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Single-nuclei multiomics analysis identifies abnormal cardiomyocytes in a murine model of cardiac development

Sickness absence rates in NHS England staff during the COVID-19 pandemic: Insights from multivariate regression and time series modelling

The COVID-19 pandemic placed immense strain on healthcare systems worldwide, with NHS England facing substantial challenges in managing staff illness-related absences amid surging treatment demands. Understanding the impact of the pandemic on sickness absence rates among NHS England staff is crucial to developing effective workforce management strategies and ensuring the continued delivery of healthcare. In this study, we use publicly available data to investigate the impact of the COVID-19 pandemic on sickness absence rates among NHS England staff between June 2020 and 2022. We begin with a data analysis to indicate the temporal patterns of sickness absence in NHS England staff between January 2015 and September 2022 inclusive. We then develop multivariate linear regression models to estimate COVID-19-related sickness absences. Indicators of COVID-19 activity, such as positive tests, hospitalizations, and ONS incidence, were incorporated. Furthermore, we use Seasonal ARIMA time series models to analyse the impact of COVID-19 on mental health-related absence. Our analysis highlights increases in sickness absence rates which coincide with the arrival of COVID-19 in England, and continue to rise throughout the pandemic. High periods of COVID-19 activity strongly correlated with staff absence, and the main categories driving the dynamics were COVID-19-related or mental health absences. We demonstrate that sickness absences in these two categories can be estimated accurately using multivariate linear regression (F(2, 15) = 132.63, P < .001 , adj R 2 =93.9%) and Seasonal ARIMA time series models, respectively. Moreover, we show that additional indicators of COVID-19 activity (positive tests, hospitalisations, ONS incidence) contain helpful information about staff infection pathways. This study offers insights into the dynamics of healthcare staff absences during a pandemic, contributing to both practical workforce management and academic research. The findings highlight the need for tailored approaches to address both infectious disease-related and mental health-related absences in healthcare settings during future health crises and opens new avenues for research into healthcare system resilience during crises.

Heterogeneous preferences and asymmetric insights for AI use among welfare claimants and non-claimants

Abstract The deployment of AI in welfare benefit allocation accelerates decision-making but has led to unfair denials and false fraud accusations. In the US and UK (N = 3249), we examine public acceptability of speed-accuracy trade-offs among claimants and non-claimants. While the public generally tolerates modest accuracy losses for faster decisions, claimants are less willing to accept AI in welfare systems, raising concerns that using aggregate data for calibration could misalign policies with the preferences of those most affected. Our study further uncovers asymmetric insights between claimants and non-claimants. Non-claimants overestimate claimants’ willingness to accept speed-accuracy trade-offs, even when financially incentivized for accurate perspective-taking. This suggests that policy decisions aimed at supporting vulnerable groups may need to incorporate minority voices beyond popular opinion, as non-claimants may not easily understand claimants’ perspectives.

The Healthy Homes Study: Protocol for a cluster randomized trial of a place-based smoke-free home intervention in affordable housing

Introduction Comprehensive clean air policies reduce exposure to secondhand tobacco and cannabis smoke, as well as nicotine aerosols, and improve health outcomes. However, these policies often do not apply to the eight million residents of multiunit affordable housing, many of whom are from minoritized populations. One strategy to promote smoke-free living environments is to increase the voluntary adoption of no-smoking rules in the home. Methods We describe the protocol for the Healthy Homes study—a wait-list cluster randomized controlled trial of a smoke-free home intervention for affordable housing residents. The intervention was adapted from a prior version using the Capability Opportunity Motivation-Behavior (COM-B) model and the Behavior Change Wheel. We will enroll 544 residents at 48 affordable housing sites across Northern California. Sites will be randomized to intervention or wait-list control. Resident participants will receive a one-hour coaching session on how to adopt a smoke-free home. Housing staff will be trained as lay health workers to provide brief cessation coaching. Residents and staff will complete follow-up visits at 3 and 6 months. The intervention will be delivered in English, Spanish, Chinese (Mandarin and Cantonese), and Vietnamese. The primary resident outcome is voluntary adoption of a smoke-free home for 90 days or more at 6 months. The secondary outcome is carbon monoxide–verified point prevalence tobacco abstinence. For lay health workers, the primary outcome is change in Smoking Knowledge, Attitudes, and Practices scores. We will assess cost-effectiveness and use the Consolidated Framework for Implementation Research to evaluate implementation outcomes, including characteristics of successful adopters and multilevel drivers of behavior change. Discussion Expanding access to smoke-free affordable housing is critical for reducing racial and ethnic health inequities. This study has the potential to support voluntary smoke-free home adoption, increase quitting, and reduce secondhand smoke exposure among affordable housing residents. Trial registration ClinicalTrials.gov NCT06170437

2-oxoglutarate:acceptor oxidoreductase-catalyzed redox cycling effectively targets coccoid forms of Helicobacter pylori

Expression of Concern: Barriers to cleaning of shared latrines in slums of Addis Ababa, Ethiopia

A single mutation may contribute to accelerated evolution of SARS-CoV-2 toward Omicron

Cost-effectiveness assessment of liquid biopsy for early detection of lung cancer in Brazil

Introduction Lung cancer has a low survival rate due to late diagnosis, with most cases detected at advanced stages. Liquid biopsy, a non-invasive alternative to tissue biopsy, has emerged as a potential screening tool for early lung cancer detection. This study evaluates the cost-effectiveness of liquid biopsy screening using an autoantibody test (EarlyCDT-Lung®) in high-risk populations from the perspective of the Brazilian Unified Health System (SUS). Methods A decision-analytic model was developed, combining a decision tree and a Markov model to compare two strategies: standard clinical diagnosis without screening and liquid biopsy screening followed by confirmatory diagnostics. Model inputs included test accuracy, treatment costs, and survival data derived from systematic reviews, national registries, and published economic evaluations. The primary outcome was the incremental cost-effectiveness ratio (ICER) per quality-adjusted life year (QALY). Sensitivity analyses assessed model robustness. Results Liquid biopsy screening analysis of a hypothetical cohort of 1,000 individuals at high-risk of lung cancer resulted in an incremental cost of $ 570,120 and an incremental effectiveness of 7.56 QALYs, with an ICER of $ 75,435.63 per QALY gained. This result has far exceeded the willingness-to-pay threshold in Brazil ($ 7,017.54–21,052.62/QALY). Therefore, in case of assuming no significant cost reductions or accuracy improvements, the strategy would only become cost-effective in contexts where lung cancer prevalence exceeds 4.0%. Probabilistic sensitivity analysis confirmed a low likelihood of cost-effectiveness, even with varying test sensitivity, lung cancer prevalence, and cost assumptions. Discussion The adoption of an autoantibody test as a liquid biopsy for early lung cancer screening in high-risk populations in Brazil led to increased costs and was not considered cost-effective under the thresholds commonly applied in the Brazilian context.

Autocrine interferon poisoning mediates ADAR1-dependent synthetic lethality in BRCA1/2-mutant cancers

Abstract ADAR1 is an RNA editing enzyme which prevents autoimmunity by blocking interferon responses triggered by cytosolic RNA sensors, and is a potential target in immuno-oncology. However, predictive biomarkers for ADAR1 inhibition are lacking. Using multiple in vitro and in vivo systems, we show that BRCA1/2 and ADAR1 are synthetically lethal, and that ADAR1 activity is upregulated in BRCA1/2-mutant cancers. ADAR1 depletion in BRCA1-mutant cells causes an increase in R-loops and consequently, an upregulation of cytosolic nucleic acid sensing pattern recognition receptors (PRR), events which are associated with a tumor cell-autonomous type I interferon and integrated stress response. This ultimately causes autocrine interferon poisoning. Consistent with a key role of R-loops in this process, exogenous RNase H1 expression reverses the synthetic lethality. Pharmacological suppression of cell-autonomous interferon responses or transcriptional silencing of cytosolic nucleic acid sensing PRR are also sufficient to abrogate ADAR1 dependency in BRCA1-mutant cells, in line with autocrine interferon poisoning playing a central part in this synthetic lethality. Our findings provide a preclinical rationale for assessing ADAR1-targeting agents in BRCA1/2-mutant cancers, and introduces a conceptually novel approach to synthetic lethal treatments, which exploits tumor cell-intrinsic cytosolic immunity as a targetable vulnerability of cancer cells.

The global, regional and national burden of pancreatitis due to alcohol use: Results from the Global Burden of Disease Study 2021 and projections to 2040

Background Alcohol use is a major risk factor for pancreatitis and global mortality. Despite its impact, comprehensive analyses of the burden across regions and sociodemographic strata remain scarce. This study examines global trends (1990–2021) and projects future burdens to 2040. Method Data on Deaths and Disability-Adjusted Life Years (DALYs) attributable to alcohol-induced pancreatitis were retrieved from the 2021 iteration of the Global Burden of Diseases (GBD) database. Trends were analyzed, Age-Period-Cohort models quantified age, period, and cohort effects on Age-Standardized Mortality Rate (ASMR) and Age-Standardized Disability-Adjusted Life Year (ASDR). Associations with SDI were evaluated, burden decomposition applied, and projections made to 2040. Results Globally, both age-standardized death rate (ASDR) and mortality ratio (ASMR) exhibited overall declines (EAPC for ASDR: −0.32%; ASMR: −0.27%), but the reduction was significantly smaller in males (ASDR-EAPC: −0.18%) compared to females (−1.34%). Notablly,Eastern Europe had the highest burden (ASDR: 64.03), High-income Asia-Pacific saw the largest declines (EAPC for ASDR: −2.45%; EAPC for ASMR: −2.96%), while Southeast Asia experienced the fastest increase (EAPC for ASDR: 1.98%; EAPC for ASMR: 2.13%). ASDR peaked at ages 45–49, with high-middle SDI countries showing the highest values. Period and cohort effects varied by SDI, with downward trends in high SDI countries and upward trends in lower SDI groups. Population growth and aging drove increases in deaths and DALYs, while epidemiologic changes reduced them. By 2040, deaths and DALYs will stabilize, ASMR will decline until 2034 then rise, and ASDR will decrease until 2035 then increase, driven by population growth. Conclusion Alcohol-related pancreatitis burden demonstrates striking gender, age, and geographic heterogeneity. Targeted policies for high-risk groups (middle-aged/elderly males) and regions (Eastern Europe, Low-middle SDI countries), coupled with preparedness for aging-related burden escalation, are urgently needed.

Bridging small molecule calculations and predictable polymer mechanical properties

Evaluating the predictive performance of PIRO score against six clinical prediction scores for COVID-19 outcomes in the emergency department

Global stroke burden attributable to household air pollution: Insights from GBD 2021 and projections to 2040

Objectives To analyze the global stroke burden attributable to household air pollution (HAP) using Global Burden of Disease (GBD) 2021 data, examine its spatiotemporal patterns from 1990–2021, and project future trends through 2040. Study design Retrospective analysis using GBD data with future projections Methods Analysis of age-standardized rates, deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) due to HAP-related stroke across 204 countries. The linear regression model examined global time trends. Cluster analysis investigated the patterns of disease burden changes across GBD regions. The Nordpred model projected trends up to 2040. Results In 2021, HAP caused 1.23 million stroke deaths and 26.78 million DALYs globally. From 1990–2021, age-standardized death rates (EAPC = −0.37), DALY rates (EAPC = −0.20), and YLL rates (EAPC = −0.30) decreased, while YLD rates increased (EAPC = 1.11). Males showed a higher burden than females, with peak rates in the 80–84 age group. Middle-SDI regions had the highest age-standardized rates, with East Asia recording the largest absolute numbers. South and East Asia showed significant increases, while Western Europe, Eastern Europe, and High-income North America showed the greatest declines. Predictions using the Nordpred model indicated rising absolute numbers of deaths (to 1.79 million), DALYs (to 34.76 million), YLDs (to 3.29 million), and YLLs (to 31.39 million), with males consistently bearing a higher burden, though ASRs are expected to decline for both sexes. Conclusions Our findings suggest that regions with higher economic development and greater adoption of clean energy are associated with lower HAP-related stroke burden, possibly through improvements in indoor air quality. The observed regional and gender disparities emphasize the need for targeted interventions, particularly in less developed regions and among high-risk groups such as men and older adults.

Multichannel bioelectronic sensing using engineered Escherichia coli

Zero-biased graphene photodetector with high responsivity integrated into silicon microring resonator

The association between remnant cholesterol and the risk of osteoporotic vertebral fracture in older adults

Background Serum lipid levels have been shown to influence bone mineral density. Additionally, a limited number of studies have suggested that remnant cholesterol (RC) may be linked to the risk of osteoporosis. However, the relationship between RC and fracture risk remains unclear. This study aimed to explore the association between RC levels and the risk of vertebral fractures in a longitudinal cohort. Methods A total of 1995 participants aged 50 years or older who underwent chest computed tomography (CT) scans for lung cancer screening between July 2016 and December 2019 were included in this study. Follow-up continued until June 2023. The concentration of RC was calculated via the following formula: total cholesterol minus the sum of high-density lipoprotein cholesterol and low-density lipoprotein cholesterol. The RC-to-cholesterol ratio was also determined. The participants were divided into low and high groups for RC, and the RC-to-cholesterol ratio was based on the median values. Vertebral fractures were assessed via the Genant semiquantitative classification system on CT-reconstructed sagittal images. Results During a median follow-up period of 60 months, 95 new vertebral fractures were recorded. The incidence of fractures was significantly greater among participants with low RC levels than among those with high RC levels (6.4% vs. 3.1%, P < 0.01). A multivariate Cox proportional hazards model indicated that individuals with high RC levels had a 41% lower risk of vertebral fractures than those with low RC levels did (adjusted hazard ratio [aHR]: 0.48, 95% confidence interval [CI]: 0.24--0.93). Similar findings were observed for the RC-to-cholesterol ratio (aHR: 0.40, 95% CI: 0.21–0.79). Restricted cubic spline analysis further demonstrated that the risk of vertebral fractures decreased as the RC level and the RC-to-cholesterol ratio increased. Subgroup analysis revealed that the association between RC and fracture risk was mainly observed in women. Conclusion Higher levels of remnant cholesterol and a higher RC-to-cholesterol ratio were associated with a reduced risk of vertebral fractures, particularly in women.

Senescence-associated lysosomal dysfunction impairs cystine deprivation-induced lipid peroxidation and ferroptosis

Non-mutated human tau stimulates Alzheimer’s disease-relevant neurodegeneration in a microglia-dependent manner

Direction matters: Comparing post-editing and human translation effort and quality

This study investigates the critical yet understudied influence of translation direction on both neural machine translation post-editing (PE) and human translation (HT) processes. While previous research has compared PE and HT, the interaction between translation mode and directionality—particularly for linguistically distant languages—remains poorly understood. We address this gap by examining how L1-L2 (Chinese-English) versus L2-L1 (English-Chinese) directionality affects translation performance across multiple dimensions. Thirty-one native Chinese translators completed both PE and HT tasks in both language directions, with their processes documented through keylogging and screen recording. Our findings reveal that PE generally outperforms HT in speed, technical efficiency, and output quality, but these advantages manifest differently depending on translation direction. The PE advantage was significantly more pronounced in the L2-L1 direction. Conversely, perceived task difficulty was primarily determined by directionality rather than translation mode, with L1-L2 translation consistently rated more challenging regardless of whether performed through PE or HT. These results demonstrate the complex interplay between translation mode and directionality, challenging the simplistic view that PE universally reduces effort compared to HT. Our findings have important implications for translator training, workflow optimization, and fair compensation models that account for both translation mode and direction.

Implications of successive blood feeding on Wolbachia-mediated dengue virus inhibition in Aedes aegypti mosquitoes

Abstract Wolbachia is a promising strategy to inhibit dengue virus (DENV) transmission by Ae. aegypti mosquitoes. Laboratory studies assessing DENV inhibition by Wolbachia typically have not considered natural frequent mosquito blood feeding behavior. Here, we determine the impact of successive feeding on DENV-2 transmission by Ae. aegypti in the presence or absence of Wolbachia ( w AlbB and w MelM strains). We show that successive feeding shortens the extrinsic incubation period (EIP) in wildtype (WT; without Wolbachia ) and w AlbB mosquitoes through enhanced dissemination. Feeding empirical data into models showed that successive feeding increases the probability of WT and w AlbB mosquitoes surviving beyond the EIP. Importantly, the more epidemiologically relevant comparison of the odds of w AlbB mosquitoes surviving beyond the EIP relative to WT, reveals a larger impact of successive feeding on WT than w AlbB. This indicates a strong inhibitory effect of Wolbachia even in the context of natural frequent mosquito blood feeding behavior.