Enhanced testing can substantially improve defense against several types of respiratory virus pandemic.

Mass testing to identify and isolate infected individuals is a promising approach for reducing harm from the next acute respiratory virus pandemic. It offers the prospect of averting hospitalizations and deaths whilst avoiding the need for indiscriminate social distancing measures. To understand scenarios where mass testing might or might not be a viable intervention, here we modeled how effectiveness depends both on characteristics of the pathogen (R, time to peak viral load) and on the testing strategy (limit of detection, testing frequency, test turnaround time, adherence).

Prognostic value of blood eosinophils for predicting survival and treatment outcomes in people with non-small cell lung cancer.

This is a protocol for a Cochrane Review (prognosis). The objectives are as follows: To assess the prognostic value of measuring pretreatment baseline blood eosinophil levels in adults receiving systemic treatment for any stage of non-small cell lung cancer.

Distinct immune cell infiltration patterns in pancreatic ductal adenocarcinoma (PDAC) exhibit divergent immune cell selection and immunosuppressive mechanisms.

Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment.

Role of primary and secondary care data in atrial fibrillation ascertainment: impact on risk factor associations, patient management, and mortality in UK Biobank.

Aims: Electronic healthcare records (EHR) are at the forefront of advances in epidemiological research emerging from large-scale population biobanks and clinical studies. Hospital admissions, diagnoses, and procedures (HADP) data are often used to identify disease cases. However, this may result in incomplete ascertainment of chronic conditions such as atrial fibrillation (AF), which are principally managed in primary care (PC).

Models for predicting risk of endometrial cancer: a systematic review.

Background: Endometrial cancer (EC) is the most prevalent gynaecological cancer in the UK with a rising incidence. Various models exist to predict the risk of developing EC, for different settings and prediction timeframes. This systematic review aims to provide a summary of models and assess their characteristics and performance.

Antiviral efficacy of fluoxetine in early symptomatic COVID-19: an open-label, randomised, controlled, adaptive platform trial (PLATCOV).

Background: The selective serotonin reuptake inhibitors (SSRIs) fluoxetine and fluvoxamine were repurposed for the treatment of early COVID-19 based on their antiviral activity , and observational and clinical trial evidence suggesting they prevented progression to severe disease. However, these SSRIs have not been recommended in therapeutic guidelines and their antiviral activity has not been characterised.

Methods: PLATCOV is an open-label, multicentre, phase 2, randomised, controlled, adaptive pharmacometric platform trial running in Thailand, Brazil, Pakistan, and Laos.

Sonic hedgehog medulloblastoma cells in co-culture with cerebellar organoids converge towards in vivo malignant cell states.

Background: In the malignant brain tumor sonic hedgehog medulloblastoma (SHH-MB) the properties of cancer cells are influenced by their microenvironment, but the nature of those effects and the phenotypic consequences for the tumor are poorly understood. The aim of this study was to identify the phenotypic properties of SHH-MB cells that were driven by the nonmalignant tumor microenvironment.

Methods: Human induced pluripotent cells (iPSC) were differentiated to cerebellar organoids to simulate the nonmaliganant tumor microenvironment.

Dataset of keywords used by European political parties on Facebook.

This dataset contains the frequency of thousands of terms (or keywords) used by political parties in the posts they have published in their Facebook pages. The data set is composed by 20,317 keywords from posts published by 279 European political parties from 28 countries and spans 5 years, from January 2019 to December 2023. Due to the large diversity of languages in the analysed countries, we have translated every post into English to compile this dataset.

Society for Cardiovascular Magnetic Resonance recommendations toward environmentally sustainable cardiovascular magnetic resonance.

Delivery of health care, including medical imaging, generates substantial global greenhouse gas emissions. The cardiovascular magnetic resonance (CMR) community has an opportunity to decrease our carbon footprint, mitigate the effects of the climate crisis, and develop resiliency to current and future impacts of climate change. The goal of this document is to review and recommend actions and strategies to allow for CMR operation with improved sustainability, including efficient CMR protocols and CMR imaging workflow strategies for reducing greenhouse gas emissions, energy, and waste, and to decrease reliance on finite resources, including helium and waterbody contamination by gadolinium-based contrast agents.

Evaluation of Patients' Satisfaction with Healthcare Services Provided at the National Health Insurance Authority Clinic of a Tertiary Hospital in South-West, Nigeria.

Background: Patient satisfaction is an essential indicator used for measuring the quality of health care delivered to a patient and contributes to strategies for the improvement of healthcare delivery. This study assessed patients' satisfaction with the quality of care at the National Health Insurance Authority (NHIA) clinic in a tertiary health facility.

Methods: The study was a descriptive cross-sectional design with 320 respondents who completed a semi-structured questionnaire.

Lead-grouped multi-stage learning for myocardial infarction localization.

The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to localize myocardial infarction (MI) that is characterized by abnormal waveform patterns on the ECG. MI is a serious cardiovascular disease, and accurate, timely diagnosis is crucial for preventing severe outcomes. Current ECG analysis methods mainly rely on intra- and inter-lead feature extraction, but most models overlook the medical knowledge relevant to disease diagnosis.

Revealing trends in measles immunity during periods of varying measles circulation in Madagascar.

Estimating the durability of immunity from vaccination is complicated by unreported re-vaccination, and unobserved natural infection or reexposure, which could result in overestimation of protection longevity. We tested serial cross-sectional serum samples from 2005 to 2015 (N=2,530) for IgG to examine measles seroprevalence, spatiotemporal patterns of titers across regions and antibody dynamics among children aged 1-9 years who grew up during varying measles circulation in Madagascar under a one-dose vaccination schedule. We found that measles seroprevalence has generally decreased over this time period.

The impact of antimicrobial stewardship ward rounds on antimicrobial use and predictors of advice, uptake, and outcomes.

Objective: To identify the impact of introducing antimicrobial stewardship (AMS) ward rounds.

Methods: We used an interrupted time-series approach to investigate the impact of implementing AMS ward rounds with in-person feedback from a multidisciplinary team in Hospital-1, also comparing to Hospital-2 in the same city where AMS ward rounds were not yet implemented. Regression models were used to identify predictors of advice given and of whether advice was followed, and associations between advice uptake and length of stay.

Viral and immune dynamics of genital human papillomavirus infections in young women with high temporal resolution.

Human papillomavirus (HPV) infections drive one in 20 new cancer cases, exerting a particularly high burden on women. Most anogenital HPV infections are cleared in less than two years, but the underlying mechanisms that favour persistence in around 10% of women remain largely unknown. Notwithstanding, it is precisely this information that is crucial for improving treatment, screening, and vaccination strategies.

Reconstructing the first COVID-19 pandemic wave with minimal data in England.

Accurate measurement of exposure to SARS-CoV-2 in the population is crucial for understanding the dynamics of disease transmission and evaluating the impacts of interventions. However, it was particularly challenging to achieve this in the early phase of a pandemic because of the sparsity of epidemiological data. We previously developed an early pandemic diagnostic tool that linked minimum datasets: seroprevalence, mortality and infection testing data to estimate the true exposure in different regions of England and found levels of SARS-CoV-2 population exposure to be considerably higher than suggested by seroprevalence surveys.

Condition monitoring and multi-fault classification of hydraulic systems using multivariate functional data analysis.

Condition monitoring and fault classification in engineering systems is a critical challenge within the scope of Prognostics and Health Management (PHM). The fault diagnosis of complex nonlinear systems, such as hydraulic systems, has become increasingly important due to advancements in big data analytics, machine learning (ML), Industry 4.0, and Internet of Things (IoT) applications.

Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.

Predicting disease-related molecular traits from histomorphology brings great opportunities for precision medicine. Despite the rich information present in histopathological images, extracting fine-grained molecular features from standard whole slide images (WSI) is non-trivial. The task is further complicated by the lack of annotations for subtyping and contextual histomorphological features that might span multiple scales.

Heritable polygenic editing: the next frontier in genomic medicine?

Polygenic genome editing in human embryos and germ cells is predicted to become feasible in the next three decades. Several recent books and academic papers have outlined the ethical concerns raised by germline genome editing and the opportunities that it may present. To date, no attempts have been made to predict the consequences of altering specific variants associated with polygenic diseases.

Estimating evolutionary and demographic parameters via ARG-derived IBD.

Inference of evolutionary and demographic parameters from a sample of genome sequences often proceeds by first inferring identical-by-descent (IBD) genome segments. By exploiting efficient data encoding based on the ancestral recombination graph (ARG), we obtain three major advantages over current approaches: (i) no need to impose a length threshold on IBD segments, (ii) IBD can be defined without the hard-to-verify requirement of no recombination, and (iii) computation time can be reduced with little loss of statistical efficiency using only the IBD segments from a set of sequence pairs that scales linearly with sample size. We first demonstrate powerful inferences when true IBD information is available from simulated data.

Developing a framework for tracking antimicrobial resistance gene movement in a persistent environmental reservoir.

Mobile genetic elements are key to the global emergence of antibiotic resistance. We successfully reconstructed the complete bacterial genome and plasmid assemblies of isolates sharing the same carbapenemase gene to understand evolution over time in six confined hospital drains over five years. From 82 isolates we identified 14 unique strains from 10 species with 113 carrying plasmids across 16 distinct replicon types.

Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections.

Background: Patients with Gram-negative bloodstream infections are at risk of serious adverse outcomes without active treatment, but identifying who has antimicrobial resistance (AMR) to target empirical treatment is challenging.

Methods: We used XGBoost machine learning models to predict antimicrobial resistance to seven antibiotics in patients with Enterobacterales bloodstream infection. Models were trained using hospital and community data from Oxfordshire, UK, for patients with positive blood cultures between 01-January-2017 and 31-December-2021.

Cognitive impairment at older ages among 8000 men and women living in Mexico City: a cross-sectional analyses of a prospective study.

Background: There is limited population-based evidence on the prevalence of cognitive impairment in Mexico, a country with a rapidly aging population and where key risk factors, such as diabetes and obesity, are common. This study describes the distribution of cognitive impairment in adults from Mexico City.

Methods: This cross-sectional population-based study included participants from the Mexico City Prospective Study which recruited 150,000 adults aged ≥ 35 years in 1998-2004.

Ethnicity and anthropometric deficits in children: A cross-sectional analysis of national survey data from 18 countries in sub-Saharan Africa.

Child anthropometric deficits remain a major public health problem in Sub-Saharan Africa (SSA) and are a key target of the UN Sustainable Development Goals (SDGs). The SDGs recommend disaggregation of health indicators by ethnic group. However, few studies have assessed how ethnicity is associated with anthropometric deficits across SSA.

Addition of Macrolide Antibiotics for Hospital Treatment of Community-Acquired Pneumonia.

Background: Guidelines recommend combining macrolides with β-lactam antibiotics for moderate-to-high severity community-acquired pneumonia (CAP); however, macrolides pose risks of adverse events and anti-microbial resistance.

Methods: We analyzed electronic health data from 8872 adults hospitalized with CAP in Oxfordshire, UK (2016-2024), initially treated with amoxicillin or co-amoxiclav. Using inverse probability treatment weighting, we examined the effects of adjunctive macrolides on 30-day all-cause mortality, time to hospital discharge, and changes in Sequential Organ Failure Assessment (SOFA) score.

Co-Delivery of aPD-L1 and CD73 Inhibitor Using Calcium Phosphate Nanoparticles for Enhanced Melanoma Immunotherapy with Reduced Toxicity.

Melanoma, a malignant skin tumor, presents significant treatment challenges, particularly in unresectable and metastatic cases. While immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 have brought new hope, their efficacy is limited by low response rates and significant immune-mediated adverse events (irAEs). Through multi-omics data analysis, it is discovered that the spatial co-localization of CD73 and PD-L1 in melanoma correlates with improved progression-free survival (PFS), suggesting a synergistic potential of their inhibitors.