Joint Physical-Psychosocial Frailty and Risks of All-Cause and Cause-Specific Premature Mortality.

Background: The importance of integrating physical and psychosocial factors in assessing frailty -health outcomes has been increasingly acknowledged, while the related evidence is lacking. We sought to investigate the associations of joint physical-psychosocial frailty with risk of premature mortality and evaluate the relative importance of individual physical and psychosocial factors.

Design: A total of 381,295 participants with no history of cancer or cardiovascular disease (CVD) were recruited from the UK Biobank cohort.

An Exploratory Investigation of Heritage and Educational Language Exposures as Factors in Medical Student Spanish Language Proficiency.

Background: Prior to enrolling in medical Spanish courses, students typically acquire their Spanish skills either through formal second language education only (L2 learners) or by being exposed to Spanish during childhood at home (heritage learners).

Objective: To categorize the language exposures of medical students who participated in a medical Spanish course and explore the associations of exposures with their medical language proficiency score on the Physician Oral Language Observation Matrix (POLOM).

Setting And Participants: Forty-one fourth-year medical students (2021-2022) self-reported demographics and prior language exposures and participated in videorecorded POLOM-rated Spanish standardized patient encounters.

Disparities in Access and Utilization of Electronic Health Record Patient Portals.

Objective: The aim of this study was to assess changes in the accessibility and utilization of electronic health record patient portals in recent years, focusing on whether these changes occurred equitably across different racial, ethnic, and socioeconomic groups.

Materials And Methods: The study utilized nationally representative samples from the 2019 and 2022 Health Information National Trends Surveys. A difference-in-differences design was used to determine if increases in access and utilization occurred equally for all segments of the population.

Operating Characteristics of the Simulated Healthy Participant Approach in Impaired Clearance Studies.

Minimizing harm is a cornerstone of ethical research practices. A drug that has undergone extensive clinical pharmacological testing in healthy participants (HPs) and a diverse selection of patients can be described with a sufficiently predictive population pharmacokinetic (PopPK) model. In impaired clearance trials, recruitment is minimized and underpowered for all but major exposure differences.

Validating the RISE Communication Play Protocol as a Diagnostic Tool for Autism in Early Childhood: A Pilot Study.

There are few validated remote tools that can be used to assess for autism and to capture subtle changes in children's social communication over time. Recently, user-centered design principles were applied to develop a parent-mediated remote assessment, the Reciprocal Imitation and Social Engagement Child Play Protocol (RISE CPP) to enable researchers to capture micro-level behaviors in children, while promoting useability for researchers and families, reducing caregiver burden, and maintaining reliability. This paper describes a pilot study to validate the RISE CPP as a tool to support clinician diagnosis of autism.

In vivo CRISPR-Cas9 genome editing in mice identifies genetic modifiers of somatic CAG repeat instability in Huntington's disease.

Huntington's disease, one of more than 50 inherited repeat expansion disorders, is a dominantly inherited neurodegenerative disease caused by a CAG expansion in HTT. Inherited CAG repeat length is the primary determinant of age of onset, with human genetic studies underscoring that the disease is driven by the CAG length-dependent propensity of the repeat to further expand in the brain. Routes to slowing somatic CAG expansion, therefore, hold promise for disease-modifying therapies.

Overcoming challenges associated with broad sharing of human genomic data.

Since the Human Genome Project, the consensus position in genomics has been that data should be shared widely to achieve the greatest societal benefit. This position relies on imprecise definitions of the concept of 'broad data sharing'. Accordingly, the implementation of data sharing varies among landmark genomic studies.

Effects of dam fear and stress on metrics of puppy welfare in commercial breeding kennels.

It is well established that maternal factors can affect the abilities of offspring to cope with stressors and can influence their overall welfare states. However, maternal effects have not been extensively explored in US commercial breeding kennels (CBKs). Therefore, the objective of this study was to identify if fear and stress in dams affected puppy welfare metrics in CBKs.

Cost-effective adaptations increase rice production while reducing pollution under climate change.

Rice is a major source of greenhouse gas (GHG) and nitrogen pollution. While best management practices have been developed to enhance the sustainability of rice production under current climates, their adaptability and efficacy under future climate scenarios remain uncertain. Here we evaluated 49 best management practices across global grid cells of rice-producing areas in terms of increasing rice production, reducing GHG emissions and minimizing nitrogen pollution under future climate conditions.

FABP4 as a therapeutic host target controlling SARS-CoV-2 infection.

Host metabolic fitness is a critical determinant of infectious disease outcomes. Obesity, aging, and other related metabolic disorders are recognized as high-risk disease modifiers for respiratory infections, including coronavirus infections, though the underlying mechanisms remain unknown. Our study highlights fatty acid-binding protein 4 (FABP4), a key regulator of metabolic dysfunction and inflammation, as a modulator of SARS-CoV-2 pathogenesis, correlating strongly with disease severity in COVID-19 patients.

Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.

Objectives: To assess glymphatic function and white matter integrity in children with autism spectrum disorder (ASD) using multi-parametric MRI, combined with machine learning to evaluate ASD detection performance.

Materials And Methods: This retrospective study collected data from 110 children with ASD (80 exploratory, 43 validation) and 68 typically developing children (50 exploratory, 18 validation) from two centers. The automated diffusion tensor imaging along the perivascular space (aDTI-ALPS), fractional anisotropy (FA), cerebrospinal fluid volume, and perivascular space (PVS) volume indices were extracted from DTI, three-dimensional T1-weighted, and T2-weighted images.

Unveiling the critical roles of cellular metabolism suppression in antibiotic tolerance.

Metabolic inhibitors are known to exhibit complex interactions with antibiotics in bacteria, potentially acting as antagonists by inducing cell dormancy and promoting cell survival. However, the specific synergistic or antagonistic effects of these inhibitors depend on factors like their mechanisms of action, concentrations, and treatment timings, which require further investigation. In our study, we systematically explored the synergistic interactions of various metabolic inhibitors-such as chloramphenicol (a translation inhibitor), rifampicin (a transcription inhibitor), arsenate (an ATP production inhibitor), and thioridazine (a PMF inhibitor)-in combination with ofloxacin.

Unraveling the distinctive gut microbiome of khulans (Equus hemionus hemionus) in comparison to their drinking water and closely related equids.

The microbial composition of host-associated microbiomes is influenced by co-evolutionary interactions, host genetics, domestication, and the environment. This study investigates the contribution of environmental microbiota from freshwater bodies to the gastrointestinal microbiomes of wild khulans (Equus hemionus hemionus, n = 21) and compares them with those of captive khulans (n = 12) and other equids-Przewalski's horse (n = 82) and domestic horse (n = 26). Using PacBio technology and the LotuS pipeline for 16S rRNA gene sequencing, we analyze microbial diversity and conduct differential abundance, alpha, and beta diversity analyses.

Distributed training of foundation models for ophthalmic diagnosis.

Vision impairment affects nearly 2.2 billion people globally, and nearly half of these cases could be prevented with early diagnosis and intervention-underscoring the urgent need for reliable and scalable detection methods for conditions like diabetic retinopathy and age-related macular degeneration. Here we propose a distributed deep learning framework that integrates self-supervised and domain-adaptive federated learning to enhance the detection of eye diseases from optical coherence tomography images.

Regulation of erm(T) MLS phenotype expression in the emergent emm92 type group A Streptococcus.

In the last decade, invasive group A Streptococcus (iGAS) infections have doubled in the US, with equivalent increases in MLS (macrolide, lincosamide, and streptogramin B)-resistance. The emm92-type isolates carrying the erm(T) gene have been associated with an alarming emergence of iGAS infections in people who inject drugs or experience homelessness. Our goal was to elucidate the mechanisms behind inducible (iMLS) and constitutive (cMLS) resistance in emm92 isolates.

Single-cell RNA-seq data augmentation using generative Fourier transformer.

Single-cell RNA sequencing (scRNA-seq) provides a powerful tool for dissecting cellular complexity and heterogeneity. However, its full potential to achieve statistically reliable conclusions is often constrained by the limited number of cells profiled, particularly in studies of rare diseases, specialized tissues, and uncommon cell types. Deep learning-based generative models (GMs) designed to address data scarcity often face similar limitations due to their reliance on pre-training or fine-tuning, inadvertently perpetuating a cycle of data inadequacy.

Fabrication of nonplanar tapered fibers to integrate optical and electrical signals for neural interfaces in vivo.

Implantable multifunctional probes have transformed neuroscience research, offering access to multifaceted brain activity that was previously unattainable. Typically, simultaneous access to both optical and electrical signals requires separate probes, while their integration into a single device can result in the emergence of photogenerated electrical artifacts, affecting the quality of high-frequency neural recordings. Among the nontrivial strategies aimed at the realization of an implantable multifunctional interface, the integration of optical and electrical capabilities on a single, minimally invasive, tapered optical fiber probe has been recently demonstrated using fibertrodes.

Field-particle energy transfer during chorus emissions in space.

Chorus waves are some of the strongest electromagnetic emissions naturally occurring in space and can cause radiation that is hazardous to humans and satellites. Although chorus waves have attracted extreme interest and been intensively studied for decades, their generation and evolution remain highly debated. Here, in contrast to the conventional expectation that chorus waves are governed by planetary magnetic dipolar fields, we report observations of repetitive, rising-tone chorus waves in the terrestrial neutral sheet, where the effects of the magnetic dipole are absent.

Neuromorphic computing at scale.

Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient computational systems, often for applications with size, weight and power constraints. With this research field at a critical juncture, it is crucial to chart the course for the development of future large-scale neuromorphic systems.

Superconductivity in 5.0° twisted bilayer WSe.

The discovery of superconductivity in twisted bilayer and trilayer graphene has generated tremendous interest. The key feature of these systems is an interplay between interlayer coupling and a moiré superlattice that gives rise to low-energy flat bands with strong correlations. Flat bands can also be induced by moiré patterns in lattice-mismatched and/or twisted heterostructures of other two-dimensional materials, such as transition metal dichalcogenides (TMDs).

Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance.

Artificial intelligence (AI) has transformed infectious disease control, enhancing rapid diagnosis and antibiotic discovery. While conventional tests delay diagnosis, AI-driven methods like machine learning and deep learning assist in pathogen detection, resistance prediction, and drug discovery. These tools improve antibiotic stewardship and identify effective compounds such as antimicrobial peptides and small molecules.