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A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans

Pharmacological and non-pharmacological modulation of striatal dopamine release: a meta-analysis of [11C]raclopride PET studies.

The dopaminergic system has long been a central focus of functional neuroimaging. Positron emission tomography (PET) with the D2/D3 receptor radioligand [11C]raclopride remains the most widely used method for indirectly quantifying striatal dopamine release in vivo. However, no previous meta-analysis has studied the relative magnitude and regional distribution of dopamine release across different interventions or cognitive interventions overall. To address this gap, in this meta-analysis of 92 [11C]raclopride PET studies (n&#x2009;=&#x2009;1640), we compared the magnitude and regional distribution of dopamine release induced by amphetamine, methylphenidate, ketamine, alcohol, and cognitive challenges with and without reward. Amphetamine induced approximately four-fold greater dopamine release than cognitive challenges (10.9 vs. 2.7%, p&#x2009;<&#x2009;0.001), and approximately twice that of alcohol (4.8%, p&#x2009;<&#x2009;0.001), with effects comparable to methylphenidate (11.5%) and slightly greater than ketamine (9.8%). Psychostimulant-induced increase in synaptic dopamine was greater in putamen and ventral striatum than in caudate, whereas alcohol preferentially engaged ventral striatum. Dopamine release did not differ between rewarded and non-rewarded cognitive tasks in the ventral striatum (p&#x2009;>&#x2009;0.14) or overall striatum (p&#x2009;>&#x2009;0.10). Methylphenidate-induced increases in synaptic dopamine appeared to attenuate with advancing age, whereas cognitive challenges were associated with greater dopamine release in older individuals. These findings demonstrate that individual pharmacological and cognitive interventions differ markedly in both magnitude and regional pattern of dopamine release. They also suggest that [&#xb9;&#xb9;C]raclopride PET may have limited sensitivity for distinguishing reward-related from non-reward-related dopamine release. These findings have implications for the design and interpretation of future neuroimaging studies of dopaminergic function in health and disease.

Journal Article

Hydroxyl Radical Inactivation of Vesicle-Cloaked and Free Murine Norovirus: Linking Biomolecular Oxidation to Lifecycle Disruption and Infectivity Loss.

Hydroxyl radicals (&#x2022;OH) play a central role in inactivating human viruses during advanced oxidation processes for water and wastewater treatment, solar disinfection, and natural attenuation in sunlit aquatic environments. Human norovirus, a leading cause of gastroenteritis, is efficiently transmitted through water and exhibits strong environmental persistence. The recent discovery of vesicle-cloaked virus clusters (viral vesicles) further challenges water treatment and reuse, particularly for norovirus elimination. We investigated &#x2022;OH inactivation kinetics and mechanisms of murine norovirus 1 (MNV-1), a human norovirus surrogate, in free-virus and vesicle-cloaked forms. &#x2022;OH rapidly inactivated both MNV-1 vesicles and free MNV-1 with second rate constants of &#x223c;1010 M-1 s-1; however, the vesicle membrane provided a 2.24-fold protective effect to cloaked MNV-1, resulting in slower inactivation kinetics than those of free MNV-1. &#x2022;OH oxidized viral capsid proteins and genomes together with vesicle proteins and lipids, resulting in impaired CD300lf receptor and cell-based binding, disrupted genome replication, and diminished viral assembly. Despite these biochemical and functional impairments, most vesicle structures remained largely intact following &#x2022;OH exposure. This study establishes a quantitative framework linking biomolecular damage to viral infectivity loss through functional impairment and lifecycle disruption, providing mechanistic insights into advance water disinfection strategies and public health protection.

Norovirus

Transcriptomic insights into the coordinated regulation of signaling, apoptosis, immunity, and metabolism during Sinonovacula constricta larval metamorphosis.

Metamorphosis is a critical ontogenetic transition for marine bivalves, marking the shift from planktonic to benthic lifestyles, where successful transformation dictates survival. The razor clam Sinonovacula constricta is economically important; however, low larval metamorphosis rates remain a major bottleneck in seedling production. To elucidate the mechanisms governing this process, we performed a comparative transcriptome analysis of S. constricta larvae at pre- and post-metamorphosis stages using Illumina sequencing. A total of 3701 differentially expressed genes (DEGs) were identified, including 3254 up-regulated and 447 down-regulated genes. Functional annotation of the respective top 20 significantly up-regulated and down-regulated DEGs indicated their potential pivotal roles in signal transduction (e.g., up-regulated: CAV1, CHRNA2; down-regulated: APP, NOTCH1), cellular proliferation and differentiation (e.g., up-regulated: TUBA, EGF1; down-regulated: KIF23, TTC25), transcriptional and epigenetic regulation (e.g., up-regulated: NFIL3; down-regulated: OVO, HMX1), substance transport (e.g., up-regulated: LRP2, LRP1B; down-regulated: SLC51A, Slc33a1), substance metabolism (e.g., up-regulated: CPK3, CYP26A1; down-regulated: RDMT1, ADAC), immunomodulation (e.g., up-regulated: CPN2, CRISP2), and protein homeostasis (e.g., up-regulated: HSP27, NAS-27). Functional enrichment analysis further revealed that DEGs were significantly enriched in pathways related to signal transduction and developmental regulation (e.g., Ras, TNF), cell death and homeostasis (e.g., apoptosis), immune responses (e.g., Toll-like receptor), energy metabolism (e.g., lipid), cardiovascular related (e.g., Fluid shear stress), cell junction and architecture (e.g., Tight junction), and infectious disease (e.g., measles). These results suggest a synergistic interplay between signaling, apoptosis, immunity, and metabolism during S. constricta metamorphosis. This study advances our understanding of marine bivalve metamorphosis and offers candidate genes for further mechanistic studies.

Animals

Outcomes of Response-Based Watch-and-Wait and Surgical Management After Total Neoadjuvant Therapy for Rectal Cancer: A Systematic Review and Meta-analysis.

BackgroundTotal neoadjuvant therapy (TNT) increases clinical complete response rates in locally advanced rectal cancer (RC), allowing response-based management strategies such as watch-and-wait (WW) as an alternative to total mesorectal excision (TME). Outcomes associated with WW after TNT remain incompletely defined. This study aimed to compare oncologic and organ-preservation outcomes between WW and surgical management following TNT.MethodsA systematic search was conducted in PubMed, Scopus, and Cochrane Central up to April 2025. Observational studies comparing WW and TME following TNT were included. Pooled odds ratios (ORs), hazard ratios (HRs), and 95% confidence intervals (CIs) were calculated using a random-effects model. Heterogeneity was assessed with I2 statistics. Secondary outcomes included tumor regrowth, salvage surgery, and permanent stoma. Risk of bias was evaluated using ROBINS-I.ResultsSix studies comprising 793 patients were analyzed. WW showed no significant difference compared with TME regarding local recurrence (OR 1.36, 95% CI 0.07-26.17; I2 = 80%), distant metastases (OR 0.62, 95% CI 0.29-1.33; I2 = 49%), 5-year disease-free survival (HR 0.97, 95% CI 0.71-1.31; I2 = 51.7%), or overall survival (HR 1.03, 95% CI 0.81-1.30; I2 = 27.9%). Permanent stoma rates were lower with WW (OR 0.12, 95% CI 0.01-1.23; I2 = 71%), becoming significant after sensitivity analysis (OR 0.04, 95% CI 0.01-0.19).ConclusionWW after TNT offers oncologic outcomes comparable to TME, with high organ preservation and reduced surgical morbidity in highly selected patients.

Humans

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans

Venomous Lepidoptera: defensive toxin systems, venom composition, and clinical significance.

Venomous Lepidoptera constitute an underrecognized yet medically significant group of toxin-producing arthropods that employ contact-mediated defensive envenomation through specialized integumentary structures such as setae, spines, and scoli. Unlike actively stinging arthropods, these insects deliver venom passively upon contact, eliciting a diverse spectrum of clinical manifestations collectively termed lepidopterism. Clinical outcomes range from localized pain and dermatitis to severe systemic effects, including hemorrhagic syndromes, complement activation, and chronic inflammatory disorders. Recent advances in proteomic and transcriptomic technologies have transformed our understanding of lepidopteran venoms, revealing unexpectedly complex toxin repertoires comprising serine proteases, phospholipases, pore-forming proteins, disulfide-rich peptides, neuroactive RF-amide peptides, and immune-modulating components. These findings have provided new insights into the molecular basis of toxicity, host-pathogen interactions, and the evolutionary diversification of venom systems within Lepidoptera. This review synthesizes current knowledge on the morphology of venom-delivery structures, venom composition, mechanisms of action, and associated clinical manifestations, while highlighting medically important taxa, particularly species of the genus Lonomia. The successful development of antivenom against Lonomia envenomation underscores the translational relevance of lepidopteran toxin research and its potential for therapeutic innovation. By integrating molecular, clinical, and evolutionary perspectives, this review repositions venomous Lepidoptera as a legitimate and important component of arthropod toxinology. Furthermore, it identifies critical methodological limitations and key knowledge gaps, providing a framework for future investigations aimed at advancing our understanding of toxin biology, immunopathology, and the development of novel biomedical applications.

Animals

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the last 50 years and how well-designed cohort studies will provide us with knowledge for research and practice in the future and aid guideline development. We have included data from a large number of cohorts from every continent that have been used to study the development and/or progression of type 2 diabetes, including cohorts that are general population-based, disease-based, intervention-based and registry-based. We have structured the results from the past 50 years based on the following themes: diagnosis and screening, complications, risk factors and pathophysiology. We also discuss the strengths and weaknesses of observational research when compared with other research designs. Finally, we discuss the emerging and future directions for type 2 diabetes research using cohorts, which include novel developments, such as artificial intelligence, precision health and the exposome. We conclude that cohort research has significantly advanced our understanding of type 2 diabetes and aided guideline development, and complements experimental work, such as human randomised controlled trials and animal studies. Both approaches are essential and complementary in our pursuit to provide a more comprehensive understanding of the development and progression of type 2 diabetes, and to change dogma, practice and policies for better outcomes.

Humans

Ultrastructural Insights Into the Reproductive Anatomy and Eggs of Cotton Pink Bollworm, Pectinophora gossypiella Saunders (Lepidoptera: Gelechiidae).

The pink bollworm, Pectinophora gossypiella Saunders is a major pest of cotton, notorious for its high reproductive potential and rapid evolution of resistance to Bacillus thuringiensis (Bt) toxins. Despite its economic significance, detailed knowledge of its reproductive anatomy and egg ultrastructure has remained limited, constraining the development of advanced molecular control strategies such as CRISPR/Cas9-based genome editing. The present study provides the first comprehensive characterization of the reproductive system and egg surface morphology of P. gossypiella using stereomicroscopy and scanning electron microscopy (SEM) techniques. The male reproductive system consists of fused, bean-shaped testes, seminal vesicles, duplex and simplex ejaculatory ducts, and paired accessory glands. The female reproductive system comprises paired ovaries with four polytrophic ovarioles per ovary, lateral and common oviducts, accessory glands, corpus bursae, and spermathecal glands. Eggs are oval, dorsoventrally flattened, exhibit a reticulated chorion with distinct micropylar and aeropylar regions. SEM images revealed 6-9 rosette cells encircling a circular micropylar plate, 14-19 first order and 17-23&#x2009;s order ribs, and 250-291 polygonal surface cells. The structural features of P. gossypiella eggs reveal key sites for sperm entry, aeropylar respiration, and candidate zones for microinjection in gene editing applications. These findings establish a morphological baseline critical for optimizing embryo manipulation and ribonucleoprotein (RNP) delivery in lepidopteran genome editing. This study represents a pioneering effort to integrate classical egg morphology with molecular entomology, thereby advancing precision genetic interventions aimed at resistance management and population suppression in P. gossypiella.

Animals

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5&#xa0;g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Phytophthora cinnamomi, a highly invasive hemibiotrophic oomycete, threatens global agriculture, forestry, and native ecosystems. Although drought and temperature effects on P. cinnamomi-host interactions are well studied, current knowledge of abiotic stress responses in P. cinnamomi remains largely centered on infection and phytopathology, with limited molecular insight into the pathogen's direct response to salinity independent of its host. To address this gap, we combined growth assays, time-resolved proteomics, and network analysis to define how P. cinnamomi responds and adapts to salinity exposure. Growth assays showed that NaCl-modified agar enhanced mycelial expansion in a concentration-dependent manner, with 100&#xa0;mM NaCl significantly increasing growth at 48, 72, and 96&#xa0;h compared with controls, while 50&#xa0;mM NaCl remained comparable to control conditions. Temporal proteomic analysis of 100&#xa0;mM NaCl treatment at 0, 1, 6, 12, and 24&#xa0;h post treatment revealed dynamic shifts in protein abundance. Early induction of ROS (Reactive Oxygen Species)-detoxifying enzymes, including glutathione S-transferases and peroxidases, was consistent with ROS-specific staining assays. Network analysis identified modules enriched for redox regulation, ATP generation, ion transport, and translational control, highlighting multi-layered adaptation to elevated NaCl levels. Notably, clusters of conserved hypothetical proteins were strongly upregulated, indicating unexplored stress tolerance components in Phytophthora species. Here, we propose that P. cinnamomi rapidly activates a three-phase strategy involving metabolism readjustments, redox defenses, and cellular structure alterations under salinity conditions. With increasing soil salinization due to climate change, our study provides first mechanistic insights into P. cinnamomi's adaptive plasticity and ecological resilience to abiotic stress. SIGNIFICANCE: This study represents the first temporal proteomic analysis of salinity stress adaptation in Phytophthora cinnamomi, revealing a sophisticated three-phase adaptation strategy. This research fundamentally advances our understanding of how this globally destructive plant pathogen, P. cinnamomi, maintains environmental resilience. Our findings reveal proteome remodelling as a mechanistic framework for understanding stress tolerance in oomycetes, a group of microorganisms responsible for some of the world's most destructive agricultural and forest diseases. Our results show proteins involved in emergency damage control through metabolic recalibration to sustained adaptation. These findings have relevance for predicting pathogen behavior under climate change scenarios, where increasing soil salinity threatens agricultural productivity while simultaneously enhancing pathogen survival and virulence. Understanding how P. cinnamomi responds to prolonged salinity exposure may inform targeted biocontrol strategies and improve predictive models of disease pressure in salt-affected agricultural regions. The temporal analysis framework we present offers a broadly applicable approach for understanding microbial stress adaptation, with implications extending beyond plant pathology to environmental microbiology and biotechnology applications where stress tolerance is paramount.

Phytophthora

UV-based homogeneous disinfection process for removal of antibiotic resistance genes: Efficiency, mechanisms and influencing factors.

The proliferation and dissemination of antibiotic resistance genes (ARGs) in aquatic environments pose a serious threat to global public health. Ultraviolet-driven homogeneous advanced oxidation processes (UV-AOPs) represent a prospective suite of technologies for the efficient removal of ARGs. This review critically assesses recent advances in the application of UV-AOPs, specifically UV/hydrogen peroxide (UV/H2O2), UV/peracetic acid (UV/PAA), UV/persulfate (UV/PS), and UV/chlorine (UV/Cl), for the elimination of extracellular ARGs and intracellular ARGs. The underlying mechanisms involve direct ultraviolet-induced DNA damage, including pyrimidine dimer formation and strand breakage, as well as oxidation mediated by radicals such as hydroxyl radicals, sulfate radicals, carbon-centered radicals, and reactive chlorine species. The relative contribution of radical and non-radical pathways is strongly influenced by water chemistry and process conditions. We further expound on the critical operational and environmental factors governing ARG removal kinetics, including UV wavelength and fluence, oxidant type and dosage, ARG sequence characteristics, pH, ubiquitous anions, and dissolved organic matter, which collectively affect radical generation, quenching, and reaction microenvironments. Notably, for i-ARGs, UV-AOPs facilitate degradation not only through direct radical attack but also by disrupting cellular integrity and permeabilizing membranes, thereby enhancing the exposure of genetic materials to oxidative and photolytic damage. This review synthesizes current understanding to provide a mechanistic basis for the design and optimization of UV-AOP systems, highlighting their potential as effective barriers against the dissemination of antibiotic resistance in water reuse and purification scenarios.

Disinfection

Redox Rewiring in Nicotine-Driven Gastric Carcinogenesis: Uncovering ROS-Dependent Oncogenic Circuits.

SIGNIFICANCE: Nicotine from tobacco products, secondhand smoke, and emerging delivery systems remains a major but underappreciated driver of gastric carcinogenesis (GC). Although reactive oxygen species (ROS) have long been implicated in tumor biology, current models incompletely explain how chronic nicotine selectively reprograms gastric epithelial signaling. This review advances the concept of redox rewiring, whereby nicotine establishes a persistent oxidative state that orchestrates multiple oncogenic programs via spatially compartmentalized NOX signaling. RECENT ADVANCES: We synthesize evidence for a unified model wherein nicotine activates nAChR/&#x3b2;-AR signaling, Ca2+ influx, PKC, and compartmentalized NOX-derived ROS to generate distinct oncogenic outputs. Beyond the established NOX/ROS/NF-&#x3ba;B/MAPK-driven IL-8 and MMP-9 axes, we integrate emerging evidence into three interconnected modules governing EMT/metastasis (ABL1/STAT3/COX-2/periostin), survival/chemoresistance (ERK/GLI1/Bcl-2), and invasion/immune evasion (miR-21/PDCD4). Collectively, these circuits suggest that ROS function not merely as damaging byproducts but as spatially organized signaling mediators dictating tumor behavior. CRITICAL ISSUES: A major challenge is distinguishing established mechanisms from incompletely validated models. The three proposed axes are testable hypotheses requiring experimental validation. Most data derive from in vitro studies with nonphysiologic nicotine concentrations, and artifacts from nonspecific ROS probes are common. Compensatory pathway activation and multi-target effects of natural products remain underexplored. FUTURE DIRECTIONS: We outline a precision-redox oncology roadmap linking pathway-specific biomarkers, mechanistically matched natural products, and biomarker-enriched trials. Priorities include genetic validation of the three axes, time-resolved ROS imaging, and pulsed natural product regimens. By reframing nicotine-driven GC as adaptive redox network remodeling, this review provides a framework for prevention, stratification, and next-generation therapy. Antioxid. Redox Signal. 00, 000-000.

gastric cancer

Gastric carcinoma classification in the WHO 6th edition (2026): Updated framework and emerging entities.

The sixth edition of the WHO Classification of Digestive System Tumours (2026) represents an important step in the continuing evolution of gastric carcinoma classification. While preserving morphology as the foundation of diagnosis, it incorporates advances in molecular pathology, genotype-phenotype correlations, tumour evolution, and predictive biomarker assessment. This review summarizes the development of the WHO classification from the third edition (2000) to the sixth edition (2026) and highlights its relationship with other major classification systems, including those of Laur&#xe9;n, Nakamura, and the Japanese Gastric Carcinoma Association (JGCA). Major histological categories remain largely unchanged; however, several important conceptual and diagnostic refinements have been introduced. These include recognition of crawling-type adenocarcinoma as a distinctive variant of tubular adenocarcinoma, subclassification of poorly cohesive carcinoma into signet-ring cell and non-signet-ring cell subtypes, introduction of the concept of pure signet-ring cell carcinoma, and increased emphasis on tumour evolution. The sixth edition also expands and refines the spectrum of uncommon gastric carcinoma subtypes, including gastric carcinoma with lymphoid stroma, AFP-producing carcinoma, micropapillary adenocarcinoma, gastric adenocarcinoma of fundic-gland type, and gastric sarcomatoid carcinoma. Crucially, molecular subgroups originally proposed by The Cancer Genome Atlas (TCGA) and actionable biomarkers-including HER2 (ERBB2), Claudin 18.2, mismatch repair deficiency/microsatellite instability (dMMR/MSI), and programmed death-ligand 1 (PD-L1)-have transitioned from research-based categories into essential tools for precision oncology. Rather than providing exhaustive diagnostic criteria, this review offers a conceptual framework and encourages consultation of the original WHO text for full details. These advances illustrate the transition of gastric carcinoma classification from a predominantly morphology-based system toward an integrated histomolecular framework that more closely links pathological diagnosis with tumour biology, prognostication, and therapeutic stratification.

Crawling-type adenocarcinoma

A systematic review and meta-analysis of radiation-induced oral complications in head and neck cancer: Prevalence and clinical outcomes.

BACKGROUND: Radiation-induced oral complications, notably xerostomia and oral mucositis (OM), are common and debilitating in patients with head and neck cancer (HNC), adversely affecting swallowing, nutritional intake, and overall quality of life (QoL). OBJECTIVES: This review aimed to quantify the prevalence of radiation-induced xerostomia and OM and synthesize their impact on dysphagia and nutritional status among HNC patients undergoing radiotherapy (RT). METHODS: A systematic review and meta-analysis were conducted following PRISMA guidelines. Comprehensive searches were performed in MEDLINE, Scopus, SciFinder, Embase, and PubMed for studies published between January 2019 and December 2025. Data from 51 studies were extracted and synthesized. RESULTS: The pooled prevalence was 85% (95% CI: 81.6-87.9%) for xerostomia and 88.3% (95% CI: 73.9-95.3%) for any-grade OM. Severe OM (Grade 3-4) had a prevalence of 39.5% (95% CI: 23.1-58.8%). These complications were strongly interrelated and significantly associated with dysphagia (69.8%; 95% CI: 53.1-83.7%), malnutrition (66.6%; 95% CI: 37.3-95.9%), and poor QoL (pooled mean QoL score: 64.13/100). Studies employing advanced radiation techniques (e.g., IMRT) demonstrated a lower prevalence of xerostomia (OR&#x202f;=&#x202f;0.58, 95% CI: 0.42-0.80) compared to conventional RT. CONCLUSION: Radiation-induced oral complications (xerostomia & OM) remain prevalent and clinically significant burden in HNC patients, contributing to a cascade of functional impairments and diminished QoL. These findings highlight the need for preventive strategies, symptom management interventions, and the broader adoption of advanced RT techniques. Longitudinal research is warranted to further evaluate long-term outcomes and guide patient-centered care models.

Humans