Covid-19 Sentry

Contents

• From Preprints
• From Clinical Trials
• From PubMed
• From Patent Search

From Preprints

• Multi-ancestry GWAS of diarrhea during acute SARS-CoV2 infection identifies multiple novel loci and contrasting etiological roles of irritable bowel syndrome subtypes -

  A substantial proportion of acute SARSCoV2 infection cases exhibit gastrointestinal symptoms, yet the genetic determinants of these extrapulmonary manifestations are poorly understood. Using survey data from 239,866 individuals who tested positively for SARSCoV2, we conducted a multi-ancestry GWAS of 80,289 cases of diarrhea occurring during acute COVID19 infection (33.5%). Six loci (CYP7A1, LZFTl1/CCR9, TEME182, NALCN, LFNG, GCKR) met genomewide significance in a trans-ancestral analysis. The top significant GWAS hit mapped to the CYP7A1 locus, which plays an etiologic role in bile acid metabolism and is in high LD (r2= 0.93) with the SDCBP gene, which was previously implicated in antigen processing and presentation in the COVID-19 context. Another association was observed with variants in the LZTFL1/CCR9 region, which is a known locus for COVID19 susceptibility and severity. PheWAS showed a shared association across three of the six SNPs with irritable bowel syndrome (IBS) and its subtypes. Mendelian randomization showed that genetic liability to IBS-diarrhea increased (OR=1.40,95%,CI[1.33,1.47]), and liability to IBS-constipation decreased (OR=0.86, 95%CI[0.79,0.94]) the relative odds of experiencing COVID19+ diarrhea. Our genetic findings provide etiological insights into the extrapulmonary manifestations of acute SARSCoV2 infection.

  🖺 Full Text HTML: Multi-ancestry GWAS of diarrhea during acute SARS-CoV2 infection identifies multiple novel loci and contrasting etiological roles of irritable bowel syndrome subtypes
• Ready-To-Use Investigational Stem Cells, MiSaver, in Patients with Recent Acute Myocardial Infarction, 1 year follow up from a Phase 1 Safety Study -

  Abstract: Objectives: This study aimed to assess the safety and preliminary efficacy of MiSaver stem cells in enhancing left ventricular ejection function and functional activity among patients with acute myocardial infarction (AMI). Background: Cardiovascular diseases (CVDs) remain the leading cause of global mortality, with heart attacks and strokes accounting for a significant portion of deaths. Recovery of left ventricular ejection fraction (LVEF) post-myocardial infarction (MI) is crucial for prognosis, as patients with poor LVEF recovery face increased risks of sudden cardiac arrest events and mortality. Stem cell therapy offers regenerative potential for cardiovascular diseases, yet accessibility remains limited. This study investigates the safety and efficacy of MiSaver, a prefabricated stem cell investigational product, in recent AMI patients, aiming to enhance accessibility and patient outcomes. Methods: Patients admitted for AMI with reduced LVEF (≤45%) were eligible. MiSaver stem cells, matched for blood group, were administered to participants in cohorts of five, with escalating dosages (0.5x10^7, 1.6x10^7, and 5.0x10^7 cells/kg) 2-5 days post-AMI onset. Echocardiographic assessments were conducted upon admission, at 6 months, and at 12 months post-treatment. Results: Out of the initially planned 15 participants, eleven were enrolled in the study. The trial was halted prematurely due to challenges associated with the COVID-19 pandemic and impractical transportation logistics. During the 12-month follow-up period, no study-related adverse events or signs of graft-versus-host disease were reported. At 12 months post-treatment, both the low and middle dose groups, as well as participant 11, showed improved left ventricular ejection fraction (LVEF), accompanied by enhanced Canadian Cardiovascular Society (CCS) class grades compared to baseline. Conclusion: Intravenous infusion of MiSaver stem cells in AMI patients demonstrated safety and tolerability for low and middle dosage groups, suggesting potential for improving left ventricular function following AMI. However, further research with larger cohorts and controlled placebos is necessary to confirm these findings and address trial limitations encountered.

  🖺 Full Text HTML: Ready-To-Use Investigational Stem Cells, MiSaver, in Patients with Recent Acute Myocardial Infarction, 1 year follow up from a Phase 1 Safety Study
• Disease diagnostics using machine learning of immune receptors -
  Clinical diagnosis typically incorporates physical examination, patient history, and various laboratory tests and imaging studies, but makes limited use of the human system’s own record of antigen exposures encoded by receptors on B cells and T cells. We analyzed immune receptor datasets from 593 individuals to develop MAchine Learning for Immunological Diagnosis (Mal-ID), an interpretive framework to screen for multiple illnesses simultaneously or precisely test for one condition. This approach detects specific infections, autoimmune disorders, vaccine responses, and disease severity differences. Human-interpretable features of the model recapitulate known immune responses to SARS-CoV-2, Influenza, and HIV, highlight antigen-specific receptors, and reveal distinct characteristics of Systemic Lupus Erythematosus and Type-1 Diabetes autoreactivity. This analysis framework has broad potential for scientific and clinical interpretation of human immune responses.
  🖺 Full Text HTML: Disease diagnostics using machine learning of immune receptors
• How Long is the Worst Part of the COVID-19 Mortality Surge? -
  Objectives: Define and quantify the critical surge period of existing on-line COVID-19 mortality data; this could be instrumental to decision makers to determine how long health controls should be in place, and how long to expect the public health system to be in great stress. Create and share on-line, open-source software to continuously monitor critical surge periods in various communities as the data set grows. Test the critical surge period computational method on hierarchical data sets of various communities: a) globally; b) countrywide (states in the US); and c) statewide (counties/towns in the US states). Study Design: This was an open-source, on-line, COVID-19 data analytics development with support for web-browsers on any current mobile device. Methods: On-line, timely data for COVID-19 mortality was automatically retrieved by a developed application using the programming Python language and Jupyter electronic notebooks. An on-line, version-controlled code repository was created for the application and also used for providing an open execution environment for the research community. The data was fitted to a modified sigmoid function via an automated non- linear least-squares method. Three optimal parameters were computed and the critical times for the maximum and minimum curvatures of the function were used to obtain the critical surge period. The goodness of the fit was measured by a standard coefficient of determination, and alternatively, by direct pointwise relative error. Results: The software developed (a Python package) is called covid-surge (repository URL: htttps://github.com/dpploy/covid-surge) and available for download from PyPI on-line (URL: https://pypi.org/project/covid-surge/). Using covid-surge, the critical surge period was computed for the communities with the most evolved COVID-19 outbreak. At the time of this writing, the critical surge period was calculated for all countries with fully evolved mortality (12 out of 188) and found to be in average 23 days with 3 days of standard deviation. Similarly, for all states/districts in the US (20 out of 56), the computed average was 25 days with 3 days of standard deviation. Likewise, for the same states in the US, counties/towns that had fully evolved mortality surge (91 total out of 981 that had death cases) had the overall average of the surge period equal to 23 days with a standard deviation of 3 days. The accuracy of these results can be reproduced on-line using the software provided. In addition, forward results using newer data can also be generated by the research community using covid-surge. Conclusions: The surge period for hierarchical data including 12 countries, 20 US states, and 91 US counties/towns is remarkably similar: a 24-day period with 3-day standard deviation for all communities across many countries and the US. All of these communities were under similar COVID-19 controls, including social distancing, improved hygiene, and isolation which helps explain the constancy of the surge period. That is, these communities experienced nearly the same amount of time during the most stressful period of the mortality surge. Although the extent to which epidemic controls are applied can vary from community to community, this study shows that the variability of the surge period is small. As the COVID-19 sweeps over the continents, additional data will be available for fully-evolved communities and a later comparison can be made with covid-surge on-line. This study suggests that communities not yet fully affected by the COVID-19 mortality may expect a period of high stress on their public health system of about 30 days (lower bound). That is, health care organizations should plan to operate at full capacity for a minimum of 30 days.
  🖺 Full Text HTML: How Long is the Worst Part of the COVID-19 Mortality Surge?
• Solid-liquid partitioning of Dengue, West Nile, Zika, Hepatitis A, Influenza A, and SARS-CoV-2 viruses in wastewater from across the United States -
  Limited information is available on the fate of respiratory and arthropod-borne viruses in wastewater. Enteric viruses have been extensively studied in wastewater treatment plants, however partition coefficients have not been well documented. This information is essential for interpreting wastewater-based surveillance (WBS) data and optimizing sample collection and processing methods. In this study, we examined the solid-liquid partitioning behavior of Dengue, West Nile, Zika, Hepatitis A, Influenza A, and SARS-CoV-2 viruses in wastewater. Samples were collected from the primary sludge line of eleven wastewater treatment plants across the United States and spiked with varying concentrations of each virus. Solid and liquid fractions were separated via centrifugation. Viral nucleic acids were extracted and quantified using reverse-transcription digital droplet PCR (RT-ddPCR). Partition coefficients (KF), determined using the Freundlich adsorption model, ranged from 4.0✕10^2 mL/g to 3.9✕10^6 mL/g (median = 1.1✕10^4 mL/g). KF values were not significantly different between viruses. However, significant differences were observed between KF for Zika and West Nile Virus between wastewater treatment plants. Further research is needed to understand how wastewater characteristics might impact the partition of viral markers. The results from this experiment underscore the importance of considering wastewater solids for the early detection and monitoring of viral infectious diseases, particularly in regions with low prevalence of infections.
  🖺 Full Text HTML: Solid-liquid partitioning of Dengue, West Nile, Zika, Hepatitis A, Influenza A, and SARS-CoV-2 viruses in wastewater from across the United States
• COVerAGE-JP: COVID-19 Deaths by Age and Sex in Japan -
  This database (https://github.com/fumiyau/COVerAGE-JP) collects COVID-19 deaths by age, sex, date, and region in Japan. As with other causes of deaths, deaths related to COVID-19 are reported by local public health center (Hokenjo), which is located in every prefecture and major metropolitan/large cities. 47 prefectures and some metropolitan cities then collect the information about COVID-19 cases and deaths to report the Ministry of Health, Labour, and Welfare (MHLW). Although MHLW provides a summary statistics about the COVID-19 cases and deaths on their webpage, the distribution broken down by age and sex is not available, that leads many volunteering organizations to collect COVID-19 information based on prefectural/municipality reports. However, even these databases do not provide COVID-19 deaths by age and sex. This database thus aims to fill in the gap by collecting COVID-19 related deaths reported by various sources as I discuss below, including prefectures’ press releases or media sources. This document explains the collection of data sources and potential uses of the data.
  🖺 Full Text HTML: COVerAGE-JP: COVID-19 Deaths by Age and Sex in Japan
• Mutational pressure drives enhanced release of proteasome-generated public CD8+ T cell epitopes from SARS-CoV-2 RBD of Omicron and its current lineages -

  The COVID-19 pandemic was the most dramatic in the newest history with nearly 7 million deaths and global impact on mankind. Here we report binding index of 305 HLA class I molecules from 18,771 unique haplotypes of 28,104 individuals to 821 peptides experimentally observed from spike protein RBD of 5 main SARS-CoV-2 strains hydrolyzed by human proteasomes with constitutive and immune catalytic phenotypes. Our data read that 4 point mutations in the hACE2-binding region RBD496-513 of Omicron B1.1.529 strain results in a dramatic increase of proteasome-mediated release of two public HLA class I epitopes. Global population analysis of HLA class I haplotypes, specific to these peptides, demonstrated decreased mortality of human populations enriched in these haplotypes from COVID-19 after but not before December, 2021, when Omicron became dominant SARS-CoV-2 strain. Noteworthy, currently circulating BA.2.86 and JN.1 lineages contain no amino acid substitutions in RBD496-513 thus preserving identified core epitopes.

  🖺 Full Text HTML: Mutational pressure drives enhanced release of proteasome-generated public CD8+ T cell epitopes from SARS-CoV-2 RBD of Omicron and its current lineages
• Machine learning-driven COVID-19 early triage and large-scale testing strategies based on the 2021 Costa Rican Actualidades survey -

  The COVID-19 pandemic underscored the importance of mass testing in mitigating the spread of the virus. This study presents mass testing strategies developed through machine learning models, which predict the risk of COVID-19 contagion based on health determinants. Using the data from the 2021 “Actualidades” survey in Costa Rica, we trained models to classify individuals by contagion risk. After theorize four possible strategies, we evaluated these using Monte Carlo simulations, analyzing the distribution functions for the number of tests, positive cases detected, tests per person, and total costs. Additionally, we introduced the metrics, efficiency and stock capacity, to assess the performance of different strategies. Our classifier achieved an AUC-ROC of 0.80 and an AUC-PR of 0.59, considering a disease prevalence of 0.26. The fourth strategy, which integrates RT-qPCR, antigen, and RT-LAMP tests, emerged as a cost-effective approach for mass testing, offering insights into scalable and adaptable testing mechanisms for pandemic response.

  🖺 Full Text HTML: Machine learning-driven COVID-19 early triage and large-scale testing strategies based on the 2021 Costa Rican Actualidades survey
• Molecular epidemiology of invasive Group A Streptococcal infections before and after the COVID-19 pandemic in Switzerland -

  Group A Streptococcus (GAS, aka Streptococcus pyogenes) poses a significant public health concern, causing a diverse spectrum of infections with high mortality rates. Following the COVID-19 pandemic, a resurgence of invasive GAS (iGAS) infections has been documented, necessitating efficient outbreak detection methods. Whole genome sequencing (WGS) serves as the gold standard for GAS molecular typing, albeit constrained by time and costs. This study aimed to characterize the postpandemic increased prevalence of iGAS on the molecular epidemiological level in order to assess whether new, more virulent variants have emerged, as well as to assess the performance of the rapid and cost-effective Fourier-transform infrared (FTIR) spectroscopy as an alternative to WGS for detecting and characterizing GAS transmission routes. A total of 66 iGAS strains isolated from nine Swiss hospitals during the COVID-19 post-pandemic increased GAS prevalence were evaluated and compared to 15 strains collected before and 12 during the COVID-19 pandemic. FT-IR measurements and WGS were conducted for network analysis. Demographic, clinical, and epidemiological data were collected. Skin and soft tissue infection was the most common diagnosis, followed by primary bacteremia and pneumonia. Viral co-infections were found in 25% of cases and were significantly associated with more severe disease requiring intensive care unit admission. WGS analysis did not reveal emerging GAS genetic distinct variants after the COVID-19 pandemic, indicating the absence of a pandemic-induced shift. FT-IR spectroscopy exhibited limitations in differentiating genetically distant GAS strains, yielding poor overlap with WGS-derived clusters. The emm1/ST28 gebotype was predominant in our cohort and was associated with five of the seven deaths recorded, in accordance with the molecular epidemiological data before the pandemic. Additionally, no notable shift in antibiotic susceptibility patterns was observed. Our data suggest that mainly non-pathogen related factors contributed to the recent increased prevalence of iGAS.

  🖺 Full Text HTML: Molecular epidemiology of invasive Group A Streptococcal infections before and after the COVID-19 pandemic in Switzerland
• Discovery of RdRp Thumb-1 as a novel broad-spectrum antiviral family of targets and MDL-001 as a potent broad-spectrum inhibitor thereof - Part I: A Bioinformatics and Deep Learning Approach -
  Positive sense, single-stranded RNA (+ssRNA) viruses consist of 12+ viral families that contain mild pathogens to pandemic-causing viruses like SARS-CoV-2, yet all share a vital and highly conserved RNA-dependent RNA polymerase (RdRp). While RdRp is the target of several viral inhibitors, the active site has several pitfalls when translating in vitro inhibitors to the clinic. The highly polar residues within the active site often necessitate the use of highly polar or charged compounds, especially when designing nucleoside analog inhibitors, posing significant challenges in optimizing drug-likeness and membrane permeability for clinical efficacy. Here, we investigated the broad-spectrum potential of the allosteric Thumb-1 cryptic site of the RdRp, which to date has only been adequately studied in Hepatitis C Virus (HCV). To explore this potential antiviral target, we used a suite of bioinformatics techniques, including homology modeling and multiple sequence alignments, to reveal the conserved landscape of the Thumb-1 site across +ssRNA viruses. We then used ChemPrint, our Mol-GDL (Molecular-Geometric Deep Learning) machine learning model to predict drug inhibition of the Thumb-1 site in RdRp across +ssRNA viruses. Here, we identify MDL-001 as a promising broad-spectrum antiviral candidate with favorable properties that enable oral and once-a-day dosing. We also show how the cryptic nature of the Thumb-1 site masks itself to conventional virtual screening techniques, like docking, where activity prediction is heavily based on solving or predicting an accurate structure of the open pocket. This study demonstrates the utility of this approach in drug discovery for broad-spectrum antivirals that target the Thumb-1 site.
  🖺 Full Text HTML: Discovery of RdRp Thumb-1 as a novel broad-spectrum antiviral family of targets and MDL-001 as a potent broad-spectrum inhibitor thereof - Part I: A Bioinformatics and Deep Learning Approach
• Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations -
  In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles and binding mechanisms of convergent evolution for the SARS-CoV-2 Spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron Spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamic simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron Spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and molecular dynamics simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and molecular dynamics simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.
  🖺 Full Text HTML: Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations
• Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand -

  Background: Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care. Methods: We constructed a state-space model with observed data of levels of SARS-CoV-2 in wastewater and reported case incidence and estimated the hidden states of R and CAR using sequential Monte Carlo methods. Results: Here, we analysed data from 1 January 2022 to 31 March 2023 from Aotearoa New Zealand. Our model estimates that R peaked at 2.76 (95% CrI 2.20, 3.83) around 18 February 2022 and the CAR peaked around 12 March 2022. We calculate that New Zealand9s second Omicron wave in July 2022 was similar in size to the first, despite fewer reported cases. We estimate that the CAR in the BA.5 Omicron wave in July 2022 was approximately 50% lower than in the BA.1/BA.2 Omicron wave in March 2022. Conclusions: Estimating R, CAR, and cumulative number of infections provides useful information for planning public health responses and understanding the state of immunity in the population. This model is a useful disease surveillance tool, improving situational awareness of infectious disease dynamics in real-time.

  🖺 Full Text HTML: Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand
• Distal Protein-Protein Interactions Contribute to SARS-CoV-2 Main Protease Substrate Binding and Nirmatrelvir Resistance -
  SARS-CoV-2 main protease, Mpro, is responsible for the processing of the viral polyproteins into individual proteins, including the protease itself. Mpro is a key target of anti-COVID-19 therapeutics such as nirmatrelvir (the active component of Paxlovid). Resistance mutants identified clinically and in viral passage assays contain a combination of active site mutations (e.g. E166V, E166A, L167F), which reduce inhibitor binding and enzymatic activity, and non-active site mutations (e.g. P252L, T21I, L50F), which restore the fitness of viral replication. Although the mechanism of resistance for the active site mutations is apparent, the role of the non-active site mutations in fitness rescue remains elusive. In this study, we use the model system of a Mpro triple mutant (L50F/E166A/L167F) that confers not only nirmatrelvir drug resistance but also a similar fitness of replication compared to the wild-type both in vitro and in vivo. By comparing peptide and full-length Mpro protein as substrates, we demonstrate that the binding of Mpro substrate involves more than residues in the active site. In particular, L50F and other non-active site mutations can enhance the Mpro dimer-dimer interactions and help place the nsp5-6 substrate at the enzyme catalytic center. The structural and enzymatic activity data of Mpro L50F, L50F/E166A/L167F, and others underscore the importance of considering the whole substrate protein in studying Mpro and substrate interactions, and offers important insights into Mpro function, resistance development, and inhibitor design.
  🖺 Full Text HTML: Distal Protein-Protein Interactions Contribute to SARS-CoV-2 Main Protease Substrate Binding and Nirmatrelvir Resistance
• Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cells -
  The ability of SARS-CoV-2 to evade antiviral immune signaling in the airway contributes to the severity of COVID-19 disease. Additionally, COVID-19 is influenced by age and has more severe presentations in older individuals. This raises questions about innate immune signaling as a function of lung development and age. Therefore, we investigated the transcriptome of different cell populations of the airway epithelium using pediatric and adult lung tissue samples from the LungMAP Human Tissue Core Biorepository. Specifically, lung lobes were digested and cultured into a biomimetic model of the airway epithelium on an air-liquid interface. Cells were then infected with SARS-CoV-2 and subjected to single-cell RNA sequencing. Transcriptional profiling and differential expression analysis were carried out using Seurat. The clustering analysis identified several cell populations: club cells, proliferating epithelial cells, multiciliated precursor cells, ionocytes, and two biologically distinct clusters of ciliated cells (FOXJ1high and FOXJ1low). Interestingly, the two ciliated cell clusters showed different infection rates and enrichment of processes involved in ciliary biogenesis and function; we observed a cell-type-specific suppression of innate immunity in infected cells from the FOXJ1low subset. We also identified a significant number of genes that were differentially expressed in lung cells derived from children as compared to adults, suggesting the differential pathogenesis of SARS-CoV-2 infection in children versus adults. We discuss how this work can be used to identify drug targets to modulate molecular signaling cascades that mediate an innate immune response and begin to understand differences in COVID-19 outcomes for pediatric vs. adult populations.
  🖺 Full Text HTML: Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cells
• Mapping immunodominant sites on the MERS-CoV spike glycoprotein targeted by infection-elicited antibodies in humans -
  Middle-East respiratory syndrome coronavirus (MERS-CoV) first emerged in 2012 and causes human infections in endemic regions. Most vaccines and therapeutics in development against MERS-CoV focus on the spike (S) glycoprotein to prevent viral entry into target cells. These efforts, however, are limited by a poor understanding of antibody responses elicited by infection along with their durability, fine specificity and contribution of distinct S antigenic sites to neutralization. To address this knowledge gap, we analyzed S-directed binding and neutralizing antibody titers in plasma collected from individuals infected with MERS-CoV in 2017-2019 (prior to the COVID-19 pandemic). We observed that binding and neutralizing antibodies peak 1 to 6 weeks after symptom onset/hospitalization, persist for at least 6 months, and broadly neutralize human and camel MERS-CoV strains. We show that the MERS-CoV S1 subunit is immunodominant and that antibodies targeting S1, particularly the RBD, account for most plasma neutralizing activity. Antigenic site mapping revealed that polyclonal plasma antibodies frequently target RBD epitopes, particularly a site exposed irrespective of the S trimer conformation, whereas targeting of S2 subunit epitopes is rare, similar to SARS-CoV-2. Our data reveal in unprecedented details the humoral immune responses elicited by MERS-CoV infection, which will guide vaccine and therapeutic design.
  🖺 Full Text HTML: Mapping immunodominant sites on the MERS-CoV spike glycoprotein targeted by infection-elicited antibodies in humans

From Clinical Trials

• Fascial Tissue Response To Manual Therapy: Implications In Long Covid Rehabilitation - Conditions: COVID-19
  Interventions: Other: Guidebook; Other: Guidebook and Myofascial Reorganization® (RMF).
  Sponsors: University of the State of Santa Catarina; Larissa Sinhorim
  Recruiting

• Effect of Probiotic Strain Lactobacillus Paracasei PS23 on Brain Fog in People With Long COVID - Conditions: Long COVID; Brain Fog; Cognitive Change
  Interventions: Dietary Supplement: Lactobacillus paracasei PS23; Dietary Supplement: microcrystalline cellulose
  Sponsors: Taipei Veterans General Hospital, Taiwan
  Not yet recruiting

• Evaluation of the Impact of Rehabilitation Strategies and Early Discharge After Respiratory Failure - Conditions: Acute Respiratory Failure
  Interventions: Behavioral: Standard of Care; Behavioral: Rehabilitation
  Sponsors: Hospital Israelita Albert Einstein
  Not yet recruiting

• Diaphragmatic Breathing Exercises for Post-COVID-19 Diaphragmatic Dysfunction (DD) - Conditions: Post-Acute Sequelae of COVID-19
  Interventions: Other: Usual care of traditional treatment; Other: Specific DB program/Diaphragmatic manipulation program
  Sponsors: University of Minnesota
  Recruiting

From PubMed

• TRAIL and IP-10 dynamics in pregnant women post COVID-19 vaccination: associations with neutralizing antibody potency - INTRODUCTION: The aim of this study is to investigate changes in TNF-related apoptosis-inducing ligand (TRAIL) and gamma interferon-induced protein 10 (IP-10) after COVID-19 vaccination in pregnant women and to explore their association with neutralizing antibody (Nab) inhibition.

• Assessment of the activity of the immune system in patients with inflammatory bowel diseases and asymptomatic COVID-19 - CONCLUSIONS: The increased concentration of IL-2 may result from its regulatory role in inhibiting excessive activation of the immune system; however, considering the studies of patients with severe COVID-19, its role in the initial phase of SARS-CoV-2 infection requires further research.

• Quercetin inhibition of porcine intestinal alpha coronavirus in vitro and in vivo - CONCLUSIONS: Therefore, this study provides compelling evidence that quercetin has great potential and promising applications for anti- SADS-CoV action.

• Immunogenicity and efficacy of VLA2001 vaccine against SARS-CoV-2 infection in male cynomolgus macaques - CONCLUSIONS: We demonstrate that the VLA2001 adjuvanted vaccine is immunogenic both in mouse and NHP models and prevent cynomolgus macaques from the viruses responsible of COVID-19.

• A rigorous theoretical and numerical analysis of a nonlinear reaction-diffusion epidemic model pertaining dynamics of COVID-19 - The spatial movement of the human population from one region to another and the existence of super-spreaders are the main factors that enhanced the disease incidence. Super-spreaders refer to the individuals having transmitting ability to multiple pathogens. In this article, an epidemic model with spatial and temporal effects is formulated to analyze the impact of some preventing measures of COVID-19. The model is developed using six nonlinear partial differential equations. The infectious…

• A randomized trial to assess the acceleration of viral clearance by the combination Favipiravir/Ivermectin/Niclosamide in mild-to-moderate COVID-19 adult patients (FINCOV) - CONCLUSION: Viral clearance rates did not differ significantly between the FPV/IVM/NCL combination therapy and FPV-alone groups of individuals with mild-to-moderate COVID-19, although the combined regimen demonstrated a synergistic effect in vitro. No discernible clinical benefit was observed. Further research is required to explore the potential benefits of FVP beyond its antiviral effects.

• SARS-CoV-2 nsp15 endoribonuclease antagonizes dsRNA-induced antiviral signaling - Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has caused millions of deaths since its emergence in 2019. Innate immune antagonism by lethal CoVs such as SARS-CoV-2 is crucial for optimal replication and pathogenesis. The conserved nonstructural protein 15 (nsp15) endoribonuclease (EndoU) limits activation of double-stranded (ds)RNA-induced pathways, including interferon (IFN) signaling, protein kinase R (PKR), and oligoadenylate synthetase/ribonuclease L (OAS/RNase L) during diverse…

• Why have SGLT2 Inhibitors Failed to Achieve the Desired Success in COVID-19? - The SARS-CoV-2 virus emerged towards the end of 2019 and caused a major worldwide pandemic lasting at least 2 years, causing a disease called COVID-19. SARS-CoV-2 caused a severe infection with direct cellular toxicity, stimulation of cytokine release, increased oxidative stress, disruption of endothelial structure, and thromboinflammation, as well as angiotensin-converting enzyme 2 (ACE2) down-regulation-mediated renin-angiotensin system (RAS) activation. In addition to glucosuria and…

• In vitro suppression of porcine epidemic diarrhea virus by Panax notoginseng saponins: assessing antiviral potential - Porcine epidemic diarrhea virus (PEDV) causes severe diarrhea and high mortality in neonatal suckling piglets, leading to significant economic losses to the swine industry. Panax notoginseng saponins (PNS) are bioactive extracts derived from the P. notoginseng plant. In this study, we investigated the anti-PEDV effect of PNS by employing various methodologies to assess their impact on PEDV in Vero cells. Using a CCK-8 (Cell Counting Kit-8) assay, we found that PNS had no significant cytotoxicity…

• The death domain-associated protein suppresses porcine epidemic diarrhea virus replication by interacting with signal transducer and activator of transcription 1 and inducing downstream ISG15 expression - Porcine epidemic diarrhea virus (PEDV) is an enteric coronavirus that causes acute enteric disease in piglets and severely threatens the pig industry all over the world. Death domain-associated protein (DAXX) is a classical chaperone protein involved in multiple biological processes, such as cell apoptosis, transcriptional regulation, DNA damage repair, and host innate immunity. However, whether DAXX functions in the anti-PEDV innate immune responses remains unclear. In this study, we found that…

• Quantitating SARS-CoV-2 Neutralizing Antibodies from Human Dried Blood Spots - CONCLUSION: SARS-CoV-2 neutralizing titers can be derived with confidence from DBS eluates, thereby opening the door to the use of these biospecimens for the analysis of vulnerable populations and normally hard to reach communities.

• Lipid Nanoparticle-Based Inhibitors for SARS-CoV-2 Host Cell Infection - CONCLUSION: Both LNP-Trap and LNP-Trim formulations were able to safely and effectively inhibit SARS-CoV-2 pseudoviral infection in airway epithelial cells. These studies provide proof-of-principle for a localized treatment approach for SARS-CoV-2 in the upper airway.

• Transcriptional-profile changes in the medial geniculate body after noise-induced tinnitus - Tinnitus is a disturbing condition defined as the occurrence of acoustic hallucinations with no actual sound. Although the mechanisms underlying tinnitus have been explored extensively, the pathophysiology of the disease is not completely understood. Moreover, genes and potential treatment targets related to auditory hallucinations remain unknown. In this study, we examined transcriptional-profile changes in the medial geniculate body after noise-induced tinnitus in rats by performing RNA…

• Acceptance, safety, and immunogenicity of a booster dose of inactivated SARS-CoV-2 vaccine in patients with primary biliary cholangitis - Inactivated coronavirus disease 2019 (COVID-19) vaccines showed impaired immunogenicity in some autoimmune diseases, but it remains unclear in primary biliary cholangitis (PBC). This study aimed to explore the antibody response to the inactivated COVID-19 vaccine in individuals with PBC, as well as to evaluate coverage, safety, and attitudes toward the COVID-19 vaccine among them. Two cohorts of patients with PBC were enrolled in this study. One cohort was arranged to evaluate the immunogenicity…

• Vgamma9Vdelta2 T-cells are potent inhibitors of SARS-CoV-2 replication and represent effector phenotypes in COVID-19 patients - Vγ9Vδ2 T-cells play a key role in the innate immune response to viral infections through butyrophilin (BTN)-3A. Here, we reported that blood Vγ9Vδ2 T-cells decreased in clinically mild COVID-19 compared to healthy volunteers (HV), and was maintained up to 28-days and in the recovery period. Terminally differentiated Vγ9Vδ2 T-cells tend to be enriched on the day of diagnosis, 28-days after and during the recovery period. These cells showed cytotoxic and inflammatory activities following…

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