cells (AT2), which protect alveolar stability. In mice subjected to ARDS by airway exposure to lipopolysaccharide (LPS), or to Pseudomonas aeruginosa, there was marked loss of MCU expression in AT2. The ability of mice to survive ARDS depended on the extent to which the MCU expression recovered, indicating that the viability of Ca2+ buffering by AT2 mitochondria critically determines ARDS severity. Mitochondrial transfer to enhance AT2 MCU expression might protect against ARDS.Animal models recapitulating the distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. However, the cause(s) and mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate inflammation in the lungs, lethality was invariably associated with viral neuroinvasion and neuronal damage (including spinal motor neurons). Neuroinvasion occurred following virus transport through the olfactory neuroepithelium in a manner that was only partially dependent on hACE2. Interestingly, SARS-CoV-2 tropism was overall neither widespread among nor restricted to only ACE2-expressing cells. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis.
COVID-19 is a respiratory disease caused by SARS-CoV-2, a betacoronavirus. Here, we show that in a widely used transgenic mouse model of COVID-19, lethality is invariably associated with viral neuroinvasion and the ensuing neuronal disease, while lung inflammation remains moderate.
COVID-19 is a respiratory disease caused by SARS-CoV-2, a betacoronavirus. Here, we show that in a widely used transgenic mouse model of COVID-19, lethality is invariably associated with viral neuroinvasion and the ensuing neuronal disease, while lung inflammation remains moderate.Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly contagious presenting a significant public health issue. Current therapies used to treat coronavirus disease 2019 (COVID-19) include monoclonal antibody cocktail, convalescent plasma, antivirals, immunomodulators, and anticoagulants, though the current therapeutic options remain limited and expensive. The vaccines from Pfizer and Moderna have recently been authorized for emergency use, which are invaluable for the prevention of SARS-CoV-2 infection. However, their long-term side effects are not yet to be documented, and populations with immunocompromised conditions (e.g., organ-transplantation and immunodeficient patients) may not be able to mount an effective immune response. In addition, there are concerns that wide-scale immunity to SARS-CoV-2 may introduce immune pressure that could select for escape mutants to the existing vaccines and monoclonal antibody therapies. Emerging evidence has shown that chimeric antigen receptor (CAR)- nat pave the way for generating 'off-the-shelf' S309-CAR-NK cells for treatment in high-risk individuals as well as provide an alternative strategy for patients unresponsive to current vaccines.The exact mechanism of coronavirus replication and transcription is not fully understood; however, a hallmark of coronavirus transcription is the generation of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and an array of subgenomic mRNAs (sgRNAs) encompassing sequences arising from discontinuous transcription. Existing PCR-based diagnostic assays for SAR-CoV-2 are qualitative or semi-quantitative and do not provide the resolution needed to assess the complex transcription dynamics of SARS-CoV-2 over the course of infection. We developed and validated a novel panel of specially designed SARS-CoV-2 ddPCR-based assays to map the viral transcription profile. Application of these assays to clinically relevant samples will enhance our understanding of SARS-CoV-2 replication and transcription and may also inform the development of improved diagnostic tools and therapeutics.
We developed a novel panel of 7 quantitative RT-ddPCRs assays for SARS-Cov-2Our panel targets nongenic and genic regions in genomic and subgenomic RNAsAll assays detect 1-10 copies and are linear over 3-4 orders of magnitudeAll assays correlated with the clinical Abbott SARS-CoV-2 Viral Load AssayClinical samples showed higher copy numbers for targets at the 3' end of the genome.
We developed a novel panel of 7 quantitative RT-ddPCRs assays for SARS-Cov-2Our panel targets nongenic and genic regions in genomic and subgenomic RNAsAll assays detect 1-10 copies and are linear over 3-4 orders of magnitudeAll assays correlated with the clinical Abbott SARS-CoV-2 Viral Load AssayClinical samples showed higher copy numbers for targets at the 3' end of the genome.Droplet digital PCR provides superior accuracy in nucleic acid quantitation. The requirement of microfluidics to generate and analyze the emulsions, however, is a barrier to its adoption, particularly in low resource or clinical settings. Here, we report a novel method to prepare ddPCR droplets by vortexing and readout the results by bulk analysis of recovered amplicons. We demonstrate the approach by accurately quantitating SARS-CoV-2 sequences using entirely bulk processing and no microfluidics. Our approach for quantitating reactions should extend to all digital assays that generate amplicons, including digital PCR and LAMP conducted in droplets, microchambers, or nanoliter wells. More broadly, our approach combines important attributes of ddPCR, including enhanced accuracy and robustness to inhibition, with the high-volume sample processing ability of quantitative PCR.The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) readily infects a variety of cell types impacting the function of vital organ systems, with particularly severe impact on respiratory function. It proves fatal for one percent of those infected. Neurological symptoms, which range in severity, accompany a significant proportion of COVID-19 cases, indicating a potential vulnerability of neural cell types. To assess whether human cortical cells can be directly infected by SARS-CoV-2, we utilized primary human cortical tissue and stem cell-derived cortical organoids. We find significant and predominant infection in cortical astrocytes in both primary and organoid cultures, with minimal infection of other cortical populations. Infected astrocytes had a corresponding increase in reactivity characteristics, growth factor signaling, and cellular stress. Although human cortical cells, including astrocytes, have minimal ACE2 expression, we find high levels of alternative coronavirus receptors in infected astrocytes, including DPP4 and CD147. Inhibition of DPP4 reduced infection and decreased expression of the cell stress marker, ARCN1. We find tropism of SARS-CoV-2 for human astrocytes mediated by DPP4, resulting in reactive gliosis-type injury.Rapidly spreading variants of SARS-CoV-2 that have arisen in the United Kingdom and South Africa share the spike N501Y substitution, which is of particular concern because it is located in the viral receptor binding site for cell entry and increases binding to the receptor. We generated isogenic N501 and Y501 SARS-CoV-2. Twenty human sera from the mRNA-based vaccine BNT162b2 trial exhibited equivalent neutralizing titers to the N501 and Y501 viruses.Background The unprecedented outbreak of a contagious respiratory disease caused by a novel coronavirus has led to a pandemic since December 2019, claiming millions of lives. The study systematically reviews and summarizes COVID-19's impact based on symptoms, demographics, comorbidities, and demonstrates the association of demographics in cases and mortality in the United States.Methods PubMed and Google Scholar were searched from December 2019- August 2020, and articles restricted to the English language were collected following PRISMA guidelines. US CDC data was used for establishing statistical significance of age, sex, and race.Results• Among 3745 patients in China, mean age is 50.63 (95% CI 36.84, 64.42) years, and 55.7 % (95% CI 52.2, 59.2) were males. Symptoms included fever 86.5% (82.7, 90.0), fatigue 41.9% (32.7, 51.4), dyspnea 29.0% (21.2, 37.5), cough 66.0% (61.3, 70.6), mucus 66% (61.3, 70.6), lymphopenia 18.9% (5.2, 38.0). Prevalent comorbidities were hypertension 16.4% (12.5, 20.8), diabetes 8.9g the recent FDA's guidance for designing Covid-19 vaccine trials, stratification factors of age, race, sex, and comorbidities need consideration in allocation. This study aimed to provide clinical researchers, health policy planners a detailed insight into the coronavirus disease.The 2019 coronavirus (COVID-19) pandemic has made the world seem unpredictable. During such crises we can experience concerns that others might be against us, culminating perhaps in paranoid conspiracy theories. Here, we investigate paranoia and belief updating in an online sample (N=1,010) in the United States of America (U.S.A). We demonstrate the pandemic increased individuals' self-rated paranoia and rendered their task-based belief updating more erratic. Local lockdown and reopening policies, as well as culture more broadly, markedly influenced participants' belief-updating an early and sustained lockdown rendered people's belief updating less capricious. Masks are clearly an effective public health measure against COVID-19. However, state-mandated mask wearing increased paranoia and induced more erratic behaviour. Remarkably, this was most evident in those states where adherence to mask wearing rules was poor but where rule following is typically more common. This paranoia may explain the lack of compliance with this simple and effective countermeasure. Computational analyses of participant behaviour suggested that people with higher paranoia expected the task to be more unstable, but at the same time predicted more rewards. In a follow-up study we found people who were more paranoid endorsed conspiracies about mask-wearing and potential vaccines - again, mask attitude and conspiratorial beliefs were associated with erratic task behaviour and changed priors. Future public health responses to the pandemic might leverage these observations, mollifying paranoia and increasing adherence by tempering people's expectations of other's behaviour, and the environment more broadly, and reinforcing compliance.We performed comparative lower respiratory tract transcriptional profiling of 52 critically ill patients with the acute respiratory distress syndrome (ARDS) from COVID-19 or from other etiologies, as well as controls without ARDS. In contrast to a cytokine storm, we observed reduced proinflammatory gene expression in COVID-19 ARDS when compared to ARDS due to other causes. COVID-19 ARDS was characterized by a dysregulated host response with increased PTEN signaling and elevated expression of genes with non-canonical roles in inflammation and immunity that were predicted to be modulated by dexamethasone and granulocyte colony stimulating factor. Compared to ARDS due to other types of viral pneumonia, COVID-19 was characterized by impaired interferon-stimulated gene expression (ISG). We found that the relationship between SARS-CoV-2 viral load and expression of ISGs was decoupled in patients with COVID-19 ARDS when compared to patients with mild COVID-19. In summary, assessment of host gene expression in the lower airways of patients with COVID-19 ARDS did not demonstrate cytokine storm but instead revealed a unique and dysregulated host response predicted to be modified by dexamethasone.The COVID-19 pandemic has become an immense global health crisis. However, the lack of efficient and sensitive on-site testing methods limits early detection for timely isolation and intervention. Here, we present a Quantitative and Ultrasensitive in-situ Immunoassay Technology for SARS-CoV-2 detection in saliva (QUIT SARS-CoV-2). Our nanoporous membrane resonator generates a rapid oscillating flow to purify and concentrate SARS-CoV-2 virus in saliva by 40 folds for in-situ detection of viral antigens based on chemiluminescent immunoassay within 20 min. This method achieved a detection sensitivity below 10 0 copies/mL viral load, comparable to the bench-top PCR equipment. The portable QUIT SARS-CoV-2 system, allowing rapid and accurate on-site viral screen with high-throughput sample pooling strategy, can be performed at the primary care settings and substantially improve the detection and prevention of COVID-19.Background In March 2020, the COVID-19 pandemic led to a national lockdown and quarantine in Italy. The aim of this study was to assess the perceived change in anxiety levels and its predictors in a non-clinical, non-infected, home-quarantined Italian sample in the very first weeks of the lockdown. Methods Online survey data on perceived change in anxiety symptoms since the beginning of the lockdown, health anxiety, social anxiety, depression, and obsessive-compulsive symptomatology before the lockdown, and background information were anonymously collected between March 26 and April 9 2020 on 660 Italian participants. Results Overall, participants reported a substantial increase of anxiety levels. Women reported more increased levels of anxiety symptoms than men. Increase of anxiety was also predicted by higher pre-existing levels of health anxiety and lower socio-economic status. Having lost the job was not associated with a perceived change in anxiety levels. Limitations Crosssectional design; sample of mostly female, young, highly educated, and not infected participants; use of self-report measures. Conclusions The results suggest the need to address mental health issues as a core element of the response to a pandemic, in order to prevent long-term social, psychological, and economic costs to society.The ongoing COVID-19 pandemic has infected millions of people, claimed hundreds of thousands of lives, and made a worldwide health emergency. Understanding the SARS-CoV-2 mechanism of infection is crucial in the development of potential therapeutics and vaccines. The infection process is triggered by direct binding of the SARS-CoV-2 receptor-binding domain (RBD) to the host cell receptor, Angiotensin-converting enzyme 2 (ACE2). Many efforts have been made to design or repurpose therapeutics to deactivate RBD or ACE2 and prevent the initial binding. In addition to direct inhibition strategies, small chemical compounds might be able to interfere and destabilize the meta-stable, pre-fusion complex of ACE2-RBD. This approach can be employed to prevent the further progress of virus infection at its early stages. In this study, Molecular docking is employed to analyze the binding of two chemical compounds, SSAA09E2 and Nilotinib, with the druggable pocket of the ACE2-RBD complex. The structural changes as a result of the interference with the ACE2-RBD complex are analyzed by molecular dynamics simulations. Results show that both Nilotinib and SSAA09E2 can induce significant conformational changes in the ACE2-RBD complex, intervene with the hydrogen bonds, and influence the flexibility of proteins. Moreover, essential dynamics analysis suggests that the presence of small molecules can trigger large-scale conformational changes that may destabilize the ACE2-RBD complex.Severe cases of coronavirus disease 2019 (COVID-19), caused by infection with SARS-Cov-2, are characterized by a hyperinflammatory immune response that leads to numerous complications. Production of proinflammatory neutrophil extracellular traps (NETs) has been suggested to be a key factor in inducing a hyperinflammatory signaling cascade, allegedly causing both pulmonary tissue damage and peripheral inflammation. Accordingly, therapeutic blockage of neutrophil activation and NETosis, the cell death pathway accompanying NET formation, could limit respiratory damage and death from severe COVID-19. Here, we demonstrate that synthetic glycopolymers that activate the neutrophil checkpoint receptor Siglec-9 suppress NETosis induced by agonists of viral toll-like receptors (TLRs) and plasma from patients with severe COVID-19. Thus, Siglec-9 agonism is a promising therapeutic strategy to curb neutrophilic hyperinflammation in COVID-19..Lynch syndrome (LS) is a hereditary cancer syndrome characterized by an increased risk of multiple cancers, predominantly endometrial and colorectal, at a younger age (typically less then 50). In prior research, high death anxiety and a lack of provider-initiated communication about advance care planning (ACP) have been shown to decrease a patient's likelihood of having advance directives. Providers often have gaps in knowledge and are uncomfortable with these conversations. We used a mixed methods approach (quantitative survey with a follow-up telephone interview) to assess knowledge, preferences, and attitudes regarding ACP in individuals with LS (n = 20). This study also assessed which ACP documents individuals already had in place and which persons (providers, family, or friends) an individual made aware of the documentation and/or preferences. These data were analyzed to determine patient preferences for who is responsible for initiating these conversations, identify motivating factors and barriers to these conversations, and determine whether the current conversations are adequate to meet the needs of this patient population. Participants recognized the importance of ACP and expressed interest in creating these documents. However, knowledge and confidence about these topics were lacking, with many participants attributing this to their young age and lack of experience. Although uncomfortable, many patients want to have ACP discussions with their providers, but frequently patients were only asked if these documents are completed with no further discussion. These findings can inform educational efforts to improve knowledge of ACP and interventional research to increase use of ACP by individuals with LS.Because most cases of coronavirus disease 2019 (COVID-19) are not severe, understanding the epidemiology of mild cases has important clinical implications. We aimed to describe the symptom profile and associated outcomes in a virtual outpatient COVID-19 clinic. We conducted a prospective cohort study from March through June 2020. We included 106 patients with positive results for SARS-CoV-2, followed up until they had 2 sequential negative tests. Exploratory regression analyses identified potential prognostic symptoms or risk factors associated with outcomes, including emergency department (ED) visits, hospitalizations, and time to resolution of viral shedding. The mean (range) patient age was 51 (18-86) years, 50% were men, and 36.5% had at least 1 risk factor, most commonly asthma (16%) and diabetes (10%). Most patients (98.1%) had symptoms-cough (80.4%), fatigue (67.6%), fever (66.0%), headache (49.0%), and ageusia (46.9%). Nine (8.5%) patients were admitted to the ED, 5 (4.7%) were hospitalized, and none died. Asthma (RR = 7.13, P = .001) and being immunocompromised (RR = 3.44, P = .03) were associated with higher risks of adverse outcomes. Asthma (HR = 0.56, P = .04) and early symptoms of ageusia (HR= 0.50, P = .01) or myalgia (HR = 0.63, P = .04) were associated with significantly longer duration of viral shedding. In contrast to reports about severe cases of COVID-19, we found a higher incidence of sinus symptoms, gastrointestinal symptoms, and myalgia and a lower incidence of fever, anosmia, and ageusia among our mild/moderate cases. Asthma and immunocompromised status were associated with adverse outcomes, and asthma and early symptoms of ageusia or myalgia with significantly longer duration of viral shedding.Autoimmune hemolytic anemia (AIHA) is increasingly recognized as a strong risk factor for venous thrombosis. However, there are currently no guidelines on thromboembolism prevention and management during AIHA. Here, we describe the case of a patient with AIHA and pulmonary embolism and resume the current knowledge on epidemiology, risk factors, treatment, and pathophysiology of thrombosis during AIHA, as well as new therapeutic perspectives to prevent thrombus formation during AIHA.Background  Coronavirus disease 2019 (COVID-19) has evolved as a pandemic of unimaginable magnitude. The health care system is facing a tremendous challenge to provide ethical and quality care. The transformation of the patient-based care to population-based care during the COVID-19 pandemic has raised ethical dilemma among urologists. Our objective is to explore the consensus in modified standard urology care, that can be adopted and applied during COVID-19 and similar pandemic. Methods  We adopted an exploratory study design using secondary data. The data were extracted from a web-based medical library using keywords "COVID-19," "severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)," and "urology." We identify and extrapolate (screening, eligibility, and inclusion) the data using PRISMA protocol, and summarize pandemic standard urology care under four main themes (1) general urology care, (2) choice of surgical modality, (3) triage, and (4) urology training. Result  We identified 63 academic papers and dynamics of the pandemic.In response to a mandate to advance human rights through social work education, this article focuses on the curricular redesign and program evaluation of one MSW Program. The program's specialization focused on advanced social work practice with individuals, families, and communities grounded in social justice and human rights. A pre-experimental one-group posttest-only program evaluation design was implemented. Multiple assessment instruments were used to measure human rights exposure in social work education, as well as a human rights lens and engagement in social work practice among 93 graduating MSW students from a public university with suburban and urban campus locations. How the program applied a human rights-based approach to social work field education will also be discussed. Findings suggest that a human rights exposure in course work and practicum is related to students' practice lens and engagement. The imperative is now to train social work students to address complex social issues through human rights exposure, engagement, and lens as we prepare for a post-pandemic world. Recommendations are provided to strengthen academic leadership and research in this area and empower students to drive a paradigm shift in the profession.A new paediatric multisystem inflammatory syndrome, linked to SARS-CoV-2 (MIS-Paed), has been described. The clinical picture is variable and is associated with an active or recent infection due to SARS-CoV-2. A review of the existing literature by a multidisciplinary group of paediatric specialists is presented in this document. Later, they make recommendations on the stabilisation, diagnosis, and treatment of this syndrome.The rapid spread of COVID-19 cases in recent months has strained hospital resources, making rapid and accurate triage of patients presenting to emergency departments a necessity. Machine learning techniques using clinical data such as chest X-rays have been used to predict which patients are most at risk of deterioration. We consider the task of predicting two types of patient deterioration based on chest X-rays adverse event deterioration (i.e., transfer to the intensive care unit, intubation, or mortality) and increased oxygen requirements beyond 6 L per day. Due to the relative scarcity of COVID-19 patient data, existing solutions leverage supervised pretraining on related non-COVID images, but this is limited by the differences between the pretraining data and the target COVID-19 patient data. In this paper, we use self-supervised learning based on the momentum contrast (MoCo) method in the pretraining phase to learn more general image representations to use for downstream tasks. We present three results. The first is deterioration prediction from a single image, where our model achieves an area under receiver operating characteristic curve (AUC) of 0.742 for predicting an adverse event within 96 hours (compared to 0.703 with supervised pretraining) and an AUC of 0.765 for predicting oxygen requirements greater than 6 L a day at 24 hours (compared to 0.749 with supervised pretraining). We then propose a new transformer-based architecture that can process sequences of multiple images for prediction and show that this model can achieve an improved AUC of 0.786 for predicting an adverse event at 96 hours and an AUC of 0.848 for predicting mortalities at 96 hours. A small pilot clinical study suggested that the prediction accuracy of our model is comparable to that of experienced radiologists analyzing the same information.
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