COVID-19 pandemic has underlined the impact of emergent pathogens as a major threat for human health. The development of quantitative approaches to advance comprehension of the current outbreak is urgently needed to tackle this severe disease. Considering different starting times of infection, mathematical models are proposed to represent SARS-CoV-2 dynamics in infected patients. Based on the target cell limited model, the within-host reproductive number for SARS-CoV-2 is consistent with the broad values of human influenza infection. The best model to fit the data was including immune cell response, which suggests a slow immune response peaking between 5 to 10 days post-onset of symptoms. The model with the eclipse phase, time in a latent phase before becoming productively infected cells, was not supported. Interestingly, all models predict that SARS-CoV-2 may replicate very slowly in the first days after infection, and viral load could be below detection levels during the first 4 days post infection. A quantitative comprehension of SARS-CoV-2 dynamics and the estimation of standard parameters of viral infections is the key contribution of this pioneering work. These models can serve for future evaluation of control theoretical approaches to tailor new potential drugs against COVID-19.

Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. We further show that including ReSCoSS conformers significantly improves COSMO-RS based predictions of physicochemical properties over single-conformation approaches. ReSCoSS has found broad adoption in the in-house drug discovery and development work streams and has contributed to establishing quantum-chemistry methods as a strategic pillar in ligand discovery.

Coronavirus disease 2019 (COVID-19) and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a particular risk to people living with preexisting conditions that impair immune response or amplify pro-inflammatory response. Low-grade chronic systemic inflammation, common in people with obesity, is associated with the development of atherosclerosis, type 2 diabetes, and hypertension, well known comorbidities that adversely affect the outcomes of patients with COVID-19. Risk stratification based on the Edmonton Obesity Staging System (EOSS), which classifies obesity based on the presence of medical, mental, and/or functional complications rather than on body mass index (BMI), has been shown to be a better predictor of all-cause mortality and it may well be that EOSS stages may better describe the risk of hyperinflammation in patients with COVID-19 infection. Analyzing a group of metabolic ill patients with obesity (EOSS 2 and 3), we found an increased interleukin-6 and linear regression analysis showed a positive correlation with C-reactive protein (CRP) (p = 0.014) and waist-to-hip-ratio (WHR) (p = 0.031). Physicians should be aware of these findings in patients with COVID-19 infection. Early identification of possible hyperinflammation could be fundamental and should guide decision making regarding hospitalization, early respiratory support, and therapy with immunosuppression to improve mortality.

Diagnosis and hospitalization for COVID-19 are disproportionately higher among black persons The purpose of this study was to explore the lived experience of being diagnosed with COVID-19 among black patients Semistructured one-on-one interviews with black patients diagnosed with COVID-19 were conducted Data were analyzed using conventional content analysis and a directed content approach Fifteen patients participated and 3 themes were identified: Panic amidst a COVID-19 diagnosis, Feeling the repercussion of the diagnosis, and Personal assessment of risks within one's individual environment Fear of dying, inadequate health benefits, financial issues, and worries about spreading the virus to loved ones were acknowledged by the patients as critical areas of concerns Majority of the patients looked to God as the ultimate way of surviving COVID-19 However, none of the patients reported receiving support for spiritual needs from health care providers This is the first study to investigate the lived experience of being diagnosed with COVID-19 among black patients Our results highlight several factors that put this group at increased risk for COVID-19 and where additional strategies are needed to address these inadequacies Integrating public health interventions to reduce socioeconomic barriers and integrating spirituality into clinical care could improve patient care delivery

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in East China, raising questions about the well-established relationship between human activities and air quality Here, using comprehensive measurements and modeling, we show the haze during the COVID lockdown were driven by enhancements of secondary pollution In particular, large decreases in NOx emissions from transportation increased ozone and nighttime NO3 radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants

OBJECTIVE: The aim of this study was to analyse the 2020 burden of Systemic Lupus Erythematosus (SLE) in Europe, from the patients perspective. METHODS: In May 2020, Lupus Europe, the European umbrella patient association for SLE, designed and disseminated a multilingual anonymous online survey to individuals with a self-reported physicians diagnosis of SLE living in Europe. RESULTS: Data from 4375 SLE survey respondents (95.9% women, median age: 45 (IQR: 36C54) years, 70.7% Caucasians) from 35 European countries were analysed. The median age at SLE diagnosis was 30 years (IQR: 22C40) and the median diagnosis delay was 2 years (IQR: 0C6). The most commonly affected organ-systems included the joints (81.8%) and skin (59.4%), with renal involvement in 30%. Another diagnosis was given before that of SLE in 45.0%, including psychological/mental disorders in 9.1% and fibromyalgia in 5.9%. The median number of symptoms reported was 9 (IQR: 6C11) out of 21, with fatigue most common (85.3%) and most bothersome. The median number of SLE-related medications was 5 (IQR: 3C7), including antimalarials (75%), oral glucocorticoids (52.4%), immunosuppressants (39.8%) and biologics (10.9%). Respondents reported significant impact over their studies, career and emotional/sexual life in 50.7%, 57.9% and 38.2%, respectively. Appropriate access to care was highly variable across countries and care component. CONCLUSION: This survey underlines the 2020 burden and strong heterogeneity in the care of SLE across Europe, from the patients perspective. Altogether, these data may prove crucial to physicians, patients and policy-makers to improve the diagnosis and management of this rare and complex disease.

Since the start of COVID-19, several relevant corpora from various sources are presented in the literature that contain millions of data points. While these corpora are valuable in supporting many analyses on this specific pandemic, researchers require additional benchmark corpora that contain other epidemics to facilitate cross-epidemic pattern recognition and trend analysis tasks. During our other efforts on COVID-19 related work, we discover very little disease related corpora in the literature that are sizable and rich enough to support such cross-epidemic analysis tasks. In this paper, we present EPIC30M, a large-scale epidemic corpus that contains 30 millions micro-blog posts, i.e., tweets crawled from Twitter, from year 2006 to 2020. EPIC30M contains a subset of 26.2 millions tweets related to three general diseases, namely Ebola, Cholera and Swine Flu, and another subset of 4.7 millions tweets of six global epidemic outbreaks, including 2009 H1N1 Swine Flu, 2010 Haiti Cholera, 2012 Middle-East Respiratory Syndrome (MERS), 2013 West African Ebola, 2016 Yemen Cholera and 2018 Kivu Ebola. Furthermore, we explore and discuss the properties of the corpus with statistics of key terms and hashtags and trends analysis for each subset. Finally, we demonstrate the value and impact that EPIC30M could create through a discussion of multiple use cases of cross-epidemic research topics that attract growing interest in recent years. These use cases span multiple research areas, such as epidemiological modeling, pattern recognition, natural language understanding and economical modeling.

(1) Background: Hydroxychloroquine is used to treat malaria and autoimmune diseases, and its potential use against COVID-19 is currently under investigation. Thus far, information on interactions of hydroxychloroquine with drug transporters mediating drug-drug interactions is limited. We assessed the inhibition of important efflux (P-glycoprotein (P-gp), breast cancer resistance protein (BCRP)) and uptake transporters (organic anion transporting polypeptide (OATP)-1B1, OATP1B3, OATP2B1) by hydroxychloroquine, tested its P-gp and BCRP substrate characteristics, and evaluated the induction of pharmacokinetically relevant genes regulated by the nuclear pregnane X (PXR) (CYP3A4, ABCB1) and aryl hydrocarbon receptor (AhR) (CYP1A1, CYP1A2). (2) Methods: Transporter inhibition was evaluated in transporter over-expressing cell lines using fluorescent probe substrates. P-gp and BCRP substrate characteristics were assessed by comparing growth inhibition of over-expressing and parental cell lines. Possible mRNA induction was analysed in LS180 cells by quantitative real-time PCR. (3) Results: Hydroxychloroquine did not inhibit BCRP or the OATPs tested but inhibited P-gp at concentrations exceeding 10 M. P-gp overexpressing cells were 5.2-fold more resistant to hydroxychloroquine than control cells stressing its substrate characteristics. Hydroxychloroquine did not induce genes regulated by PXR or AhR. (4) Conclusions: This is the first evidence that hydroxychloroquines interaction potential with drug transporters is low, albeit bioavailability of simultaneously orally administered P-gp substrates might be increased by hydroxychloroquine.

Patient: Male, 73-year-old Final Diagnosis: Severe COVID-19 pneumonia complicated by right atrium thrombus Symptoms: Fever ? dyspnea ? cough Medication: Clinical Procedure: Specialty: Critical Care Medicine OBJECTIVE: Educational purpose BACKGROUND: Recent studies demonstrated evidence of coagulation dysfunction in hospitalized patients with severe coronavirus disease 2019 (COVID-19) due to excessive inflammation, hypoxia, platelet activation, endothelial dysfunction, and stasis. Effective anticoagulation therapy may play a dominant role in the management of severe COVID-19 cases. CASE REPORT: A 73-year-old man with a 6-day history of fever up to 38.5C, dyspnea, cough, and fatigue was diagnosed with COVID-19. He had a past medical history significant for hypertension and coronary artery bypass grafting. Two days after hospital admission, the patient developed acute respiratory failure, requiring intubation, mechanical ventilation, and transfer to the intensive care unit (ICU). He received treatment including antibiotics, hydroxychloroquine, tocilizumab, vasopressors, prone positioning, and anticoagulation with enoxaparin at a prophylactic dose. After a 15-day ICU stay, the patient was hemodynamically stable but still hypoxemic; a transthoracic echocardiogram at that time, followed by a transesophageal echocardiogram for better evaluation, revealed the presence of a right atrium thrombus without signs of acute right ventricular dilatation and impaired systolic function. Since the patient was hemodynamically stable, we decided to treat him with conventional anticoagulation under close monitoring for signs of hemodynamic deterioration; thus, the prophylactic dose of enoxaparin was replaced by therapeutic dosing, which was a key component of the patients successful outcome. Over the next few days he showed significant clinical improvement. The follow-up transesophageal echo-cardiogram 3 weeks after effective therapeutic anticoagulation revealed no signs of right heart thrombus. CONCLUSIONS: The presented COVID-19 case, one of the first reported cases with evidence of right heart thrombus by transesophageal echocardiography, highlights the central role of diagnostic imaging strategies and the importance of adequate anticoagulation therapy in the management of severe COVID-19 cases in the ICU.

Lessons from Florence Nightingale are just as relevant today as they were more than 150 years ago. Learn how nurse leaders can follow her lead and embrace the importance of nurturing highly motivated nurses who are critical thinkers.

The burden of COVID-19 has been noted to be disproportionately greater in minority women, a population that is nevertheless still understudied in COVID-19 research. We conducted an observational study to examine COVID-19-associated mortality and cardiovascular disease outcomes after testing (henceforth index) among a racially diverse adult women veteran population. We assembled a retrospective cohort from a Veterans Affairs (VA) national COVID-19 shared data repository, collected between February and August 2020. A case was defined as a woman veteran who tested positive for SARS-COV-2, and a control as a woman veteran who tested negative. We used Kaplan-Meier curves and the Cox proportional hazards model to examine the distribution of time to death and the effects of baseline predictors on mortality risk. We used generalized linear models to examine 60-day cardiovascular disease outcomes. Covariates studied included age, body mass index (BMI), and active smoking status at index, and pre-existing conditions of diabetes, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), and a history of treatment with antiplatelet or anti-thrombotic drug at any time in the 2 years prior to the index date. Women veterans who tested positive for SARS-CoV-2 had 4 times higher mortality risk than women veterans who tested negative (Hazard Ratio 3.8, 95% Confidence Interval CI 2.92 to 4.89) but had lower risk of cardiovascular events (Odds Ratio OR 0.78, 95% CI 0.66 to 0.92) and developing new heart disease conditions within 60 days (OR 0.67, 95% CI 0.58 to 0.77). Older age, obesity (BMI > 30), and prior CVD and COPD conditions were positively associated with increased mortality in 60 days. Despite a higher infection rate among minority women veterans, there was no significant race difference in mortality, cardiovascular events, or onset of heart disease. SARS-CoV-2 infection increased short-term mortality risk among women veterans similarly across race groups. However, there was no evidence of increased cardiovascular disease incidence in 60 days. A longer follow-up of women veterans who tested positive is warranted.

Purpose: This study attempts to identify the supply chain risks (SCRs) induced during the COVID-19 disruption in an Indian handloom saree industry and determine suitable risk mitigation strategies (RMSs) to overcome the impact of the epidemic disruption Design/methodology/approach: This work determined 11 SCRs through an extensive literature review in the context of the handloom apparel industry and validated through the experts Further, a multiple case-based approach is used in this research Within case and cross-case analyses of four relevant Indian handloom make-to-order saree manufacturing firms are conducted to determine the severity of the SCRs considering the pandemic situations to identify appropriate strategies to mitigate the shock of SCRs Findings: This study identified the critical SCRs in the context of the Indian handloom make-to-order saree industries that emerged during the COVID-19 and proposed a risk mitigation strategy matrix (RMSM) to address the SCRs based on their criticality and predictability dimensions Research limitations/implications: The study provides a novel contribution to the body of knowledge on supply chain risk management (SCRM) in the form of the RMSM tool Supply chain managers from the different sectors can extend the proposed RMSM to overcome the SCRs Multiple case analyses facilitate supply chain professionals working in handloom apparel industries to benchmark and adopt the proposed RMSs in their firm Originality/value: This research is one of its kind that carried exploratory investigation of the handloom apparel industry cases to assess and determine the strategies for mitigating the SCRs caused during a pandemic outbreak ? 2021, Emerald Publishing Limited

The current global health problem caused by SARS-CoV-2 has challenged the scientific community in various ways. Therefore, worldwide several scientific groups are exploring SARS-CoV-2 from different aspects including its origin, spread, severe infectivity, and also to find a cure. It is now well known that spike glycoprotein helps SARS-CoV-2 to enter inside the human host through a cellular receptor ACE2. However, the role of coevolutionary forces that makes SARS-CoV-2 spike glycoprotein more fit towards its human host remains unexplored. Therefore, in present bioinformatics study we identify coevolving amino acids in spike glycoprotein. Additionally, the effects of coevolution on the stability of the spike glycoprotein as well as its binding with receptor ACE2 were predicted. The results clearly indicate that coevolutionary forces play a pivotal role in increasing the fitness of spike glycoprotein against ACE2.

We measured the cleavage of angiotensin I (Ang I) metabolites by angiotensin I-converting enzyme (ACE) in cultured cells and examined how they augment actions of bradykinin B2 receptor agonists. Monolayers of Chinese hamster ovary cells transfected to stably express human ACE and bradykinin B2 receptors coupled to green fluorescent protein (B2GFP) or to express only coupled B2GFP receptors. We used 2 ACE-resistant bradykinin analogues to activate the B2 receptors. We used high-performance liquid chromatography to analyze the peptides cleaved by ACE on cell monolayers and found that Ang 1-9 was hydrolyzed 18x slower than Ang I and &30% slower than Ang 1-7. Ang 1-7 was cleaved to Ang 1-5. Although micromol/L concentrations of slowly cleaved substrates Ang 1-7 and Ang 1-9 inhibit ACE, they resensitize the desensitized B2GFP receptors in nmol/L concentration, independent of ACE inhibition. This is reflected by release of arachidonic acid through a mechanism involving cross-talk between ACE and B2 receptors. When ACE was not expressed, the Ang 1-9, Ang 1-7 peptides were inactive. Inhibitors of protein kinase C-alpha, phosphatases and Tyr-kinase blocked this resensitization activity, but not basal B2 activation by bradykinin. Ang 1-9 and Ang 1-7 enhance bradykinin activity, probably by acting as endogenous allosteric modifiers of the ACE and B2 receptor complex. Consequently, when ACE inhibitors block conversion of Ang I, other enzymes can still release Ang I metabolites to enhance the efficacy of ACE inhibitors.

The prevalence of upper tract infection / ARI in primary schools is 15% in 2019. Currently, upper respiratory infections cause most students to be absent from school compared to other disease factors. One of the most important causes of ARI is hand hygiene;therefore, washing hands using soap is the most critical effort to reduce ARI's prevalence in primary schools. This study aimed to determine the effect of the online video competition model on elementary school students to improve the ability to wash hands in 6 steps. The research design was an experimental control group. The number of research subjects was 30 students for the treatment group and 30 students for the untreated group. The length of the study is one month. The results showed that students who took part in online competitions experienced a significant increase in knowledge, attitudes, and behavior towards washing hands using soap. The research results on the intervention video competition as an educational medium about washing hands six steps compared to the control group. The video competition improves the ability to do handwashing in 6 steps, namely by doing, seeing, and listening.

Objectives: In communities across the United States, large numbers of children and adolescents with acute psychiatric presentations are being held for days and weeks in emergency departments and pediatric medical units, awaiting placement for inpatient psychiatric hospital treatment. These settings are not designed to safely and effectively care for these children. The prolonged waiting is usually attributed to an inadequate supply of beds, and the solution seems self-evident: build more beds. This simple statement belies the complexity of determining the adequate number of beds for a given community, a number dependent on a variety of factors including the epidemiology of childrens mental illness, social determinants of health, the functioning of other mental health services, and the availability of community supports. The aim of this session is to provide a detailed background of the scope of our inpatient access problem and its consequences. Methods: Available state and national data will be reviewed and synthesized to describe the availability and distribution of inpatient child and adolescent psychiatry hospital beds. The impact of the limitation in beds on children and adolescents and families as well as healthcare systems will be described. The needs of special populations and the clinical profiles of patients most likely to experience prolonged boarding will be reviewed. As a case example, the efforts of state regulators in Massachusetts to address this problem will be described. Results: Boarding of children and adolescents with acute mental illness has been associated with scarcity and maldistribution of inpatient beds and is highly prevalent and widespread across the United States. The problem appears to have been severely exacerbated during the SARS-CoV-2 pandemic. Conclusions: Boarding of children in emergency departments is associated with elevated safety risks, poor clinical quality, poor patient experience, disruption of nonpsychiatric emergency services, and excessive costs. In order to address this issue, state and local policymakers need tools to determine the number and types of childrens psychiatric inpatient units needed for their communities. ICP, CC, PUP

OBJECTIVE: To develop a population pharmacokinetic model for lopinavir boosted by ritonavir in coronavirus disease 2019 (Covid-19) patients. METHODS: Concentrations of lopinavir/ritonavir were assayed by an accredited LC-MS/MS method. The population pharmacokinetics of lopinavir was described using non-linear mixed-effects modeling (NONMEM version 7.4). After determination of the base model that better described the data set, the influence of covariates (age, body weight, height, body mass index (BMI), gender, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), C reactive protein (CRP), and trough ritonavir concentrations) was tested on the model. RESULTS: From 13 hospitalized patients (4 females, 9 males, age = 64 16 years), 70 lopinavir/ritonavir plasma concentrations were available for analysis. The data were best described by a one-compartment model with a first-order input (KA). Among the covariates tested on the PK parameters, only the ritonavir trough concentrations had a significant effect on CL/F and improved the fit. Model-based simulations with the final parameter estimates under a regimen lopinavir/ritonavir 400/100 mg b.i.d. showed a high variability with median concentration between 20 and 30 mg/L (Cmin/Cmax) and the 90% prediction intervals within the range 1-100 mg/L. CONCLUSION: According to the estimated 50% effective concentration of lopinavir against SARS-CoV-2 virus in Vero E6 cells (16.7 mg/L), our model showed that at steady state, a dose of 400 mg b.i.d. led to 40% of patients below the minimum effective concentration while a dose of 1200 mg b.i.d. will reduce this proportion to 22%.

El brote actual de la enfermedad por coronavirus (COVID-19), que se inform por primera vez en Wuhan, China, el 31 de diciembre de 2019, ha dejado un saldo al 19 de abril de 2020 de ms de 3500000 infectados y 160000 muertes en 185 pases. En este trabajo utilizamos un modelo basado en el Mtodo de Cadena Microscpica de Markov (MCMM, Markov Microscopic Chain Approach) para estimar la propagacin del COVID-19 en la ciudad de Pereira (Risaralda-Colombia). Este modelo incorpora importantes aspectos de la poblacin, relacionados con: ubicacin espacial dentro de la ciudad discretizada por comunas, movilidad entre comunas, estratificacin por grupos de edad y separacin de individuos en siete compartimientos epidemiolgicos. Este modelo se utiliza para predecir, en una lnea de tiempo, la incidencia de epidemias en poblaciones geolocalizadas, lo que se traduce en una herramienta indicadora para tomar medidas de control. As, el resultado de la metodologa caracteriza la evolucin en el tiempo y el espacio de la proporcin de los individuos en cada uno de los compartimientos epidemiolgicos y en cada grupo etario. Los datos que se refieren a COVID-19, desde la municipalidad de Pereira, hasta el 20 de abril de 2020, se utilizan para alimentar el modelo y obtener las proyecciones espacio-temporales. Los resultados presentados consideran mltiples escenarios de movilidad, de forma que el aplanamiento de las curvas de los diferentes compartimientos epidemiolgicos pueda ser visualizados de acuerdo a diferentes estrategias de confinamiento. Por tratarse de un modelo espacio-temporal, los resultados del modelo pueden ser presentados fcilmente como mapas de calor sobre cada uno de los compartimientos epidemiolgicos, a fin de facilitar los procesos de toma de decisiones.Alternate : The current outbreak of coronavirus disease (COVID-19), which was first reported in Wuhan, China on December 31, 2019, has left a balance as of April 19, 2020 of more than 3500000 infected and 160000 deaths in 185 countries. In this work we use a model based on the Markov Microscopic Chain Approach (MMCA) to estimate the spread of COVID-19 in the city of Pereira (Risaralda-Colombia). This model incorporates important aspects of the population related to spatial location within the city which is discretized by communes, mobility between communes, stratification by age groups and separation of individuals into seven epidemiological compartments. This model is used to predict, in a timeline, the incidence of epidemics in geolocated populations, which translates into an indicator tool to take control measures. The data referring to COVID-19, from the municipality of Pereira, until April 20, 2020 are used to feed the model and obtain the spatio-temporal projections. The results presented consider multiple mobility scenarios, so that the flattening of the curves of the different epidemiological compartments can be visualized according to different confinement strategies. As it is a spatio-temporal model, the results of the model can easily be presented as heat over each of the epidemiological compartments, in order to facilitate decision-making processes.

Virome (viral megagenomics) detection using next generation sequencing has been widely applied in virology, but its methods remain complicated and need optimization. In this study, we detected the viromes of RNA viruses of one mock sample, one pooled duck feces sample and one pooled mink feces sample on the Personal Genome Machine platform using the sequencing libraries prepared by three methods. The sequencing primers were added through random hybridization and ligation to fragmented viral RNA using a RNA-Seq kit in method 1, through random reverse transcription (RT) and polymerase chain reaction (PCR) in method 2 which was developed in our laboratory, and through hybridization and ligation to fragmented amplicons of random RT-PCR using a single primer in method 3. Although the results of these three samples (nine libraries) all showed that more classified viral families and genera were identified using methods 2 and 3 than using method 1, and more classified viral families and genera were identified using method 2 than using method 3, most of the differences were of no statistical significance. Moreover, 11 mammalian viral genera in minks were possibly identified for the first time through this study.

Lung transplantation has become an established therapy for end-stage lung diseases. Early postoperative complications can impact immediate, mid-term, and long-term outcomes. Appropriate management, prevention, and early detection of these early postoperative complications can improve the overall transplant course. In this review, we highlight the incidence, detection, and management of these early postoperative complications in lung transplant recipients.