The role of Toll-like receptor 10 in modulation of trained immunity

Toll-like receptor 10 (TLR10) is the only member of the human Toll-like receptor family with an inhibitory function on the induction of innate immune responses and inflammation. However, its role in the modulation of trained immunity (innate immune memory) is unknown. In the present study, we assessed whether TLR10 modulates the induction of trained immunity induced by beta-glucan or bacillus Calmette-Guerin (BCG). Interleukin 10 receptor antagonist production was increased upon activation of TLR10 ex vivo after BCG vaccination, and TLR10 protein expression on monocytes was increased after BCG vaccination, whereas anti-TLR10 antibodies did not significantly modulate beta-glucan or BCG-induced trained immunity in vitro. A known immunomodulatory TLR10 missense single-nucleotide polymorphism (rs11096957) influenced trained immunity responses by beta-glucan or BCG in vitro. However, the in vivo induction of trained immunity by BCG vaccination was not influenced by TLR10 polymorphisms. In conclusion, TLR10 has a limited, non-essential impact on the induction of trained immunity in humans

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Expanding the role of village malaria workers in Cambodia: Implementation and evaluation of four health education packages

Background: Early access to correct diagnosis and appropriate treatment is essential for malaria elimination, and in Cambodia this relies on village malaria workers (VMWs). Decreasing malaria transmission leave VMWs with diminished roles. Activities related to the control of other health conditions could keep these community health workers relevant. Methods: During 2022, 120 VMWs attended training at local health centres on four health education packages: 1. hygiene and sanitation; 2. disease surveillance; 3. management of mild illness; 4. vaccination and antenatal care. All training and evaluation sessions were documented through meeting minutes, and 19 focus group discussions (FGDs) were conducted among VMWs and health centre personnel. Audio-records of FGDs were transcribed and translated in English and underwent thematic analysis. Results: VMWs reported strong interest in the training and welcomed the expansion of their roles thus assuring their continued relevance. VMWs prioritized disease surveillance and management of mild illness among the available training packages because these topics were seen as most relevant. While training was considered comprehensible and important, the low literacy among VMWs was an impediment suggesting training materials need to be delivered visually. Since VMWs have limited resources, incentives could ensure that VMWs are motivated to undertake additional roles and responsibilities. Conclusions: The transformation of VMWs into community health workers with roles beyond malaria is a promising approach for sustaining health care provision in remote areas. Training needs to consider the low scientific literacy, time constraints and limited resources of VMWs

L’influence des relations familiales et sociales sur la consommation de médicaments psychotropes chez les personnes âgées

Les psychotropes occupent le deuxième rang dans la consommation de médicaments chez les personnes âgées. L'objectif de cette étude est de vérifier un modèle explicatif de la consommation de psychotropes dans cette population. Notre principale hypothèse est que la qualité des relations qu'entretient une personne âgée avec autrui, et particulièrement avec ses enfants, a une influence directe sur son bien-être psychologique, lequel a une influence directe sur la non-consommation de psychotropes. Une enquête a été réalisée auprès d'un échantillon de 500 personnes âgées de 65 à 84 ans, vivant à domicile. Au cours des trois mois précédant l'entrevue, 31,8 % des répondants ont consommé des psychotropes. Les données empiriques n'ayant pas permis de vérifier le modèle théorique retenu, des analyses multivariées ont conduit à l'élaboration d'un modèle explicatif de la consommation qui met en évidence que le bien-être psychologique et la santé sont les meilleurs prédicteurs de cette consommation. Un bien-être psychologique élevé diminue la consommation alors qu'un mauvais état de santé l'augmente. Les relations sociales influencent directement le bien-être psychologique alors que les relations familiales ont un effet de moindre importance. Le modèle explicatif proposé explique 13 % du phénomène de la consommation de psychotropes chez les personnes âgées.Psychotropic drugs are the second most commonly used medication by Quebec's elderly. The objective of this study is to test a theoretical model of psychotropic drug use in the elderly. The principal hypothesis is that the quality of relationships the elderly person has with others, particularly with his or her children, has a direct influence on his or her psychological well-being, which, in turn, directly affects the consumption of psychotropic agents. A survey was conducted on a sample of 500 elderly people, aged 65-84 years, living at home. 31.8% of the respondents used psychotropic drugs during the three-month period preceding the interview. Path analysis led to the elaboration of a modified model for the consumption of psychotropic drugs by the elderly which indicates that the best predictors of consumption are both the psychological well-being and the state of health of the individual. More elevated is the psychological well-being, less is the consumption of psychotropic drugs, whereas poor health condition increases it. The quality of an individual's social relationships has a direct influence on his or her psychological well-being, whereas family relationships are of lesser importance. Our model accounts for 13% of the predictors of psychotropic consumption by the elderly

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages