194 lines
52 KiB
HTML
194 lines
52 KiB
HTML
<!DOCTYPE html>
|
||
<html lang="" xml:lang="" xmlns="http://www.w3.org/1999/xhtml"><head>
|
||
<meta charset="utf-8"/>
|
||
<meta content="pandoc" name="generator"/>
|
||
<meta content="width=device-width, initial-scale=1.0, user-scalable=yes" name="viewport"/>
|
||
<title>06 July, 2022</title>
|
||
<style type="text/css">
|
||
code{white-space: pre-wrap;}
|
||
span.smallcaps{font-variant: small-caps;}
|
||
span.underline{text-decoration: underline;}
|
||
div.column{display: inline-block; vertical-align: top; width: 50%;}
|
||
</style>
|
||
<title>Covid-19 Sentry</title><meta content="width=device-width, initial-scale=1.0" name="viewport"/><link href="styles/simple.css" rel="stylesheet"/><link href="../styles/simple.css" rel="stylesheet"/><link href="https://unpkg.com/aos@2.3.1/dist/aos.css" rel="stylesheet"/><script src="https://unpkg.com/aos@2.3.1/dist/aos.js"></script></head>
|
||
<body>
|
||
<h1 data-aos="fade-down" id="covid-19-sentry">Covid-19 Sentry</h1>
|
||
<h1 data-aos="fade-right" data-aos-anchor-placement="top-bottom" id="contents">Contents</h1>
|
||
<ul>
|
||
<li><a href="#from-preprints">From Preprints</a></li>
|
||
<li><a href="#from-clinical-trials">From Clinical Trials</a></li>
|
||
<li><a href="#from-pubmed">From PubMed</a></li>
|
||
<li><a href="#from-patent-search">From Patent Search</a></li>
|
||
</ul>
|
||
<h1 data-aos="fade-right" id="from-preprints">From Preprints</h1>
|
||
<ul>
|
||
<li><strong>Integrative analysis of viral entry networks and clinical outcomes identifies a protective role for spironolactone in severe COVID-19</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Treatment strategies that target host entry factors have proven an effective means of impeding viral entry in HIV and may be more robust to viral evolution than drugs targeting viral proteins directly. High-throughput functional screens provide an unbiased means of identifying genes that influence the infection of host cells, while retrospective cohort analysis can measure the real-world, clinical potential of repurposing existing therapeutics as antiviral treatments. Here, we combine these two powerful methods to identify drugs that alter the clinical course of COVID-19 by targeting host entry factors. We demonstrate that integrative analysis of genome-wide CRISPR screening datasets enables network-based prioritization of drugs modulating viral entry, and we identify three common medications (spironolactone, quetiapine, and carvedilol) based on their network proximity to putative host factors. To understand the drugs9 real-world impact, we perform a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients and show that spironolactone use is associated with improved clinical prognosis, measured by both ICU admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in a human lung epithelial cell line. Our results suggest that spironolactone may improve clinical outcomes in COVID-19 through tissue-dependent inhibition of viral entry. Our work further provides a potential approach to integrate functional genomics with real-world evidence for drug repurposing.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22277181v1" target="_blank">Integrative analysis of viral entry networks and clinical outcomes identifies a protective role for spironolactone in severe COVID-19</a>
|
||
</div></li>
|
||
<li><strong>Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico</strong> -
|
||
<div>
|
||
Up to November 2021, over 200 different SARS-CoV-2 lineages circulated in Mexico. To investigate lineage replacement dynamics, we applied a phylodynamic approach to explore the evolutionary trajectories of five dominant lineages that circulated during the first year of the local epidemic. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in the country. Lineages B.1.1.222 and B.1.1.519 showed comparable dynamics, represented by clades likely originating in Mexico and persisting for over a year. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. We further explored viral movements across the country, applied within the largest clades identified (belonging to lineage B.1.617.2). Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.biorxiv.org/content/10.1101/2022.07.05.498834v1" target="_blank">Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico</a>
|
||
</div></li>
|
||
<li><strong>COVID-19 Neuropathology: evidence for SARS-CoV-2 invasion of Human Brainstem Nuclei</strong> -
|
||
<div>
|
||
Neurological manifestations are common in COVID-19, the disease caused by SARS-CoV-2. Despite reports of SARS-CoV-2 detection in the brain and cerebrospinal fluid of COVID-19 patients, it’s still unclear whether the virus can infect the central nervous system, and which neuropathological alterations can be ascribed to viral tropism, rather than immune mediated mechanisms. Here, we assess neuropathology alterations in 24 COVID-19 patients and 18 matched controls who died due to pneumonia / respiratory failure. Aside from a wide spectrum of neuropathological alterations, SARS-CoV-2-immunoreactive neurons were detected in specific brainstem nuclei of 5 COVID-19 subjects. Viral RNA was also detected by real-time RT-PCR. Quantification of reactive microglia revealed an anatomically segregated pattern of inflammation within affected brainstem regions, and was higher when compared to controls. While the results of this study support the neuroinvasive potential of SARS-CoV-2, the role of SARS-CoV-2 neurotropism in COVID-19 and its long-term sequelae require further investigation.
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.biorxiv.org/content/10.1101/2022.06.29.498117v1" target="_blank">COVID-19 Neuropathology: evidence for SARS-CoV-2 invasion of Human Brainstem Nuclei</a>
|
||
</div></li>
|
||
<li><strong>Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of COVID-19 in Africa</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Background The COVID-19 pandemic has had a devastating impact on global health, the magnitude of which appears to differ intercontinentally: for example, reports suggest 271,900 per million people have been infected in Europe versus 8,800 per million people in Africa. While Africa is the second largest continent by population, its reported COVID-19 cases comprise <3% of global cases. Although social, environmental, and environmental explanations have been proposed to clarify this discrepancy, systematic infection underascertainment may be equally responsible. Methods We seek to quantify magnitude of underascertainment in COVID-199s cumulative incidence in Africa. Using serosurveillance and postmortem surveillance, we constructed multiplicative factors estimating ratios of true infections to reported cases in African nations since March 2020. Results Multiplicative factors derived from serology data - in a subset of 12 nations - suggested a range of COVID-19 reporting rates, from 1 in 630 infections reported in Kenya (May 2020) to 1 in 15 infections reported in South Africa (November 2021). The largest multiplicative factor, 3,795, corresponded to Malawi (June 2020), suggesting <0.05% of infections captured. A similar set of multiplicative factors for all nations derived from postmortem data points toward the same conclusion: reported COVID-19 cases are unrepresentative of true infections, suggesting a key reason for low case burden in many African nations is significant underdetection and underreporting. Conclusions While estimating COVID-199s exact burden is challenging, the multiplicative factors we present provide incidence curves reflecting likely-to-worst-case ranges of infection. Our results stress the need for expansive surveillance to allocate resources in areas experiencing severe discrepancies between reported cases, projected infections, and deaths.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.03.22277196v1" target="_blank">Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of COVID-19 in Africa</a>
|
||
</div></li>
|
||
<li><strong>Using machine learning probabilities to identify effects of COVID-19</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
COVID-19, the disease caused by the SARS-CoV-2 virus, has had and continues to have extensive economic, social and public health impacts in the United States and around the world. To date, there have been more than 500 million reported cases of SARS-CoV-2 infection worldwide with more than 6 million reported deaths, more than 80 million of those cases and more than 1 million of those deaths have been reported in the United States. Retrospective analysis throughout the pandemic, which identified comorbidities, risk factors and treatments, has underpinned the response COVID-19. As the situation transitions from a pandemic to an endemic, retrospective analyses using electronic health records will be increasingly important to identify long term effects of COVID-19. However, these analyses can be complicated by the incompleteness of electronic health records, which in turns makes it difficult to differentiate visits where the patient has COVID-19. To address this, we trained a random forest classifier to assign a probability of a patient having been diagnosed with COVID-19 during each visit using demographic data, temporal data and visit-specific diagnoses (Training AUROC = 0.9867, Training OOB AUROC = 0.8957, Evaluation AUROC = 0.8958). Using these probabilities, we identified conditions associated with higher COVID-19 probabilities irrespective of clinical history and when accounting for previous diagnosis and estimated the hazards ratio for myocardial infarction (Hazards ratio = 121.736 (87.375, 169.611), p = 3.796E-177 and Hazards ratio = 80.262 (4.134, 4.637), p = 4.543E-256, respectively), urinary tract infection (Hazards ratio = 72.021 (58.116 - 89.253), p < 2.225E-308 and Hazards ratio = 61.380 (51.273 - 73.479), p < 2.225E-308, respectively), acute renal failure (Hazards ratio = 1.264E4 (9.278E4 - 1.724E4), p < 2.225E-308 and Hazards ratio = 6.333E3 (4.947E3 - 8.108E3), p < 2.225E-308, respectively) and type 2 diabetes (Hazards ratio = 345.730 (283.180 - 422.098), p < 2.225E-308 and Hazards ratio = 217.271 (187.898 - 251.235), p = 1.39E-22, respectively) when accounting for demographics and the ten most common clinical conditions.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22277179v1" target="_blank">Using machine learning probabilities to identify effects of COVID-19</a>
|
||
</div></li>
|
||
<li><strong>Revisiting biological sex as a risk factor for COVID-19: a fact or mirage of numbers?</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Biological sex is considered a risk factor for COVID-19. The prevailing view supposes males are about two-fold more impacted than females based on early-stage studies. The observed higher male deaths in COVID-19 are purportedly a result of biological differences that make males more vulnerable to adverse outcomes in infectious diseases. Research and policy paradigms seem to follow a similar line of thought to mitigate COVID-19 impact on populations. The analysis of sex-disaggregated data could help us evaluate the veracity of assertions for a preferred evidence-guided response. The analysis of the sex-disaggregated data available for the top 70 countries contributing about 80% of total deaths (as of 15 September 2021; on average two waves of infections experienced) indicates average Case Sex (Male: Female) ratio (CSR) of 1.09±0.35 (marginally more male cases) and Death Sex ratio (DSR) of 1.48± 0.47. Consideration of only laboratory-confirmed cases indicates the mortality sex ratio (MSR) in COVID-19 (MSR-COVID) to be 1.37±0.30. The prevailing MSR for the same countries was 1.758±0.409. The relative change in the mortality rate for males as compared to females in COVID-19 (ratio: MSR-COVID/prevailing MSR-PP) was 0.818±0.261 much lower than anticipated (2 or higher). Overall, over three-fold more countries (51/70) experienced a higher rate of female mortality than male mortality (15/70). Together, it suggests a more disproportionately severe impact of COVID-19 on females than on males, contrary to the prevailing view. Identification and analysis of country-specific factors contributing to differential impact on sexes, whether biological or environmental, seem warranted.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22276577v1" target="_blank">Revisiting biological sex as a risk factor for COVID-19: a fact or mirage of numbers?</a>
|
||
</div></li>
|
||
<li><strong>Post SARS-CoV-2 cell mediated Immune profiles; Case studies</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Cell-mediated immunity (CMI), which includes T-cells (both T helper and cytotoxic), is critical for effective antiviral defenses against coronavirus disease-2019 (COVID-19). To better understand the immunological characteristics of CD markers on T-cells in post-COVID-19 patients, we investigated the expression of differential CD markers in the patient groups in this study. Flow cytometry was used to quantify total lymphocyte count and assess the levels of expression of CD markers in the samples. The percentage of Lymphocytes decreased significantly in the post-SARS-COV-2 patients in comparison to normal subjects, which is usually happening in any viral infection. In contrast to that, expression of CD8 was increased in the patient group having long SARS-COV-2 infection with comorbid complications with respect to the normal individuals and long SARS-COV-2 infection without comorbid complications. This data revealed that the cellular immunological responses corroborated with an earlier report of COVID-19 infection were mediated by CD8 upregulation and cytotoxic T lymphocyte hyperactivation.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22276875v1" target="_blank">Post SARS-CoV-2 cell mediated Immune profiles; Case studies</a>
|
||
</div></li>
|
||
<li><strong>CD19+ B cell numbers predict the increase of anti-SARS CoV2 antibodies in fingolimod-treated and COVID-19-vaccinated patients with multiple sclerosis</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Treatment with fingolimod for multiple sclerosis (MS) reduces the efficacy of COVID-19 vaccination. We evaluated by a multivariate linear regression model whether main lymphocyte subsets and demographic feature correlated to the subsequent increase in anti-SARS-CoV2 antibodies following the third dose of COVID-19 vaccination. We found that number and proportion of peripheral blood CD19+ B lymphocytes before the third dose of vaccination in MS patients treated with fingolimod, predict the subsequent increase of anti-SARS-CoV2 antibodies (respectively p = 0.013; p = 0.015). This work suggests that evaluating the numbers of CD19+ B cells may be important to identify patients at risk of not producing SARS-CoV-2 antibodies, with possible reduced protection from COVID-19.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22277178v1" target="_blank">CD19+ B cell numbers predict the increase of anti-SARS CoV2 antibodies in fingolimod-treated and COVID-19-vaccinated patients with multiple sclerosis</a>
|
||
</div></li>
|
||
<li><strong>Clinical characteristics and factors associated with COVID-19-related mortality and hospital admission in 5 rural provinces in Indonesia: a retrospective cohort study</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Background Data on COVID-19 clinical characteristics and severity from resource-limited settings are limited. This study examined clinical characteristics and factors associated with COVID-19 mortality and hospitalisation in rural settings of Indonesia, from 1 January to 31 July, 2021. Methods This retrospective cohort included individuals diagnosed with COVID-19 based on polymerase chain reaction or rapid antigen diagnostic test, from Lampung, Gorontalo, Central Sulawesi, Southeast Sulawesi, and East Nusa Tenggara Provinces. We extracted demographic and clinical data, including hospitalisation and mortality from COVID-19 surveillance records. We used mixed-effect logistic regression to examine factors associated with COVID-19-related mortality and hospitalisation. Results Of 6,583 confirmed cases, 205 (3.1%) died, and 1,727 (26%) were hospitalised. The median age was 37 years (IQR 26-52), with 825 (12.53%) under 20 years, and 3,371 (51.21%) females. 4,533 (68.86%) cases were symptomatic, 319 (4.85%) had a clinical diagnosis of pneumonia, and 945 (14.36%) with at least one pre-existing comorbidity. The mortality and hospitalisation rate ranged from 2.0% and 13.4% in East Nusa Tenggara to 4.3% and 36.1% in Lampung. Age-specific mortality rates were 0.9% (2/340) for 0-4 years; 0% (0/112) for 5-9 years; 0.2% (1/498) for 10-19 years; 0.8% (11/1,385) for 20-29 years; 0.9% (12/1,382) for 30-39 years; 2% (23/1,095) for 40-49 years; 5% (57/1,064) for 50-59 years; 11% (62/576) for 60-69 years; 16% (37/232) for ≥70 years. Older age, pre-existing diabetes, liver diseases, malignancy, and pneumonia were associated with higher risk of mortality and hospitalisation. Pre-existing hypertension, cardiac diseases, chronic kidney disease, COPD, and immunocompromised condition were associated with risk of hospitalisation but not with mortality. Conclusion Clinical characteristics and risk factors of severe COVID-19 outcomes in rural provinces were broadly similar to those in urban settings. The risk of COVID-19-related mortality and hospitalisation was associated with higher age, pre-existing chronic comorbidities, and clinical presentation of pneumonia.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.03.22277201v1" target="_blank">Clinical characteristics and factors associated with COVID-19-related mortality and hospital admission in 5 rural provinces in Indonesia: a retrospective cohort study</a>
|
||
</div></li>
|
||
<li><strong>Impact of dementia, living in a long-term care facility, and physical activity status on COVID-19 severity in older adults</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Background: Japan is fast becoming an extremely aged society and older adults are known to be at risk of severe COVID-19. However, the impact of risk factors specific to this population for severe COVID-19 caused by the Omicron variant of concern (VOC) are not yet clear. Methods: We performed an exploratory analysis using logistic regression to identify risk factors for severe COVID-19 illness among 4,868 older adults with a positive SARS-CoV-2 test result who were admitted to a healthcare facility between 1 January 2022 and 16 May 2022. We then conducted one-to-one propensity score (PS) matching for three factors-dementia, admission from a long-term care facility, and poor physical activity status-and used Fisher9s exact test to compare the proportion of severe COVID-19 cases in the matched data. We also estimated the average treatment effect on treated (ATT) in each PS matching analysis. Results: Of the 4,868 cases analyzed, 1,380 were severe. Logistic regression analysis showed that age, male sex, cardiovascular disease, cerebrovascular disease, chronic lung disease, renal failure and/or dialysis, physician-diagnosed obesity, admission from a long-term care facility, and poor physical activity status were risk factors for severe disease. Vaccination and dementia were identified as factors associated with non-severe illness. The ATT for dementia, admission from a long-term care facility, and poor physical activity status was -0.04 (95% confidence interval -0.07, -0.01), 0.09 (0.06, 0.12), and 0.17 (0.14, 0.19), respectively. Conclusions: Our results suggest that poor physical activity status and living in a long-term care facility have a substantial impact on the risk of severe COVID-19 caused by the Omicron VOC, while dementia might be associated with non-severe illness.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.01.22277144v1" target="_blank">Impact of dementia, living in a long-term care facility, and physical activity status on COVID-19 severity in older adults</a>
|
||
</div></li>
|
||
<li><strong>Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission and control. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection and transmission—for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we re-analyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same data set reported shorter mean observed incubation period (3.2 days vs 4.4 days) and serial interval (3.5 days vs 4.1 days) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8–4.5 days) for both variants but a shorter mean generation interval for the Omicron variant (3.0 days; 95% CI: 2.7–3.2 days) than for the Delta variant (3.8 days; 95% CI: 3.7–4.0 days). We further note that the differences in estimated generation intervals may be driven by the “network effect”—higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.02.22277186v1" target="_blank">Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2</a>
|
||
</div></li>
|
||
<li><strong>The clinical utility and epidemiological impact of self-testing for SARS-CoV-2 using an-tigen detecting diagnostics: a systematic review and meta-analysis</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
Introduction Self-testing for COVID-19 (C19ST) based on antigen detecting diagnostics could signifi-cantly support controlling the SARS-CoV-2 pandemic. To inform the World Health Organiza-tion in developing a C19ST guideline, we performed a systematic review and meta-analysis of the available literature. Methods We electronically searched Medline and the Web of Science core collection, performed secondary reference screening, and contacted experts for further relevant publications. Any study published between December 1, 2020 and November 30, 2021 assessing the epidemio-logical impact and clinical utility of C19ST was included. Study quality was evaluated using the Newcastle Ottawa Scale (NOS). The review was registered on PROSPERO (CRD42022299977). Results 11 studies only from high-income countries with an overall low quality (median of 3/9 stars on the NOS) were found. Pooled C19ST positivity was 0.2% (95% CI 0.1% to 0.4%; eight data sets) in populations where otherwise no dedicated testing would have occurred. The impact of self-testing on virus transmission was uncertain. Positive test results mainly resulted in people having to isolate without further confirmation of results (eight data sets). When testing was voluntary by study design, pooled testing uptake was 53.2% (95% CI 36.7% to 68.9%; five data sets. Outside direct health impacts, C19ST reduced quarantine duration and absenteeism from work, and made study participants feel safer. Study participants favored self-testing and were confident that they performed testing and sampling correctly. Conclusions The present data suggests that C19ST could be a valuable tool in reducing the spread of COVID-19, as it can achieve good uptake, may identify additional cases, and was generally perceived as positive by study participants. However, data was very limited and heterogenous, and further research especially in low- and middle-income countries is needed to assess the clinical utility and epidemiological impact of C19ST in more detail.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.03.22277183v1" target="_blank">The clinical utility and epidemiological impact of self-testing for SARS-CoV-2 using an-tigen detecting diagnostics: a systematic review and meta-analysis</a>
|
||
</div></li>
|
||
<li><strong>Impact of age-structure and vaccine prioritization on COVID-19 in West Africa</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
The ongoing COVID-19 pandemic has been a major global health challenge since its emergence in 2019. Contrary to early predictions that sub-Saharan Africa (SSA) would bear a disproportionate share of the burden of COVID-19 due to the region9s vulnerability to other infectious diseases, weak healthcare systems, and socioeconomic conditions, the pandemic9s effects in SSA have been very mild in comparison to other regions. Interestingly, the number of cases, hospitalizations, and disease-induced deaths in SSA remain low, despite the loose implementation of non-pharmaceutical interventions (NPIs) and the low availability and administration of vaccines. Possible explanations for this low burden include epidemiological disparities, under-reporting (due to limited testing), climatic factors, population structure, and government policy initiatives. In this study, we formulate a model framework consisting of a basic model (in which only susceptible individuals are vaccinated), a vaccine-structured model, and a hybrid vaccine-age-structured model to reflect the dynamics of COVID-19 in West Africa (WA). The framework is trained with a portion of the confirmed daily COVID-19 case data for 16 West African countries, validated with the remaining portion of the data, and used to (i) assess the effect of age structure on the incidence of COVID-19 in WA, (ii) evaluate the impact of vaccination and vaccine prioritization based on age brackets on the burden of COVID-19 in the sub-region, and (iii) explore plausible reasons for the low burden of COVID-19 in WA compared to other parts of the world. Calibration of the model parameters and global sensitivity analysis show that asymptomatic youths are the primary drivers of the pandemic in WA. Also, the basic and control reproduction numbers of the hybrid vaccine-age-structured model are smaller than those of the other two models indicating that the disease burden is overestimated in the models which do not account for age-structure. This result is also confirmed through the vaccine-derived herd immunity thresholds. In particular, a comprehensive analysis of the basic (vaccine-structured) model reveals that if 84% (73%) of the West African populace is fully immunized with the vaccines authorized for use in WA, vaccine-derived herd immunity can be achieved. This herd immunity threshold is lower (68%) for the hybrid model. Also, all three thresholds are lower (60% for the basic model, 51% for the vaccine structured model, and 48% for the hybrid model) if vaccines of higher efficacies (e.g., the Pfizer or Moderna vaccine) are prioritized, and higher if vaccines of lower efficacy are prioritized. Simulations of the models show that controlling the COVID-19 pandemic in WA (by reducing transmission) requires a proactive approach, including prioritizing vaccination of more youths or vaccination of more youths and elderly simultaneously. Moreover, complementing vaccination with a higher level of mask compliance will improve the prospects of containing the pandemic. Additionally, simulations of the model predict another COVID-19 wave (with a smaller peak size compared to the Omicron wave) by mid-July 2022. Furthermore, the emergence of a more transmissible variant or easing the existing measures that are effective in reducing transmission will result in more devastating COVID-19 waves in the future. To conclude, accounting for age-structure is important in understanding why the burden of COVID-19 has been low in WA and sustaining the current vaccination level, complemented with the WHO recommended NPIs is critical in curbing the spread of the disease in WA.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2022.07.03.22277195v1" target="_blank">Impact of age-structure and vaccine prioritization on COVID-19 in West Africa</a>
|
||
</div></li>
|
||
<li><strong>Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention-based neural networks</strong> -
|
||
<div>
|
||
Viral infections represent a major health concern worldwide. The alarming rate at which SARS-CoV-2 spreads, for example, led to a worldwide pandemic. Viruses incorporate genetic material into the host genome to hijack host cell functions such as the cell cycle and apoptosis. In these viral processes, protein-protein interactions (PPIs) play critical roles. Therefore, the identification of PPIs between humans and viruses is crucial for understanding the infection mechanism and host immune responses to viral infections and for discovering effective drugs. Experimental methods such as yeast two-hybrid assays and mass spectrometry are widely used to identify human-virus PPIs, but these experimental methods are time-consuming, expensive, and laborious. To overcome this problem, we developed a novel computational predictor, named cross-attention PHV, by implementing two key technologies of the cross-attention mechanism and a one-dimensional convolutional neural network (1D-CNN). The cross-attention mechanisms were very effective in enhancing prediction and generalization abilities. Application of 1D-CNN to the word2vec-generated feature matrices reduced computational costs, thus extending the allowable length of protein sequences to 9000 amino acid residues. Cross-attention PHV outperformed existing state-of-the-art models using a benchmark dataset and accurately predicted PPIs for unknown viruses. Cross-attention PHV also predicted human-SARS-CoV-2 PPIs with area under the curve values >0.95.
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.biorxiv.org/content/10.1101/2022.07.03.498630v1" target="_blank">Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention-based neural networks</a>
|
||
</div></li>
|
||
<li><strong>Shedding of Infectious SARS-CoV-2 Despite Vaccination</strong> -
|
||
<div>
|
||
<p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom">
|
||
The SARS-CoV-2 Delta Variant of Concern is highly transmissible and contains mutations that confer partial immune escape. The emergence of Delta in North America caused the first surge in COVID-19 cases after SARS-CoV-2 vaccines became widely available. To determine whether individuals infected despite vaccination might be capable of transmitting SARS-CoV-2, we compared RT-PCR cycle threshold (Ct) data from 20,431 test-positive anterior nasal swab specimens from fully vaccinated (n = 9,347) or unvaccinated (n=11,084) individuals tested at a single commercial laboratory during the interval 28 June-1 December 2021 when Delta variants were predominant. We observed no significant effect of vaccine status alone on Ct value, nor when controlling for vaccine product or sex. Testing a subset of low-Ct (<25) samples, we detected infectious virus at similar rates, and at similar titers, in specimens from vaccinated and unvaccinated individuals. These data indicate that vaccinated individuals infected with Delta variants are capable of shedding infectious SARS-CoV-2 and could play a role in spreading COVID-19.
|
||
</p>
|
||
</div>
|
||
<div class="article-link article-html-link">
|
||
🖺 Full Text HTML: <a href="https://www.medrxiv.org/content/10.1101/2021.07.31.21261387v7" target="_blank">Shedding of Infectious SARS-CoV-2 Despite Vaccination</a>
|
||
</div></li>
|
||
</ul>
|
||
<h1 data-aos="fade-right" id="from-clinical-trials">From Clinical Trials</h1>
|
||
<ul>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Immuno-bridging Study of COVID-19 Protein Subunit Recombinant Vaccine</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Biological: COVID-19 Protein Subunit Recombinant Vaccine; Biological: Active Comparator<br/><b>Sponsors</b>: PT Bio Farma; Fakultas Kedokteran Universitas Indonesia; Faculty of Medicine Universitas Diponegoro; Faculty of Medicine Universitas Andalas; Faculty of Medicine Universitas Hassanudin<br/><b>Recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Study to Learn About the Study Medicines (Called Nirmatrelvir/Ritonavir) in People 12 Years Old or Older With COVID-19 Who Are Immunocompromised</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Drug: Nirmatrelvir; Drug: Ritonavir; Drug: Placebo for nirmatrelvir; Drug: Placebo for ritonavir<br/><b>Sponsor</b>: Pfizer<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Randomized Controlled Trial of a Digital, Self-testing Strategy for COVID-19 Infection in South Africa.</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Device: Abbott Panbio rapid antigen self-tests; Other: COVIDSmart CARE! app<br/><b>Sponsors</b>: McGill University Health Centre/Research Institute of the McGill University Health Centre; University of Cape Town Lung Institute<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Immunogenicity and Safety Study of One Booster Dose of Trivalent COVID-19 Vaccine (Vero Cell), Inactivated</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Biological: Trivalent COVID-19 Vaccine (Vero Cell), Inactivated, Prototype Strain, Delta Strain and Omicron Strain; Biological: COVID-19 Vaccine (Vero Cell), Inactivated<br/><b>Sponsors</b>: Sinovac Biotech (Colombia) S.A.S.; Sinovac Life Sciences Co., Ltd.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Randomized, Single-Center, Single-Blind, Placebo Controlled, Investigator Initiated Trial to Evaluate the Efficacy of PanCytoVir™ 500 mg Twice Daily and 1000 mg Twice Daily for the Treatment of Non-Hospitalized Patients With COVID-19 Infection</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Drug: PanCytoVir™ (probenecid); Drug: Placebo<br/><b>Sponsor</b>: TrippBio, Inc.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>IMM-BCP-01 in Mild to Moderate COVID-19</strong> - <b>Conditions</b>: SARS-CoV2 Infection; COVID-19<br/><b>Interventions</b>: Drug: IMM-BCP-01; Drug: Placebo<br/><b>Sponsors</b>: Immunome, Inc.; United States Department of Defense<br/><b>Recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Study to Evaluate the Safety, Tolerability, and Immunogenicity of SARS-CoV-2 Variant (COVID-19 Omicron) mRNA Vaccine (Phase 1)</strong> - <b>Condition</b>: COVID-19<br/><b>Intervention</b>: Biological: ABO1009-DP<br/><b>Sponsor</b>: Suzhou Abogen Biosciences Co., Ltd.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Study to Evaluate Safety, Tolerability, and Immunogenicity of SARS-CoV-2 Variant (COVID-19) mRNA Vaccines</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Biological: ABO1009-DP; Biological: ABO-CoV.617.2; Other: Placebo<br/><b>Sponsor</b>: Suzhou Abogen Biosciences Co., Ltd.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Can Intensive Insulin Therapy Improve Outcomes of COVID-19 Patients</strong> - <b>Conditions</b>: COVID-19; Dysglycemia<br/><b>Interventions</b>: Drug: Insulin; Drug: Subcutaneous Insulin<br/><b>Sponsor</b>: Benha University<br/><b>Completed</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Mesenchymal Stromal Cells for the Treatment of Patients With COVID-19.</strong> - <b>Conditions</b>: COVID-19 Pneumonia; COVID-19<br/><b>Interventions</b>: Biological: Mesenchymal stem cell; Other: Placebo<br/><b>Sponsors</b>: Paulo Brofman; Conselho Nacional de Desenvolvimento Científico e Tecnológico<br/><b>Recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Study to Evaluate the Safety and Immunogenicity of Ad5-vector Based Vaccine Against Coronavirus Variants in Adults (≥18 Years) Immunized With 2 Doses of mRNA Vaccines Plus One Dose of Booster AZD1222 Vaccine</strong> - <b>Condition</b>: COVID-19<br/><b>Interventions</b>: Biological: Bivalent Recombinant COVID-19 Vaccine (Adenovirus Type 5 Vector); Biological: Bivalent Recombinant COVID-19 Vaccine (Adenovirus Type 5 Vector) for Inhalation; Biological: mRNA-based COVID-19 vaccine<br/><b>Sponsor</b>: CanSino Biologics Inc.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>A Study to Evaluate Immunogenicity and Safety of MVC-COV1901 Vaccine Compared With AZD1222</strong> - <b>Condition</b>: COVID-19 Vaccine<br/><b>Interventions</b>: Biological: MVC-COV1901; Biological: AZD1222<br/><b>Sponsor</b>: Medigen Vaccine Biologics Corp.<br/><b>Not yet recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Study of Self-Amplifying Messenger Ribonucleic Acid (samRNA) Vaccines Against COVID-19 in Healthy Adults and People Living With Human Immunodeficiency Virus (HIV)</strong> - <b>Conditions</b>: COVID-19; SARS-CoV-2<br/><b>Interventions</b>: Drug: GRT-R912, samRNA-Spikebeta-TCE11; Drug: GRT-R914, samRNA-Spikebeta-TCE9; Drug: GRT-R918, samRNA-SpikeOmicron-N-TCE11<br/><b>Sponsor</b>: Gritstone bio, Inc.<br/><b>Recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Laser Therapy on Tension-type Cephalea and Orofacial Pain in Post-covid-19 Patients</strong> - <b>Conditions</b>: Tension-Type Headache; Orofacial Pain; COVID-19<br/><b>Intervention</b>: Radiation: Photobimodulation<br/><b>Sponsor</b>: University of Nove de Julho<br/><b>Recruiting</b></p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Safety, Tolerability, and Pharmacokinetics of Q-Griffithsin Intranasal Spray</strong> - <b>Condition</b>: COVID-19 Prevention<br/><b>Interventions</b>: Drug: Q-Griffithsin 3.0; Drug: Q-Griffithsin 6.0<br/><b>Sponsors</b>: Kenneth Palmer; United States Department of Defense<br/><b>Recruiting</b></p></li>
|
||
</ul>
|
||
<h1 data-aos="fade-right" id="from-pubmed">From PubMed</h1>
|
||
<ul>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Current status and prospects of IL-6-targeting therapy</strong> - INTRODUCTION: Persistent and excess IL-6 production often contributes to a variety of immune diseases. IL-6-targeting therapy was first approved for Castleman disease, then rheumatoid arthritis, and now it is broadly used. Furthermore, it has been approved not only for chronic and acute inflammatory diseases but also for autoantibody-induced diseases such as neuromyelitis optica spectrum disorder and interstitial lung disease due to systemic sclerosis.</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>In vitro evaluation of antiviral activity of Sisybrium irio (Khaksi) against SARS-COV-2</strong> - SARS-CoV-2 pandemic, drawn attention to the need of virus culture. In vitro SARS-COV-2 culture was performed to carry out therapeutic, environmental and virus genome studies. Isolation of virus from nasopharyngeal swab was performed by inoculating virus positive samples in available cell lines. SARS-CoV-2 topography was observed by using Scanning Electron Microscopy (SEM). Virus specificity was defined by serological confirmation through neutralization assay with COVID 19 convalescent sera. The…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>An outlook on potential protein targets of COVID-19 as a druggable site</strong> - CONCLUSION: Using cryo-electron microscopy or X-ray diffraction, hundreds of crystallographic data of SARS-CoV-2 proteins have been published including structural and non-structural proteins. These proteins have a significant role at different aspects in the viral machinery and presented themselves as potential target for drug designing and therapeutic interventions. Also, there are few host cell proteins which helps in SARS-CoV-2 entry and proteolytic cleavage required for viral infection.</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Istradefylline, an adenosine A2a receptor antagonist, inhibits the CD4<sup>+</sup> T-cell hypersecretion of IL-17A and IL-8 in humans</strong> - Extracellular adenosine produced from ATP plays a role in energy processes, neurotransmission, and inflammatory responses. Istradefylline is a selective adenosine A2a receptor (A2aR) antagonist used for the treatment of Parkinson’s disease. We previously showed using mouse models that adenosine primes hypersecretion of interleukin (IL)-17A via A2aR, which plays a role in neutrophilic inflammation models in mice. This finding suggests that adenosine is an endogenous modulator of neutrophilic…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>THE COVID-19 ORAL DRUG MOLNUPIRAVIR IS A CES2 SUBSTRATE: POTENTIAL DRUG-DRUG INTERACTIONS AND IMPACT OF CES2 GENETIC POLYMORPHISM IN VITRO</strong> - Molnupiravir is one of the two COVID-19 oral drugs that were recently granted the emergency use authorization by the Food and Drug Administration (FDA). Molnupiravir is an ester and requires hydrolysis to exert antiviral activity. Carboxylesterases constitute a class of hydrolases with high catalytic efficiency. Humans express two major carboxylesterases (CES1 and CES2) that differ in substrate specificity. Based on the structural characteristics of molnupiravir, this study was performed to…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Low Prevalence of Mild Alpha-1-Antitrypsin Deficiency in Hospitalized COVID-19-Patients</strong> - CONCLUSION: Mild AATD (PI<em>MS or PI</em>MZ) was rare in a small cohort of hospitalized patients with COVID-19 in a study setting with a high background prevalence of AATD.</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Recent advances in antiviral effects of probiotics: potential mechanism study in prevention and treatment of SARS-CoV-2</strong> - SARS-CoV-2 is responsible for coronavirus disease 2019 (COVID-19), progressively extended worldwide countries on an epidemic scale. Along with all the drug treatments suggested to date, currently, there are no approved management protocols and treatment regimens for SARS-CoV-2. The unavailability of optimal medication and effective vaccines against SARS-CoV-2 indicates the requirement for alternative therapies. Probiotics are living organisms that deliberate beneficial effects on the host when…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Skills-approximate occupations: using networks to guide jobs retraining</strong> - An issue often confronting economic development agencies is how to minimize unemployment due to disruptions like technological change, trade wars, recessions, or other economic shocks. Decision makers are left to craft policies that can absorb surplus labor with as little pain to workers as possible. The questions they face include how to re-employ displaced workers and how to fill labor shortages. To address such questions, we quantify the proximity of any two occupations based on the skills…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Inhibition of SARS-CoV-2 wild-type (Wuhan-Hu-1) and Delta (B.1.617.2) strains by marine Sulfated Glycans</strong> - The COVID-19 pandemic has steered the global therapeutic research efforts towards the discovery of potential anti-SARS-CoV-2 molecules. The role of the viral spike glycoprotein (S-protein) has been clearly established in SARS-CoV-2 infection through its capacity to bind to the host cell surface heparan sulfate proteoglycan (HSPG) and angiotensin-converting enzyme-2 (ACE2). The antiviral strategies targeting these two virus receptors are currently under intense investigation. However, the rapid…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>JAK Inhibition as a New Treatment Strategy for Patients with COVID-19</strong> - The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic continues to spread globally. The rapid dispersion of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 drives an urgent need for effective treatments, especially for patients who develop severe pneumonia. The excessive and uncontrolled release of pro-inflammatory cytokines has proved to be an essential factor in the rapidity of disease progression, and some cytokines are significantly associated with adverse…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Ångstrom-scale silver particles potently combat SARS-CoV-2 infection by suppressing the ACE2 expression and inflammatory responses</strong> - The SARS-CoV-2 pandemic has become a severe global public health event, and the development of protective and therapeutic strategies is urgently needed. Downregulation of angiotensin converting enzyme 2 (ACE2; one of the important SARS-CoV-2 entry receptors) and aberrant inflammatory responses (cytokine storm) are the main targets to inhibit and control COVID-19 invasion. Silver nanomaterials have well-known pharmaceutical properties, including antiviral, antibacterial, and anticancer…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>SARS-CoV-2 fusion-inhibitory lipopeptides maintain high potency against divergent variants of concern (VOCs) including Omicron</strong> - The emergence of SARS-CoV-2 Omicron and other variants of concern (VOCs) has brought huge challenges to control the COVID-19 pandemic, calling for urgent development of effective vaccines and therapeutic drugs. In this study, we focused on characterizing the impacts of divergent VOCs on the antiviral activity of lipopeptide-based fusion inhibitors that we previously developed. First, we found that pseudoviruses bearing the S proteins of five VOCs (Alpha, Beta, Gamma, Delta, and Omicron) and one…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Pacritinib Inhibition of IRAK1 Blocks Aberrant TLR8 Signalling by SARS-CoV-2 and HIV-1-Derived RNA</strong> - Macrophages promote an early host response to infection by releasing pro-inflammatory cytokines such as interleukin (IL) 1β (IL-1β), tumour necrosis factor (TNF), and IL-6. One of the mechanisms through which cells sense pathogenic microorganisms is through Toll-like receptors (TLRs). IL-1 receptor-associated kinase (IRAK) 1, IRAK2, IRAK3, and IRAK4 are integral to TLR and IL-1 receptor signalling pathways. Recent studies suggest a role for aberrant TLR8 and NLRP3 inflammasome activation during…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Efficacious Preclinical Repurposing of the Nucleoside Analogue Didanosine against COVID-19 Polymerase and Exonuclease</strong> - Analogues and derivatives of natural nucleosides/nucleotides are considered among the most successful bioactive species of drug-like compounds in modern medicinal chemistry, as they are well recognized for their diverse and efficient pharmacological activities in humans, especially as antivirals and antitumors. Coronavirus disease 2019 (COVID-19) is still almost incurable, with its infectious viral microbe, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continuing to wreak…</p></li>
|
||
<li data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><p data-aos="fade-left" data-aos-anchor-placement="bottom-bottom"><strong>Pharmacokinetics, Pharmacodynamics and Antiviral Efficacy of the MEK Inhibitor Zapnometinib in Animal Models and in Humans</strong> - The mitogen-activated protein kinase (MEK) inhibitor zapnometinib is in development to treat acute viral infections like COVID-19 and influenza. While the antiviral efficacy of zapnometinib is well documented, further data on target engagement/pharmacodynamics (PD) and pharmacokinetics (PK) are needed. Here, we report zapnometinib PK and PD parameters in mice, hamsters, dogs, and healthy human volunteers. Mice received 25 mg/kg/day zapnometinib (12.5 mg/kg p. o. twice daily, 8 h interval)….</p></li>
|
||
</ul>
|
||
<h1 data-aos="fade-right" id="from-patent-search">From Patent Search</h1>
|
||
|
||
|
||
<script>AOS.init();</script></body></html> |