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PubMed2026

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV > 100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation↗

PubMed2026

Micro- and nanoplastics-induced neurotoxicity: a CNS-centered, evidence-graded adverse outcome pathway framework based on systematic weight-of-evidence assessment.

Micro- and nanoplastics (MPs/NPs) are ubiquitous anthropogenic particulate pollutants posing emerging threats to human neurological health. Severe heterogeneity in particle physicochemical properties, environmental aging status, exposure paradigms and experimental platforms has created persistent mechanistic uncertainties in MP/NP neurotoxicology, hindering reliable hazard characterization and risk translation. Here, we systematically consolidate empirical toxicological evidence and construct a dedicated central nervous system (CNS)-targeted adverse outcome pathway (AOP) network integrated with rigorous weight-of-evidence (WoE) grading to elucidate the hierarchical, particle-specific toxic cascades underlying MP/NP-induced neural injury. Our synthesis overturns the conventional linear toxicity paradigm, demonstrating that MPs/NPs trigger neurotoxicity via a complex multi-input mechanistic network. We definitively establish oxidative stress as a robust early convergent key event-rather than a universal molecular initiating event-orchestrating ROS overproduction, lipid peroxidation, mitochondrial dysfunction, and neuroinflammation to propagate neuronal damage. This core module is driven by five distinct particulate upstream triggers: particle-biomolecule interfacial perturbation, corona-facilitated cellular internalization, plastic-associated chemical leaching, aging-derived free radical reactivity, and gut-borne systemic neurotoxic signaling. Downstream pathogenic outcomes encompass glial overactivation, neurotransmitter dyshomeostasis, autophagy-lysosome dysfunction, metabolic reprogramming, regulated neuronal cell death, and behavioral impairments. Tiered WoE analysis confirms strong validation for early oxidative/inflammatory cascades, moderate support for gut-brain axis crosstalk and intracellular trafficking disruption, and nascent evidence for synaptic dysfunction and neurodegeneration-linked proteostatic defects. Extrapolation to human health risk remains constrained by the frequent use of high-dose exposure paradigms, limited validated data on internal dosimetry in the human brain, discrepancies between effective concentrations in experimental models and environmentally relevant human tissue burdens, and insufficient causal validation of distal adverse outcomes. We highlight key research priorities including aged mixed-particle exposure systems, leachate-controlled assays, quantitative internal dose evaluation, and mechanistic intervention verification. This evidence-stratified AOP framework resolves longstanding mechanistic ambiguities in particulate neurotoxicity, providing a standardized, causality-based foundation for future mechanistic exploration and health risk assessment of global plastic pollution.

Adverse outcome pathway↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Effects of exercise on muscle strength and characteristics in rheumatic diseases and sarcopenia: Protocol for the Care for Muscle (C4M) Study.

OBJECTIVE: Muscle weakness is prevalent in rheumatoid arthritis (RA), osteoarthritis (OA) and sarcopenia (SARC). Endurance exercises may improve mitochondrial function and oxidative capacity, while strength exercises are thought to stimulate myofibrillar protein synthesis. This study aims to compare the effects of strength and endurance exercise and explore the association between muscle characteristics and exercise outcomes in patients with RA, OA and SARC. We hypothesize that responses to endurance and strength exercises in patients with muscle weakness are influenced by intramuscular pathology including muscle morphology, mitochondrial function, and systemic inflammation, based on their disease pathology, potentially requiring personalized training schedules. METHODS: This two-arm, parallel-group exploratory trial will enroll 69 patients (23 RA, 23 OA, 23 SARC), randomized to endurance (n = 35) or muscle strength exercises (n = 34), using minimization to balance disease type and gender. The 8-week intervention includes two supervised sessions per week using a controlled cable pulley device (Reforter™) and fitness equipment, plus one weekly home-based session. The primary outcome is isokinetic muscle strength (peak torque), measured with the Biodex system®. Secondary outcomes include muscle morphology, mitochondrial function, systemic inflammation and muscle endurance (by Biodex and 6 Minute Walk test). Muscle morphology will be assessed via 3D ultrasound imaging of the vastus lateralis. Mitochondrial function will be analyzed using high-resolution respirometry on muscle biopsies. Systemic inflammation will be measured using multiplex assays or ELISA on serum samples. DISCUSSION: This study will explore differential responses to muscle endurance and muscle strength exercises in patients with RA, OA, and SARC, offering novel insights into the molecular mechanisms of muscle weakness. The findings may help identify potential mechanisms underlying variability in exercise response and provide effect size estimates to guide future confirmatory studies and more targeted exercise interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT06480643 (date of registration28-06-24).

Humans↗

PubMed2026

Stigma, discrimination-related events, and determinants among adult people living with systemic lupus erythematosus (SLE): Systematic review and indicator-level meta-analysis.

BackgroundSystemic lupus erythematosus (SLE) is a complex autoimmune disease with 0.4 million new cases diagnosed annually. With its wide variety of visible and invisible manifestations, people living with SLE report being exposed to stigmatization, which impacts their personal and professional lives. However, the current literature is unclear on whether healthcare management teams assess this concern during follow-up. This study aims to synthesize existing evidence on the prevalence and determinants of stigma among people living with SLE.MethodsThis systematic review and meta-analysis gathered evidence from observational studies identified from three databases on 16 July 2025. Dual independent screening, data extraction, and risk-of-bias assessment (using the Newcastle-Ottawa Scale) were performed. Results were synthesized using descriptive statistics, narrative synthesis, and indicator-level meta-analyses.ResultsWithin the past two decades, 11 studies comprising 2254 people living with SLE reported and measured stigma- and discrimination-related events using various scales. Stigma was found to be prevalent across its three constructs: interpersonal, perceived, and intrapersonal stigma. This review demonstrated that people living with SLE reported a moderate overall burden of stigma (34.71 [95% CI 26.15, 43.27]), with average stigma scores indicating psychological impact. Additionally, nearly one in two persons (46% [95% CI 28-66%]) experienced at least one form of stigma or discrimination, most commonly social isolation and unfair treatment. Mental health associations were correlated with higher stigma burden.ConclusionThis review demonstrates that stigma and discrimination are not just social challenges but also critical determinants of health. With cautious interpretation, pooled evidence reveals a consistent high prevalence of stigma and discrimination, which act as "toxic" stressors, creating a vicious cycle with psychological stress and psychiatric manifestations and disease activity. There is an urgent clinical need to move beyond a mere biological approach to disease assessment and management and to begin screening for the "invisible" burden of invalidation and discrimination.

Humans↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2026

Nutrition and Diet-Related Training and Curriculum in the US Predoctoral Dental Programs.

PURPOSE: Nutrition and diet are vital for oral and systemic health. It is unclear how well US predoctoral dental programs prepare students in nutrition screening and counseling. This study analyzed US dental school curricula on these topics. METHODS: A cross-sectional online survey was sent to the publicly available email addresses of 67 of 72 academic dental deans at US Commission on Dental Accreditation-accredited dental schools. Items assessed availability, modes and hours of instruction, curricular topics, clinical integration, and instructors. Descriptive statistics summarized responses. RESULTS: A total of 21 academic deans responded, for an overall response rate of 29%. Most (85%) of responding academic dental deans reported that nutrition and diet education was mandatory, with none treating it as optional. Of these schools, 83% offered both classroom and clinical training, while 17% provided only didactic teaching. Didactic hours varied; 42% reported 10 or fewer hours. Foundational nutrition topics were common, although dietary guidelines such as MyPlate were reported less often (66%). Oral health-related nutrition content was broadly covered, with all respondents reporting instruction related to caries, erosion, periodontal disease, and oral dysfunction. Counseling content was less consistent, particularly public health nutrition (67%) and the impact of oral dysfunction on diet and nutrition (72%). CONCLUSION(S): Most responding academic dental deans report including nutrition and diet education in their curricula. However, it remains uncertain whether these topics are incorporated at schools that did not participate in the survey. Variability in curricular time, counseling, and teaching highlights the need for clearer competencies and more clinical training. Improving this could better prepare future dentists for common dietary risks affecting oral and systemic health.

dental caries↗

PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

Humans↗

PubMed2026

Genetic mutations driving ciprofloxacin resistance in laboratory-evolved Salmonella Typhimurium.

Ciprofloxacin resistance in Salmonella Typhimurium is a significant public health concern, and the mechanisms by which the resistance evolves are poorly defined. Here, by serial passaging under antibiotic selection, we isolated ciprofloxacin-resistant S. Typhimurium mutants and subjected them to whole-genome sequencing to reveal the major mutations associated with resistance. The Low CipR mutant acquired four chromosomal mutations in ramR, icdA, lipB, and gyrA, and the High CipR mutant gained additional mutations in gyrB, yaiC, and corA. Functional characterization determined that mutations in ramR resulted in efflux pump upregulation, while disruptions in the TCA cycle caused by mutations in icdA and lipB led to metabolic alterations. These changes indirectly enhanced resistance by increasing the expression of the global regulator MarA and reducing OmpF-dependent membrane permeability. Despite the observation of the G105A substitution in GyrA, enzymatic assays confirmed the failure to support resistance to ciprofloxacin, possibly because the structural alteration remained minimal. GyrB488-489dup was associated with maintained supercoiling under ciprofloxacin and enhanced fluoroquinolone resistance, suggesting a major role in resistance evolution. Other mutations in yaiC impaired biofilm and, in corA, intracellular accumulation of magnesium, possibly stabilizing the bacterial cell envelope under antibiotic pressure. The findings provide novel explanations for the multifaceted mechanisms leading to ciprofloxacin resistance in Salmonella and suggest targets to combat antimicrobial resistance.IMPORTANCEAntibiotic resistance in Salmonella Typhimurium is an increasing public health concern, yet the genetic changes that allow bacteria to become resistant are not fully understood. In this study, we evolved ciprofloxacin-resistant Salmonella in the laboratory and identified the mutations that arise during resistance development. We found that resistance does not result from a single change but from multiple adaptations affecting drug efflux, metabolism, and the antibiotic target. Some mutations increased the activity of pumps that remove antibiotics from the cell, while others altered bacterial metabolism and reduced membrane permeability, making it harder for the drug to enter. A duplication in the DNA gyrase subunit GyrB played a particularly important role in maintaining DNA function under antibiotic stress. Together, these results reveal how diverse genetic changes cooperate to generate ciprofloxacin resistance and provide insights that may help guide strategies to combat drug-resistant Salmonella infections.

DNA gyrase↗

PubMed2026

Photon-counting detector computed tomography (PCD-CT) in multiple myeloma: a systematic review and trial sequential meta-analysis on image quality and radiation dose.

OBJECTIVES: To systematically review and perform a meta-analysis comparing the effects of PCD-CT versus EID-CT on image quality (sharpness) and radiation dose (CTDIvol) in patients with bone lesions due to multiple myeloma (MM). METHODS: A comprehensive search of PubMed, Embase, Scopus, and Cochrane Central was conducted from inception to October 2025. Studies comparing PCD-CT and EID-CT in MM patients were included. Methodological quality was assessed using ROBINS-I, and the certainty of evidence was assessed using GRADE. RESULTS: A total of 41 studies were identified that matched our search criteria. After duplicate removal and screening, five studies (n = 170 patients) were included in the systematic review, with four contributing to the meta-analysis. PCD-CT showed a significant pooled mean difference in image sharpness (mean difference, + 0.99 points; 95% CI, 0.62-1.37; p < 0.001). PCD-CT also demonstrated a reduction in radiation dose (mean difference, -4.95 milligrays; 95% CI, -8.39 to -1.50; p = 0.005). Trial sequential analysis (TSA) confirmed stability of pooled estimates, with conclusive evidence for image sharpness improvement, and suggestive yet incomplete evidence for radiation dose reduction. CONCLUSION: Compared to EID-CT in MM, PCD-CT significantly improves subjective image sharpness as supported by trial sequential analysis. Conventional meta-analysis suggested a reduction in radiation dose with PCD-CT; however, trial sequential analysis indicated that the cumulative evidence remains inconclusive. Further large-scale studies are suggested to confirm the magnitude of the radiation dose reduction benefit.

Humans↗

PubMed2026

Clustering patterns of behavioral and metabolic risk factors for noncommunicable diseases in Iran: findings from a national STEPS survey.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading cause of mortality in Iran, driven by behavioral and metabolic risk factors that frequently co-occur. OBJECTIVE: To identify patterns of co-occurring behavioral and metabolic NCD risk factors among Iranian adults and characterize their demographic and socioeconomic correlates. METHODS: This cross-sectional study analyzed data from 16,618 adults aged ≥25 years who participated in Iran's 2021 nationally representative STEPS survey. Thirteen behavioral and metabolic variables, including physical activity, nutrition score, smoking frequency, alcohol intake, salt intake, body mass index, blood pressure, fasting plasma glucose, and lipid markers, were entered into a K-means clustering analysis. Clusters were characterized by their risk profiles and demographic/socioeconomic attributes. Multinomial logistic regression examined associations between cluster membership and sociodemographic factors. RESULTS: Five distinct behavioral-metabolic clusters emerged. The smokers-drinkers (SD) cluster (3.1%) comprised mostly older, less-educated men with high smoking and alcohol use. The healthy-low-risk (HLR) cluster (40.3%) showed favorable profiles and included younger, more educated individuals. The physically active (PA) cluster (6.6%) was characterized mainly by younger men with markedly high physical activity levels. The dyslipidemic (DLP) cluster (26.0%) exhibited high dyslipidemia and overweight prevalence, while the hypertensive-diabetic (HTD) cluster (24.0%) had the highest obesity, hypertension, and diabetes rates, common among older urban adults. CONCLUSION: Behavioral and metabolic NCD risk factors in Iran formed five distinct co-occurrence patterns. Nearly half of adults belonged to metabolically high-risk clusters, highlighting the need for targeted prevention strategies that combine lifestyle interventions with screening and management of obesity, hypertension, diabetes, and dyslipidemia.

Humans↗

PubMed2026

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (≥18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

Humans↗

PubMed2026

Vesicoureteral reflux and anorectal malformations.

BACKGROUND: Renal and urinary tract anomalies are frequently associated with anorectal malformations (ARMs) and may adversely affect long-term renal outcomes, if not detected early. However, reliable clinical predictors for significant urologic abnormalities across different ARM phenotypes remain poorly defined. OBJECTIVE: To determine the prevalence and grade distribution of vesicoureteric reflux (VUR) in neonates with ARMs, and to explore its association with renal and urinary tract anomalies, the complexity of the ARM phenotype, and other factors are associated with high-grade VUR. METHODS: In this retrospective cross-sectional study, medical records of 64 neonates diagnosed with ARMs and managed at a tertiary children's hospital between 2018 and 2025 were reviewed. All patients underwent renal and urinary tract ultrasonography. Voiding cystourethrography (VCUG) was performed for all neonates according to our institutional protocol, regardless of ultrasound findings or ARM phenotype. Demographic characteristics, ARM phenotype (less-complex vs. complex), urologic findings, urinary tract infection (UTI) history, and associated anomalies were analyzed. Multivariable logistic regression models were used to identify independent predictors of complex ARM phenotype and high-grade VUR. RESULTS: The cohort consisted of 64 neonates (75% male) with a mean gestational age of 37.36 ± 1.83 weeks and a mean birth weight of 2940 ± 601 g. Renal and urinary tract anomalies were common, with hydronephrosis observed in 48.4%, VUR of any grade in 39.1% and hydroureter in 35.9%,of patients. High-grade VUR was identified in 21.9% of patients, and a documented history of UTI was present in 18.8% of the entire cohort. In multivariable analyses, birth weight, presence of VUR, and UTI history were not independently associated with complex ARM phenotype. Additionally, no demographic or clinical variables reliably predicted high-grade VUR. The predictive performance of the regression model for high-grade VUR was limited (AUC = 0.60). CONCLUSION: Renal and urinary tract anomalies are highly prevalent among neonates with ARMs, with VUR representing a prominent finding. The lack of robust clinical predictors for complex ARM phenotype or high-grade VUR underscores the limitations of selective screening strategies and supports the role of comprehensive urologic evaluation in neonates with ARM, regardless of anatomic subtype.

Humans↗

PubMed2026

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2 ng/mL) for sunitinib and axitinib, 1 ng/mL for pazopanib, 5-7 ng/mL for sorafenib, 0.5-1.5 ng/mL for regorafenib metabolic products, and 0.1-0.5 ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000 ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the μg/mL range and linearity of 10-240 μg/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans↗

PubMed2026

The psychosocial supports and interventions accessed by family members of patients with developmental and epileptic encephalopathies: A systematic review.

AIM: Family members of patients with developmental and epileptic encephalopathies (DEEs) face profound emotional, social and practical challenges, yet little is known about how they access psychosocial support. We synthesised the literature on the psychosocial support accessed by family members of patients with DEEs, including evidence-based interventions. METHOD: Four databases were searched. Two reviewers independently screened and extracted data, appraised study quality (QualSyst Tool), and determined certainty of evidence (GRADE-CERQual Framework). Data were synthesised using inductive thematic analysis. RESULTS: 28 papers comprising 27 unique studies were included and methodological quality was high overall (median = 0.91, IQR = 0.85-1.00). Most studies focused on parent experiences; only two included siblings' perspectives. Families reported high psychological needs which were rarely met by psychological support. Clinicians rarely provided adequate information, quality communication or addressed mental health. Families valued respite care, but experienced barriers to access. Peer support was the most common and valued resource. Three studies tested interventions and appeared feasible and acceptable for parents. However, evidence for intervention effectiveness is preliminary and limited to small, uncontrolled pilot studies. INTERPRETATION: Gaps exist in psychosocial support provision for families of patients with DEEs, including insufficient research on siblings' and grandparents' needs, and lack of evidence-based interventions. We propose evidence-informed research and implementation strategies to address these gaps.

Humans↗

PubMed2026

Prevalence and pattern of psychological symptoms in form of dental fear and anxiety in children and adolescents with traumatic dental injuries: a systematic review.

BACKGROUND/AIMS: This systematic review aimed to evaluate the level and pattern of dental fear and anxiety (DFA) amongst children and adolescents with traumatic dental injuries (TDI) and, where available, to compare these outcomes with non-traumatised controls. METHODS: An a priori protocol was developed and registered in PROSPERO (CRD420261329946). A comprehensive literature search was conducted in PubMed, EMBASE, Web of Science, and Scopus on 3 March 2026, with additional grey literature, citation, and reference searching. No language or time restrictions were applied. Observational clinical studies assessing DFA in individuals with TDI using validated tools were included. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Joanna Briggs Institute checklist. Certainty of evidence was evaluated using the GRADE approach. RESULTS: A total of 2885 records were identified, of which 4 cross-sectional studies met the inclusion criteria after screening. Studies were conducted in Croatia and Kosovo and included paediatric populations. Sample sizes ranged from 147 to 505 participants. Different validated scales (CFSS-DS, CDAS, S-DAI) were used to assess DFA. Overall, children with TDI demonstrated predominantly low levels of dental fear and anxiety across assessment tools. However, findings were inconsistent, with some studies reporting lower or similar anxiety levels in TDI patients compared to controls. Risk of bias was moderate or high in three of the four studies, and the overall certainty of evidence was rated as low to very low due to methodological limitations, heterogeneity, and imprecision. CONCLUSION: The limited available evidence suggests that children and adolescents with TDI do not consistently present with higher levels of dental fear and anxiety than non-traumatised controls. These findings indicate that TDI does not inherently cause DFA, underscoring the critical role of empathetic behaviour support in mitigating post-traumatic dental fear. However, the evidence is based on a small number of regionally concentrated cross-sectional studies with low to very low certainty. Future prospective studies using standardised TDI classifications, validated DFA instruments, and clearly defined assessment time points are needed.

Dental anxiety↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗