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PubMed2026

Scalable, open-access and multidisciplinary data integration pipeline for climate-sensitive diseases.

Climate-sensitive infectious diseases pose an important challenge for human, animal and environmental health and it has been estimated that over half of known human pathogenic diseases can be aggravated by climate change. While climatic and weather conditions are important drivers of transmission of vector-borne diseases, socio-economic, behavioural, and land-use factors as well as the interactions among them impact transmission dynamics. Analysis of drivers of climate-sensitive diseases require rapid integration of interdisciplinary data to be jointly analysed with epidemiological (including genomic and clinical) data. Current tools for the integration of multiple data sources are often limited to one data type or rely on proprietary data and software. To address this gap, we develop a scalable and open-access pipeline for the integration of multiple spatio-temporal datasets that requires only the declaration of the country and temporal range and resolution of the study. The tool is locally deployable and can easily be integrated into existing climate-disease-modelling applications. We demonstrate the utility of the tool for dengue modelling in Vietnam where epidemiological data are legally required to remain local. We include a pipeline for bias correction of climate data to enhance their quality for downstream modelling tasks. The Dengue Advanced Readiness Tools-Pipeline empowers users by simplifying complex download, correction, and aggregation steps, fostering data-driven discovery of relationships between infectious diseases and their drivers in space and time, and enhancing reproducibility in research. Additional modules and datasets can be added to the existing ones to make the pipeline extendable to use cases other than the ones presented here.

automated workflows↗

PubMed1975

[Veterinary genetics].

At the age of scientific and technical progress and of industrialization of animal husbandry neither theoretical nor applied science can dispense with the data of the veterinary genetics. Unfortunately this branch of science does not receive the attention it deserves. The following three problems have to be solved by the veterinary genetics: (1) the investigation of the relationship between the heredity and the pathology of animals; the examination of the mechanism of pathology at the molecular and organism genetic levels; (2) the elaboration of the methods of genetic diagnostics; (3) the search for scientifically-substantiated directions in breeding of animal breeds highly resistant to diseases. The main attention will be paid to the investigation of the mechanisms ensuring the natural resistance of animals to certain definite diseases. The establishment and development of veterinary genetics will exert a favourable influence on the progress of biological sciences. Its data will be indispensable both for the theory and the practice of agriculture.

Animal Diseases↗

PubMed1979

Intensive care data--I: Computer controlled analysis.

A flexible, simple computer-controlled system for analysis of administrative and clinical data in intensive care is described. The system uses an interactive data input programme to facilitate data entry, an editor to correct errors, and the Statistical Package for the Social Sciences (SPSS) for data selection, retrieval and analysis. The system has the following features: data input is simple; large amounts of data can be handled rapidly and accurately; old data is readily available for comparison with new data and can be included in the present analysis; available statistical packages remove the need for a programmer; complex analyses are possible. The system has been successfully used for two years to provide administrative and clinical data which is pertinent to patient care.

Australia↗

PubMed1977

The impact of an elective curriculum in pathology.

Under the revised medical curriculum at Duke University, elective courses were offered in the third and fourth years beginning in 1968-1969. Departmental electives in autopsy, surgical, and systemic pathology were offered as major courses, and the subspecialty courses in cardiovascular, renal, pulmonary, pediatric, and neuropathology were taught by specialists in those areas. Special topics in subcellular and molecular pathology, neoplasia, environmental diseases, and experimental pathology were subscribed by medical and graduate students alike. To determine the impact of elective courses in pathology, these electives were compared to those offered by other basic science disciplines. Tabulation of total courses offered, student enrollment, and total academic credit hours were constructed for each basic science area. The data show that over the six year study period the students elected more courses in pathology than in any other basic science. The most heavily subscribed electives in pathology were those that were clinically oriented, such as cardiovascular or renal pathology. One impact of this elective system may be to enhance recruitment. During the period studied, 29 Duke graduates interned in pathology compared to six under a comparable time period in the traditional curriculum.

Curriculum↗

PubMed2026

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n = 10, 62.5%), language (n = 2, 12.5%), gait (n = 2, 12.5%), caregiver proximity (n = 1, 6.3%), EEG power (n = 1, 6.3%), and arousal (n = 1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps, and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans↗

PubMed2025

CAKL: Commutative algebra k-mer learning of genomics.

Despite the availability of various sequence analysis models, comparative genomic analysis remains a challenge in genomics, genetics, and phylogenetics. Commutative algebra, a fundamental tool in algebraic geometry and number theory, has rarely been used in data and biological sciences. In this study, we introduce commutative algebra k-mer learning (CAKL) as the first-ever nonlinear algebraic framework for analyzing genomic sequences. CAKL bridges between commutative algebra, algebraic topology, combinatorics, and machine learning to establish a new mathematical paradigm for comparative genomic analysis. We evaluate its effectiveness on three tasks-genetic variant identification, phylogenetic tree analysis, and viral genome classification-typically requiring alignment-based, alignment-free, and machine-learning approaches, respectively. Across eleven datasets, CAKL outperforms five state-of-the-art sequence analysis methods, particularly in viral classification, and maintains stable predictive accuracy as dataset size increases, underscoring its scalability and robustness. This work ushers in a new era in commutative algebraic data analysis and learning.

Journal Article↗

PubMedDate not supplied

The role of the forensic pathologist in the investigation of fatal traffic accidents--the Finnish system.

In Finland about one-half of the fatal traffic accidents are investigated by special Boards of Inquiry. The cumulating data serves multidisciplinary sciences, juridical and insurance purposes and legislation. The participating physicians benefit from the systematic work of the Boards in many ways. As an example of the results a list of causes of accidents is shown.

Accidents, Traffic↗

PubMed2026

CAKR: commutative algebra k-mer representations for genomics.

Despite the availability of various sequence analysis models, comparative genomic analysis remains a challenge in genomics, genetics, and phylogenetics. Commutative algebra, a fundamental tool in algebraic geometry and number theory, has rarely been used in data and biological sciences. In this study, we introduce commutative algebra k-mer representations as a nonlinear algebraic framework for analyzing genomic sequences. This representation bridges commutative algebra, algebraic topology, combinatorics, and machine learning to establish a mathematical framework for comparative genomic analysis. We evaluate its effectiveness on three tasks including genetic variant classification, phylogenetic tree reconstruction, and viral classification, typically requiring alignment-based, alignment-free, and machine-learning approaches, respectively. In this work, we show that commutative algebra k-mer representations outperform five state-of-the-art sequence analysis methods across twelve primary datasets, with two additional supplementary fragment-placement benchmarks, especially in viral classification, and maintain relatively stable predictive accuracy as dataset size increases, underscoring scalability and robustness.

Genomics↗

PubMed1978

Healthy family functioning: a cross-cultural appraisal.

It is increasingly recognized that rapid cultural, social, economic, and technological changes are imposing increasing stress on family structures, traditional values, and the ability to adapt to new environments in different societies. For the purposes of this paper, "healthy family functioning" is defined in terms of a family unit (however it is conceived in any given culture) effectively coping with cultural, environmental, psychosocial, and socioeconomic stresses throughout the family life cycle. While a review of international literature in the behavioural and biomedical sciences yields little data on comparative studies, there is growing awareness of the need for cooperative international research on family coping mechanisms and determinants of self-reliant communal coping behaviour, as well as more efficient utilization of already available knowledge. After consideration of methodological pitfalls of assessment procedures, there is a presentation of an evolving theory of healthy family functioning with the suggestion that studies of young married couples constitute a particularly promising vehicle for developing needed cooperative cross-cultural research.

Cross-Cultural Comparison↗

PubMed1979

Information system, data bases, and on-line services of the Japan Information Center of Science and Technology (JICST).

The JICST information processing system consists of the data-base production system, authority file management system, bibliographic retrieval system, and printed issue compiling system. The bibliographic retrieval service based on the JICST On-line Information System (JOIS-I) has been available through leased line since 1976 and now also through dial-up line, which covers five data bases: the JICST bibliographic and on-going research information files, CA Condensates, MEDLARS, and TOXLINE files. The on-line output in Japanese kanji is also available. The newly revised JOIS-II system is now being developed.

Forecasting↗

PubMed1979

AVLINE: a search resource for audiovisual instructional materials.

This manuscript describes the historical development and present scope of AVLINE (AudioVisuals-on-LINE), the National Library of Medicine's computer data base of information on nonprint instructional materials in dentistry, medicine, nursing, and allied health. The manuscript outlines the early and present review processes and involvement of dentistry peer reviewers; and provides data describing AVLINE titles by health science discipline and media characteristics for the total data base and the subset of dentistry. The manuscript also includes information on how to access AVLINE and a sample AVLINE citation.

Audiovisual Aids↗

PubMed2026

Neurometabolites and Antipsychotic Response in Psychosis: A Mega-Analysis.

IMPORTANCE: Revealing neurobiological markers of antipsychotic nonresponse in psychosis may aid outcome prediction and inform novel treatment targets. OBJECTIVE: To examine differences in neurometabolites in antipsychotic nonresponsive compared to antipsychotic-responsive psychosis using individual participant data and meta-analysis. DATA SOURCES: Web of Science was searched for studies published between January 1, 1980, and November 1, 2025. Authors of 21 eligible studies identified before August 2024 were invited to contribute individual participant data. STUDY SELECTION: Eighteen studies examining neurometabolites by treatment response in psychosis contributed individual participant data for the mega-analysis. These studies plus a further 5 studies were included in the meta-analyses of standardized mean differences and variability. DATA EXTRACTION AND SYNTHESIS: Individual participant data were analyzed using linear mixed models with study as a random effect. Subgroup analyses examined prospective designs and treatment-resistant samples. Published group means and standard deviations were extracted for meta-analyses. MAIN OUTCOMES AND MEASURES: Group differences in glutamate, glutamate plus glutamine, choline, myo-inositol, N-acetylaspartate, γ-aminobutyric acid, and glutathione in the medial frontal cortex, dorsolateral prefrontal cortex, thalamus, and basal ganglia. RESULTS: The mega-analysis included 1189 participants from 18 studies; of these, 476 were treatment nonresponders (mean [SD] age, 33.0 [12.5] years; 340 male), 427 were treatment responders (mean [SD] age, 30.3 [11.5] years; 299 male), and 286 were healthy control individuals (mean [SD] age, 31.0 [12.5] years; 170 male). Compared with the antipsychotic response group, nonresponders showed elevations in medial frontal glutamate (Glass Δ = 0.21; P = .02), glutamate plus glutamine (Glass Δ = 0.29; P = .002), choline (Glass Δ = 0.22; P = .03), and myo-inositol (Glass Δ = 0.35; P = .001); similar elevations were observed relative to control individuals. Elevated medial frontal glutamate plus glutamine in antipsychotic nonresponders compared with responders was also observed prospectively in first-episode psychosis (Glass Δ = 0.41; P = .002), whereas myo-inositol elevations were greatest in individuals meeting criteria for treatment-resistance (Glass Δ = 0.64; P = .001). The meta-analysis of 23 studies (1844 participants) also showed elevated medial frontal choline and myo-inositol in antipsychotic nonresponse compared with response. CONCLUSIONS AND RELEVANCE: These findings provide evidence of an association between antipsychotic nonresponse in psychosis with elevations in medial frontal glutamate, choline, and myo-inositol. The presence of elevations in these markers supports the continued investigation of glutamate-acting and inflammatory pathway-associated interventions for psychosis and schizophrenia.

Humans↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Clade-dependent antifungal resistance and susceptibility in Candidozyma auris: A global scoping review.

BACKGROUND: Candidozyma auris (formerly Candida auris) is an emerging multidrug-resistant fungal pathogen that has spread globally since its first identification in 2009 and is now classified as a critical-priority pathogen by the World Health Organization. Distinct genetic clades are associated with variations in geographic distribution, antifungal susceptibility, and resistance mechanisms; however, clade-specific evidence remains fragmented. AIMS: To systematically map global evidence on clade diversity, antifungal susceptibility patterns, resistance mechanisms, and clinical implications of C. auris. METHODS: A scoping review was conducted following PRISMA-ScR guidelines. Peer-reviewed primary studies published between 2009 and September 2025 were included if they reported clade attribution and antifungal susceptibility or resistance data. PubMed/MEDLINE, Scopus, and Web of Science were searched. Two reviewers independently screened studies and extracted data using a standardized form. RESULTS: Of 2050 records identified, 105 studies met inclusion criteria, representing 29 countries and diverse study designs. Whole-genome sequencing was the most common typing method. Antifungal susceptibility varied substantially across clades. High fluconazole resistance was consistently reported (MIC 4 to >256μg/mL). Echinocandins generally retained activity, although reduced susceptibility associated with FKS1 mutations was observed. Resistance mechanisms primarily involved mutations in ERG11, FKS1, and efflux-related genes. Studies also reported challenges in healthcare-associated transmission, environmental persistence, and diagnostic misidentification. CONCLUSIONS: C. auris exhibits marked clade-dependent variability in antifungal susceptibility and resistance mechanisms. These findings support the need for clade-informed interpretation of susceptibility data, standardized surveillance, improved diagnostics, and development of novel antifungal therapies.

Antifungal Agents↗

PubMed1978

Management data for collection analysis and development.

Sound management data are needed to evaluate the collections of health sciences libraries. This study reports the utilization of computer data bases to compare the libary collections of The University of Texas Health Science Center at San Antonio. The University of Texas Medical Branch, and the National Library of Medicine's CATLINE data base. The imprint dates of the records of two libraries are compared to measure acquisitions rates. Subject profiles for the Q and W classes demonstrate the similarity of the collections. Reasons for the variances are considered.

Analysis of Variance↗

PubMed2026

Effects of blood flow restriction training combined with resistance training on lower-limb strength and sport-specific performance in athletes: a systematic review and meta-analysis.

BACKGROUND: In contemporary sports science, athletes and coaches continuously explore strategies to reduce training load and injury risk while increasing muscular strength and sport-specific performance. This meta-analysis evaluated the effects of blood flow restriction training (BFRT) combined with resistance training (RT) on lower-limb muscle strength and sport-specific performance in athletes. METHODS: Relevant randomized controlled trials (RCTs) were systematically searched across major databases (e.g. PubMed, Web of Science, Cochrane, CNKI, Wanfang Data, and Embase) from inception until November 2024. Two independent reviewers carefully assessed the studies. Data analysis was carried out using RevMan 5.4 software, which included heterogeneity testing, meta-analysis, subgroup analysis, and assessment of publication bias. RESULTS: Ten RCTs (181 athletes; 91 in the BFRT and RT group, 90 in the control group) were included. Outcomes determined BFRT combined with RT yielded notable enhancements in lower-limb muscle strength (SMD = 1.09, 95% CI [0.52, 1.66], p < 0.05) and muscle hypertrophy (MD = 1.09, 95% CI [0.10, 2.09], p < 0.05) compared to control training. However, no significant improvement in sport-specific performance was found (SMD = 0.11, 95% CI [-0.18, 0.40], p = 0.46). Substantial heterogeneity was observed for strength outcomes (I2 = 75%), whereas low heterogeneity was observed for sport-specific performance and hypertrophy outcomes (I2 = 0%). No evidence of significant publication bias was detected. CONCLUSION: BFRT combined with RT appears to provide effective augmentation of lower-limb muscle strength and hypertrophy in athletes compared to RT or conventional training alone. It may be prudent to integrate this approach systematically into training cycles to optimize physiological muscle stimulation and training outcomes, despite not directly improving sport-specific performance.

Humans↗

PubMed1979

Searching the MEDLARS file on NLM and BRS a comparative study.

A comparison of the MEDLARS data base as it is currently available from the National Library of Medicine and Bibliographic Retrieval Services (BRS), Inc., is presented in chart format, and some major capability differences between the two systems are highlighted. The information inlcuded justifies the dual availability of the data base in health sciences libraries. This paper is intended for searchers and others familiar with one or both systems. Administrators considering the acquisition of the BRS system may find the study useful.

MEDLARS↗

PubMed2025

A decentralized future for the open-science databases.

The continuous and reliable open access to curated biological data repositories is indispensable for accelerating rigorous scientific inquiry and fostering reproducible research outcomes. However, the current paradigm, which relies heavily on centralized infrastructure for the storage and distribution of foundational biomedical datasets, inherently introduces significant vulnerabilities. This centralized model is susceptible to single points of failure, including cyberattacks, technical malfunctions, natural disasters, and even political or funding uncertainties. Such disruptions can lead to widespread data unavailability, data loss, integrity compromises, and substantial delays in critical research, ultimately impeding scientific progress. The downstream effect of such interruptions can be the widespread paralysis of diverse research activities, including computational, clinical, molecular, and climate studies. This scenario vividly illustrates the inherent dangers of consolidating essential scientific resources within a single geopolitical or institutional locus. As data generation is accelerating and the global landscape continues to fluctuate, the sustainability of centralized models must be critically re-evaluated. A shift toward federated and decentralized architectures may offer a robust and forward-looking approach to enhancing the resilience of scientific data infrastructures by reducing exposure to governance instability, infrastructural fragility, and funding volatility, while also promoting equity and global accessibility. Inspired by established models such as ELIXIR's federated infrastructure and the policy and funding frameworks developed by CODATA and the Global Biodata Coalition (GBC), emerging Decentralized Science (DeSci) initiatives can contribute to building more resilient, fair, and incentive-aligned data ecosystems. The future of open science depends on integrating these complementary approaches to establish a globally distributed, economically sustainable, and institutionally robust infrastructure that safeguards scientific data as a public good, further ensuring continued accessibility, interoperability, and preservation for generations to come. Here, we examine the structural limitations of centralized repositories, evaluate federated and decentralized models, and propose a hybrid framework for resilient, fair, and sustainable scientific data stewardship.

data accessibility↗