Hjorthnoer6669

Hospital admissions (OR 0∙80, 95%CI 0∙51 - 1∙28), and length of stay (-1∙89 days, 95%CI -4∙57 - 0∙78) were lower for cases, while Ct values were higher (30∙8 versus 28∙8, p = 0.053). B.1.1.7 was the predominant lineage in cases (100/108, 92.6%) and controls (341/446, 76.5%). Genomic analysis identified one post-vaccination case harboring the E484K vaccine escape mutation (B.1.525 lineage).

Previous vaccination reduces mortality when B.1.1.7 is the predominant lineage. No significant lineage-specific genomic changes during phylogenetic, SNP and MVA analysis were detected.

Previous vaccination reduces mortality when B.1.1.7 is the predominant lineage. No significant lineage-specific genomic changes during phylogenetic, SNP and MVA analysis were detected.The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. Artificial intelligence (AI) and machine learning (ML) offer promising solutions that could accelerate the discovery and optimization of new antivirals. Motivated by this, in this paper, we present an extensive survey on the application of AI and ML for combating COVID-19 based on the rapidly emerging literature. Particularly, we point out the challenges and future directions associated with state-of-the-art solutions to effectively control the COVID-19 pandemic. We hope that this review provides researchers with new insights into the ways AI and ML fight and have fought the COVID-19 outbreak.

Cipargamin (KAE609) is a potent antimalarial in Phase II. Here we report efficacy, pharmacokinetics, and resistance marker analysis across a range of cipargamin doses. These were secondary endpoints from a study primarily conducted to assess the hepatic safety of cipargamin (hepatic safety data are reported elsewhere).

This Phase II, multicenter, randomized, open-label, dose-escalation trial was conducted in sub-Saharan Africa, in adults with uncomplicated P. falciparum malaria. Cipargamin monotherapy was given as single doses up to 150mg or up to 50mg once daily for 3 days, with artemether-lumefantrine as control. Key efficacy endpoints were parasite clearance time (PCT), and PCR-corrected and uncorrected adequate clinical and parasitological response (ACPR) at 14 and 28 days. Pharmacokinetics and molecular markers of drug resistance were also assessed.

All single or multiple cipargamin doses ≥50mg were associated with rapid parasite clearance, with median PCT of 8 hours versus 24 hours for artemether-lumefantrine. PCR-corrected ACPR at 14 and 28 days was over 75% and 65%, respectively, for each cipargamin dose. A treatment-emerging mutation in the Pfatp4 gene, G358S, was detected in 65% of treatment failures. Pharmacokinetic parameters were consistent with previous data, and approximately dose proportional.

Cipargamin, at single doses of 50mg to 150mg was associated with very rapid parasite clearance, PCR-corrected ACPR at 28 days of over 65% in adults with uncomplicated P. falciparum malaria and recrudescent parasites frequently harboured a treatment-emerging mutation. Cipargamin will be further developed with a suitable combination partner.

NCT03334747.

NCT03334747.To design a simple and reproducible classifier predicting the overall survival (OS) of patients with acute myeloid leukemia (AML) ≥60 years of age treated with 7 + 3, we sequenced 37 genes in 471 patients from the ALFA1200 (Acute Leukemia French Association) study (median age, 68 years). DBZ inhibitor molecular weight Mutation patterns and OS differed between the 84 patients with poor-risk cytogenetics and the 387 patients with good (n = 13), intermediate (n = 339), or unmeasured (n = 35) cytogenetic risk. TP53 (hazards ratio [HR], 2.49; P = .0003) and KRAS (HR, 3.60; P = .001) mutations independently worsened the OS of patients with poor-risk cytogenetics. In those without poor-risk cytogenetics, NPM1 (HR, 0.57; P = .0004), FLT3 internal tandem duplications with low (HR, 1.85; P = .0005) or high (HR, 3.51; P less then 10-4) allelic ratio, DNMT3A (HR, 1.86; P less then 10-4), NRAS (HR, 1.54; P = .019), and ASXL1 (HR, 1.89; P = .0003) mutations independently predicted OS. Combining cytogenetic risk and mutations in these 7 genes, 39.1% of patients could be assigned to a "go-go" tier with a 2-year OS of 66.1%, 7.6% to the "no-go" group (2-year OS 2.8%), and 3.3% of to the "slow-go" group (2-year OS of 39.1%; P less then 10-5). Across 3 independent validation cohorts, 31.2% to 37.7% and 11.2% to 13.5% of patients were assigned to the go-go and the no-go tiers, respectively, with significant differences in OS between tiers in all 3 trial cohorts (HDF [Hauts-de-France], n = 141, P = .003; and SAL [Study Alliance Leukemia], n = 46; AMLSG [AML Study Group], n = 223, both P less then 10-5). The ALFA decision tool is a simple, robust, and discriminant prognostic model for AML patients ≥60 years of age treated with intensive chemotherapy. This model can instruct the design of trials comparing the 7 + 3 standard of care with less intensive regimens.Propensity score (PS) methods are popular when estimating causal effects in non-randomized studies. Drawing causal conclusion relies on the unconfoundedness assumption. This assumption is untestable and is considered more plausible if a large number of pre-treatment covariates are included in the analysis. However, previous studies have shown that including unnecessary covariates into PS models can lead to bias and efficiency loss. With the ever-increasing amounts of available data, such as the omics data, there is often little prior knowledge of the exact set of important covariates. Therefore, variable selection for causal inference in high-dimensional settings has received considerable attention in recent years. However, recent studies have focused mainly on binary treatments. In this study, we considered continuous treatments and proposed the generalized outcome-adaptive LASSO (GOAL) to select covariates that can provide an unbiased and statistically efficient estimation. Simulation studies showed that when the outcome model was linear, the GOAL selected almost all true confounders and predictors of outcome and excluded other covariates. The accuracy and precision of the estimates were close to ideal. Furthermore, the GOAL is robust to model misspecification. We applied the GOAL to seven DNA methylation datasets from the Gene Expression Omnibus database, which covered four brain regions, to estimate the causal effects of epigenetic aging acceleration on the incidence of Alzheimer's disease.Digital technologies govern a large part of our social lives, including the pursuit of a romantic partner. Despite recent inquiries into the social consequences of meeting online, what remains unclear is how the link between education and union formation varies in online versus offline meeting contexts, particularly on the backdrop of growing educational gaps in marriage. Using 2008-2019 pairfam data from Germany (N = 3,561), this study ran a series of Fine-Gray competing risks models to assess how online dating shapes the transition to marriage for partnered adults with nontertiary and tertiary education. Results reveal that irrespective of education, men in online-formed couples had greater chances of marrying than men in couples established offline. Highly educated women who met their partner in nondigital ways were less prone to marry than lower-educated women; for women in couples initiated online, however, the pattern was reversed. The internet dating marriage advantage of well-educated women was partly related to better matching on marriage attitudes and gender ideology. Facing a scarcity of eligible partners offline, high-educated women draw on more abundant online options to select more egalitarian-minded men. This study overall suggests that internet dating fosters an uneven distribution of opportunities for marriage, highlighting the role of digital partner markets in the social demography of union formation.Xylem is a complex tissue that forms the bulk of tree bodies and has several functions, including to conduct water, store water and nutrients, and biomechanically support the plant body. We examined how xylem functional traits varied at different positions within Populus balsamifera spp. trichocarpa (Black Cottonwood). Whole trees were excavated, and xylem samples were collected at 1m increments along the main root-to-shoot axis of six trees, from root tip to shoot tip. We examined biomechanical and water storage traits of the xylem, including using a non-invasive imaging technique to examine water content within long, intact branches (high resolution computed tomography; microCT). Xylem density, strength, and stiffness were higher in shoots than roots. Along the main root-to-shoot axis, xylem strength and stiffness were greatest at shoot tips and tissue became linearly weaker and less stiff down the plant and through the root. Roots had greater water storage with reduced biomechanical support, and shoots had biomechanically stronger and stiffer xylem with reduced water storage. These findings support trade-offs among xylem functions between roots and shoots. Understanding how xylem functions differ throughout tree bodies is important in understanding whole-tree function and how terrestrial plants endure numerous environmental challenges over decades of growth.Completion of a 5-day course of remdesivir was associated with approximately 17-fold increased odds of survival among a sample of 54 nursing home residents with SARS-CoV-2 infection during the course of an outbreak from October to December, 2020. Remdesivir was well-tolerated; administration was logistically feasible in a pre-hospital environment.

The Systemic Lupus International Collaborating Clinics (SLICC) frailty index (FI) was recently developed as a measure of susceptibility to adverse outcomes in systemic lupus erythematosus (SLE). We aimed to externally validate the SLICC-FI in a prevalent cohort of individuals with more longstanding SLE.

This secondary analysis included data from a single-centre prospective cohort of adult patients with established SLE (disease duration >15 months at enrolment). The baseline visit was the first at which both SLICC/ACR Damage Index (SDI) and Short Form-36 (SF-36) data were available. Baseline SLICC-FI scores were calculated. Cox regression models estimated the association between baseline SLICC-FI values and mortality risk. Negative binomial regression models estimated the association of baseline SLICC-FI scores with the rate of change in SDI scores during follow-up.

The 183 eligible SLE patients were mostly female (89%) with mean (SD) age 45.2 (13.2) years and median (interquartile range) disease duration 12.4 (7.8-17.4) years at baseline. Mean (SD) baseline SLICC-FI score was 0.17 (0.09), with 54 patients (29.5%) classified as frail (SLICC-FI >0.21). Higher baseline SLICC-FI values (per 0.05 increase) were associated with increased mortality risk (Hazard Ratio 1.31; 95%CI 1.01-1.70), after adjusting for age, sex, education, SLE medication use, disease duration, smoking status, and baseline SDI. Higher baseline SLICC-FI values (per 0.05 increase) were associated with increased damage accrual over time (Incidence Rate Ratio 1.18; 95%CI 1.07-1.29), after adjusting for potential confounders.

Frailty, measured using the SLICC-FI, predicts organ damage accrual and mortality risk among individuals with established SLE.

Frailty, measured using the SLICC-FI, predicts organ damage accrual and mortality risk among individuals with established SLE.