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ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

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

Redefining the real problem in psychedelic trials: Why fighting the Lessebo matters more than blinding integrity.

Imperfect blinding is not specific to psychedelic trials. In randomized trials, treatment allocation is frequently correctly guessed, yet blinding integrity is rarely assessed outside of psychedelic research and is generally not considered a barrier in regulatory evaluation. The intense debate in psychedelics may reflect a broader double standard affecting mental health research, when uncertainties arising from imperfect blinding are confounded by those linked to patient-reported outcome measures. Indeed, people living with mental disorders are often viewed as unreliable reporters, despite well-documented limitations of clinician-rated scales and the absence of robust biological markers of symptomatic change. Importantly, it is the maintenance of reasonable doubt of treatment allocation that sustains internal validity and ethical feasibility of placebo-controlled designs, rather than perfect blinding. Concerns about expectancy bias in psychedelic trials are closely tied to blinding debates. When allocation is inferred, expectations may cluster in the arm perceived as active or in stereotyped experiences and influence outcomes differently in active and control arms, leading to a risk of lessebo, a negative placebo effect due to the negative expectation related to receiving a placebo. However, we argue that an underrecognized mechanism of lessebo is disappointment. This risk may reflect insufficient clinical management of disappointment rather than pre-treatment expectation alone. We therefore propose shifting the emphasis from preserving inevitably imperfect blinding towards mitigating disappointment in both arms. Establishing non-stereotyped expectations prior to treatment through structured psychoeducation, strengthened therapeutic alliance, and realistic preparation would help avoid lessebo effects. Such strategies would enhance ethical rigor, interpretability, and the clinical usefulness of psychedelic trials.

Humans

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans

Effects of rumen fluid transplantation on longissimus dorsi muscle development in Xizang sheep: An association analysis based on transcriptomic and serum metabolomic profiles.

This study aimed to investigate the effects of rumen fluid transplantation (RFT) on the growth and development of the longissimus dorsi muscle in female Xizang sheep. After RFT, muscle lightness differed significantly between the two groups, with the LDC group showing significantly higher lightness than the LDT group. In contrast, no significant differences were observed between groups in other muscle phenotypic traits, including drip loss, pH, cooking loss, shear force, redness, and yellowness. Antioxidant-related indices (SOD, GSH-PX, MDA, CAT, and T-AOC) also showed no significant differences between groups. Histological analysis revealed that muscle fiber length, width, and density were significantly greater in the experimental group than in the control group. Transcriptomic analysis identified 515 differentially expressed genes (DEGs), of which 419 were downregulated. KEGG analysis indicated that genes involved in muscle development-related pathways, such as cell adhesion and the PI3K-Akt signaling pathway, were predominantly downregulated. Key serum metabolites (L-kynurenine, IPA, allantoin, and propionylcarnitine) showed highly significant positive correlations with muscle fiber growth indices. In contrast, metabolites such as l-carnitine, acetylcarnitine, and citrulline were negatively correlated with muscle fiber growth, but positively correlated with the expression of muscle structure-related genes (COL11A1 and EFNA5) and with meat lightness. Overall, this study provides new insights into the potential molecular basis by which RFT influences muscle growth and development. However, the mechanisms by which RFT affects muscle development and meat quality-related traits remain unclear and warrant further investigation.

Animals

A multi-model genome-wide association study identifies genetic variants underlying resistance to Largemouth Bass Ranavirus (LMBV) in Micropterus salmoides.

Largemouth bass (Micropterus salmoides) is an economically important freshwater aquaculture species, yet recurrent outbreaks of Largemouth Bass Ranavirus (LMBV) continue to impair production and cause substantial losses. The genetic basis of host variation in LMBV resistance remains insufficiently characterized. Here, we applied a multi-model genome-wide association study (GWAS) to identify loci associated with resistance following a controlled challenge with the LMBV-23PY strain. Whole-genome resequencing was performed for 146 phenotyped fish, including 72 susceptible and 74 resistant individuals. After stringent quality control, 877,262 high-quality variants were retained and tested using six GWAS models. Across binary survival status and survival time phenotypes, 32 shared suggestive variants were consistently detected across models, representing suggestive loci for LMBV-23PY resistance. Genes within ±50 kb of these loci were annotated, and functional enrichment highlighted immune- and redox-related biological processes. Three prioritized candidates-GSTT3L (glutathione S-transferase theta-3-like), CGRP2 (calcitonin gene-related peptide 2), and NPPC (natriuretic peptide C)-were associated with pathways involved in oxidative stress responses and immune regulation. Collectively, these results provide insight into the genetic architecture of LMBV-23PY resistance in largemouth bass and identify suggestive variants and associated candidate genes for downstream validation, functional interrogation, and the development of marker-assisted and genome-enabled breeding strategies.

Animals

Evolutionary expansion of the NF-Y gene family in bivalves and divergent subunit responses to thermal and pathogenic stress in the noble scallop.

Nuclear factor Y (NF-Y) is a conserved eukaryotic transcription factor complex that specifically interacts with the CCAAT motif. Prior research has demonstrated that this gene family participates in various biological processes, encompassing growth, development, and stress responses, across a broad spectrum of organisms. However, research on the role of the NF-Y family in bivalves remains limited. In this study, we comprehensively identified the NF-Y family in 34 bivalve species, and further investigated its expression in the noble scallop Chlamys nobilis. A total of 296 NF-Y genes were identified and classified into three subfamilies, NF-YA, NF-YB, and NF-YC. Phylogenetic analysis revealed that NF-YA and NF-YC have remained relatively conserved, whereas NF-YB has undergone significant expansion. Additionally, while substantial disparities in gene copy numbers exist across species, the motif composition and exon-intron structures within each subfamily demonstrate notable conservation. Tissue expression profiling revealed distinct expression patterns among CnNF-Y genes, with several members exhibiting relatively high transcript abundance in gonadal tissues. Furthermore, qRT-PCR results demonstrated that CnNF-YA2, CnNF-YB6, and CnNF-YC were significantly and continuously upregulated under heat stress. Conversely, several genes, particularly CnNF-YA2, CnNF-YB3, and CnNF-YB4, exhibited dynamic transcriptional responses to Vibrio parahaemolyticus exposure. These findings enhance our understanding of the evolutionary trajectory and functional diversification of the NF-Y gene family in bivalves, laying a theoretical foundation for future research on thermal adaptation, immune regulation, and molecular breeding in scallops.

Animals

Mechanisms of high-humidity hot air impingement blanching (HHAIB) on microbial counts, functional properties, phenolic profile transformation, and volatile compounds in celery stalks (Apium graveolens L.).

In this study, celery stalks were pretreated with different durations (0-150 s) of high-humidity hot air impingement blanching (HHAIB), followed by far-infrared radiation assisted pulsed vacuum freeze-drying (FIR-PVFD) at 60, 65, and 70 °C. The effects of HHAIB on the physicochemical properties, composition and transformation of phenolic compounds, volatile components, and antioxidant capacity of FIR-PVFD-dried celery stalks were systematically investigated. The results showed that HHAIB not only effectively reduced the counts of total mesophilic aerobic bacteria (TMAB) and total yeast and mold (TYM), but also decreased the relative activities of polyphenol oxidase (PPO) and lipoxygenase (LOX) by more than 91% after 90 s of treatment. HHAIB altered the cellular structure of celery stalks, shortened the drying time by 29.33-41.43%, and improved their hydration properties. HHAIB pretreatment promoted the conversion of bound phenolics to free phenolics in celery stalks, with significant increases in the contents of p-coumaric acid, apigenin, graveobioside A, and other components. The total free phenolic content increased by 56.99%, thus HHAIB enhanced the antioxidant activity. An electronic nose and sensory evaluation revealed that HHAIB-pretreated celery stalks better retained the characteristic herbal and pungent notes. GC-MS results indicated that HHAIB treatment optimized the aroma profile by regulating the contents and composition of terpenes, aldehydes, ketones, alcohols, and aromatic compounds.

Apium

Understanding Suicide through Coroners' Narratives: implications for primary care from a mixed‑methods study of 157 Coroners' reports.

Suicide is a major public health concern, and general practice is often a recent point of contact before death. While mental illness is well recognised, the broader social and contextual factors influencing suicide risk remain under-reported in primary care and epidemiological research Aim To describe the demographic, clinical, and psychosocial characteristics of individuals who died by suicide, integrating coronial quantitative data with qualitative narrative accounts to identify implications for primary/ secondary care and public health. Design and setting Explanatory sequential mixed‑methods study of 157 consecutive deaths by suicide recorded by coroners (2018-19) across five English local authorities. Method Demographic, clinical, and social data were extracted from coroners' records and summarised descriptively. Narrative case summaries were coded and analysed thematically to identify contextual, relational, and service factors preceding death. Results Of 157 individuals: 79% were male; 65% lived in the most deprived IMD quintile; 85% had a diagnosed mental health condition; 62% had a long‑term physical illness; 41% had a previous suicide attempt. About half consulted a GP in the preceding three months; mental health featured in about half of those consultations. Common stressors were relationship breakdown (37.2%), housing instability (22.1%), and work pressures (18.2%). Seven interlinked themes were identified: Mental health; Alcohol/Substance use, Physical health; Social connectedness; Life course trauma, Socioeconomic and Structural Vulnerability; Healthcare access. Service transitions were key vulnerability points Conclusion Coroners' records offer important insights into the complex circumstances preceding suicide and highlight opportunities for GPs to recognise intersectional complexity and support integrated, cross-sector suicide prevention approaches.

General Practice

Depth-dependent microbial succession and interspecies hydrogen transfer drive pit mud maturation in Chinese strong-flavor baijiu fermentation.

Microbial communities in fermentation pit mud play a key role in determining the quality of Chinese strong-flavor baijiu (CSFB). However, the ecological processes underlying pit mud maturation across spatial and temporal scales remain unclear. In this study, amplicon sequencing and metagenomic analyses were employed to investigate the taxonomic succession, community assembly, and metabolic functions of bacterial and archaeal communities during the transition from fresh pit mud (FPM) to new pit mud (NPM) and old pit mud (OPM). A pronounced depth-dependent succession pattern was observed, with 4 cm representing a critical ecological boundary separating distinct community structures and maturation trajectories. During surface-layer maturation, community assembly shifted from stochastic to deterministic processes, accompanied by homogeneous selection and increasing network complexity. In contrast, stochastic processes remained dominant throughout deep-layer maturation. Metagenomic analyses revealed a functional transition from lactate and acetate production, primarily associated with Lactobacillus in FPM and NPM, to butyrate and caproate production associated with Clostridium and Caproiciproducens in OPM. This functional transition was accompanied by enhanced amino acid metabolism, which was associated with the enrichment of Proteiniphilum and Aminobacterium. Notably, methanogen-mediated interspecies hydrogen transfer (IHT) emerged as a key ecological feature during pit mud maturation. In OPM, IHT networks primarily involving Methanobacterium and Methanosarcina linked methanogenesis with reverse β-oxidation through diverse hydrogen-transfer pathways, reinforcing metabolic interactions underlying caproate production. These findings provide new insights into the ecological mechanisms underlying pit mud maturation and offer a theoretical basis for the directed cultivation of high-quality pit mud in CSFB production.

Hydrogen

Transformation of antibiotics mediated by iron-bearing minerals: A review.

Iron-bearing minerals are ubiquitous in water, sediments and soil, where their surface chemical properties and redox activity can play an important role in degradation of trace antibiotics. This review systematically summarizes the roles of various iron-bearing minerals in chemical transformation and microbial degradation of antibiotics and reaction mechanisms involved, and refines the critical idea for iron-driven control of antibiotics with trace level in natural environment. Overall, antibiotics removal in the presence of iron-bearing minerals involves combination of adsorption, surface oxidative degradation, photo-induced degradation, Fenton-like reaction and microbial degradation. Adsorption of antibiotics by Fe(III)-minerals involves electrostatic interaction, complexation, H-bonding, π-π interaction and hydrophobic interaction. Adsorbed antibiotics form complexes with Fe(III)-minerals, undergoing electron transfer to generate radical intermediates, subsequently generating final products through hydroxylation, dealkylation, and deamination. Additionally, Fe(III)-minerals can be excited to produce electrons and holes under sunlight and to produce antibiotics-degrading hydroxyl radical through O2 reduction, H2O oxidation and ligand-to-metal charge transfer. Reduced iron minerals can activate oxygen to participate in Fenton-like degradation reactions. Finally, antibiotics are mainly removed by bio-driven Fenton reaction and direct enzyme biodegradation. The presence of iron-bearing minerals can promote antibiotics microbial degradation by providing nutrients for microorganisms or by changing microbial activity and microbial community structure. Existing problems and future research directions are identified. New insights for application of iron-bearing minerals in transformation of antibiotics are proposed. The work aims to suggest new methods and insights for pollution control and remediation of emerging contaminants including trace antibiotics in the natural environment.

Anti-Bacterial Agents

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines

Multi-omics insights into the physiological mechanisms of bile acid accumulation in the gallbladder in brumation-like snakes.

Hibernation/brumation represents an important physiological adaptation for animals to cope with seasonal environmental changes. Field observations suggested increased gallbladder weight in the Five-pacer viper (Deinagkistrodon acutus) during brumation, and our quantitative measurements confirmed this increase together with bile acid accumulation. By integrating a multi-omic approach, this study elucidates the regulatory mechanisms of bile acid accumulation in the gallbladder during brumation. Results showed that taurocholic acid (TCA) and taurodeoxycholic acid (TDCA) were the major components in the gallbladder of the brumation-like group, with significantly elevated concentrations of bile acids, whereas bile acid concentrations in serum and intestinal contents were markedly reduced, indicating suppression of the enterohepatic circulation and consequent accumulation of bile acids in the gallbladder. Hepatic transcriptomic analysis revealed significant downregulation of bile acid synthesis and regulatory genes in brumation-like snakes. In contrast, the alternative synthesis pathway gene sterol 27-hydroxylase (CYP27A1) and some transporter genes were slightly upregulated. Further, some modification genes and regulatory genes showed no significant differences between active and brumation-like states. Gut microbiota analysis demonstrated Akkermansia muciniphila, Bacteroides fragilis, and Citrobacter freundii were more enriched in the active group, which were common microbes related to bile acid metabolism, and the correlation analysis confirmed this relationship. Taken together, these findings indicate that the "physiological bile acid accumulation" observed in snakes during brumation-like state is jointly driven by suppressed hepatic synthesis, reduced enterohepatic circulation, and remodeled microbial community structure. The study provides novel comparative physiological insights into extreme metabolic homeostasis in animals.

Animals

Metabolomics and genomics reveal high diversity and concentrations of cyanopeptides during a Microcystis bloom.

Cyanobacterial blooms are an immense global problem that release complex mixtures of poorly characterized biologically active cyanopeptides into freshwater. In this study, metabolomics and genomics were used to assess the diversity and concentrations of cyanopeptides during a dense Microcystis bloom during the late summer of 2023 in Lake Champlain, a large transboundary lake situated between Canada and the United States. Despite the relatively low genetic diversity of the bloom determined by 16S rRNA metabarcoding, 151 cyanopeptides were detected by non-targeted metabolomics. This represents the most recorded cyanopeptides from a single lake plankton bloom event to date. Fifty-two cyanopeptides were previously reported and 99 represent putative new structures. Standards from the microcystin, cyanopeptolin, microginin, and anabaenopeptin groups were used to either quantify or approximate respective cyanopeptide concentrations over the sampling period. Cyanopeptolins were the most diverse (n = 68) cyanopeptides and the second most abundant, reaching 12,892 μg/L. Microginins were the second most diverse (n = 24) and reached the highest concentrations (18,262 μg/L). Anabaenopeptins were the third most diverse (n = 17) cyanopeptides, reaching 4,818 μg/L. Only 8 microcystins were detected, reaching 4,935 μg/L, where MC-LR was the dominant congener. Target cyanopeptide biosynthesis genes for microcystins (mcyE), cyanopeptolins (mcnC), anabaenopeptins (apnD), microviridins (mdnC), and aeruginosins (aerA) were also quantified using digital droplet PCR (ddPCR). The gene copy numbers for mcyE, mcnC, and apnD were highly correlated with their corresponding cyanopeptide concentrations. Overall, the studied Microcystis bloom produced a very diverse cyanopeptide mixture with high cyanopeptide concentrations including non-microcystin groups.

Microcystis

Dynamics of soil fungal communities restored with biochar from a quarry site.

Quarrying activities have intensified due to population expansion, leading to landscape degradation and ecological destruction. Quarry restoration is usually mandatory in Hong Kong, China. Although biochar is used for sustainable soil amendment, its effectiveness in restoring quarry soil with poor properties has rarely been investigated. A 24-month field study was conducted to evaluate the ecological feasibility of restoring a quarry site by using native species (that is, Castanopsis fissa and Cyclobalanopsis edithiae) and biochar amendment. The results revealed that after 24 months, the application of biochar increased the organic carbon, phosphorus and potassium of the vegetated soil by at least 120 %, 31 % and 12 %, respectively, due to higher cation exchange capacity and better plant growth. The relative abundance of Ascomycota and Basidiomycota increased by 24 % and 47 % with biochar application when C. fissa was planted, which was likely associated with the improved nutrient cycling and soil fertility. Even though adding biochar to bare soil was found to increase the complexity of fungal co-occurrence networks, biochar application only increased fungal diversity in vegetated quarry soil but usually reduced its fungal richness. Moreover, fungal co-occurrence networks in vegetated soil became less complex, suggesting that biochar potentially helped plants to assemble specific, beneficial fungal communities. This effect is most pronounced in the soil planted with C. edithiae, where the structure of fungal communities after 24 months was significantly different from that at other restoration times. This study identifies key fungal phyla enhanced by biochar in quarry soil and provides an effective strategy for facilitating the restoration and management of degraded lands, especially quarry sites.

Charcoal

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

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

IMPROVE kidney care: perspectives from marginalised people with CKD and risk factors for CKD on access to, and experience of, kidney care services: a cross-sector collaborative exploration, employing qualitative approaches.

BACKGROUND: Access to, and experience of, chronic kidney disease (CKD) care is inequitable-with barriers to accessing quality care for marginalised groups. We conducted an exploratory study employing qualitative approaches to understand the factors that influence access to, and experience of, healthcare services for marginalised people with CKD and at risk of CKD. METHODS: An exploratory study employing qualitative approaches was conducted as a cross-sector collaboration between kidney care services and an activist, antiracist community-based research and social justice organisation (Mabadiliko Community Interest Company (CIC)). Two groups were recruited: 1) those with risk factors for CKD or early-stage CKD, and 2) people who presented late to kidney care services. Semi-structured interviews were co-designed with people with lived experience and conducted by Mabadiliko CIC. Thematic analysis was undertaken, with themes refined by participants. RESULTS: Twenty interviews were undertaken with a diverse cohort of participants. Knowledge and awareness of CKD was limited, and compounded by a lack of delivery of accessible, culturally congruent information. Significant barriers to accessing kidney care exist for marginalised people, including people who are from global majority ethnic backgrounds, Disabled people, and/or people experiencing material hardship. These barriers are compounded by interpersonal discrimination and paternalistic power dynamics within healthcare interactions. CONCLUSION: This study captures the experiences of marginalised people at different stages of their journey with CKD, in accessing and engaging with kidney care services. Participants faced a complex array of challenges, highlighting opportunities for multi-level intervention. We outline recommendations to address these issues, co-developed with participants.

chronic kidney disease