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PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2026

Impact of Integrated Continuous Team Midwifery Care on Breastfeeding Success within the Iranian Health System: A Randomized Controlled Trial.

INTRODUCTION: Supporting women during the perinatal period helps build confidence, strengthens early bonding between mother and baby, and encourages successful breastfeeding. Continuous midwifery care models are one of the ways that support women in this periods. OBJECTIVE: This study aimed to evaluate the effect of integrated continuous team midwifery care (ICTMC) in enhancing breastfeeding success in the Iranian health system. METHODS: In this randomized controlled trial, 200 low-risk primiparous women with a gestational age of less than 12 weeks were recruited from public health centers. Participants were randomly assigned to either the intervention group, which received continuous midwifery care throughout pregnancy, childbirth, and postnatal follow-up, or the control group, which received routine care. The primary outcomes were early skin-to-skin contact and breastfeeding success at the time of discharge and at 4-6 weeks postpartum. Data were analyzed using Stata, employing descriptive statistics, Chi-square, independent t-test, Phi/Cramer's V, and Cohen's d. The p < 0.05 is significant. Data were analyzed with SPSS 26. RESULTS: ICTMC groups were significantly more likely to initiate skin-to-skin contactearly skin-to-skin contact immediately after birth (92% vs. 74%, p < 0.001) and achieve successful breastfeeding at the discharge time (88% vs. 70%, p = 0.002) compared to the control group. At 6 weeks postpartum, breastfeeding success remained higher in the intervention group (82% vs. 65%, p = 0.004). CONCLUSION: Women with ICTMC, effectively support skin-to-skin contactearly mother-infant bonding and enhance breastfeeding success among low-risk primiparous women. Integrating this model into routine maternal care may improve perinatal outcomes.

Humans↗

PubMed2026

Anabolic androgen therapy in critically ill adults: A systematic review and meta-analysis.

Critical illness is characterized by a catabolic, proinflammatory state. Anabolic agents, such as testosterone, have therefore been proposed as therapeutic targets. Our objectives were to assess the effects of testosterone in critically ill populations on patient-important outcomes and identify design limitations to inform future studies. We searched for randomized control trials (RCTs) through Medline, Embase, and EBM Reviews databases from inception through February 24, 2026, including English language articles enrolling adults (≥18 years) admitted to ICU where anabolic androgen therapies (AAT) were compared with placebo or standard of care. Studies had to report at least one of: mortality, ICU and hospital lengths of stay, or duration of mechanical ventilation. We extracted data independently using a standardized data extraction tool, and feedback was received from all co-authors to ensure agreement. For each outcome, we performed meta-analyses using a random-effects model with inverse variance weighting in RevMan. We used the GRADE approach to assess certainty in pooled estimates of effect. Of 1325 screened articles, we found 4 that fit our inclusion criteria. Together, we judged risk of bias as 'some concerns' in 3 trials and 'high' in the final trial, and ultimately found that the effects of anabolic-androgen therapy on patient-important outcomes uncertain. With the uncertainty of current evidence for the effects of anabolic-androgen therapy in critically ill adults, there is insufficient support for its routine use. Future randomized evidence is needed to determine whether anabolic-androgen therapy improves clinically-important outcomes and better define its safety profile in critically ill adults.

Humans↗

PubMed2026

Costs of surgeries in low- and middle-income countries: a systematic literature review.

BACKGROUND: Surgical care is essential for achieving global health equity, yet low- and middle-income countries (LMICs) face major gaps in access and planning, partly due to limited evidence on the costs and resource requirements of surgical interventions. Understanding these costs is vital for designing efficient and equitable health systems. METHODS: We conducted a systematic literature review (covering MEDLINE, EMBASE, Global Health, EconLit and grey literature) to identify studies reporting the costs of surgeries in LMICs from January 2000 to June 2023. Minor and major surgical procedures were considered, focusing on therapeutic procedures (excluding diagnostic interventions). Studies that clearly identified, quantified and costed hospital resources and services deployed in the provision of surgical care, and included at least two of the surgical production factors (ie, consumables, diagnostics, personnel, infrastructure and overhead) in the costing were included. Costs were standardised to 2023 International dollars (I$) for comparability. RESULTS: A total of 74 studies from 29 countries met the inclusion criteria, with 210 cost estimates across 65 procedure groups. Costs varied widely: from I$1.54 for a caesarean section in Tanzania to I$618 098 for paediatric cataract surgery in Zambia. Full costing studies reported higher estimates than partial costing studies. Most studies (60%) originated from upper-middle-income countries, with limited data (10%) from low-income settings. CONCLUSION: This review provides a reference list of surgical procedure costs across LMICs, highlighting considerable cost variation by procedure, specialty and country. The findings underscore the need for better-quality, standardised cost data-especially from low-income countries-to inform national surgical plans, universal health coverage benefit packages and reimbursement policies.

Developing Countries↗

PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

Humans↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Role of nicotine metabolite ratio in pharmacological interventions on smoking cessation: A systematic review and meta-analyses of randomized controlled trials.

BACKGROUND AND OBJECTIVES: Emerging evidence suggests that the nicotine metabolite ratio (NMR) may influence the efficacy of smoking cessation, yet its role across pharmacotherapies remains unclear. This study aims to investigate how NMR affects cessation outcomes under different medications to guide personalized treatment. METHODS: We searched PubMed, Medline, EMBASE, and the Cochrane Central Register of Controlled Trials (inception to September 30, 2024) for randomized controlled trials on pharmacotherapy for smoking cessation with NMR data. Data were synthesized using random-effects models, with heterogeneity assessment. The primary outcome was verified smoking cessation rate at the end of treatment or the closest time-point. RESULTS: Eleven RCTs with accessible full text were included in the qualitative analyses and nine were included in the quantitative synthesis. For non-titratable nicotine replacement therapy (NRT), normal/fast metabolizers demonstrated lower odds of smoking cessation than slow metabolizers (Odds Ratio, OR=0.81, 95% confidence interval, CI=0.68-0.96; 5 studies, I²=62.5%). No significant associations were shown between normal/fast and slow metabolizers using titratable NRT (OR=1.04, 95% CI=0.95-1.14; 2 studies, I²=0%), bupropion (OR=0.67, 95% CI=0.38-1.16; 2 studies, I²=51.4%), or varenicline (OR=1.17, 95% CI=0.79-1.74; 4 studies, I²=59.8%). CONCLUSION: Current evidence demonstrates that NMR moderates' treatment efficacy among those who smoke using non-titratable NRT, with slow metabolizers achieving significantly better cessation outcomes than normal/fast metabolizers. Substantial further research is needed to determine optimal medication hierarchies across metabolic profiles.

Humans↗

PubMed2026

Complementary feeding patterns in preterm and term infants.

Complementary feeding is essential for infants' nutritional status and development, marking the transition to solid foods when breast milk or formula alone is insufficient. Despite its importance, clear recommendations on which foods to introduce when initiating complementary feeding in preterm infants are lacking. By using data from our previously published randomized controlled trial on the timing of complementary feeding in preterm infants, the current study explores the complementary feeding patterns of preterm infants and compares them with those of term-born infants, providing insights into parental decision-making and potential long-term health impacts. Complementary feeding practices differed significantly between preterm (n = 255) and term (n = 159) infants, with preterm infants more often receiving vegetables as their first solid food (85.4% versus 68.8%, difference 17.6% with 95% CI 12-35%). The group with early introduction of vegetables had a lower BMI-for-age z-scores (β -0.28 [95% CI -0.55 - 0.02]) and weight-for-height z-scores (β -0.27 [95% CI -0.53 to -0.01]) at two years of age. Additionally, preterm infants showed a greater variety in the numbers of different fruits and vegetables consumed by six months (corrected) age than term-born counterparts (8.29 (SD 3.65) versus 6.26 (SD 3.47), p < 0.001). These results indicate that complementary feeding patterns in preterm infants differ from term-born infants, with potential positive implications on growth. These data contribute to the development of accurate feeding protocols for preterm infants. Given that feeding practices are culturally influenced, further multinational research is essential to refine complementary feeding guidelines for preterm infants and support caregivers in informed decision-making.

Humans↗

PubMed2026

Relational care in community mental health: Evaluating staff experiences in Intensive Community Care Services (ICCS) vs treatment as usual.

BACKGROUND: The quality of healthcare delivery relies heavily on building strong relationships between healthcare providers (HCPs) and clients. This study presents the results of a process evaluation for a Randomised Controlled Trial (RCT) examining the effectiveness of Intensive Community Care Service (ICCS) vs Treatment as Usual (TAU; inpatient or core community CAMHS). METHODS: Thirty-four semi-structured interviews were conducted with staff across various services, including 20 from ICCS and 14 other TAU services. A thematic decomposition analysis was conducted on the data, and specific themes relevant to staff experiences of young people's engagement with services and overall recovery. RESULTS: Three main themes were observed in the HCP data (1. Relational Ecologies: barriers and enablers to engagement, 2. flexibility of approach amidst systemic pressures and 3. the web of trust in the relationship-building process). HCPs highlighted the necessity of developing trust and rapport through non-clinical engagement strategies, such as informal visits and personalised interactions. HCPs emphasised that without trust, treatment effectiveness diminishes, necessitating a tailored approach rather than a one-size-fits-all model. The flexibility in duration of treatment and methods of engagement was noted as crucial in accommodating individual client needs and fostering an open, trusting environment necessary for long-term recovery. CONCLUSION: The findings highlight the vital importance of relational care models, especially ICCS, in addressing the complex needs of Children and Young People (CYP). Flexible, family-centred approaches improve trust, engagement, and long-term recovery outcomes. Recommendations include tackling systemic barriers and expanding relational care models within CAMHS to meet increasing mental health demands effectively. Further research should investigate scalable strategies for integrating these insights into wider mental health service frameworks.

Humans↗

PubMed2026

Genetic Ancestry and Carrier Variant Frequency Enrichment in a Colombian Andean Population: Insights From the Eje Cafetero.

Colombia is one of the most genetically diverse populations in Latin America, and its demographic process has promoted the persistence and local enrichment of deleterious alleles, increasing the frequency of autosomal recessive disorders, particularly in semi-isolated Andean populations such as the Eje Cafetero. However, exome-based reference data from this region remain scarce, limiting ancestry-aware variant interpretation and carrier screening strategies. We aimed to characterize the ancestry proportions of this population using exome data, and to estimate the carrier frequency and distribution of pathogenic and likely pathogenic (P/LP) variants in clinically relevant recessive genes. We conducted a cross-sectional study with whole-exome sequencing (WES) in 316 unrelated individuals from the Colombian Eje Cafetero. P/LP variants were evaluated in 454 genes associated with autosomal recessive disorders. The global ancestry proportions were estimated using a validated panel of 250 exome-compatible ancestry-informative markers. Carrier frequencies were compared against Non-Finnish Europeans (NFE) and Admixed Americans (AMX) from gnomAD v4. The cohort showed predominant European ancestry (mean 51%), followed by Native American (36%) and African (13%) components. We identified 151 carriers of 89 distinct pathogenic variants across autosomal recessive genes. The most frequent variants were SERPINA1 c.863A>T (5.5%), CFTR c.1210-11T>G (3.5%), and PYGM c.1094C>T (1.5%). Also, recurrent variants were significantly enriched compared with both NFE and AMX populations, supporting regional founder effects. This study represents one of the most comprehensive exome-based genetic characterizations of the Colombian Eje Cafetero, revealing ancestry-specific enrichment of clinically relevant autosomal recessive variants driven by founder effects.

Female↗

PubMed2026

Water intake, switching between bites and sips, and drinking behavior are associated with food intake across meals varying in spiciness: A secondary analysis of two randomized crossover studies.

Widespread nutrition advice instructs consumers to drink water with meals to increase fullness and reduce energy intake. However, recent data indicates greater water intake is associated with more food intake at a meal, not less. Switching between meal components (e.g., alternating between food and water), has also been associated with increased food intake at a pasta meal, but it remains unclear whether this applies to other foods. In a secondary analysis, we pooled existing data from 2 crossover experiments (total n = 86) where adults ate an ad libitum lunch consisting of 650 g of beef chili (n = 52) or chicken tikka masala (n = 34) with 450 g of water twice in the laboratory while being video-recorded. For both experiments, the spiciness of the lunch was varied by adding different ratios of hot:sweet paprika. Videos were coded to measure sip number, sip size (g/sip), drinking rate (g/min), and number of switches between bites of food and sips of water. As we previously reported, increasing spiciness slowed eating rate and reduced food intake; in secondary analyses described here, the reduction in food intake was not moderated by water intake, switching, or drinking behaviors (all p > 0.73). Notably, across all meals, greater water intake (p < 0.001) and switching (p = 0.02) associated with greater food intake. Overall, individuals ate more when they drank more and switched between bites and sips more often, highlighting the potential influence of water and drinking behaviors on food consumption. This finding challenges the widespread dietary advice to drink water with meals to reduce food intake.

Humans↗

PubMed2026

The potential of clustering methods for pre-test triage in sleep medicine: A systematic review.

Sleep disorders exhibit substantial heterogeneity, and traditional classifications may not fully capture clinically relevant subtypes. Clustering techniques can identify patient subgroups that improve phenotypic characterization and may support personalized management. This systematic review evaluated the application of clustering in sleep medicine, with particular focus on its potential use as a pre-test triage tool prior to formal sleep testing. PubMed/MEDLINE, Embase, Web of Science, and Scopus were searched to February 2025. Eligible studies applied clustering to classify sleep disorders in adults. Two reviewers independently conducted screening, data extraction, and risk-of-bias assessment using QUADAS-2. The protocol was registered on PROSPERO. Fifty-one studies (1983-2025) were included, predominantly focused on obstructive sleep apnea (OSA) (n = 38, 74%). Hierarchical clustering (n = 20) and K-means clustering (n = 14) were the most frequently used techniques. Internal validation was reported in only 18% of studies, and external validation was reported in only 1 study. Seven studies relied exclusively on baseline clinical, demographic, or questionnaire data, representing pre-test scenarios, whereas most incorporated polysomnography-derived variables, limiting their applicability to early clinical stratification. Hierarchical clustering was the most commonly applied method; however, the overall lack of validation limits confidence in the robustness and clinical applicability of identified phenotypes. The potential role of clustering as a pre-test triage strategy remains largely unexplored, as most studies focused on post-diagnostic phenotyping and were affected by incorporation bias. Future research should prioritize pre-test clinical variables, rigorously validate internally and externally, and adopt standardized methodological and reporting practices to facilitate clinical translation.

Humans↗

PubMed2026

Thyroid-joint crosstalk: a systematic review and meta-analysis of thyroid autoimmunity and dysfunction in juvenile idiopathic arthritis.

BACKGROUND: Recent observational studies outlined the concomitant presence of autoimmune diseases in children with juvenile idiopathic arthritis (JIA), including endocrine autoimmunity. Despite the growing evidence of thyroid involvement in JIA, available data are heterogeneous and fragmented. We aimed to systematically review the available evidence on the prevalence of thyroid autoantibody positivity and thyroid dysfunction in patients with JIA. METHODS: PubMed/Medline, Cochrane, and Scopus databases were approached to identify studies reporting data on thyroid autoantibody positivity and dysfunction in children with JIA. RESULTS: A total of 15 studies were included in the final analysis, encompassing 19 015 children with JIA (13 225 females, 69.6%) with a weighted mean age of 8.0 years (range 1.8-21 years). The pooled prevalence estimates of antithyroid antibody positivity and thyroid dysfunction were 0.04 (95% CI: 0.03-0.05) and 0.04 (95% CI: 0.03-0.08), respectively. The risk difference for thyroid autoantibody positivity between children with JIA and controls was 0.08 (95% CI: 0.02-0.14). Possible risk factors were analyzed: the presence of family history for thyroid autoimmune disease (odds ratio - OR 3.91, 95% CI 1.86-8.25), concurrent Antinuclear Antibodies (ANA) positivity (OR 1.62, 95% CI 1.13-2.31), and older age (MD 2.10 years, 95% CI 1.32-2.89) were associated with thyroid autoantibody positivity and/or thyroid dysfunction in children with JIA. No significant difference emerged for the specific JIA form. CONCLUSION: Thyroid dysfunction may be detected in children with JIA, with a significant risk difference in comparison to healthy controls. Specific clinical characteristics, such as family history, ANA positivity, and older age at JIA onset, may suggest which patients should benefit from thyroid autoantibody screening.

Humans↗

PubMed2026

Life-course stress exposure and cognitive decline in middle-aged and older Chinese adults: The role of sex differences and educational protection.

BACKGROUND: Stressful life events (SLEs) across the life course have been associated with cognitive decline, but evidence on their cumulative impact and potential modifiers remains limited. We aimed to examine the associations between SLE exposure in childhood, adulthood, or both life stages and cognitive trajectories, and to investigate whether these associations vary by sex and education. METHODS: We used data from the China Health and Retirement Longitudinal Study, a nationally representative cohort of adults aged ≥45 years. Participants with complete data on SLEs, cognition, and covariates were included (n = 5922). SLEs were retrospectively assessed for childhood and adulthood. Cognitive function was measured using a composite score (range 0-21) across three waves (2011-2015). Linear mixed-effects models examined longitudinal associations, adjusting for sociodemographic factors, health behaviors, and chronic conditions, with interaction analyses for sex and education. RESULTS: Compared with participants reporting no SLEs, cumulative exposure showed the strongest association with cognitive decline (β = -0.52, 95% CI -0.69 to -0.35), followed by childhood-only (β = -0.34, -0.48 to -0.20) and adulthood-only exposure (β = -0.22, -0.37 to -0.07). Sex significantly moderated the associations for childhood and cumulative exposure, with women exhibiting greater cognitive vulnerability. Higher educational attainment attenuated the associations between single-period stress and cognitive decline, with only partial protection observed against cumulative adversity. CONCLUSION: Cumulative life-course stress is associated with accelerated cognitive decline in Chinese middle-aged and older adults. Women appear more vulnerable to stress-related cognitive effects, whereas higher education confers partial resilience, highlighting the need for sex-sensitive and education-informed prevention strategies.

Humans↗

PubMed2026

Test-retest reliability of spatiotemporal, kinematic, and kinetic measures in marker-based 3D gait analysis: A systematic review.

BACKGROUND: Marker-based 3D gait analysis (3DGA) is widely used to quantify impairments and evaluate treatment effects. For longitudinal clinical interpretation, clinicians and researchers need reference values for inter-session measurement error. For this purpose, this systematic review synthesized Standard Error of Measurement (SEM) values for spatiotemporal, kinematic, and kinetic (moments) outcomes obtained from marker-based 3DGA studies. METHODS: PubMed and Scopus were searched (final search: 11 December 2025). Studies reporting inter-session test-retest SEM and/or MDC for steady-state overground or treadmill walking using marker-based motion capture were included. Two authors screened records and appraised methodological/reporting quality using a custom tool informed by COSMIN, GRRAS, and biomechanics-specific items. Due to heterogeneity, results were synthesized descriptively using study-level median SEM values, stratified by joint, plane, population (healthy, pathological, single subgroups), and walking condition. Minimal Detectable Change (MDC) values were computed for all available data. RESULTS: Thirty-four studies (762 participants, 44.2% females) were included, with substantially more evidence for overground than treadmill walking. Overground spatiotemporal outcomes showed low errors (walking speed SEM of 0.06 m/s; timing typically ≤0.03 s; spatial parameters generally ≤0.03 m). For joint kinematics during overground walking, median SEMs were 2.4° (sagittal), 1.9° (frontal), and 3.3° (transverse). The corresponding joint-kinetic SEMs were approximately 0.06, 0.04, and 0.03 Nm/kg, respectively. Treadmill data followed similar patterns. SIGNIFICANCE: Marker-based 3DGA allows for accurate assessment of spatiotemporal, kinematic, and kinetic gait features. We provided detailed SEM/MDC lookup tables to support clinical decision-making. Results further offer a benchmark for validating emerging gait assessment technologies (e.g., markerless systems) against realistic limits of marker-based 3DGA.

Humans↗

PubMed2026

Maternal obesity in rats results in male-specific increases in genome-wide DNA methylation in postnatal offspring liver.

Male-specific peripubertal DNA demethylation in the liver has been reported in mice. Here, we investigated whether it also occurs in rats, the influence of maternal obesity and whether DNA demethylation changes contribute to observed sex-specific effects of maternal obesity in offspring. Female rats were fed a high-fat, high-sugar 'cafeteria' (Caf) diet before mating with standard chow-fed males. The offspring liver methylome and transcriptome were examined. Body weight was higher in Caf-fed dams prior to mating, during gestation and at parturition. Male and female offspring from Caf-fed dams had lower birth weights but higher adult weights and adiposity than offspring from chow-fed dams. A comparison of DNA methylation in 3-week-old weaner males versus female siblings from chow-fed dams did not reveal the male-specific DNA demethylation that was previously reported in mice. However, strong maternal diet effects in male weaner offspring methylation were observed. A comparison of female weaners from chow- versus Caf-fed dams showed a range of differences, with 39% of differentially methylated regions (DMRs) having higher methylation in Caf offspring and 61% of DMRs having higher methylation in chow offspring. In stark contrast, 99% of maternal-diet-induced DMRs in male weaner offspring had higher methylation in offspring from Caf-fed dams. This suggests that maternal obesity induces widespread hypermethylation in the male offspring liver at weaning. However, a comparison with RNA sequencing data revealed limited transcriptional changes at this developmental stage or in adult offspring. While these data highlight how environmentally sensitive DNA methylation is in the male rodent perinatal period, these methylation changes may not be a major contributor to sex differences in developmentally programmed liver disease.

Animals↗

PubMed2026

Non-motor symptoms and healthcare utilization before diagnosis of myasthenia gravis: a nationwide cohort study.

BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.

Humans↗