A comprehensive evaluation of large language models for information extraction from unstructured electronic health records in residential aged care.

Despite rapid healthcare digitization, extracting information from unstructured electronic health records (EHRs), such as nursing notes, remains challenging due to inconsistencies and ambiguities in clinical documentation. Generative large language models (LLMs) have emerged as promising tools for automating information extraction (IE); however, their application in real-world clinical settings, such as residential aged care (RAC), is limited by critical gaps. Prior studies have often focused on structured EHR data and conventional evaluation metrics such as accuracy and F1 score, overlooking critical aspects like robustness, fairness, bias, and contextual relevance, particularly in unstructured clinical narratives.

Enlarged choroid plexus is associated with reduced gray matter volumes and increased plasma amyloid-beta: a population-based study of older adults.

Objectives: To characterize brain structures and plasma Alzheimer's-related biomarkers associated with enlarged choroid plexus (ChP) among rural older adults in China.

Methods: This population-based cross-sectional study included 1115 older adults (age ≥ 60 years) derived from the Multimodal Interventions to delay Dementia and disability in rural China, who underwent structural brain MRI scans (3.0 T) in 2018-2020; of these, plasma biomarkers for Alzheimer's disease and neurodegeneration, i.

Twenty-eight cases of thalassemia: A retrospective study of autologous and allogeneic erythrocyte transfusions during cesarean section.

Aim: Erythrocytes from patients with thalassemia might be susceptible to hemolysis during recycling and washing. Therefore, autologous erythrocyte transfusion using erythrocytes from parturient women with thalassemia has been suggested as a relative contraindication. Only a limited number of successful cases have been documented to date, and few clinical studies with large sample sizes are available as evidence to support this practice.

Association between estimated glomerular filtration rate and memory function mediated by brain Gray matter volumes: a cross-sectional study using the ADNI database.

Background: Estimated glomerular filtration rate (eGFR) is associated with gray matter volumes (GMVs) in memory-related regions, but its relationship with memory function and the mediating role of GMVs remain unclear. We aimed to investigate whether eGFR levels are associated with memory function and whether GMVs mediate this association.

Methods: This study utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

[Effects of vacuum freeze-drying based on different lyoprotectants on the stability of foot-and-mouth disease virus-like particles].

Vaccination is a crucial strategy for the prevention and control of infectious diseases. Virus-like particles (VLPs), composed of structural proteins, have garnered significant attention as a novel type of vaccine due to their excellent safety and immunogenicity. However, similar to most vaccine antigens, VLPs exhibit insufficient thermal stability, which not only restricts the widespread application of vaccines but also increases the risk of vaccine inactivation.

[Process parameter optimization and immunogenicity evaluation of calcium phosphate-coated foot-and-mouth disease virus-like particles].

Bio-mineralization has emerged as a promising strategy to enhance vaccine immunogenicity. This study optimized the calcium phosphate (CaP) mineralization process of foot-and-mouth disease virus-like particles (FMD VLPs) to achieve high mineralization efficiency and scalability. Key parameters, including concentrations of Ca, HPO, NaCl, and VLPs, as well as stirring speed, were systematically optimized.

Combining echocardiography with carotid ultrasound parameters in predicting major adverse cardiovascular events among older individuals with coronary artery disease.

Objective: To investigate the predictive value of combining echocardiography with carotid ultrasound for major adverse cardiovascular events (MACE) among older individuals with coronary artery disease.

Methods: A total of 138 elderly individuals diagnosed with coronary artery disease and admitted to our facility from June 2020 to June 2021 were included in this study. These patients were categorized into two groups: a non-MACE group consisting of 84 patients and a MACE group with 54 patients, based on whether they experienced MACE within three years following their discharge.

High allostatic load in women in the third trimester associated with delayed onset of lactogenesis: A prospective study.

Problem: Stress is an important factor affecting postpartum lactation and is associated with the delayed onset of lactogenesis. Allostatic load is a comprehensive index for measuring chronic stress that effectively reflects the degree of chronic stress in pregnant women. However, no studies have explored the relationship between allostatic load and delayed onset of lactogenesis in pregnant women.

Precision Fishing for Enzyme-like Materials: Identifying and Engineering Mesoporous Catalytic Sites for Ferroptosis Induction.

The discovery of nanomaterials with enzyme-like activities, termed nanozymes, holds the potential to revolutionize traditional inhibitor-based therapies. However, precise identification of nanozymes for specific substrates and uncovering their catalytic domains remain significant challenges. Here, we developed a "fishing" method that utilizes AFM probes coated with substrate baits, functioning as fishing rods to enable visualization of enzymatic reactions on nanomaterial surfaces.

Unequal roles of symptoms in Internet gaming disorder: A network analysis in early adolescence and emerging adulthood.

Internet Gaming Disorder (IGD), recognized as a psychiatric condition especially prevalent among young people, still requires further clarification regarding the age-related differences. The current study employed graphical Least Absolute Shrinkage and Selection Operator (gLASSO) network to assess the central symptoms of IGD in adolescents. Additionally, directed acyclic graphs (DAG) were used to explore the directed dependence among these symptoms.

Mechanistic investigation of calcium phosphate mineralization potentiating the cellular immune response of foot-and-mouth disease virus-like particle vaccines.

Virus-like particles (VLPs), composed of structural proteins, have emerged as a promising vaccine platform for preventing infectious diseases due to their outstanding advantages. Enhancing immune responses specific to VLPs, particularly cellular immunity, has emerged as a pivotal area of current immunological research. The nanovaccines for the foot-and-mouth disease virus (FMDV) composed of VLPs mineralized with calcium phosphate (VLPs-CaP), developed based on biomineralization principles, demonstrates superior immunogenicity.

Association between exposure to terpene compounds and risk of metabolic syndrome: exploring the potential mediating role of inflammatory response.

Background: Terpenes are potentially harmful substances that are associated with endocrine disruption due to their ability to produce oxidizers, aldehydes, and secondary aerosol particles. However, the exact association between terpenoids and metabolic syndrome remains unclear.

Objective: This study aims to examine the relationship between individual and mixed exposure to terpene compounds and the risk of developing metabolic syndrome.

CDEMapper: enhancing National Institutes of Health common data element use with large language models.

Objective: Common Data Elements (CDEs) standardize data collection and sharing across studies, enhancing data interoperability and improving research reproducibility. However, implementing CDEs presents challenges due to the broad range and variety of data elements. This study aims to develop a CDE mapping tool to bridge the gap between local data elements and National Institutes of Health (NIH) CDEs.

Unraveling the connection between endocrine-disrupting chemicals and anxiety: An integrative epidemiological and bioinformatic perspective.

Background: The evidence linking endocrine-disrupting chemicals (EDCs) to anxiety in adults is currently sparse, while the effects of various categories of EDCs on the risk of anxiety, along with the underlying mechanisms, remain poorly understood.

Methods: Four EDCs-polycyclic aromatic hydrocarbons (PAHs), phenols, pesticides, and phthalates-were quantified in 3927 adults from the National Health and Nutrition Examination Survey (NHANES) (2007-2012). We employed five statistical models to assess the individual and joint impacts of EDCs on anxiety risk.

Cerebral small vessel disease among rural-dwelling Chinese older adults: prevalence, distribution, and associated factors.

Epidemiological characteristics of cerebral small vessel disease (cSVD) in the general population, especially among rural older adults, are poorly defined. Here, we reported the prevalence, distribution, and associated factors of cSVD in a rural-dwelling older population in China. This population-based cross-sectional study included 1272 older adults (age ≥60 years; mean age 69.

Significant but Overlooked: The Role of Anthropogenic Monoterpenes in Ozone Formation in a Chinese Megacity.

Recent observations have revealed unexpectedly high concentrations of monoterpenes (MT) in urban areas, frequently surpassing those in forested regions. These findings suggest significant anthropogenic contributions (MT), challenging the traditional view that MT emissions are predominantly natural (MT) in current inventories. This oversight likely results in a substantial underestimation of MT's role in urban ozone (O) production.

Natural Language Processing for Digital Health in the Era of Large Language Models.

Objectives: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize the current state of research in this rapidly evolving space.

Methods: We conducted a review of the most recent studies on biomedical NLP facilitated by LLMs, sourcing literature from PubMed, the Association for Computational Linguistics Anthology, IEEE Explore, and Google Scholar (the latter particularly for preprints).

Benchmarking large language models for biomedical natural language processing applications and recommendations.

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, their effectiveness in BioNLP tasks remains unclear due to limited benchmarks and practical guidelines.

Enlarged choroid plexus is linked with poorer physical function in rural older adults: a population-based study.

Background: The choroid plexus (ChP) plays an important role in producing cerebrospinal fluid (CSF) and physical dysfunction has been associated with alterations in CSF circulation. However, no population-based studies have thus far examined the association of ChP with physical function in older people.

Methods: This population-based cross-sectional study included 1217 participants (age ≥ 60 years; 57.

The Development Landscape of Large Language Models for Biomedical Applications.

Large language models (LLMs) have become powerful tools for biomedical applications, offering potential to transform healthcare and medical research. Since the release of ChatGPT in 2022, there has been a surge in LLMs for diverse biomedical applications. This review examines the landscape of text-based biomedical LLM development, analyzing model characteristics (e.

Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials.

Concerns regarding chronic injuries (e.g., fibrosis and carcinogenesis) induced by nanoparticles raised public health concerns and need to be rapidly assessed in hazard identification.

Medical foundation large language models for comprehensive text analysis and beyond.

Recent advancements in large language models (LLMs) show significant potential in medical applications but are hindered by limited specialized medical knowledge. We present Me-LLaMA, a family of open-source medical LLMs integrating extensive domain-specific knowledge with robust instruction-following capabilities. Me-LLaMA is developed through continual pretraining and instruction tuning of LLaMA2 models using diverse biomedical and clinical data sources (e.

Online Processing of Grammatical Aspect in Subsamples of Preschool Mandarin-acquiring Autistic Children.

Grammatical comprehension remains a strength in English-acquiring autistic preschoolers, yet limited studies have examined how autistic children process grammatical constructions in real time, in any language. This study sought to characterize the online processing of grammatical aspect in a diverse sample of Mandarin-acquiring autistic children. Forty-six 3-6-year-old autistic children, further divided into high (N = 23) and low verbal subgroups (N = 23) based on their expressive vocabulary levels, were assessed via Intermodal Preferential Looking (IPL).

PH-LLM: Public Health Large Language Models for Infoveillance.

Background: The effectiveness of public health intervention, such as vaccination and social distancing, relies on public support and adherence. Social media has emerged as a critical platform for understanding and fostering public engagement with health interventions. However, the lack of real-time surveillance on public health issues leveraging social media data, particularly during public health emergencies, leads to delayed responses and suboptimal policy adjustments.