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PubMed2026

Evolution of Candidaemia and azole resistance in Italy: A multicentre retrospective study.

PURPOSE: Candidaemia is the most common healthcare-associated invasive fungal infection. The evolution of the epidemiology of candidaemia in Italy has not been assessed, except at the local level. The primary objective of this study is monitoring changes in the epidemiology of candidaemia and in the susceptibility profiles of Candida isolates between 2015 and 2023. METHODS: This retrospective multicentre study (2015-2023), involved 11 tertiary-care hospital microbiology laboratories across the Italian country. The confirmed candidaemia episodes were included and demographic data, hospital ward, species identification, and antifungal susceptibility profiles (Sensititre Yeast One) were collected. RESULTS: 6,927 candidaemia cases were identified; incidence increased from 1.1/1000 hospitalisations in 2017 to 2.3/1000 in 2020-2021, peaking during the COVID-19 pandemic, and declined in 2023 while remaining above prepandemic levels. Patients older than 65 years accounted for most infections. Medical wards represented the main setting of occurrence, followed by intensive care units, especially during pandemic years. C. albicans remained the most common species (45.4%), followed by C. parapsilosis (24.7%), C. glabrata (11.8%), and C. tropicalis (11.4%). Echinocandin resistance remained low (< 2% for C. albicans and C. glabrata), whereas azole resistance increased markedly, particularly in C. parapsilosis, reaching fluconazole resistance rates of 25.6% in 2022. CONCLUSIONS: Candidaemia increased during the 9-year study period in Italy, particularly in the COVID-19 pandemic, in medical wards and ICU. Emerged a growing azole resistance, underscoring the need for enhanced surveillance and informed empirical treatment strategies.

Candida species etiology↗

PubMed2026

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans↗

PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗

PubMed2026

Low Carbohydrate Availability in Energy Balance Alters Bone Turnover and Muscle Proteomic Response With Limited Endocrine Disruption.

Training with low carbohydrate availability (LCA) has been proposed as an independent determinant of physiological perturbations commonly attributed to low energy availability (LEA) and to increase skeletal muscle oxidative machinery, yet the effects of LCA in isolation from LEA remain unclear. We examined whether short-term carbohydrate restriction under energy balance alters endocrine and metabolic markers associated with LEA and skeletal muscle proteomic response. In a randomized crossover design, eight trained males completed 4 days of either a low-carbohydrate high-fat diet (LOW; 12% carbohydrate, 69% fat, 19% protein) or a normal-carbohydrate diet (NORM; 62% carbohydrate, 19% fat, 19% protein), while undertaking daily cycloergometer exercise (15 kcal kg FFM-1 day-1) and maintaining energy availability at 45 kcal kg FFM-1 day-1. LOW induced a clear metabolic shift consistent with LCA, evidenced by elevated circulating free fatty acids, glycerol and β-hydroxybutyrate, in fasting conditions and fat oxidation at rest and during exercise, alongside reduced exercise glucose concentrations. Despite these responses, LOW did not alter insulin, testosterone, triiodothyronine, leptin, hepcidin, or P1NP. In contrast, β-CTX increased and IGF-1 decreased relative to NORM. Muscle glycogen concentration decreased only in LOW (40% ± 14%). Proteomic analysis identified 671 proteins; 57 differentially expressed in LOW relative to NORM were limited to fatty acid metabolism pathways and suppression of ribosomal, sarcomeric, and extracellular matrix proteins. These findings indicate that isolated LCA exerts limited endocrine disruption but may selectively compromise bone turnover and muscle anabolic response, suggesting that without acute LEA, LCA has limited influence on muscle oxidative phenotype.

Male↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Menopause in the All of Us Research Program: a descriptive summary of electronic health record and survey response across sociodemographic characteristics.

OBJECTIVES: Menopause is a significant physiological transition with implications for health outcomes (eg, cardiometabolic disease), yet gaps remain in understanding this transition, including how menopause timing and type influence health outcomes. Large-scale cohort studies in midlife (age=40-60) females, including the All of Us Research Program (AoURP), provide opportunities to study menopause across diverse populations and data modalities. We characterized menopause-related data in AoURP, focusing on age distributions and concordance between electronic health record (EHR) diagnosis codes and survey responses. METHODS: We analyzed menopause-related surveys, EHR diagnostic codes, and genomic data among ~396,000 AoURP female participants. We summarized menopause-related variables across data sources, evaluated overlap between survey, EHR, and genomic data sets, and described age distributions overall and across sociodemographic characteristics. RESULTS: Among ~396,000 females, survey responses captured ~193,000 menopause observations, nearly seven times more than EHR diagnoses (~28,000), suggesting under-ascertainment in EHR data. Nearly all females (~99%) with an EHR menopause diagnosis reported menopause in the survey. Approximately 22,000 participants had overlapping menopause-related EHR, survey, and genomic data. Survey age patterns matched expectations, with participants predominantly <40 years reporting premenopausal status and those >60 years reporting postmenopausal status. A small subset with age >70 years (N≈1,700; 4%) reported no menopause, suggesting response or recall bias. EHR menopause codes were concentrated after age 45 years, with a notable spike at age 65. Modest differences in survey-based menopause age distributions were observed across sociodemographic characteristics (eg, race and ancestry). CONCLUSIONS: These findings inform sampling strategies, power calculations, phenotype definition, and study design for menopause research using AoURP data.

Age↗

PubMed2026

Efficacy of smartphone- and bibliotherapy-delivered multicomponent lifestyle medicine interventions for probable depression: A three-arm randomized controlled trial.

BACKGROUND: This study examined the efficacy of smartphone- (AG) and bibliotherapy-delivered (BG) lifestyle medicine (LM) interventions compared with a waitlist control group (WLG) in reducing depressive symptoms. METHODS: A total of 122 adults with probable depression were randomized to AG (n = 41), BG (n = 40), or WLG (n = 41). AG and BG received the same core 8-week multicomponent LM intervention via a smartphone application or booklets, respectively. The core content included lifestyle psychoeducation, physical activity, diet and nutrition, stress and sleep management, goal-setting, and motivational techniques. Outcomes were assessed at baseline and immediate post-intervention (Week 9) in all groups, with 1-month (Week 13) and 3-month (Week 21) follow-ups conducted in the intervention groups only. RESULTS: At Week 9, AG (d = 0.89) and BG (d = 0.64) showed significantly greater reductions in depressive symptoms than WLG, with within-group improvements maintained at 1- and 3-month follow-ups (ps <.001, d = 0.77-0.96). Clinically significant improvement was achieved by 78% of AG and 55% of BG participants, both significantly higher than WLG (19.5%; ps <.001). Compared with WLG, both interventions yielded greater improvements in overall lifestyle and physical activity (d = 0.59-0.91) at Week 9. The AG showed additional benefits for perceived stress, health responsibility, nutrition, spiritual growth, and stress management (d = 0.58-0.73), whereas BG uniquely improved insomnia symptoms (d = 0.83). CONCLUSION: Smartphone- and bibliotherapy-delivered LM interventions are efficacious for managing probable depression. Further RCTs comparing them with established treatments are warranted.

Humans↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗

PubMed2026

Acceptability of capillary point-of-care testing: a systematic review.

OBJECTIVE: To identify and synthesise evidence on the acceptability and perceived experience of finger-prick point-of-care testing (POCT) among patients and clinicians across healthcare settings. DESIGN: Systematic review conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. DATA SOURCES: Medline, Embase, PsycInfo, CINAHL, Cochrane and Web of Science were searched from inception to January 2024 and re-run in July 2025, supplemented by citation tracking of relevant studies. ELIGIBILITY CRITERIA: Studies reporting patient and clinicians' experiences, perceptions, satisfaction or acceptability relating to finger-prick POCT for any health condition or blood parameter were eligible. Quantitative, qualitative and mixed-methods designs were included. DATA EXTRACTION AND SYNTHESIS: Data were extracted independently by two reviewers and synthesised using thematic analysis and narrative synthesis. Methodological quality was appraised using the Mixed-Methods Appraisal Tool. RESULTS: 21 studies met the inclusion criteria, encompassing 9128 participants (17 quantitative, 3 qualitative, 1 mixed methods). Across diverse clinical contexts, finger-prick POCT was reported as generally acceptable, less distressing and perceived as a convenient alternative to venous sampling in comparative studies. Thematic synthesis identified two major themes: (1) enhancing the patient-clinician relationship through improved engagement, communication and understanding of care and (2) clinical implications of finger-prick POCT on clinicians' workflow, confidence and skill acquisition. Finger-prick POCT was perceived to promote personalised consultations, enable immediate discussion of results and streamline decision-making. Clinicians highlighted its potential to expand task sharing, improve efficiency and strengthen continuity of care, although concerns regarding training, reliability and quality assurance were identified. CONCLUSIONS: Finger-prick POCT is generally acceptable to patients and clinicians, improving comfort, convenience, engagement and perceived efficiency. Implementation should prioritise training, infrastructure and quality assurance frameworks to maximise clinical and experiential benefits. PROSPERO REGISTRATION NUMBER: CRD42024512130.

Humans↗

PubMed2025

Quantitative Outcomes for Shared Assessment and Management in Forensic Mental Health: A Meta-Analysis and Systematic Review.

Despite leading models of mental health care encouraging user involvement, users in forensic mental health (FMH) report poor involvement given the difficulty in reconciling shared approaches with risk-averse and legally mandated settings. While previous research has demonstrated qualitative benefits to shared approaches in FMH and has led to a proliferation of self-rated assessment tools, there remains to quantify agreement on self-rated tools and to clarify the impact of shared approaches on care. This meta-analysis examines (1) the correlation between clinician and user ratings, (2) the predictive validity of self-ratings for violence, and (3) the effects of shared risk management on violence and restriction in FMH. Five databases were searched from inception to April 2024, selecting for adult FMH inpatients, shared risk assessment, needs assessment or violence management as interventions, and quantitative outcomes (correlation, agreement, predictive validity, and effect on violence or restriction rates). Fifteen quantitative evaluations were retained. One of three planned meta-analyses could be conducted, with seven records providing paired clinician-user t-tests. Eleven more records provided clinical recommendations on operationalizing shared approaches. Random-effects meta-analysis showed a significant and large paired standard difference of .95 (95% CI = [.49,1.42]) across tools, with significant differences in DUNDRUM-3, DUNDRUM-4, and CANFOR sub-models. While acknowledging between-study heterogeneity, results substantiate quantitative differences where clinicians generally rate more needs and lesser progress than users across tools, showing that self-ratings can and should be used to broach collaborative discussions on needs and progress during FMH treatment. There remains an evidence gap for quantitative benefits in care outcomes and a need to standardize agreement measures for future comparisons and clinical sub-group analyses.

Humans↗

PubMed2026

Beyond species trees: pervasive gene flow limits phylogenomic resolution in the diversification of Juniperus from the Qinghai-Tibet Plateau.

Understanding how lineages diversify despite persistent ancestral polymorphism and recurrent gene flow remains a central challenge in evolutionary biology. Juniperus distributed across the Qinghai-Tibet Plateau provide an ideal system for addressing this question because repeated geological uplift and climatic oscillations have likely promoted cycles of lineage divergence, range shifts, and secondary contact. Here, we combined approximately 1.08 million genome-wide SNPs from 164 individuals representing thirteen Juniperus lineages with phylogenomic datasets comprising 3,381 nuclear single-copy genes and nearly complete plastomes. We detected extensive phylogenomic discordance and cytonuclear incongruence across genomic datasets. Topology weighting, coalescent simulations, quartet-based tests, and analyses of gene flow and reticulation collectively support the interpretation that these patterns were shaped by the combined effects of prolonged incomplete lineage sorting and gene flow during lineage diversification. Ecological niche analyses further provide a spatial and climatic context in which environmentally similar lineages may have had greater opportunities for secondary contact during historical range shifts. Collectively, our results reveal that the evolutionary history of Qinghai-Tibet Plateau Juniperus is characterized by reticulate diversification rather than strictly bifurcating evolution, and demonstrate how genome-wide discordance can provide biological insights into the evolutionary processes underlying lineage diversification.

Gene Flow↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Assessing the Concurrent Validity of the Australian Treatment Outcomes Profile in a Methamphetamine Dependent Treatment-Seeking Population.

INTRODUCTION: The Australian Treatment Outcomes Profile (ATOP) is a brief clinical tool assessing substance use, health and well-being used in Australian alcohol and other drug treatment services. It is validated for use with clients using alcohol, opioids and cannabis, but not yet for clients who primarily use methamphetamine. METHODS: An embedded validation study was undertaken in treatment-seeking adults enrolled in a randomised double-blind placebo-controlled trial of lisdexamfetamine for methamphetamine dependence with sites in New South Wales, South Australia and Victoria. Participant demographics were collected during study screening. The ATOP and comparators (Time Line Follow Back, Opiate Treatment Index, Depression Anxiety Stress Scale, WHOQOL-BREF and Personal Wellbeing Index) were collected at baseline. Continuous ATOP items were analysed using Pearson's correlation coefficient, and dichotomous items were analysed using Fleiss's κ. Agreement was rated as strong where measures were ≥ 0.50, moderate where agreement was 0.30-0.49, and weak where < 0.30. RESULTS: One hundred and eighteen study participants (2018-2020) had data for concurrent validity analysis. Strong validity was demonstrated for physical health, psychological health, quality of life, injecting drug use and crime items, and for days of use for amphetamines, alcohol, cannabis and cocaine. There was weak validity for days of use for benzodiazepines. Heroin use days and other opioid use days were endorsed by fewer than five participants and were therefore unable to be assessed. DISCUSSION AND CONCLUSIONS: The ATOP is valid for use in a treatment-seeking methamphetamine-dependent population, expanding the range of tools for assessment and standardised outcome monitoring across different settings and services.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗

PubMed2026

Effect of brewers' yeast or beta-glucan derived from Saccharomyces cerevisiae on breast milk supply following preterm birth: the BLOOM randomised controlled trial.

OBJECTIVE: Breast milk is the optimal source of nutrition for preterm infants; however, low breast milk production is common following a preterm birth. This study aimed to determine if taking brewers' yeast or beta-glucan improves daily expressed breast milk volume. DESIGN: Randomised, blinded, parallel, placebo-controlled trial. SETTING: Three Australian tertiary-level neonatal units. PATIENTS: Mothers with a singleton or twin pregnancy who gave birth at <34 weeks' gestation. INTERVENTIONS: Mothers were randomised within 72 hours of birth into three parallel groups in a 1:1:1 ratio to receive either brewers' yeast, beta-glucan or placebo capsules for 7 days. MAIN OUTCOME MEASURE: Total expressed breast milk volume over a 24-hour period on day 7 of intervention. RESULTS: A total of 105 mothers underwent randomisation between August 2022 and April 2024 (36 brewers' yeast, 35 beta-glucan and 34 placebo). The adjusted mean difference in daily expressed breast milk volume was 94 mL/day (95% CI -51 mL/day to 239 mL/day) between the brewers' yeast and placebo groups and -25 mL/day (95% CI -173 mL/day to 123 mL/day) between the beta-glucan and placebo groups. Maternal side effects were similar across groups. CONCLUSION: We found no clear effect of short-term administration of brewers' yeast or beta-glucan on breast-milk production following preterm birth; both interventions were well tolerated. Given the small sample size, these findings do not rule out the possibility of a clinically meaningful benefit of brewers' yeast and suggest further research with a larger sample size may be warranted to clarify the potential clinical impact. TRIAL REGISTRATION NUMBER: ACTRN12622000968774.

Intensive Care Units, Neonatal↗

PubMed2026

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (≥54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

Humans↗

PubMed2026

Temporal Trends and Spatial Variation in Preterm Prelabour Rupture of Membranes: A Population-Based Study.

OBJECTIVE: To describe the temporal trends in Preterm prelabour rupture of membranes (PPROM) in metropolitan France and the geographical distribution at the administrative division level. DESIGN: Exploratory population-based study using administrative data of the French National Health Data System. SETTING: Metropolitan France, 2015 to 2023. POPULATION: Pregnancy with a diagnosis of PROM before 37 SA. METHODS: Annual crude incidence of PPROM was calculated by dividing the number of pregnancies with PPROM diagnosis by the number of live births recorded during the same period. Annual trend was estimated by a binomial negative mixed model. Smoothed standardised incidence ratios were estimated based on a BYM2 model, which accounts for spatial variability between departments. MAIN OUTCOME: PPROM cases, defined as pregnancies with first hospitalizations with a diagnosis of PROM before 37 weeks. RESULTS: Over the study period, we included 150 615 PPROM cases representing 16 735 (±596) per year. Incidence of PPROM cases showed an ascending trend over time (incidence rate ratio 1.023 per year; 95% CI: 1.017-1.030) with an annual crude incidence ranging from 2.2% in 2015 to 2.7% in 2023. A decrease in the incidence was observed in 2020 relative to other years (incidence rate ratio 0.903, 95% CI: 0.887-0.920). A map of smoothed SIRs of PPROM cases at the French administrative division level revealed geographical inequalities. CONCLUSIONS: This first population-based study describing PPROM cases in metropolitan France paves the way for further studies to explore environmental hypotheses. Identifying temporal and geographical disparities in PPROM incidence is relevant to public health policy and practice as such disparities argue for the development of targeted prevention strategies in high-risk areas.

French national health data system↗