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Causal Relationship of Polyunsaturated Fatty Acids With Mental Disorders: A Systematic Review and Meta-analysis.

CONTEXT: Mental disorders (MDs) pose a important global health challenge, with a complex pathogenesis complicating treatment development. Nutritional interventions, particularly polyunsaturated fatty acids (PUFAs), have gained attention as potential therapeutic options. OBJECTIVE: This Mendelian randomization (MR) meta-analysis aimed to evaluate the potential causal relationship between PUFAs and MDs. DATA SOURCES: Genome-wide association study data were utilized to analyze the association between PUFAs (including omega-3, omega-3 percentage [omega-3%], omega-6, omega-6 percentage [omega-6%], and omega-6 to omega-3 ratio) and 12 major MDs. DATA EXTRACTION: Two-sample MR technology was used to assess the role of PUFAs in MDs. DATA ANALYSIS: The MR analysis revealed that genetically predicted omega-3 was causally linked to MDs, such as obsessive-compulsive disorder, bipolar disorder, schizophrenia, and major depressive disorder. Omega-3% exhibited protective effects against emotional personality disorder. Conversely, omega-6 was inversely correlated with attention-deficit/hyperactivity disorder risk, while a high omega-6 to omega-3 ratio was associated with an increased risk of depression and other mood disorders. CONCLUSION: High omega-3 levels and omega-3% may reduce the risk of MDs, whereas a high omega-6:omega-3 ratio may elevate the risk. These findings highlight the potential of PUFAs, particularly omega-3, in MD prevention and treatment, while underscoring the need for further research into the complex interactions between omega-3 and omega-6. The study provides a scientific foundation for future clinical trials and dietary intervention strategies. SYSTEMATIC REVIEW REGISTRATION: PROSPERO no. CRD42024598472.

Humans

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans

Risk factors for bleeding after endoscopic retrograde cholangiopancreatography: a systematic review and meta-analysis.

BACKGROUND AND AIMS: ERCP is associated with adverse events, including bleeding, which occurs in up to 1.3% of cases. This meta-analysis aims to identify and quantify risk factors associated with post-ERCP bleeding. METHODS: A comprehensive literature search of electronic databases was conducted from inception to January 10, 2025. Studies were eligible if they used multivariate analysis to identify predictors of post-ERCP bleeding. Risk factors reported in at least 2 studies were pooled using a random-effects model to calculate odds ratios (ORs) with 95% CIs. A further subgroup analysis was performed, including risk factors for postsphincterotomy bleeding and postendoscopic papillectomy bleeding. RESULTS: Twenty-seven studies (4 prospective and 23 retrospective studies) comprising 149,870 patients were included, of whom 1865 experienced post-ERCP bleeding. Twenty potential risk factors were analyzed. The meta-analysis identified several factors significantly associated with increased odds of post-ERCP bleeding in the pooled adjusted analysis, including male gender (OR, 1.24; 95% CI, 1.05-1.46), anticoagulation therapy (OR, 2.75; 95% CI, 1.66-4.56), cirrhosis (OR, 2.54; 95% CI, 1.76-3.65), hemodialysis (OR, 5.82; 95% CI, 3.32-10.18), coagulopathy (OR, 11.01; 95% CI, 2.50-48.40), endoscopic sphincterotomy (EST) (OR, 3.19; 95% CI, 1.69-6.01), precut sphincterotomy (OR, 2.24; 95% CI, 1.52-3.30), and intraoperative bleeding (OR, 2.57; 95% CI, 1.80-3.66). Several factors in the pooled adjusted analysis were not found to be significantly associated with higher odds of post-ERCP bleeding, including high body mass index (BMI), nonsteroidal anti-inflammatory drug (NSAID) use, antiplatelet therapy, thrombocytopenia, common bile duct stones, cholangitis, endoscopic papillary balloon dilatation, and covered self-expandable metal stent insertion. CONCLUSIONS: This meta-analysis identified that the anticoagulation therapy, cirrhosis, hemodialysis, coagulation disorder, EST, precut sphincterotomy, and male gender are associated with increased odds of post-ERCP bleeding in the pooled adjusted analysis. Conversely, age, high BMI, cholangitis, choledocholithiasis, pancreatic duct stones, needle-knife sphincterotomy, NSAID use, and antiplatelet therapy were not significantly associated with higher odds of post-ERCP bleeding in the pooled adjusted analysis. Incorporating our results into a prediction model may assist in identifying patients at increased risk, optimizing informed consent, and guiding prevention and management strategies for post-ERCP bleeding.

Humans

Performance of AI-Based Screening Tools for Obstructive Sleep Apnea Across Apnea-Hypopnea Index Thresholds: Systematic Review and Meta-Analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent but remains substantially underdiagnosed. Polysomnography (PSG) is the reference standard, but its cost and limited availability constrain large-scale case identification. AI-based screening tools may support risk stratification and referral prioritization, but their diagnostic accuracy across apnea-hypopnea index (AHI) thresholds remains uncertain. OBJECTIVE: This review aimed to systematically evaluate the diagnostic accuracy of AI-based OSA screening tools at AHI thresholds of ≥5, ≥15, and ≥30 events/hour, with emphasis on models using non-PSG-derived inputs. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies published from January 1, 2016, to May 3, 2026. Eligible studies included adults evaluated for suspected OSA or recruited from population-based cohorts, assessed AI-based models intended or interpretable for OSA screening, risk prediction, or screening-oriented severity classification, used PSG as the reference standard, and reported sufficient data to construct or reconstruct 2×2 contingency tables. Diagnostic accuracy was synthesized separately by AHI threshold and input source using bivariate random-effects models, with 95% CIs and prediction intervals (PIs). Risk of bias and certainty of evidence were assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation), respectively. RESULTS: A total of 60 studies were included, of which 47 contributed data to the meta-analysis. At AHI thresholds of ≥5, ≥15, and ≥30 events/hour, pooled sensitivities were 0.94 (95% CI 0.92-0.96; 95% PI 0.71-0.99), 0.87 (95% CI 0.84-0.89; 95% PI 0.66-0.96), and 0.83 (95% CI 0.79-0.87; 95% PI 0.61-0.94), respectively; the corresponding specificities were 0.77 (95% CI 0.69-0.84; 95% PI 0.30-0.96), 0.81 (95% CI 0.75-0.85; 95% PI 0.39-0.96), and 0.91 (95% CI 0.87-0.94; 95% PI 0.55-0.99), respectively. The corresponding areas under the summary receiver operating characteristic curves were 0.943, 0.907, and 0.920. For non-PSG-derived tools, sensitivities were 0.92, 0.85, and 0.81, and specificities were 0.70, 0.74, and 0.85 at the 3 thresholds, respectively. For PSG-derived models, sensitivities were 0.96, 0.90, and 0.85, and specificities were 0.82, 0.88, and 0.96, respectively. Exploratory subgroup analyses suggested performance variation across selected study and model characteristics, including region, algorithmic framework, data source, and validation method. CONCLUSIONS: AI-based tools showed generally favorable screening performance for OSA across clinically relevant AHI thresholds, although wide PIs suggest variable performance across future comparable populations and settings. By synthesizing diagnostic accuracy across 3 AHI thresholds and distinguishing non-PSG-derived from PSG-derived models, this review extends previous broad or modality-specific reviews and offers a clinically interpretable, pathway-specific basis for linking model performance to intended use. The findings may clarify potential roles for non-PSG-derived tools in front-end screening and referral prioritization and for PSG-derived models in reduced-channel assessment and sleep-laboratory workflow support. Given substantial heterogeneity, limited external validation, and low or very low certainty of evidence, prospective validation is needed before routine implementation.

Humans

Angiography-Based Index of Microcirculatory Resistance in Assessing the MVO and Infarct Size in STEMI Patients.

OBJECTIVES: To evaluate angiography-based index of microcirculatory resistance (angio-IMR) in assessing microvascular obstruction (MVO) and infarct size (IS) in ST-segment elevation myocardial infarction (STEMI). BACKGROUND: The effect of thrombolysis on post-percutaneous coronary intervention (PCI) angio-IMR, and its associations with MVO and IS remains unclear. METHODS: One hundred twenty-three STEMI patients randomized to receive 5&#x2009;mg intravenous bolus of recombinant staphylokinase (r-SAK) or normal saline (NS) before PCI were recruited. Angio-IMR was computed in infarct-related arteries. MVO and IS were detected by cardiac magnetic resonance imaging. RESULTS: Compared with NS group, r-SAK group exhibited numerically lower post-PCI angio-IMR (39.12 U vs. 42.57 U; p&#x2009;=&#x2009;0.567), MVO (54.0% vs. 70.9%; p&#x2009;=&#x2009;0.059), MVO extent (0.70% vs. 1.90%; p&#x2009;=&#x2009;0.101) and IS (21.30% vs. 24.50%; p&#x2009;=&#x2009;0.079). Post-PCI angio-IMR was positively correlated with MVO extent (&#x3c1;&#x2009;=&#x2009;0.347; p&#x2009;<&#x2009;0.001) and IS (&#x3c1;&#x2009;=&#x2009;0.324; p&#x2009;<&#x2009;0.001). Receiver operating characteristic analyses showed moderate diagnostic performance of angio-IMR for MVO (area under the curve [AUC] = 0.750; p&#x2009;<&#x2009;0.001), MVO&#x2009;>&#x2009;2.6% (AUC&#x2009;=&#x2009;0.735; p&#x2009;<&#x2009;0.001) and IS&#x2009;>&#x2009;25% (AUC&#x2009;=&#x2009;0.712; p&#x2009;<&#x2009;0.001). The exploratory optimal cut-off values for these endpoints were approximately 40&#x2009;U. CONCLUSIONS: In STEMI patients, a single bolus of r-SAK before PCI was associated with numeric reductions in post-PCI angio-IMR, MVO, MVO extent and IS. Additionally, angio-IMR exhibited a significantly positive correlation with both MVO extent and IS, demonstrating the diagnostic value of this wire-free method for assessing microvascular injury.

Humans

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3&#xa0;:&#xa0;1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC >&#xa0;0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence

Changes in heroin-related ambulance attendances following the introduction of a medically supervised injecting room in Victoria, Australia.

BACKGROUND: Injecting drug use contributes significantly to morbidity, mortality and broader social harms globally. Supervised Injecting Facilities (SIFs) are harm reduction interventions that reduce overdose risk and facilitate access to health services for marginalised individuals. While international evidence supports the effectiveness of SIFs, Australian population-level surveillance data quantifying their impact on emergency medical service utilisation remain limited. METHODS: Using data from the National Ambulance Surveillance System, we conducted a retrospective, interrupted time series analysis of heroin-related ambulance attendances within the local catchment of the Medically Supervised Injecting Room (MSIR) between January 2015 and December 2023. Supplementary analysis included comparisons with central Melbourne suburbs and the broader state of Victoria. Key intervention timepoints, including the opening of the MSIR on 30 June 2018, expansion of its operating hours in July 2019, and the COVID-19 pandemic from April 2020 to October 2021, were examined to assess changes in heroin-related attendances over time. Segmented regression models were used to assess changes in heroin-related ambulance attendance trends over time. RESULTS: At the time the MSIR opened, the model-predicted heroin-related ambulance attendance rate within the MSIR catchment was 123 per 100,000 population per month, equivalent to approximately 48 heroin-related ambulance attendances per month. Prior to implementation, the attendance rate was increasing by an estimated 0.74 per 100,000 population per month. Following the opening of the MSIR, the previously increasing trajectory reversed, with ambulance attendance rates declining by approximately 2.3 per 100,000 population per month relative to the pre-intervention trend. By the end of the study period (December 2023), the predicted monthly heroin-related ambulance attendance rate had declined to 36 per 100,000 population (approximately 14 attendances per month), representing an overall reduction of 70.7% from the time of MSIR implementation. These reductions persisted throughout the COVID-19 lockdown period and were sustained after restrictions lifted. Supplementary analysis showed no comparable reductions in the central Melbourne region or the remainder of Victoria. CONCLUSIONS: The introduction of the MSIR in Richmond was associated with a sustained reduction in heroin-related ambulance attendances within its catchment area. These findings provide strong population-level evidence that SIFs reduce acute heroin-related harms requiring emergency ambulance response, reinforcing their role as an effective harm reduction strategy within the Australian context.

Humans

Activity shapes large herbivores' ecological influences.

The ecological effects of large herbivores are shaped by their spatial and temporal patterns of activity (i.e. where, when and how intensely they use specific locations). When large herbivores' ecological influences are perceived to be undesirable, the traditional approach has been to reduce their population size. This numbers-first logic assumes that ecological effects scale primarily with abundance. We argue that this framing provides an incomplete understanding of large herbivores' ecological impacts. Using African elephants (Loxodonta africana) as a well-documented case study, we show that ecological effects on plants, animals and ecosystem processes correlate more with spatio-temporal patterns of activity than with population size. In large, open systems characterized by strong gradients of water availability, forage quality, shade and risk, elephants concentrate into predictable hotspots while relaxing activity elsewhere, generating localized impacts and opportunities for recovery. By contrast, in small, fenced or fragmented landscapes, where movements are constrained, and gradients are weak, spatial self-regulation breaks down, producing homogenized use and widespread ecological effects. We contend that understanding where, when and under what constraints herbivores use space provides a more general and mechanistic basis for interpreting ecological influence than abundance alone, with implications that extend beyond elephants to large herbivores globally.

Animals

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74&#xb7;1 months (IQR 68&#xb7;3-75&#xb7;4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0&#xb7;84 [95% CI 0&#xb7;79-0&#xb7;88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11&#xb7;6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0&#xb7;41-0&#xb7;93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0&#xb7;36-0&#xb7;48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (&#x2265;70&#xb7;0%; mean absolute improvement 12&#xb7;1 percentage points [SD 2&#xb7;8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0&#xb7;010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans

Axial Length Adjustment and AL/R Ratio Optimization of IOL Power Calculation in Extremely Long Eyes.

PURPOSE: To evaluate the accuracy of modern intraocular lens (IOL) power calculation formulas and axial length (AL) adjustment methods in eyes with AL &#x2265; 30.0 mm. DESIGN: Retrospective consecutive cross-sectional study. PARTICIPANTS AND CONTROLS: A total of 308 eyes (308 patients) with AL &#x2265; 30.00 mm were included. METHODS: Accuracy of modern online formulas, alone or with established AL adjustments methods, was analyzed. Subgroup analyses were performed based on AL, keratometry (K), anterior chamber depth (ACD), lens thickness (LT), and AL-to-corneal radius (AL/R) ratio. MAIN OUTCOME MEASURES: Predictive accuracy was evaluated using the formula performance index (FPI), root mean square absolute prediction error (RMSAE), standard deviation (SD) of prediction error (PE), and percentage of eyes within &#xb1;0.25 and &#xb1;0.50 diopters (D). RESULTS: Overall, Holladay 1 combined with the nonlinear polynomial Wang-Koch axial length adjustment (H1-PWK) demonstrated the best overall performance, achieving the lowest SD (0.40), RMSAE (0.40), and highest FPI (0.494). A tendency toward hyperopic error was observed in eyes with AL &#x2265; 32.0 mm, K &#x2265; 46.0 D. The AL/R ratio showed a significant positive correlation with PE in the Ladas Super formula, Barrett Universal II, EVO, PEARL-DGS, and Hoffer QST formulas. Spline-based regression analysis indicated that the transition point of AL/R from myopic to hyperopic PE varied across different formulas. CONCLUSIONS: H1-PWK provides robust refractive accuracy in extremely long eyes. The AL/R ratio may provide a useful composite biometric stratification parameter compared to AL alone.

Humans

Neuroimaging anxious children and adolescents before and after cognitive behavioral therapy: a systematic review.

OBJECTIVE: This systematic review investigates brain changes in youths with anxiety disorders following cognitive behavioral therapy (CBT) and neural markers that predict CBT responses. METHODS: We conducted a systematic search using the electronic databases PubMed, Web of Science, and ProQuest. The inclusion deadline was set to October 27, 2025. We included fifteen peer-reviewed neuroimaging studies that examined the effects of CBT in youths under 19 years old with a primary clinical diagnosis of an anxiety disorder based on DSM-5 criteria. RESULTS: Although the existing literature is marked by substantial diversity in methods and outcomes, task-related neural response in the anterior cingulate cortex (ACC, 2/8, 25.0%), insula (1/8, 12.5%) increased from pre to post CBT and these changes were further correlated with clinical symptom improvements. Moreover, CBT outcomes were predicted by pre-treatment activity or connectivity in the ACC and amygdala (3/13, 23.0%). A smaller proportion of studies (2/13, 15.3%) found that activity or connectivity in the insula, precuneus/cuneus, postcentral gyrus, and activity or structure in the nucleus accumbens (NAcc) predicted response to CBT. The low consistency of these findings was driven by methodological variability, low reliability of the neural markers, and relatively small sample sizes. CONCLUSIONS: This review highlights promises of neural predictors and outcomes to enhance anxiety disorder treatments in children and adolescents, facilitating future personalized and effective CBT. Beyond this initial promise, the field is hindered by methodological inconsistencies and limited replications. While longitudinal and personalized approaches are important next steps, the central challenge remains: identifying neural markers that are both reliable and robust.

Adolescent

Factors Associated With Accelerated Fracture Healing in Patients With Traumatic Brain Injury and Extremity Comminuted Fractures: A Retrospective Case-Control Study.

OBJECTIVE: Although traumatic brain injury (TBI) has been clinically associated with accelerated bone healing, the factors that determine which patients experience this phenomenon remain poorly defined, and previous findings are conflicting. This study aimed to investigate the clinical factors associated with accelerated fracture healing in patients with TBI combined with comminuted fractures of the limbs, so as to provide an evidence-based foundation for elucidating the clinical phenomenon of TBI-promoted fracture healing. METHODS: A retrospective case-control study design was employed. Patients between January 2020 and April 2024 with concurrent diagnoses of TBI and comminuted fractures were included. Based on radiographic findings and RUST/mRUST scores, patients were divided into an accelerated healing group (AHG) and a normal/delayed healing group (NDHG). Clinical data including demographics (age, sex, BMI), TBI characteristics (injury site, GCS score), admission laboratory indices (blood count, coagulation function, inflammatory markers), and fracture site/local soft tissue conditions, as well as functional outcomes assessed by the Short Musculoskeletal Function Assessment (SMFA) questionnaire at final follow-up were collected. Univariate analysis and multivariate logistic regression analysis were used to identify independent factors influencing accelerated fracture healing. Receiver operating characteristic (ROC) curves were plotted to evaluate their predictive value. RESULTS: A total of 119 patients were included, with 69 in the AHG and 50 in the NDHG. Significant differences were observed between the two groups in terms of age, BMI, GCS score, and platelet count (p&#x2009;<&#x2009;0.05). Univariate analysis showed that age, BMI, GCS score, red blood cell count, and platelet count were associated with accelerated fracture healing (p&#x2009;<&#x2009;0.20). Multivariate logistic regression analysis indicated that younger age (OR&#x2009;=&#x2009;0.875, 95% CI: 0.821-0.934) and lower GCS score (indicating more severe TBI; OR&#x2009;=&#x2009;0.490, 95% CI: 0.339-0.707) were independent predictors of accelerated fracture healing. ROC curve analysis showed that the area under the curve (AUC) for age and GCS score in predicting accelerated healing were 0.893 and 0.851, respectively. CONCLUSIONS: In patients with TBI combined with comminuted fractures, younger age and greater TBI severity (lower GCS score) are independent predictors of accelerated fracture healing. These findings assist clinicians in the early identification of patients with high healing potential to optimize treatment strategies, facilitate the early identification of high-risk patients, and provide clinical clues for further exploration of the molecular mechanisms underlying neurohumoral regulation of bone regeneration.

Humans

Ruling out pediatric bacterial epididymo-orchitis with urinalysis - The case for minimizing unnecessary antibiotic prescription.

INTRODUCTION: Epididymo-orchitis in pediatric patients is predominantly non-bacterial, often stemming from viral or reactive etiologies. Despite guidelines recommending conservative management for non-bacterial cases, antibiotic overtreatment remains prevalent in the outpatient setting. We evaluated the diagnostic accuracy of urinalysis in ruling out bacterial infection to support antibiotic stewardship in this population. METHODS: We conducted a cross-sectional diagnostic accuracy study using electronic health records from a large health maintenance organization in Israel. The cohort included patients younger than 18 years with a diagnosis of epididymo-orchitis or clinically overlapping entities (acute scrotum, appendage torsion) who had paired urinalysis and urine culture results within one week of diagnosis. Logistic regression and ROC curve analysis were performed to assess the ability of urinalysis parameters to predict positive urine cultures. RESULTS: Of 682 eligible cases, confirmed bacterial infection was rare, occurring in only 17 patients (2.5%). Nitrite positivity was the strongest independent predictor of infection (OR 43.98; p < 0.001). A prediction model incorporating all urinalysis parameters yielded an area under the curve (AUC) of 0.825 and achieved a 97.7% classification accuracy for correctly predicting negative cultures. Despite the low prevalence of infection, antibiotics were prescribed in 237 cases (34.7%). Urinary anatomic abnormalities were significantly associated with culture positivity. CONCLUSIONS: Bacterial coinfection in pediatric epididymo-orchitis is uncommon. Urinalysis serves as a highly accurate screening tool to rule out bacterial etiology. A negative urinalysis supports withholding antibiotics in this setting, reserving treatment for children with positive markers or known anatomic abnormalities. This evidence-based approach This evidence-based approach has the potential to reduce unnecessary antibiotic exposure, however prospective studies are needed to validate these findings before broad implementation.

Humans

Serum Albumin on Admission: A Prognostic Marker of Morbidity and Mortality in Burns? A Systematic Review and Meta-Analysis.

Albumin is essential for maintaining oncotic pressure and vascular integrity. In burn injuries, increased capillary permeability leads to hypoalbuminemia, which is a recognized marker of poor outcomes in critical illness. However, its prognostic value in acute burn care remains underexplored. This study evaluated the prognostic value of admission serum albumin in predicting mortality, acute kidney injury (AKI), hospital and intensive care unit length of stay, ventilatory requirements, sepsis, and pulmonary infection in patients with burn injuries. A systematic search of PubMed, Scopus, Cochrane Library, Web of Science, MEDLINE, and Embase was conducted. Of 5587 studies screened, 19 were included in the systematic review and 9 in the meta-analysis. Statistical analysis was performed using RStudio, with pooled outcomes reported as odds ratios (ORs), standardized mean differences, and hierarchical summary receiver operating characteristic curves. Heterogeneity was assessed using Cochran's Q, I2, and tau2. Hypoalbuminemia on admission was significantly associated with increased mortality during admission (OR 9.51; 95% CI, 3.04-29.78; I2 49.3%). Admission hypoalbuminemia was also associated with an increased risk of AKI (OR 2.83; 95% CI, 2.49-3.22; I2 0%). Evidence for other outcomes was limited and heterogeneous. Admission serum albumin appears to be a valuable prognostic marker in patients with burn injuries, particularly for mortality and AKI. Further research is required to support its integration into burn-specific risk models, characterize albumin trends within the first 24&#xa0;h postinjury, and establish optimal cut-off values.

Humans

Association Between 24-Hour Blood Pressure and Rates of Retinal Nerve Fiber Layer Progression in Glaucoma: The Vascular Imaging in Glaucoma Study.

PURPOSE: Low systemic blood pressure (BP) has been implicated as a risk factor for glaucoma progression. The purpose of this study was to investigate the association between 24-hour BP and rates of retinal nerve fiber layer (RNFL) loss in eyes with primary open-angle glaucoma. DESIGN: Prospective cohort study. PARTICIPANTS: Seventy-nine eyes from 42 subjects with glaucoma (mean age, 68.5 &#xb1; 7.6 years) enrolled in the Vascular Imaging in Glaucoma Study at the Bascom Palmer Eye Institute. METHODS: Participants underwent 24-hour ambulatory BP monitoring at baseline. Follow-up evaluations were conducted at 4-month intervals and included ophthalmic examination, BP measurement, and peripapillary RNFL thickness measurement with spectral-domain optical coherence tomography. The association between BP and RNFL loss over time was assessed using linear mixed-effects models adjusted for age, sex, race, baseline RNFL thickness, central corneal thickness, and intraocular pressure. MAIN OUTCOME MEASURES: The effect of baseline 24-hour mean arterial pressure (MAP), systolic BP (SBP), and diastolic BP (DBP) on the rate of average RNFL loss over time. RESULTS: Eyes underwent an average of 13 &#xb1; 3 optical coherence tomography exams over 43 &#xb1; 10 months of follow-up. The mean rate of RNFL loss was -0.34 &#xb1; 0.64 &#xb5;m/y (median: -0.32; interquartile range: -0.66 to -0.04 &#xb5;m/y). After adjusting for confounding factors, every 10 mm Hg lower in 24-hour minimum MAP, SBP, and DBP was associated with -0.542 &#xb5;m/y (P < .001), -0.360 &#xb5;m/y (P = .003), and -0.458 &#xb5;m/y (P = .008) faster RNFL loss, respectively. Eyes in the lowest quartile of average 24-hour MAP (81-90 mm Hg) and minimum 24-hour DBP (35-47 mm Hg) experienced significantly faster progression compared to those in the highest quartile, with differences of -0.68 &#xb5;m/y (P = .017) and -0.63 &#xb5;m/y (P = .030), respectively. CONCLUSIONS: Lower systemic BP, especially minimum MAP, SBP, and DBP measured by 24-hour ambulatory BP monitoring, is associated with faster rates of RNFL loss in primary open-angle glaucoma eyes. 24-hour BP monitoring may help predict glaucoma patients at greater risk of progression.

Humans

Fungal drivers of mycotoxin contamination in wheat: Early warning and plasma-based control.

Mycotoxin contamination in wheat is a major food safety concern; however, quantitative evidence linking fungal community signals, mycotoxin exceedance risk, and wheat quality traits in naturally contaminated wheat remains limited. In this study, wheat samples were collected from mycotoxin-prone monitoring sites under unusually rainy conditions in 2022 to explore early-warning indicators and post-harvest mitigation strategies. According to the National Food Safety Standard of China GB 2761-2017, aflatoxin B1 (AFB1), deoxynivalenol (DON), and zearalenone (ZEN) exceeded the maximum limits in 52.24, 47.76, and 23.88% of samples, respectively; 38.81% exceeded the reference EU threshold for T-2 toxin, and 46.27% showed co-contamination with at least two mycotoxins above their respective thresholds. Although Alternaria, Cladosporium, and Epicoccum dominated the fungal community, Fusarium abundance was significantly associated with DON contamination and Fusarium-damaged kernels (FDKs). Mediation analysis identified DON as a significant mediator linking Fusarium abundance to FDKs, accounting for 68.41% of the total effect. In addition, Fusarium abundance above 3.70% showed strong predictive performance for DON exceedance, with an area under the curve of 0.906, indicating its potential as an early-warning indicator. Culture-based assays confirmed the toxigenic potential of Aspergillus and Fusarium isolates under simulated temperature and moisture conditions. After optimization using a toxin-spiked wheat flour model, dielectric barrier discharge cold plasma degraded AFB1, DON, and ZEN by 29.30-35.68%, disrupted the morphology of toxigenic fungi, and did not significantly affect wheat quality. This study provides practical insights into mycotoxin risk warning and post-harvest mitigation in wheat.

Triticum