Synthesis, molecular docking, and dynamic simulation targeting main protease (Mpro) of new, Thiazole clubbed pyridine scaffolds as potential COVID-19 inhibitors

Many biological activities of pyridine and thiazole derivatives have been reported, including antiviral activity and, more recently, as COVID-19 inhibitors. Thus, in this paper, we designed, synthesized, and characterized a novel series of N-aminothiazole-hydrazineethyl-pyridines, beginning with a N′-(1-(pyridine-3-yl)ethylidene)hydrazinecarbothiohydrazide derivative and various hydrazonoyl chlorides and phenacyl bromides. Their Schiff bases were prepared from the condensation of N-aminothiazole derivatives with 4-methoxybenzaldehyde. FTIR, MS, NMR, and elemental studies were used to identify new products. The binding energy for non-bonding interactions between the ligand (studied compounds) and receptor was determined using molecular docking against the SARS-CoV-2 main protease (PDB code: 6LU7). Finally, the best docked pose with highest binding energy (8a = −8.6 kcal/mol) was selected for further molecular dynamics (MD) simulation studies to verify the outcomes and comprehend the thermodynamic properties of the binding. Through additional in vitro and in vivo research on the newly synthesized chemicals, it is envisaged that the achieved results will represent a significant advancement in the fight against COVID-19

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

The Saudi Critical Care Society practice guidelines on the management of COVID-19 in the ICU: Therapy section

BACKGROUND: The rapid increase in coronavirus disease 2019 (COVID-19) cases during the subsequent waves in Saudi Arabia and other countries prompted the Saudi Critical Care Society (SCCS) to put together a panel of experts to issue evidence-based recommendations for the management of COVID-19 in the intensive care unit (ICU). METHODS: The SCCS COVID-19 panel included 51 experts with expertise in critical care, respirology, infectious disease, epidemiology, emergency medicine, clinical pharmacy, nursing, respiratory therapy, methodology, and health policy. All members completed an electronic conflict of interest disclosure form. The panel addressed 9 questions that are related to the therapy of COVID-19 in the ICU. We identified relevant systematic reviews and clinical trials, then used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach as well as the evidence-to-decision framework (EtD) to assess the quality of evidence and generate recommendations. RESULTS: The SCCS COVID-19 panel issued 12 recommendations on pharmacotherapeutic interventions (immunomodulators, antiviral agents, and anticoagulants) for severe and critical COVID-19, of which 3 were strong recommendations and 9 were weak recommendations. CONCLUSION: The SCCS COVID-19 panel used the GRADE approach to formulate recommendations on therapy for COVID-19 in the ICU. The EtD framework allows adaptation of these recommendations in different contexts. The SCCS guideline committee will update recommendations as new evidence becomes available

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Statistical Machine Learning Regression Models for Salary Prediction Featuring Economy Wide Activities and Occupations

A holistic occupational and economy-wide framework for salary prediction is developed and tested using statistical machine learning (ML). Predictive models are developed based on occupational features and organizational characteristics. Five different supervised ML algorithms are trained using survey data from the Saudi Arabian labor market to estimate mean annual salary across economic activities and major occupational groups. In predicting the mean salary over economic activities, the Bayesian Gaussian process regression ML showed a marked improvement in R2 over multiple linear regression (from 0.50 to 0.98). Moreover, lower error levels were obtained: root-mean-square error was reduced by 80% and mean absolute error was reduced by almost 90% compared to multiple linear regression. However, the salary prediction over major occupational groups resulted in artificial neural networks performing the best in terms of both R2, with an improvement from 0.62 in multiple linear regression to 0.94 and errors were reduced by approximately 60%. The proposed framework can help estimate annual salary levels across different types of economic activities and organization sizes, as well as different occupations

A unique presentation of metastatic esophageal adenocarcinoma: The painful thigh

The incidence of esophageal adenocarcinoma is increasing, and with this increase is an influx of unusual presentations in the literature. Skeletal muscles are generally rare as sites of metastasis. We report a case of a middle aged-man who presented with a painful swelling of the thigh which turned out to be consistent with esophageal adenocarcinoma metastasis. Few reports have preceded ours. The prognosis is poor and the therapeutic modalities of such an advanced disease are limited

Implementation of medication reconciliation at admission and discharge in Ministry of Defense Health Services hospitals: a multicentre study

There is potential for many medication errors to occur due to the complex medication use process. The medication reconciliation process can significantly lower the incidence of medication errors that may arise from an incomplete or inaccurate medication history as well as reductions in length of hospital stay, patients’ readmissions and lower healthcare costs.The quality improvement collaborative project was conducted as a pilot study in two hospitals, then implemented on a broader scale in 18 hospitals in Saudi Arabia. The goal of the project was to reduce the percentage of patients with at least one outstanding unintentional discrepancy at admission by 50%, over 16-month period (July 2020–November 2021). Our interventions were based on the High 5’s project medication reconciliation WHO, and Medications at Transitions and Clinical Handoffs toolkit for medication reconciliation by Agency for Healthcare Research and Quality. Improvement teams used the Institute of Healthcare Improvement’s (IHI’s) Model for improvement as a tool for testing and implementing changes. Collaboration and learning between hospitals were facilitated by conducting learning sessions using the IHI’s Collaborative Model for Achieving Breakthrough Improvement. The improvement teams underwent three cycles.By the end of the project significant improvements were observed. The percentage of patients with at least one outstanding unintentional discrepancy at admission showed a 20% reduction (27% before, 7% after; p value <0.05) (Relative Risk (RR) 0.74) with a mean reduction in the number of discrepancies per patient by 0.74. The percentage of patients with at least one outstanding unintentional discrepancy at discharge showed 12% reduction (17% before, 5% after; p value <0.05) (RR 0.71) with a mean reduction in the number of discrepancies per patient by 0.34.Compliance to medication reconciliation documentation within 24 hours of admission and discharge showed significant improvement by an average of 17% and 24%, respectively. Additionally, the implementation of medication reconciliation had a negative correlation with the percentage of patients with at least one outstanding unintentional discrepancy at admission and discharge