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Protein sorting and proteostasis mechanisms in CFTR-related exocrine pancreas dysfunction: A systematic narrative review.

The pancreas consists of exocrine and endocrine compartments. In the exocrine pancreas, cystic fibrosis transmembrane conductance regulator (CFTR) functions mainly in ductal epithelial cells as a chloride and bicarbonate channel. Its activity depends on proper protein folding, trafficking, and localization to the apical membrane. This systematic narrative review aims to synthesize the available evidence on the role of protein sorting machinery in CFTR channelopathies and its contribution to exocrine pancreatic dysfunction. A thorough search was conducted using PRISMA criteria on PubMed, Wiley Online Library, and Scopus for studies published in English between January 2000 and November 2025. Twenty studies that met the inclusion criteria were included in this review. Pathogenic CFTR variants impair protein folding, endoplasmic reticulum (ER) exit, and endosomal recycling, resulting in reduced apical membrane expression and stability. These defects disrupt the localization of associated transporters and secretory proteins, impair ductal bicarbonate secretion, alter zymogen handling, and promote acinar injury, although these claims are supported mainly by indirect experimental models and therefore require clinical confirmation. CFTR channelopathies in the exocrine pancreas encompass both ion transport defects and broader disruptions of protein sorting machinery. CFTR may contribute to the assembly, stabilization, or localization of selected apical transport complexes, and its loss can secondarily alter epithelial organization. Therapeutic approaches targeting both channel correction and intracellular trafficking may improve pancreatic function and mitigate disease progression.

Humans

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans

Uncovering hidden complexity in the Apis mellifera mitotranscriptome: a polyadenylation-centered perspective.

Mitochondrial transcription is gaining increasing attention as researchers seek to better understand the full coding potential of mitochondrial DNA (mtDNA). Emerging evidence suggests that mtDNA may encode additional elements beyond classical oxidative phosphorylation genes, pointing to a more complex transcriptional architecture than previously recognized. In this study, we explored the mitochondrial transcriptome of Apis mellifera (Insecta: Hymenoptera), with a particular focus on polyadenylation-associated features. Our analysis revealed that both sense and antisense transcripts undergo polyadenylation, although transcript abundance and poly(A) tail lengths varied markedly across mitochondrial genes. Several transcripts exhibited alternative isoforms, either extended or truncated, frequently including intergenic regions. These regions may represent functional non-coding elements or structural variants rather than conventional untranslated regions (UTRs). Interestingly, some transcripts also contained non-templated nucleotide additions particularly cytosine residues immediately upstream of the poly(A) tails. Monocistronic units that included portions of downstream intergenic regions were among the most abundantly represented, suggesting a possible regulatory role for these sequences. To experimentally validate our in silico findings, we performed RT-qPCR to assess relative gene expression and applied 3' RACE-PCR to define transcript boundaries. These approaches confirmed the presence of multiple transcript isoforms and supported the involvement of polyadenylation in shaping mitochondrial RNA diversity. Together, our findings reveal a previously underappreciated level of complexity in the A. mellifera mitochondrial transcriptome and highlight the potential regulatory significance of polyadenylation dynamics and intergenic region transcription.

Animals

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

Pcgf5 controls the exit from totipotency in mouse embryonic stem cells.

Mouse embryonic stem cell (ESC) cultures contain a rare subpopulation of two-cell-like cells (2CLCs) that transiently reactivate a two-cell embryo-like transcriptional program characteristic of zygotic genome activation (ZGA), including the endogenous retrovirus MERVL and Zscan4, and thereby regain a totipotent-like state. Polycomb repressive complex 1 (PRC1)-mediated H2AK119ub1 has been implicated in restraining entry into the 2C-like state through Pcgf6, yet the factors governing exit from this state and loss of totipotency remain poorly defined. Here, we show that among the six Pcgf paralogs, Pcgf5, which is most prominently upregulated in 2CLCs and forms an MERVL-driven chimeric transcript (Pcgf5MT2C_Mm) during ZGA in 2-cell embryos, controls exit from the 2C-like state in mouse ESCs. Using a reporter ESC line carrying MERVL-tdTomato and Zscan4c-EGFP (MtZG), we manipulated Pcgf5 dosage bidirectionally. Doxycycline (Dox)-inducible overexpression (OE) of Pcgf5 reduced the double-positive (DP) 2C-like population. Conversely, CRISPR-mediated knockout (KO) of Pcgf5 by targeting a common exon shared by all Pcgf5 variants (hereafter, total Pcgf5) increased the DP population. Time-lapse imaging directly confirmed that these changes reflected genuine differences in duration of the 2C-like state: OE shortened, whereas KO prolonged, the time cells spent in this state. These findings reveal that a Polycomb group factor controls not only entry into but also exit from the 2C-like state.

Animals

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans

Mendelian randomisation for rheumatology: beyond hype-what it's good for, what it can't do, and how to read it critically.

Mendelian randomisation (MR) has become abundant in the literature, with variation in quality and frequent overinterpretation of causality. This creates a problem for clinical readers, reviewers, and editors: some MR studies can sharpen causal thinking, prioritise drug targets, and challenge misleading observational claims, whereas others are little more than automated exposure-outcome scans with causal claims disproportionate to the evidence. MR can strengthen causal inference when randomised trials are impractical and conventional observational studies are vulnerable to confounding, reverse causation, or selection bias. In rheumatology, credible MR can contribute to questions about disease aetiology, modifiable risk factors, therapeutic target validation, adverse-effect anticipation, and phenotype validation. However, its interpretation depends on whether the exposure is plausibly instrumentable, whether the genetic instruments are biologically defensible, whether assumptions are interrogated in ways appropriate to the design, and whether findings are triangulated with clinical, observational, experimental, and mechanistic evidence. Instead of recapitulating all methodological issues of MR, this review aims to help rheumatologists distinguish robust MR from weak or overinterpreted analyses quickly. We provide an accessible framework for reading and triaging MR studies in rheumatology. Papers that use poorly justified instruments, treat medication use as drug-target evidence, interpret genetic liability as diagnosis, rely on mechanical sensitivity analyses, ignore prior evidence or ask no clinically meaningful question can often be passed over by readers. The goal is not to discourage MR in rheumatology, but to raise the standard; useful MR should clarify causal reasoning rather than simply generate another statistically significant association.

Journal Article

Medically Unexplained Symptoms: A Systematic Umbrella Review of Current Terminology and Reported Rationales.

OBJECTIVES: Toaddress current naming conventions for Medically Unexplained Symptoms (MUS) through a systematic umbrella review. The terminology used and the provided rationales were considered. METHODS: Registered with PROSPERO (CRD42024526020), this review searched 8 key databases, last on January 28, 2025. Reviews including medically unexplained symptoms (or synonym or subtype) in their systematic search terms were included (N=422). RESULTS: A total of 577 references to 111 terms were made across the reviews, with numerous reviews using the same overarching terms, including "functional" (n=233), "somatic" (or variants thereof, n=51), and "medically unexplained" (n=28). Thirty percent of terms (n=179) were to specific syndromes or terms that did not group together under an overarching term, suggesting substantial variability in terms, even though over 60% of authors were primarily associated with just 3 disciplines: medicine, allied health, and psychology. A subset of 23 reviews provided rationales, which were subjected to content analysis and a ROBIS (Risk of Bias in Systematic Reviews) risk-of-bias assessment. This analysis showed that rationales tended to (1) highlight differences between psychological, psychiatric, and other medical fields (n=7); (2) focus on the patient perspective and patient-practitioner therapeutic relationship (n=10); or (3) follow broad and/or commonly used terms (n=7). DISCUSSION: The current landscape of terminology used for MUS remains varied, nuanced, and inconsistent between disciplines. Moving forward to a more universal language accepted and used by both patients and practitioners would aid in the diagnosis, management, and treatment of MUS.

Humans

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n&#x2009;=&#x2009;688) and an independent prospective test cohort (n&#x2009;=&#x2009;193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' &#x3ba; of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7&#xa0;s to 9.9&#xa0;s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

Humans

Factors influencing the enhancement&#xa0;of the new iron triangle&#xa0;in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The&#xa0;healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise&#xb4;s Multiplication Appliqu&#xe9;&#xb4; a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans

Sex- and age-specific associations of VEGFA polymorphisms with multiple sclerosis susceptibility.

AIM: To evaluate six VEGFA polymorphisms (rs1570360, rs699947, rs3025033, rs2146323, rs1413711 and rs833061) and serum VEGFA concentrations in 270 Lithuanian patients with multiple sclerosis (MS) and 270 matched healthy controls. METHODS: Genotyping was performed using real-time PCR, and serum VEGFA levels were measured by enzyme-linked immunosorbent assay. Statistical analyses were conducted using IBM SPSS version 31.0. RESULTS: Nominal differences in VEGFA genotype and allele distributions were observed in sex- and age-stratified analyses. Among females, the rs1413711 C allele was more frequent (p&#x2009;=&#x2009;0.005), whereas the rs833061 C allele was less frequent (p&#x2009;=&#x2009;0.006), in MS patients than controls. In participants aged >38 years, the rs1413711 C allele was also more frequent in MS cases (57.5% vs. 46.0%, p&#x2009;=&#x2009;0.008). Logistic regression identified nominal associations, particularly for rs1413711, rs699947 and rs833061, but none remained significant after correction for multiple testing. Serum VEGFA levels were higher in MS patients than controls (p&#x2009;=&#x2009;0.004). Nominal genotype-related differences in serum VEGFA levels and haplotype associations with reduced MS odds were also observed, but did not remain significant after multiple-testing correction. No consistent associations were found between VEGFA variants and clinical parameters. CONCLUSION: VEGFA genetic variation and elevated serum VEGFA may be associated with MS, but the genetic findings require confirmation in larger independent cohorts.

Humans

Early infantile developmental and epileptic encephalopathy: clinical spectrum, diagnosis, outcomes, and evolving treatment strategies.

Early infantile developmental and epileptic encephalopathy (EIDEE) is among the most severe epilepsy syndromes, with onset before three months of age and an estimated incidence of approximately 10 per 100,000 live births. The 2022 International League Against Epilepsy classification unified the historically distinct Ohtahara syndrome and early myoclonic encephalopathy under a single diagnostic framework defined by frequent drug-resistant tonic and/or myoclonic seizures, an abnormal neurological examination, and an abnormal interictal electroencephalogram-most characteristically a burst-suppression pattern. This narrative review synthesizes the clinical, electrophysiological, neuroimaging, genetic, and therapeutic literature within the EIDEE framework. The clinical phenotype is characterized by central hypotonia, postnatal microcephaly, cortical visual impairment, and age-dependent syndromic evolution toward infantile epileptic spasms syndrome or Lennox-Gastaut syndrome in the majority of patients. Electroencephalography remains essential for syndromic classification, while systematic metabolic screening and early trio whole-exome or whole-genome sequencing are central to the etiologic workup, achieving diagnostic yields of 60-65%. The most commonly identified genetic causes include STXBP1, KCNQ2, and SCN2A variants. Outcomes are poor overall and strongly etiology-dependent: vitamin-responsive disorders carry a substantially more favorable prognosis, whereas mortality reaches 25% in genetic cohorts. Genotype-guided pharmacotherapy is now applicable to a clinically meaningful subset of patients, with sodium channel blockers, potassium channel openers, and emerging antisense oligonucleotide therapies representing important therapeutic advances. Gene therapy trials are underway but have encountered early safety signals, underscoring the vulnerability of this population. Critical unmet needs include earlier molecular diagnosis, precision therapies targeting developmental outcomes beyond seizure control, and prospective international registries to characterize the long-term natural history of EIDEE.

Humans

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals

Prevalence of psychosis in South Asia: A systematic review and meta-analysis.

BACKGROUND: Psychotic disorders are a major contributor to global disability, yet prevalence data from South Asia which inhabits a quarter of the world's population, remain limited. Reliable estimates are essential for health service planning, policy, and closing the substantial treatment gap. This review provides the first comprehensive synthesis of psychosis prevalence across South Asia. METHODS: We searched PubMed, Embase, Web of Science, Global Health, and Medline to 18 December 2024 for DSM- or ICD-based prevalence studies in Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. Cross-sectional and longitudinal studies in community or clinical populations were included. Study quality was assessed using the Joanna Briggs Institute checklist. Random-effects meta-analyses estimated pooled prevalence using the logit transformation. Heterogeneity was explored with meta-regression of key methodological variables (publication year, diagnostic system, residential setting). FINDINGS: Thirty-one studies from five countries were included. Among community-dwelling adults, pooled point prevalence was 0.85% and lifetime prevalence was 1.40%, with inter-country differences (India 1.18%, Pakistan 2.13%, Nepal 2.90%). Clinical samples showed substantially higher proportions of individuals with psychosis in service settings (11.44%), reflecting concentration of cases in treatment-seeking samples. Data for children and adolescents were limited and summarised narratively. Heterogeneity was high across meta-analyses, and exploratory meta-regression did not identify any significant moderators. INTERPRETATION: Psychosis prevalence estimates in South Asia appear higher than global averages but should be interpreted cautiously due to substantial heterogeneity and methodological variation; nevertheless, they highlight the need for culturally sensitive screening, improved detection, and strengthened mental health services.

Humans

Cis-regulatory variation in the MdCKX6 promoter is associated with allele-specific expression and fruit size in apple.

Fruit size is a key determinant of apple fruit quality and market value and is strongly influenced by phytohormone-regulated cell proliferation and expansion during early fruit development. Cytokinin oxidase/dehydrogenase (CKX) enzymes regulate cytokinin homeostasis by irreversibly degrading active cytokinins, but the contribution of natural variation in CKX genes to fruit size remains poorly understood. Here, we identified MdCKX6 as a candidate regulator of fruit growth in apple (Malus domestica). MdCKX6 exhibited pronounced allele-specific expression during fruit development in the cultivar 'Royal Gala'. Sequence analysis identified a promoter SNP associated with differential promoter activity and allele-specific expression. Genotyping of diverse apple cultivars and wild Malus accessions revealed a significant association between MdCKX6 promoter genotype and fruit size. Cultivars carrying low-expression alleles produced larger fruits, whereas high-expression alleles were associated with smaller fruits. To investigate gene function, MdCKX6 was overexpressed in tomato, resulting in reduced fruit size. Histological analyses of the transgenic tomato fruit revealed smaller pericarp cells. Transcriptome analysis of transgenic fruits revealed widespread changes in genes associated with cell-cycle regulation, cell wall modification, hormone-related processes, and transcriptional regulation. Together, these results identify MdCKX6 as a potential negative regulator of apple fruit growth and reveal an association between cis-regulatory variants, gene expression, and fruit size. This study provides new insights into the role of cytokinin metabolism in fruit development and highlights regulatory variation in MdCKX6 as a potential target for apple breeding.

Malus

Evaluation of one-step amplicon-based targeted enrichment for SARS-CoV-2 whole-genome sequencing using the Midnight amplicon scheme.

Genomic surveillance proved invaluable during the COVID-19 pandemic for tracking SARS-CoV-2 variants and guiding outbreak responses, underscoring the ongoing need to reduce whole-genome sequencing (WGS) costs and improve workflow efficiency to ensure accessibility in resource limited settings. Here, we evaluated a one-step reverse transcription polymerase chain reaction (RT-PCR) approach using the Midnight V2 primer scheme for targeted amplification of the SARS-CoV-2 genome, assessed its compatibility with Illumina sequencing, and compared its performance to a well-established two-step method. Initially, we determined optimal RT-PCR reaction conditions using the Midnight V2 primer panel for the one-step RT-PCR kit and scaled reaction volumes for both RT-PCR and library preparation. Clinical specimens (n&#x202f;=&#x202f;53) that had undergone routine WGS for surveillance purposes using the established two-step RT-PCR method were compared using the one-step RT-PCR assay. For samples with genome completeness greater than 70%, both methods gave comparable results with similar sequence coverage and 100% concordance for lineage assignment. Further investigation revealed a higher percentage of reads aligning to the SARS-CoV-2 genome with a greater depth of coverage using the one-step method compared to the two-step method. Finally, analysis of scaled one-step and library reaction volumes revealed significant cost savings for samples undergoing WGS. Overall, the results presented here verify the accuracy and reproducibility of one-step targeted amplification and offer an efficient and cost-effective workflow for routine SARS-CoV-2 genomic surveillance.

Humans