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Effectiveness of Caregiver-Mediated Spoken Language Interventions for Children Under Five at Risk of Developmental Language Disorder: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIMS: Caregiver-mediated interventions are commonly used by Speech and Language Therapists to support early language development. Developmental Language Disorder (DLD) is associated with reduced quality of life throughout the lifespan. Understanding factors that predict intervention success is essential for developing appropriate, cost-effective therapy provision for the approximately 12% of preschool children who present with early markers for Developmental Language Disorder (DLD). This systematic review and meta-analysis examined the effectiveness of caregiver-mediated spoken language interventions for under-fives at risk of DLD, and factors influencing intervention effectiveness. METHODS: A systematic review following PRISMA guidelines was conducted. Five electronic databases were searched to identify experimental studies comparing caregiver-mediated spoken language interventions to control conditions in under-fives presenting with risk factors for DLD. Risk factors included prematurity, socioeconomic factors, caregiver language development concerns, and formal or informal language screening or assessment scores. Twenty-six experimental studies with 1407 child participants were included in qualitative synthesis. Meta-analysis was performed on nine Randomised Controlled Trials involving 947 children. RESULTS: Effectiveness was examined for outcomes including child language gains, child wellbeing, inclusion and attainment. Meta-analysis indicated a significant effect of caregiver-mediated spoken language interventions on language outcomes compared to treatment-as-usual, non-language intervention or waitlist control conditions. Non-language outcomes were evaluated via qualitative synthesis. Interventions significantly improved language development trajectories for under-fives presenting with risk factors or early markers for DLD. CONCLUSION AND IMPLICATIONS: This review contributes to the growing evidence base demonstrating that caregiver-mediated interventions can positively impact language development and wellbeing outcomes for children under five at risk of DLD. These findings support the implementation of caregiver-mediated environmental language interventions in clinical practice to maximise accessibility and cost-effectiveness while delivering optimal outcomes for vulnerable populations. WHAT THIS PAPER ADDS: What is already known on this subject Previous research on caregiver-mediated spoken language interventions has highlighted gaps in the evidence regarding the impact of risk factors, demographic characteristics, dosage and intervention components on child language outcomes. Developmental Language Disorder has relatively high population prevalence, estimated at 7%. Prevalence is associated with risk factors including low household socioeconomic status (SES), prematurity and late language emergence. In contrast to its prevalence, there is low public and professional awareness of DLD and a low diagnostic rate. Therefore, a strengthened evidence base and additional insights into the factors affecting success of family-based interventions is important in order to increase the effectiveness of service provision and care planning for this underserved population. Timely and effective intervention with young children presenting with early markers for DLD has the potential to offer lifelong improvement to their wellbeing, inclusion and attainment outcomes. Recent systematic reviews of the effectiveness of caregiver-mediated language interventions had differences in population age range and diagnostic inclusion criteria. What this paper adds to existing knowledge Our review examines the effectiveness of caregiver-mediated early spoken language interventions on child language, attainment and wellbeing, and on caregiver self-efficacy and adherence to language support strategies. Our population was children under five presenting with risk factors for Developmental Language Disorder, in the absence of other neurodevelopmental or genetic conditions such as intellectual disability or autism. This review adds depth and detail to the evidence base supporting the effectiveness of caregiver-mediated spoken language interventions in improving outcomes for this population of young children, and factors that influence their success. What are the potential or actual clinical implications of this work? The high prevalence of Developmental Language Disorder, estimated at around 7% of the population, and the strong association with risk factors including low SES, prematurity and late language emergence, coupled with the low awareness of DLD and low diagnostic rate, mean that a strengthened evidence base and additional insights into the factors affecting success of family-based interventions can increase the effectiveness of service provision and care planning for this population. Timely and effective intervention in this group of young children has the potential to improve wellbeing and attainment outcomes across the lifespan. This review contributes to our understanding of how to implement cost-effective, socially valid and maximally engaging partnership working with families of young children at risk for DLD.

Humans

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma

Comparative safety of lipid-lowering drugs alone or in combination: insights from a systematic review and network meta-analysis.

BACKGROUND AND AIMS: Although the safety profile of lipid-lowering therapies (LLTs) is known, there are no comprehensive comparative assessments. We aimed to compare the risk of muscle-related events, diabetes, liver dysfunction, and cognitive disorders among LLTs through a network meta-analysis. METHODS AND RESULTS: Databases were searched from inception to May 2025. Eligible studies included adult patients, using statins, ezetimibe, PCSK9 monoclonal antibodies (PCSK9mAbs), inclisiran, bempedoic acid, or their combinations as intervention, reporting the information about any of the selected adverse events, a total sample size of ≥200 subjects, and had ≥1 month of intervention. Pooled estimates were assessed by fixed effects model within a frequentist setting. Pooled relative risks (RR) and their 95% confidence interval were estimated. A total of 303,397 subjects from 153 RCTs were included. Bempedoic acid ranked the lowest risk of myalgia (vs PCSK9mAbs, RR 0.80 [0.69, 0.93]). PCSK9mAbs were associated with lower incidence of creatine kinase (CK) elevation, diabetes, and liver dysfunction comparing to statins (statins vs PCSK9mAbs, RR 1.44 [1.14, 1.81], RR 1.13 [1.05, 1.22], and RR 1.38 [1.17, 1.62], respectively). In terms of muscle-related events and cognitive disorders, no significant risk differences were found among treatments and their combinations. CONCLUSIONS: PCSK9mAbs appear to have a more favourable safety profile regarding the risk of CK elevation, diabetes, and liver dysfunction. Bempedoic acid seem to be a better choice for subjects with high risk of myalgia. This information can be valuable when selecting therapy for specific patient subgroups at higher risk of certain adverse events.

Humans

Magnesium sulphate for women at risk of preterm birth for neuroprotection of the fetus.

BACKGROUND: Magnesium sulphate is a common therapy in perinatal care. Its benefits when given to women at risk of preterm birth for fetal neuroprotection (prevention of cerebral palsy for children) were shown in a 2009 Cochrane review. Internationally, use of magnesium sulphate for preterm cerebral palsy prevention is now recommended practice. As new randomised controlled trials (RCTs) and longer-term follow-up of prior RCTs have since been conducted, this review updates the previously published version. OBJECTIVES: To assess the effectiveness and safety of magnesium sulphate as a fetal neuroprotective agent when given to women considered to be at risk of preterm birth. SEARCH METHODS: We searched Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) on 17 March 2023, as well as reference lists of retrieved studies. SELECTION CRITERIA: We included RCTs and cluster-RCTs of women at risk of preterm birth that assessed prenatal magnesium sulphate for fetal neuroprotection compared with placebo or no treatment. All methods of administration (intravenous, intramuscular, and oral) were eligible. We did not include studies where magnesium sulphate was used with the primary aim of preterm labour tocolysis, or the prevention and/or treatment of eclampsia. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed RCTs for inclusion, extracted data, and assessed risk of bias and trustworthiness. Dichotomous data were presented as summary risk ratios (RR) with 95% confidence intervals (CI), and continuous data were presented as mean differences with 95% CI. We assessed the certainty of the evidence using the GRADE approach. MAIN RESULTS: We included six RCTs (5917 women and their 6759 fetuses alive at randomisation). All RCTs were conducted in high-income countries. The RCTs compared magnesium sulphate with placebo in women at risk of preterm birth at less than 34 weeks' gestation; however, treatment regimens and inclusion/exclusion criteria varied. Though the RCTs were at an overall low risk of bias, the certainty of evidence ranged from high to very low, due to concerns regarding study limitations, imprecision, and inconsistency. Primary outcomes for infants/children: Up to two years' corrected age, magnesium sulphate compared with placebo reduced cerebral palsy (RR 0.71, 95% CI 0.57 to 0.89; 6 RCTs, 6107 children; number needed to treat for additional beneficial outcome (NNTB) 60, 95% CI 41 to 158) and death or cerebral palsy (RR 0.87, 95% CI 0.77 to 0.98; 6 RCTs, 6481 children; NNTB 56, 95% CI 32 to 363) (both high-certainty evidence). Magnesium sulphate probably resulted in little to no difference in death (fetal, neonatal, or later) (RR 0.96, 95% CI 0.82 to 1.13; 6 RCTs, 6759 children); major neurodevelopmental disability (RR 1.09, 95% CI 0.83 to 1.44; 1 RCT, 987 children); or death or major neurodevelopmental disability (RR 0.95, 95% CI 0.85 to 1.07; 3 RCTs, 4279 children) (all moderate-certainty evidence). At early school age, magnesium sulphate may have resulted in little to no difference in death (fetal, neonatal, or later) (RR 0.82, 95% CI 0.66 to 1.02; 2 RCTs, 1758 children); cerebral palsy (RR 0.99, 95% CI 0.69 to 1.41; 2 RCTs, 1038 children); death or cerebral palsy (RR 0.90, 95% CI 0.67 to 1.20; 1 RCT, 503 children); and death or major neurodevelopmental disability (RR 0.81, 95% CI 0.59 to 1.12; 1 RCT, 503 children) (all low-certainty evidence). Magnesium sulphate may also have resulted in little to no difference in major neurodevelopmental disability, but the evidence is very uncertain (average RR 0.92, 95% CI 0.53 to 1.62; 2 RCTs, 940 children; very low-certainty evidence). Secondary outcomes for infants/children: Magnesium sulphate probably resulted in little to no difference in severe intraventricular haemorrhage (grade 3 or 4) (RR 0.81, 95% CI 0.64 to 1.04; 6 RCTs, 6542 infants; moderate-certainty evidence) and may have resulted in little to no difference in chronic lung disease/bronchopulmonary dysplasia (average RR 0.92, 95% CI 0.77 to 1.10; 5 RCTs, 6689 infants; low-certainty evidence). Primary outcomes for women: Magnesium sulphate may have resulted in little or no difference in severe maternal outcomes potentially related to treatment (death, cardiac arrest, respiratory arrest) (RR 0.32, 95% CI 0.01 to 7.92; 4 RCTs, 5300 women; low-certainty evidence). However, magnesium sulphate probably increased maternal adverse effects severe enough to stop treatment (average RR 3.21, 95% CI 1.88 to 5.48; 3 RCTs, 4736 women; moderate-certainty evidence). Secondary outcomes for women: Magnesium sulphate probably resulted in little to no difference in caesarean section (RR 0.96, 95% CI 0.91 to 1.02; 5 RCTs, 5861 women) and postpartum haemorrhage (RR 0.94, 95% CI 0.80 to 1.09; 2 RCTs, 2495 women) (both moderate-certainty evidence). Breastfeeding at hospital discharge and women's views of treatment were not reported. AUTHORS' CONCLUSIONS: The currently available evidence indicates that magnesium sulphate for women at risk of preterm birth for neuroprotection of the fetus, compared with placebo, reduces cerebral palsy, and death or cerebral palsy, in children up to two years' corrected age. Magnesium sulphate may result in little to no difference in outcomes in children at school age. While magnesium sulphate may result in little to no difference in severe maternal outcomes (death, cardiac arrest, respiratory arrest), it probably increases maternal adverse effects severe enough to stop treatment. Further research is needed on the longer-term benefits and harms for children, into adolescence and adulthood. Additional studies to determine variation in effects by characteristics of women treated and magnesium sulphate regimens used, along with the generalisability of findings to low- and middle-income countries, should be considered.

Humans

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans

Global prevalence of metabolic syndrome in adults with obstructive sleep apnea: a systematic review and meta-analysis.

STUDY OBJECTIVES: Metabolic syndrome (MetS) is considered to exhibit increased prevalence among adults with obstructive sleep apnea (OSA), but the reported prevalence estimates among such patients vary. Thus, this systematic review and meta-analysis aimed to investigate the global prevalence of MetS in adults with confirmed OSA. MATERIALS AND METHODS: Ovid Medline, Embase, CINAHL, and the Cochrane Library databases were searched for all primary studies published in English that used standard polysomnography for OSA diagnosis and reported MetS estimates. At least two reviewers independently screened for eligible studies, extracted data, and graded the risk of bias using the Risk of Bias Assessment Tool for Non-randomised Studies. Three-level random-effects model was applied for the meta-analysis, reporting pooled prevalence estimate with 95% confidence intervals (CIs). Pre-specified subgroup analyses and meta-regression were also performed. Heterogeneity was quantified using I2 and chi-square statistics. RESULTS: A total of 102 studies were eligible for inclusion (34&#x2009;013 adults with OSA from 28 countries). The combined MetS prevalence was 55.4% (95% CI: 51.0%, 59.8%). Considerable heterogeneity was noted among the included studies (I2&#x2009;=&#x2009;97.8%), whilst the risk of bias ranged from low to high. Subgroup analysis examining the effects of geographic region, study design, MetS definition, and apnea-hypopnea index threshold showed a significant variation in prevalence estimates across most subgroups (p&#x2009;<&#x2009;0.0001). Meta-regression analysis indicated a positive association between mean body mass index (&#x3b2;&#x2009;=&#x2009;0.0772, t&#x2009;=&#x2009;4.56, p&#x2009;<&#x2009;0.0001) and MetS prevalence. CONCLUSIONS: MetS has a high prevalence among adults with polysomnography-confirmed OSA, underscoring the need for prompt MetS screening in these patients. Future longitudinal and genetic/mechanistic studies should investigate the factors accounting for this association. PROSPERO REGISTRATION NUMBER: CRD420251073055.

Humans

Tigecycline-resistant Staphylococcus in waiting pens of a pig slaughterhouse: genomic insights into a food safety alert.

BACKGROUND: The waiting pens of slaughterhouses represent a critical control point in the 'farm-to-fork' continuum, yet their role in the emergence and dissemination of antimicrobial resistance remains understudied. This study investigated tigecycline-resistant Staphylococcus (TRS) in these high-risk zones to assess their prevalence, resistance mechanisms, and transmission dynamics. METHODS: 400 samples were collected from the waiting pens of a pig slaughterhouse in Guangzhou, China. Antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, and molecular cloning were employed to characterize resistance mechanisms and transmission patterns. RESULTS: 78 TRS strains were isolated and classified into three species, including S. borealis, S. ureilyticus, and S. pasteuri. These isolates exhibited multidrug-resistant phenotypes and carried new mutations in rpsJ and tet(M), which were functionally confirmed to reduce tigecycline susceptibility. Phylogenetic evidence demonstrated clonal transmission between pig farms and the slaughterhouse. The tet(M) gene was located within Staphylococcal cassette chromosome mec elements mediated by IS257, while tet(L) was carried by plasmids formed through IS256/IS257-mediated recombination. CONCLUSIONS: Waiting pens serve as crucial reservoirs for the amplification and dissemination of antimicrobial resistance. Our findings underscore the urgent need for enhanced biosecurity measures, improved waste management, and routine molecular surveillance in these high-risk zones to mitigate the spread of resistance along the food production chain.

Animals

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide

Atopic dermatitis and the risk of osteoporosis and fractures: a meta-analysis of cohort studies.

BACKGROUND: This meta-analysis aims to evaluate the risk of osteoporosis and fractures in patients with atopic dermatitis (AD) by synthesizing data from cohort studies. We also provide a comprehensive analysis of fracture risks across different severities of AD and anatomical sites. METHODS: Following the PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Embase, and the Cochrane Library up to May 30, 2025. Studies that investigated the relationship between AD and osteoporosis or fractures were included in the analysis. Data extraction and screening were performed independently by two reviewers. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was applied, alongside sensitivity and subgroup analyses. Publication bias was evaluated using funnel plots and Egger's test. RESULTS: Ten cohort studies, involving 368 to over 2 million AD patients, were included. NOS scores ranged from 7 to 8, indicating generally high study quality. The pooled analysis revealed a 56% increased risk of osteoporosis (OR = 1.56, 95% CI: 1.14-2.13; I2&#xa0;=&#xa0;99.9%, p&#x2009;<&#x2009;0.0001) and an 8% increased risk of all-cause fractures (OR = 1.08, 95% CI: 1.05-1.10; I2&#xa0;=&#xa0;82.1%, p&#x2009;<&#x2009;0.0001) in AD patients. Subgroup analyses demonstrated a progressive increase in fracture risk with the severity of AD. Specific risks were significantly higher for vertebral fractures (OR = 1.14, 95% CI: 1.08-1.20; I2&#xa0;=&#xa0;67.3%, p&#x2009;=&#x2009;0.009) and lower limb fractures (OR = 1.11, 95% CI: 1.08-1.13; I2&#xa0;=&#xa0;65.0%, p&#x2009;=&#x2009;0.014). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected (p&#x2009;=&#x2009;0.316). CONCLUSION: AD is associated with an increased risk of osteoporosis and fractures, particularly among patients with severe AD and those experiencing vertebral or lower limb fractures. These findings highlight the importance of targeted bone health monitoring in the clinical management of AD patients.Registration: (PROSPERO: CRD420251066550).

Humans

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans

Frequent readmissions after hospitalization for alcohol withdrawal: a systematic review and meta-analysis.

BACKGROUND: Alcohol use disorder and alcohol withdrawal syndrome impose substantial clinical and economic burdens, with repeated hospitalizations being common. We aimed to systematically review readmission rates following inpatient detoxification, assess variation across study designs and hospital settings, and identify key risk and protective factors. METHODS: We performed a literature search in Embase and Pubmed on 10/04/2026 focusing on studies assessing in hospital alcohol detoxification. Exclusion criteria included studies on substance use other than alcohol and outpatient or residential treatment. Main outcome was rehospitalization, and meta-analysis was performed to estimate pooled readmission proportions. Secondary outcomes were risk factors and protective factors influencing the rate of rehospitalization. RESULTS: Twenty-five studies were included. The pooled proportion of readmissions following alcohol detoxification was estimated at 17% (95% CI: 14%-21%; 13 studies, n&#xa0;=&#xa0;287,896) within 1&#xa0;month, increasing to 44% (95% CI: 36%-52%; 8 studies, n&#xa0;=&#xa0;2,877) at 1&#xa0;year. Substantial between-study heterogeneity was observed. Subgroup analyses found no significant differences by hospital setting or time period. Findings for study aim and study design were mixed and based on limited data A small number of studies suggested associations with housing stability, employment, and treatment engagement. CONCLUSIONS: This meta-analysis suggests that approximately one in six patients are readmitted within 1&#xa0;month and nearly half within 1&#xa0;year after inpatient alcohol detoxification. However, readmission rates varied considerably across settings and populations. Future research should evaluate targeted interventions to reduce readmissions among high-risk patient groups.

Humans

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging

Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75&#x2009;161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et&#xa0;al., Nanda et&#xa0;al., Naylor et&#xa0;al., and Van Leeuwen et&#xa0;al., each showing fair discrimination. The Teede et&#xa0;al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et&#xa0;al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et&#xa0;al. and van Leeuwen et&#xa0;al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.

Humans

Rationale, design, and experiences from the vanguard phase of the bariatric surgery for the reduction of cardiovascular events (BRAVE) trial.

BACKGROUND: Observational studies suggest that metabolic/bariatric surgery (MBS) reduces mortality and major adverse cardiovascular events in patients with obesity, but adequately powered randomized trials (RCTs) are lacking. The Bariatric Surgery for the Reduction of Cardiovascular Events (BRAVE) trial was designed to address this evidence gap. METHODS: BRAVE is an investigator-initiated, multi-center, open-label RCT with blinded endpoint adjudication comparing MBS vs guideline-based medical weight management (MWM) in adults with obesity and high-risk cardiovascular disease (CVD). Eligible participants have a body-mass index &#x2265;35 kg/m&#xb2; or &#x2265;30 kg/m&#xb2; with type 2 diabetes or age >55 years, and prior myocardial infarction (MI), coronary intervention, heart failure (HF), atrial fibrillation (AF) with elevated CHA&#x2082;DS&#x2082;-VASc score, cerebrovascular disease, or peripheral arterial disease. Participants are randomized 1:1 to MBS (sleeve gastrectomy, Roux-en-Y gastric bypass, or duodenal switch) or MWM, which includes dietary, behavioral, and pharmacologic therapies. The primary outcome is the composite of all-cause death, MI, stroke, HF events, coronary revascularization, AF hospitalization, and renal events. A vanguard phase of 200 participants was implemented to optimize recruitment and logistics. RESULTS: As of October 2025, 2,514 individuals have been screened from 17 centers in Canada, Brazil, Italy and Spain, with 444 entered MBS work-up, and 200 have been randomized. The randomized cohort (mean age 59.8 years; 37% female; mean BMI 44.0 kg m&#x207b;&#xb2;) has high burden of hypertension (82%), diabetes (45%), coronary artery disease (44%), HF (39%), and AF (48%). Recruitment barriers were identified and addressed through targeted education and enhanced patient engagement. CONCLUSIONS: BRAVE is the first large RCT evaluating whether MBS safely reduces major cardiovascular events compared with medical therapy in high-risk patients with obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05531474.

Humans

Ecotoxicological responses of aquatic macrophytes to 2,4-D: A global synthesis of species sensitivity and ecological risk.

The widespread use of 2,4-dichlorophenoxyacetic acid (2,4-D) has raised concern about its persistence, mobility, and effects on non-target aquatic vegetation in freshwater ecosystems. Here, we provide a global synthesis of the ecotoxicological responses of aquatic macrophytes to 2,4-D based on a PRISMA-guided systematic review of 86 peer-reviewed studies published between 1947 and 2025. A consistent gradient of species-specific sensitivity was observed across macrophyte growth forms. The submerged species Myriophyllum spicatum showed high susceptibility, with EC&#x2085;&#x2080; values of 0.04-0.182 mg/L and marked growth inhibition at low concentrations, whereas floating species such as Lemna minor and Pontederia crassipes were more tolerant, requiring higher concentrations (7.08 to >100 and 8.1 mg/L, respectively) to produce comparable effects. Importantly, this sensitivity ranking was consistent across laboratory and field experimental settings. These interspecific differences likely reflect variation in herbicide uptake, translocation, and detoxification capacity associated with growth form. The overlap between EC&#x2085;&#x2080; values for M. spicatum and regulatory thresholds for 2,4-D in surface waters suggests that current limits may be insufficient to protect sensitive submerged macrophyte communities. Regarding remediation, L. minor and Salvinia natans emerged as the most promising candidates for phytoremediation, while P. crassipes showed limited capacity to reduce herbicide concentrations in water. Despite advances, no study directly compared oxidative stress biomarkers between submerged and floating species, representing a critical gap in understanding the biochemical basis of the sensitivity gradient. Overall, this synthesis highlights the need to account for taxon-dependent sensitivity when evaluating the ecological risks of 2,4-D and provides a basis for improving regulatory frameworks and management of herbicide contamination in freshwater ecosystems.

2,4-Dichlorophenoxyacetic Acid

Compliance With Ecological Momentary Assessment Among Patients With Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Patients with cancer often experience substantial fluctuations in psychological states during disease management. Traditional research tools are limited in capturing these dynamic changes in real time, constraining clinicians' understanding of patients' true conditions. Ecological momentary assessment (EMA) enables high-frequency, real-time data collection, providing patient-reported data with greater ecological validity. However, the effectiveness of EMA studies critically depends on patient compliance, and reported compliance rates vary widely, with a lack of systematic quantitative synthesis. OBJECTIVE: This study aims to systematically review and quantitatively analyze compliance with EMA among patients with cancer, and to examine whether EMA design characteristics were associated with compliance. METHODS: Web of Science, PubMed, Embase, Cochrane Library, CINAHL, PsycINFO, CNKI, and Wanfang databases were searched for literature published up to April 30, 2026. Compliance was defined as completed prompts divided by delivered prompts. Single-group proportions were pooled using logit transformation and random-effects models with the Hartung-Knapp-Sidik-Jonkman adjustment. Prediction intervals were calculated to describe the expected distribution of compliance in future comparable settings. Subgroup analyses, univariable meta-regressions, leave-one-out sensitivity analyses, and tests for small-study effects were performed. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data, methodological reporting quality was assessed using a modified Checklist for Reporting EMA Studies, and certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: Twenty-three studies involving 13,565 participants were included. The pooled compliance rate was 78.55% (95% CI 73.48%-82.87%), with a prediction interval of 48.59%-93.41%. Subgroup analyses identified no robust differences across study characteristics. Although study length showed a statistically significant subgroup test, the result was not stable after excluding singleton categories. Meta-regression analyses similarly found no significant linear associations for study length, prompts per day, items per prompt, or assessment window. Leave-one-out analyses showed that no single study drove the pooled estimate. Regarding the risk of bias, 2 studies were judged as low, while 21 were judged as moderate risk. Quality scores ranged from 6.5 to 9.0, and the certainty of evidence for the pooled compliance rate was rated as very low according to the Grading of Recommendations Assessment, Development, and Evaluation approach. CONCLUSIONS: Overall compliance with EMA among patients with cancer was moderate to high, suggesting that repeated real-world assessment may be feasible in oncology research settings. Nevertheless, the very high heterogeneity, wide prediction interval, and very low certainty of evidence indicate that compliance is context-dependent. The pooled estimate should therefore be interpreted as an approximate benchmark rather than a universal expected rate. Future oncology EMA studies should use standardized compliance denominators, report missing prompts transparently, and prospectively evaluate patient-centered design strategies that reduce burden while preserving data quality.

Humans

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2&#xa0;>&#xa0;0.99), LODs (0.03-0.36&#xa0;&#x3bc;g/kg), and recoveries (76.53%-120.0%, RSD&#xa0;<&#xa0;15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates &#x2265; 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100&#xa0;&#x3bc;g/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r&#xa0;=&#xa0;0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins