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PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

A homogeneous immunoassay based on AlphaLICA technology for detecting florfenicol residues in animal-derived foods.

Florfenicol (FF), a broad-spectrum amide antibiotic widely used in livestock, poultry, and aquaculture, poses potential threats to food safety and public health due to its residual accumulation. In this study, a novel homogeneous immunoassay based on Amplified Luminescent Proximity Homogeneous Assay (AlphaLICA) technology was developed for the first time for rapid screening of FF residues in milk and egg matrices. By covalently immobilizing the FF-BSA conjugate and goat anti-mouse IgG onto luminescent and photosensitive microspheres, respectively, the method achieved wash-free, homogeneous quantitative detection through a competitive immunoreaction. Under optimized conditions, the assay exhibited a linear range of 0.2-16.2 ng mL-1, with a limit of detection of 9.7 pg mL-1 and a limit of quantification of 183 pg mL-1. The intra- and inter-batch coefficients of variation ranged from 3.08% to 5.70% and 2.44% to 7.09%, respectively. Spike recovery rates in milk and egg matrices ranged from 93.18% to 107.17% (RSD ≤ 5.57%). Cross-reactivity with 11 other common antibiotics, including chloramphenicol and thiamphenicol, was below 0.1%, demonstrating excellent specificity. Comparative analysis with a commercial ELISA kit showed high consistency (r2 = 0.9332, p < 0.001). With high sensitivity, strong specificity, simple operation, and a detection time of only 10 min, this method provides a reliable technical platform for high-throughput, rapid monitoring of FF residues in milk and egg matrices.

Journal Article↗

PubMed2026

Public health, public protest: The role of health burdens and healthcare access in protest mobilisation.

Health and politics are intertwined, yet few studies have examined the association between health and protest. This study examined whether population health burdens were associated with protest incidence and whether healthcare access modified these associations. Analysis was based on an unbalanced 2004-2023 country-year panel, combining protest counts from ACLED with rates for 22 GBD causes. Mixed-effects negative-binomial models estimated incidence-rate ratios (IRRs) with interactions for healthcare access (±1 SD). Two-way fixed-effects Poisson models were estimated as a benchmark to distinguish cross-national associations from within-country dynamics. Health burdens were systematically, but heterogeneously, associated with protest. Rates for several non-communicable burdens were associated with protest, notably musculoskeletal disorders (IRR 1.72, 95% CI 1.37-2.15), neoplasms (1.24, 1.06-1.44), substance-use disorders (1.32, 1.12-1.56) and HIV/AIDS and other STIs (1.24, 1.12-1.38). Higher healthcare access generally attenuated health-protest associations. Fixed-effects models confirmed several associations (e.g. HIV/AIDS, neoplasms) but revealed that others (e.g. maternal/neonatal disorders, enteric infections) were driven primarily by cross-national differences. Population health burdens were associated with cross-national variation in protest mobilisation. Chronic, non-communicable burdens were associated with heightened protest, whereas poverty-linked and early-life burdens were associated with lower mobilisation. Healthcare access was associated with attenuation of these relationships.

Humans↗

PubMed2026

Moderate expression and activity of flocculins underlie the characteristic flocculation phenotype of Saccharomyces pastorianus.

Flocculation is a key technological trait in lager brewing, governing fermentation performance, yeast recovery, and beer quality. In the allo-aneuploid hybrid yeast Saccharomyces pastorianus, the genetic basis of flocculation remains poorly resolved due to its complex dual sub-genome architecture. Here, we systematically re-annotated and functionally characterized the complete FLO gene repertoire of the Group II strain CBS 1483. Thirteen FLO genes were identified, including allelic variants and a previously uncharacterized adhesin, Flo12, containing a Hyphal_reg_CWP domain instead of the canonical PA14 lectin-binding domain. Structural modeling revealed strong conservation of Ca²+-binding residues in PA14 domains, alongside repeat-region diversification likely contributing to functional variability. Using optogenetic expression in a FLO-null background, we demonstrated that SpcI-FLO9-1 and SpcI-FLO9-2_1 are the strongest drivers of flocculation, exhibiting NewFlo-like sugar sensitivity. Transcriptomic analysis during 17°P wort fermentation showed dynamic induction of these genes coinciding with flocculation onset. Surprisingly, deletion of both loci in CBS 1483 did not abolish but only delayed sedimentation in wort, accompanied by improved maltose utilization and attenuation. These findings reveal functional redundancy and compensatory mechanisms within the FLO network of lager yeast, highlighting the genetic complexity underlying flocculation, and providing a molecular framework to inform yeast selection, strain development, and optimization of the lager fermentation processes.IMPORTANCEFlocculation, the process by which yeast cells aggregate and settle, is essential for producing clear, high-quality lager beer, and for efficient yeast recovery during brewing. However, the genetic basis of this trait in lager yeast has remained poorly understood because these strains possess unusually complex hybrid genomes. In this study, we systematically identified and characterized the complete set of flocculation genes in the industrial lager yeast Saccharomyces pastorianus CBS 1483. We demonstrated that lager yeast flocculation is not controlled by a single dominant gene, but instead emerges from the combined action of several moderately active adhesion proteins that are expressed at low levels during fermentation. Surprisingly, deleting the two strongest candidate genes only delayed, rather than eliminated, sedimentation, revealing a robust compensatory network that preserves brewing performance. These findings refine the current understanding of yeast flocculation and provide a molecular framework for developing brewing strains with improved fermentation efficiency, product consistency, and flavor quality.

Saccharomyces pastorianus↗

PubMed2026

A risk-need-responsivity (RNR)-informed systematic review of needs during the pretrial period.

OBJECTIVE: Pretrial risk assessments are becoming increasingly popular in the United States. Despite the importance of assessing and intervening around "needs" in the risk-need-responsivity model, few pretrial risk assessments include comprehensive assessment of needs. We aim to provide a systematic review of the prevalence of and predictive utility of needs within the pretrial population. HYPOTHESES: There were no hypotheses given the nature of the study. METHOD: We conducted searches for articles in the EBSCO, ProQuest, and Google Scholar databases using key words related to 11 needs domains: antisocial personality, procriminal attitudes, procriminal associates, substance use, family/marital relationships, school/work, prosocial recreational activities, self-esteem, housing, mental health, and physical health. We identified 215 articles that reported on the prevalence of needs or explored their predictive associations with pretrial misconduct outcomes in adult populations. RESULTS: Overall, we find few comprehensive investigations of needs in the pretrial domain, apart from substance use. Variation in methodology and operationalization contributes to wide variability in prevalence estimates. We found only 15 articles that examined predictive associations between pretrial needs and outcomes, which were limited to investigations of behavioral health, employment, and housing needs. Substance use and housing needs emerged as the only consistent predictors of pretrial misconduct. CONCLUSIONS: Researchers should more directly assess the prevalence and predictive utility of needs within the pretrial period to bolster the evidence base for including these factors in pretrial risk assessments. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans↗

PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

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

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

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

Acrylamide↗

PubMed2026

How Do Climatic Factors Directly Influence the Incidence and Risk of Meningococcal Meningitis Across the African Meningitis Belt? A Narrative Literature Review.

Globally, the highest incidence of meningococcal meningitis occurs within the African meningitis belt, spanning 26 countries across sub-Saharan Africa. Meningococcal meningitis incidence is highly seasonal in this region specifically, with outbreaks mostly occurring during the dry season, characterized by low rainfall and atmospheric humidity, high temperature, and increased dust and wind speed. The strong seasonality of meningococcal outbreaks coincides with seasonal variation in climatic factors. This multicollinearity can make it difficult to identify environmental drivers of disease and the mechanisms by which they operate. This review aims to collate existing evidence to better clarify the mechanisms by which climatic variables influence meningococcal meningitis incidence. We examined the impact of dust, wind speed, temperature, rainfall, and land cover on meningococcal meningitis outbreaks. Within the literature, atmospheric dust and wind speed had the strongest statistical association with meningococcal outbreaks and demonstrated greater predictive probability than other climatic variables. However, several climatic factors have demonstrable influences on one another, reflected in the seasonality of meningococcal meningitis. Atmospheric dust can reduce precipitation levels in part through its radiative properties. Decreased rainfall and increasing temperatures can dry out soil, increasing its availability to be uplifted as dust. Alongside, this lower atmospheric humidity increases evaporative demand, leading to faster soil moisture loss and enhanced surface drying. We argue that rainfall, temperature, and land cover variability may act as part of a broader climatic mechanism, increasing atmospheric dust. This increases the incidence and risk of meningococcal meningitis.

Africa↗

PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2026

Avian egg incubation period: Revisiting existing allometric relationships via surface area-to-volume ratio of an egg.

The incubation period (I) for bird eggs varies among species and is used in establishing allometric relationships. Research on variations in I shed light on the evolutionary mechanisms that gave rise to the differentiation of embryonic development in distinct taxa of birds. Here, using a sampling of 444 images from 444 avian species, 89 families and 30 orders, we calculated their major geometric dimensions: volume (V) and surface area (S). An assessment of the relationship between I and the measured and calculated egg parameters demonstrated the closest and most significant correlation (R = -0.760) between I and the S/V ratio that was adopted as a conditional indicator and reflects the embryo's metabolic rate. Approximation of the values of these parameters made it possible to derive a power-law dependence for the prediction of I depending on the S/V value of a particular egg (R2 = 0.757). The prediction accuracy was higher (R2 = 0.783) if the eggs of the family Procellariiformes (petrels), whose I value is characterized by a longer time, were removed from the general sampling computation. We conclude that the value of the S/V ratio can characterize both the metabolism of an embryo and the conditional thermal conductivity of an egg, which aids in ensuring the temperature regime of egg incubation.

Animals↗

PubMed2026

Pesticide occurrence, transformation, and transport from wastewater treatment plants into stream networks with diverse land uses.

Neonicotinoid insecticides and strobilurin fungicides are detected in many environmental compartments and have been associated with negative environmental and human health implications. Wastewater treatment plants (WWTPs) are often hotspots for introducing such contaminants into the environment. Therefore, the occurrence of strobilurin fungicides, neonicotinoids, and their metabolites at two WWTPs with varying land uses and population sizes was investigated. Polar organic chemical integrative samplers were deployed in WWTP influent and effluent and placed upstream and downstream of the effluent mixing zone for 2 weeks in April and July 2022. Biosolids were also collected at each time point. Neonicotinoids were detected with the highest frequency (68%), followed by strobilurin fungicides (49%) and neonicotinoid metabolites (31%). Time-weighted average concentrations for influent/effluent ranged from 85.2 ± 87.8 to 409.4 ± 74.5 ng/L. Pesticide concentrations, specifically the metabolites, typically increased from influent to effluent, resulting in effluent having higher pesticide loads than influent. Pesticide concentrations varied between the upstream and downstream monitoring locations by analyte, with WWTP samples in the highly developed region having significantly higher concentrations of pesticides and less variation by monitoring period. Chronic ecotoxicity benchmarks for freshwater invertebrates for imidacloprid were surpassed in treated effluent at both WWTPs in July and in the downstream monitoring location in the heavily developed area. Findings support the need for further exploration of pesticide contributions from WWTPs to river systems, specifically related to metabolite contributions to downstream streams and their effects on aquatic environments.

Water Pollutants, Chemical↗

PubMed2026

Genome-wide characterization of heat shock protein genes reveals thermal stress-responsive candidates in Litopenaeus vannamei.

Heat shock proteins (HSPs) are conserved molecular chaperones involved in protein folding, refolding, aggregation prevention, and degradation of damaged proteins. However, the genomic organization and thermal responsiveness of HSP genes in the Pacific white shrimp (Litopenaeus vannamei) remain incompletely understood. Here, we performed a genome-wide analysis of the HSP gene family and examined its phylogenetic relationships, structural features, duplication patterns, sequence variation, interaction networks, and transcriptional responses to acute heat stress. A total of 34 HSP genes were identified and classified into the HSP90, HSP70, HSP40/DNAJ, HSP60, and small HSP families. Phylogenetic, motif, gene structure, synteny, and subcellular localization analyses revealed evolutionary conservation and structural diversification among family members. Three duplicated gene pairs were identified, comprising two segmental duplications and one tandem duplication. All pairs exhibited Ka/Ks ratios below 1, consistent with purifying selection of varying strength. Sequence analysis identified 295 nonsynonymous single-nucleotide polymorphisms, of which 12 were consistently predicted to be deleterious by multiple algorithms. Protein-protein interaction analysis indicated enrichment of protein-folding and cellular stress-response functions. RT-qPCR analysis showed significant induction of HSPA4, HSP90AA1, TRAP1, BiP, and DNAJA1 after 6, 12, and 24 h of exposure to 34 °C, whereas DNAJC3 was significantly induced only at 12 h. All six genes reached their highest transcript abundance at 12 h. These findings may provide a genomic framework for HSP genes in L. vannamei and identify candidate genes and variants associated with thermal stress responses.

Animals↗

PubMed2026

Comprehensive identification and evolutionary analysis of the Wnt gene family in bivalves: Insights into the larval development of the noble scallop Chlamys nobilis.

The Wnt gene family regulates fundamental developmental processes in metazoans, but its evolutionary composition and developmental deployment in bivalves remain largely unresolved. Here, we performed a comparative genomic analysis of Wnt genes in 19 bivalve species and examined developmental expression profiles in the noble scallop Chlamys nobilis, with Crassostrea gigas and Chlamys farreri used for cross-species comparison. A total of 235 Wnt genes were identified and assigned to 12 subfamilies. No reliable Wnt3 ortholog was detected in any analyzed bivalve, supporting the view that Wnt3 loss occurred early during lophotrochozoan evolution rather than representing a lineage-specific absence. Most Wnt proteins retained the conserved WNT domain, indicating strong structural conservation, whereas lineage-specific copy-number variation and gene loss were observed among species. C. farreri and C. gigas each retained 12 Wnt genes and lacked Wnt3, whereas C. nobilis lacked Wnt3, Wnt7, and Wnt16. Developmental transcriptome analysis and RT-qPCR revealed clear stage-specific expression patterns. In C. gigas, Wnt2/10/A were highly expressed during earlydevelopment and peaked around the D-shaped larval stage, while Wnt8 and Wnt11 showed distinct stage-specific peaks. By contrast, Wnt1/5/6/9 were more active during later larval development or juvenile formation. These results provide a comparative framework for bivalve Wnt evolution and identify candidate Wnt genes potentially involved in larval development and aquaculture-relevant developmental transitions.

Animals↗

PubMed2026

Unraveling the Clinical Spectrum of DNASE1L3 Deficiency: Insights from Case Series and Systematic Literature Review.

BACKGROUND: DNASE1L3 deficiency is a rare monogenic cause of lupus and lupus-like autoimmunity resulting from impaired extracellular DNA clearance and sustained immune activation. Although most reported patients present with early-onset systemic lupus erythematosus (SLE), emerging evidence suggests broader phenotypic variability, including vasculitic and overlap manifestations. Whether these presentations represent distinct clinical entities or a continuum of DNASE1L3-associated immune dysregulation remains unclear. We aimed to define the clinical spectrum of DNASE1L3 deficiency and examine the relationship between recurrent pathogenic variants and disease severity. METHODS: We conducted a combined pediatric case series and systematic literature review. Four children with genetically confirmed biallelic DNASE1L3 variants followed at a tertiary pediatric rheumatology centre were retrospectively analysed for clinical, immunological, genetic, treatment, and outcome data. In parallel, a systematic search of PubMed/MEDLINE, Scopus, and Web of Science identified previously reported patients with confirmed biallelic pathogenic or likely pathogenic DNASE1L3 variants and extractable patient-level clinical data. To facilitate cross-case comparison, we applied an exploratory three-tier descriptive framework reflecting increasing disease severity: vasculitic or organ-limited disease (G1), systemic lupus or overlap phenotypes without irreversible organ damage (G2), and severe systemic organ-damaging disease (G3). The assigned grades were descriptive rather than permanent categories, as some patients may meet the criteria for a higher grade if broader systemic manifestations or irreversible organ damage develop during follow-up. FINDINGS: Fifteen reports provided extractable patient-level data, corresponding to 45 unique previously reported patients after accounting for known or probable overlapping reports. Combined with four patients from our centre, the analysis included 49 genetically confirmed individuals. SLE-dominant disease was the most frequent phenotype (27 [60%] of 45), followed by hypocomplementaemic urticarial vasculitis/HUVS-dominant disease (10 [22.2%]) and overlap phenotypes (8 [17.8%]). Renal involvement was reported in 30 (66.7%) of 45 patients, and disease onset occurred by age 3 years in 20 (44.4%). Persistent hypocomplementemia affecting C3 and C4 was frequently reported across the spectrum. Recurrent DNASE1L3 variants were observed across multiple phenotypic and severity grades. Variants such as p.Asn191Ser and p.Thr97Ilefs*2 occurred in patients spanning organ-limited vasculitic disease, lupus overlap phenotypes, and severe multisystem lupus with major organ involvement. CONCLUSION: DNASE1L3 deficiency was associated with a broad clinical spectrum of immune-mediated disease rather than a single clinicopathological entity. The occurrence of identical pathogenic variants across distinct phenotypic and severity states argues against a simple genotype-phenotype model and suggests that additional modifiers influence disease expression.

Humans↗

PubMed2026

Trio-based whole-exome sequencing identifies convergent epithelial junction-related pathways in syndromic hidradenitis suppurativa.

INTRODUCTION: Hidradenitis suppurativa (HS)-related autoinflammatory syndromes, simply termed as syndromic HS (sHS), represent a group of rare immune-mediated inflammatory disorders in which HS coexists with systemic or cutaneous autoinflammatory features like PASH (pyoderma gangrenosum-PG-, acne and HS), PAPASH (PASH, pyogenic arthritis), PASS (PG, acne, HS, and ankylosing spondylitis), and SAPHO syndrome (synovitis, acne, pustulosis, hyperostosis, and osteitis). In recent years, genetic studies identified several novel pathogenic variants underlying sHS; however, most investigations rely exclusively on affected individuals sequencing and the absence of parental genomic information limits the possibility to determine inheritance patterns. METHODS: To address these gaps, we performed trio-based whole-exome sequencing (WES) on five individuals diagnosed with sHS and their unaffected parents. RESULTS: The pathway related to epidermal adhesion and desmosome organization was the most represented across our cohort, encompassing seven genes: DSC3, DSG1, FAT1, LAMA3, MICALL2, PLEC and TJP2. Integrin-extracellular matrix (ECM) adhesion signaling pathway, represented by ten genes (CSPG4, FERMT3, ITGA3, LAMA3, LAMA5, LIMS2, LTBP3, PLEC, TGM2, TNC) was also retrieved. Also, variants affecting innate immune pathways, including cytokine signalling and antigen presentation, have been observed. CONCLUSION: Our exploratory findings suggest that genetically heterogeneous variants in syndromic HS converge on biological processes involving epithelial junction organisation, extracellular matrix interactions and innate immune regulation. Although not establishing a unique pathogenic mechanism, these observations identify epithelial barrier biology as a candidate pathway warranting validation in larger cohorts and functional studies.

Journal Article↗

PubMed2026

Failure modes and effects analysis for clinical implementation of online adaptive radiotherapy: A systematic review.

BACKGROUND: The accuracy of radiotherapy is limited by anatomical variations occurring over time scales ranging from sub-seconds to days. Online Adaptive Radiotherapy (OART) addresses this by enabling daily plan adaptation based on real-time imaging. While OART offers improved dose conformity, its dynamic, time-constrained workflow introduces novel failure modes that challenge traditional quality assurance protocols. PURPOSE: This study aims to synthesize the existing literature on Failure Modes and Effects Analysis (FMEA) for OART to systematically catalog risks and identify mitigation strategies. METHODS: A systematic literature search was conducted to identify studies applying FMEA to OART workflows. Eleven studies were included, covering MR-guided (ViewRay MRIdian, Elekta Unity), CBCT-guided (Varian Ethos), and MR-enhanced C-arm linac systems. To address heterogeneity in risk scoring methodologies (e.g., TG-100 10-point scales vs. 5-point rankings), extracted failure modes were harmonized into a standardized three-tier risk classification system (Class I: Low, Class II: Intermediate, Class III: High). RESULTS: A total of 300 unique failure modes were identified, with 49.6 percent classified as high-risk (Class III). Analysis revealed that the majority of high-risk failures were concentrated in the online treatment delivery phase, specifically within human-computer interactions and anatomical contouring steps. CONCLUSIONS: This study supports the development of tailored, robust QA frameworks that prioritize human factors and process consistency to guide safe implementation in diverse clinical settings.

Humans↗