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Ramu stunt virus genome reveals previously unreported segments and nucleocapsid domain duplication in Mechlorovirus.

Ramu stunt virus (RmSV), a member of the genus Mechlorovirus within the family Phenuiviridae, was previously described as a six-segmented RNA virus infecting sugarcane. In this study, we re-examined type material and additional isolates using high-throughput sequencing and RT-PCR validation, revealing that RmSV possesses a nine-segmented genome, making it the largest reported in the Phenuiviridae. This expanded architecture includes duplicated RNA segments (RNA 2a and RNA 2b) encoding nucleocapsid-like proteins and two novel segments (RNA 7 and RNA 8). Comparative analysis showed that RNA 2a and 2b share about 84% amino acid identity, while RNA 5 encodes a third nucleocapsid homolog, indicating unprecedented domain redundancy. Structural modeling confirmed that all three nucleocapsid proteins maintain a conserved fold despite low sequence identity, with electrostatic mapping suggesting differential RNA-binding potential. Additionally, RNA 6 encodes a hypothetical protein structurally similar to the rice stripe virus disease-specific S-protein, implicating a role in symptom development. Transcript abundance analysis revealed RNA 6 as the most highly expressed segment across isolates. These findings revise the genomic composition of RmSV, highlight mechanisms of genome plasticity and adaptive evolution in plant-infecting bunyaviruses, and underscore practical implications for diagnostic assay design, resistance breeding, and biosecurity surveillance.

Genome, Viral

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article

Sarcomas: Research on Ultrarare Subtypes Gains Ground.

Rare cancers account for almost one fourth of all cancers. Sarcomas belong to the group of cancerous diseases with an incidence of less than 6 cases per 100,000 inhabitants. Over the past decade, activities were launched worldwide to elucidate the peculiarities of many of the more than 100 sarcoma subtypes described in the World Health Organization handbook. The major contributor to exact diagnosis is molecular pathology. The subgroup of ultrarare sarcomas (URS) poses a significant problem as each URS type has its own morphology, biology, natural history, and prognosis. In 2020, 35 international sarcoma centers agreed to standards of evaluating URS. The threshold was set to an incidence of less than 1 case per 1,000,000 inhabitants, and 77 URS subtypes were defined. Also quality criteria for centers to be selected for retrieving data to registries were consented. This issue of Cancer Epidemiology, Biomarkers & Prevention contains the first article to validate these principles of URS using the data from a nationwide cancer database. The authors from Taiwan also pointed out limitations of the approach. Combination with the national death database allowed to calculate overall survival (OS) and identified age as a significant factor for OS per URS type. These new data might foster future research on diagnosis and treatment of URS. See related article by Lee et al., p. 1654.

Humans

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

CNNM2 in schizophrenia: multilevel evidence of genetic susceptibility, magnesium homeostasis, neurodevelopment and cognitive dysfunction.

Schizophrenia (SCZ) is a common psychiatric disorder with a complex, genetically and environmentally influenced etiology, but the specific pathogenesis remains unclear. In recent years, the SCZ susceptibility gene CNNM2 (encoding cyclin M2) located at the 10q24.32-33 locus has received widespread attention. The well-validated SCZ risk interval 10q24.32-33 harbors two independent risk variants: rs11191580 in NT5C2 (significantly associated with CNNM2 mRNA and protein levels) and rs7914558 in CNNM2. Results from functional genomic analyses indicate that lower CNNM2 expression is significantly associated with SCZ. Imaging genetics studies have demonstrated that carriers of risk alleles of CNNM2 SNPs exhibit alterations in brain structure. Animal model studies have revealed that Cnnm2 downregulation in mice leads to impairments in sensorimotor gating and cognitive function. As an Mg2+ transporter, CNNM2 primarily maintains systemic Mg2+ homeostasis. According to clinical studies, a proportion of patients with SCZ exhibit reduced Mg2+ concentrations in plasma and cerebrospinal fluid. CNNM2 dysfunction may contribute to the pathology of SCZ by disrupting Mg2+ homeostasis, thereby affecting neurodevelopment and synaptic plasticity. A systematic consolidation of current evidence supporting the involvement of CNNM2 in SCZ pathogenesis provides a direction for further investigation of the pathological mechanisms underlying this disease, and for identification of novel targets for clinical intervention..

Schizophrenia

How to assess different types of abstract concepts in brain disorders: A systematic review.

The clinical evaluation of semantic knowledge has predominantly relied on tools targeting concrete concepts, whereas abstract knowledge has historically received limited attention despite its importance in everyday communication. Only a few instruments have explored the internal subdivision of abstract knowledge, likely due to the intrinsic difficulty of defining specific types of concepts or dimensions, resulting in a fragmented and heterogeneous neuropsychological assessment framework that limits our understanding of this domain. This systematic review examined the tools used to assess various types of abstract concepts in clinical populations. A literature search has been performed on the electronic databases of PubMed and Google Scholar (last update: October 2025). A total of 17 tests is reviewed, differing in the test characteristics, i.e. ranging from automatic to controlled processes and varying in ecological validity, the type of stimuli employed, and the abstract dimensions explored. Most studies have focused on neurodegenerative patients, while comparatively few have examined other clinical conditions. The risk of bias of the reviewed studies was assessed using an ad hoc developed instrument. This review highlights the need for future research to extend investigations to additional abstract domains and clinical populations, while also identifying key challenges related to stimulus selection and the determination of the most appropriate assessment framework.

Humans

Genome-wide identification and characterization of ABC transporters and their expression in response to saline-alkaline stress and WSSV infection in Fenneropenaeus chinensis.

ATP-binding cassette (ABC) transporters play crucial roles in stress responses across organisms, yet their functions in Fenneropenaeus chinensis remain largely unknown. In this study, we identified 42 FcABC genes (FcABCs) in the F. chinensis genome and analyzed their phylogenetic relationships, gene structures, and chromosomal distributions. Phylogenetic analysis grouped the FcABCs into eight subfamilies (ABCA-ABCH), with conserved motif and domain compositions within each subfamily. Expression analysis showed that several FcABC genes, including FcABCG5, FcABCA1, and FcABCC3, were significantly induced under saline-alkaline stress in gill and hepatopancreas tissues. In contrast, most FcABCs were downregulated after WSSV challenge, though a subset (e.g., FcABCB1, FcABCC1) exhibited early upregulation. Functional validation via RNA interference demonstrated that knockdown of FcABCG5 increased shrimp mortality under saline-alkaline stress. Cis-regulatory element analysis revealed an enrichment of stress- and immune-related elements in FcABC promoters. Protein-protein interaction network predictions indicated potential roles for FcABCs in cholesterol metabolism and organic anion transport. Our findings provide insights into the roles of FcABC genes in stress adaptation and immune defense, offering candidate genes for the breeding of stress-resistant shrimp varieties.

Animals

Embedding cardiovascular risk assessment into routine BTK inhibitor management in chronic lymphocytic leukemia.

INTRODUCTION: Cardiovascular (CV) toxicities remain a major challenge during Bruton tyrosine kinase inhibitor (BTKi) therapy for chronic lymphocytic leukemia (CLL). Selecting the optimal BTKi based solely on a history of overt CV disease may underestimate underlying cardiovascular vulnerability. AREAS COVERED: We performed a targeted, non-systematic review of PubMed and MEDLINE to examine the association between baseline CV comorbidities and BTKi-related CV toxicities in CLL. Current evidence indicates that preferential use of BTKis with more favorable CV safety profiles, coupled with appropriate cardio-oncology surveillance, reduces the risk of CV adverse events in patients with pre-existing CV disease. In patients without established CV disease, the Systematic Coronary Risk Evaluation 2 (SCORE2) and SCORE2-Older Persons (SCORE2-OP) may help identify clinically meaningful latent CV risk, enabling early optimization of modifiable risk factors in line with the proactive cardiovascular management strategy endorsed by the 2026 European Hematology Association (EHA) CLL guidelines. EXPERT OPINION: A structured, risk-adapted approach integrating standardized CV risk assessment, early management of modifiable risk factors, individualized BTKi selection, and multidisciplinary cardio-oncology collaboration may improve the safety and tolerability of BTKi therapy in CLL. Pending prospective validation, SCORE2 and SCORE2-OP should complement, rather than replace, dedicated cardio-oncology evaluation.

Humans

Efferocytosis regulatory factors in atherosclerosis: A preclinical systematic review.

BACKGROUND: Impaired efferocytosis is a key driver of plaque instability during atherosclerosis progression. Efficient clearance of apoptotic cells through efferocytosis relies on the coordinated action of multiple regulatory factors. METHODS: PubMed, Web of Science, ScienceDirect, OVID MEDLINE, and Scopus were searched for studies published up to February 7, 2026. Eligible preclinical studies were systematically reviewed to identify endogenous factors that regulate efferocytosis in atherosclerosis. Clinical evidence was also incorporated to enable a preliminary translational assessment of these regulatory factors. RESULTS: Thirty-five endogenous regulatory factors were identified from 36 included studies, and their functional roles across distinct stages of efferocytosis were characterized. Notably, metabolic regulators such as PKM2, PFKFB3, GLS1, and Drp1 were involved in distinct efferocytosis stages. This suggests that metabolic reprogramming may provide the metabolic support require for efficient efferocytosis and inflammation resolution. Ten factors were supported by preliminary clinical evidence consistent with preclinical data. PKM2 was the only candidate biomarker with prospective observational data. However, its independent predictive value still requires validation in multicenter prospective studies. CONCLUSIONS: This review provides a systematic synthesis of 35 endogenous efferocytosis regulators and elucidates their regulatory network in atherosclerosis based on a functional stage framework. Metabolic reprogramming is identified as a central hub linking efferocytosis efficiency to inflammation resolution. This review offers a new theoretical basis for efferocytosis-targeted intervention strategies.

Animals

A transcription factor-focused CRISPR screen identifies SKI as a BCL11A-independent repressor of ζ-globin.

The regulation of α-like globin genes, particularly the embryonic ζ-globin gene (HBZ), remains incompletely understood. To identify transcriptional regulators of HBZ, we establish a GFP reporter system based on the HBZ-P2A-GFP allele in erythroid cell lines and conduct a CRISPR/Cas9 screen targeting 1639 transcription factors. This screen identifies SKI as a potent HBZ repressor. Functional validation shows that SKI loss increases HBZ expression without impairing erythropoiesis, whereas SKI overexpression suppresses HBZ. Tet-on-inducible SKI overexpression and auxin-inducible SKI degradation indicate that SKI rapidly represses HBZ transcription. Transcriptome profiling further reveals that SKI deletion activates HBZ while minimally affecting other erythroid genes. Mechanistically, genome-wide occupancy analyses show that SKI binds the distal enhancers HS-10 and HS-40, with partial co-occupancy by BCL11A. Despite this overlap, dual knockout of SKI and BCL11A synergistically increases HBZ expression, as does base editing of the SKI-binding site within HS-10. We also identify a naturally occurring variant (chr16:193207G>A) within this enhancer in α-thalassemia patients with elevated ζ-globin levels. Together, these findings establish SKI as a direct, BCL11A-independent transcriptional repressor of ζ-globin. This work advances our understanding of globin gene regulation and suggests targeted ζ-globin reactivation as a potential therapeutic strategy for α-thalassemia.

Enhancer

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

Tripled-Stranded Antisense Oligonucleotide for Biomarker-Activated Suppression of Essential Genes.

Conditional activation of antisense oligonucleotides (ASOs) is a promising strategy for selective suppression of cancer cells without affecting normal cells. In this study, we developed a tripled-stranded ASO (tsASO) that is rendered inactive through complexation with two additional oligonucleotides. The key innovation is the use of partial overlap between the parent ASO and the biomarker sequence, combined with toehold-mediated strand displacement, enabling precise conditional activation. The tsASO effectively triggered RNase H-mediated degradation of DYNC1I2 and DARS1 RNAs exclusively in the presence of the ERBB2 sequence. In cell-free systems, the tsASO demonstrated high cleavage efficiency (up to 81%), comparable to the parent ASO efficiency, with minimal background activity in the absence of the biomarker sequence, validating the concept at the molecular level. However, in cells using lipid-based transfection, the tsASO exhibited nonspecific cytotoxicity that did not correlate with biomarker presence or target gene expression. Detailed analysis showed no clear support for known sequence-driven toxicity mechanisms (CpG/TLR9, G-quadruplexes) in the nonimmune cell lines, suggesting that the primary limitation is intracellular delivery rather than the tsASO design. Future work should focus on optimizing delivery platforms to achieve controlled cellular uptake and biomarker-dependent release, unlocking the therapeutic potential of this conditional gene silencing approach.

Oligonucleotides, Antisense

Online Risk Behavior in Adolescents: A Systematic Review.

Identifying and categorizing online risk behaviors is crucial for assessing their impact on adolescents. Despite extensive research, previous studies have not provided a clear classification of these behaviors. This systematic review synthesizes the quantitative literature on adolescent online risk behaviors from the inception of research to September 2023, aiming to: (a) offer a comprehensive overview of the types of online risk behaviors and the specific actions encompassed within each category among adolescents; (b) summarize the adverse outcomes associated with these behaviors; and (c) discuss the implications and future research directions. Utilizing key terms, this study sourced studies from four electronic databases (Scopus, PubMed, Web of Science, and EMBASE), ultimately including 22 English-language quantitative studies. The review reveals that online risk behaviors are primarily categorized into content risk behaviors, contact risk behaviors, and conduct risk behaviors. Adolescents engaging in these behaviors are at an increased risk of experiencing physical health issues, mental health problems, externalizing behaviors, and even self-harm and suicidal thoughts or actions. Further research is needed to develop and validate an online risk behavior scale and conduct longitudinal and experimental studies to establish causal relationships and examine the long-term effects of these behaviors on adolescent well-being. The review concludes with implications for future research and potential prevention, intervention, and policy strategies to mitigate online risk behaviors in adolescents.

Humans

Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.

The field of prevention science seeks to identify and implement effective strategies to address social, emotional, and health challenges. A critical aspect of this endeavor is determining the core components of prevention programs that drive positive outcomes. This article presents a case study utilizing artificial intelligence (AI)-assisted systematic review methods to identify key components of healthy marriage and relationship education programs. Given the growing body of research in this domain, AI tools offer a promising means to enhance the efficiency and accuracy of literature reviews. This study employed AI to screen, code, and validate research articles, demonstrating its effectiveness in expediting systematic reviews while maintaining high accuracy in inclusion screening. This case study involved a systematic review of 22,028 resources (identified from PsycINFO, Academic Search Ultimate, and Google) and a final data set of 268 relevant studies. AI screening was integral in effectively conducting multiple rounds of screening. However, findings also highlight challenges in AI-assisted qualitative data abstraction, underscoring the continued need for human expertise in complex coding tasks. The study contributes to the ongoing discourse on integrating AI into prevention science methodologies and offers insights for optimizing AI applications in systematic reviews.

Artificial Intelligence

Genome-wide identification and expression analysis of the CREB/ATF family and its potential role in melanogenesis in the Manila clam (Ruditapes philippinarum).

Ruditapes philippinarum is an economically important bivalve species in China, and shell color is a trait of ecological and commercial significance. Melanin is a key determinant of shell color, and members of the CREB/ATF family have been reported to participate in melanogenesis in other organisms. In this study, members of the CREB/ATF family were systematically identified at the whole-genome level based on genomic and transcriptomic datasets, followed by analyses of their phylogenetic relationships, gene structures, and expression patterns. A total of six CREB/ATF family members were identified and classified into five subfamilies. Expression profiling and RT-qPCR validation revealed that most CREB/ATF genes were highly expressed in the mantle and displayed clear differences among shell-color phenotypes. Except for RpATF4 and RpCREBZF, most members exhibited relatively high expression levels in dark-colored shell strains, particularly in black and zebra-striped clams. Moreover, most genes showed low expression during early embryonic and larval stages but increased expression at the single-siphon spat and juvenile stages. These results suggest that the CREB/ATF family may be involved in melanin-associated shell-color regulation in R. philippinarum, providing important candidate genes and a theoretical basis for further elucidating the molecular mechanisms of shell-color formation in mollusks.

Animals

Toxicological effects of propyl 4-hydroxybenzoate on gallstone pathogenesis: An integrated mendelian randomization, network toxicology, and experimental study.

BACKGROUND: Gallstone disease is a prevalent digestive disorder with substantial global socioeconomic burden. Propyl 4-hydroxybenzoate (PP), a widely used paraben preservative, exhibits potential metabolic and hepatic toxicity, yet its role in gallstone pathogenesis remains unclear. This study aimed to explore the causal association between PP exposure and gallstone formation and the underlying mechanism. METHODS: Two-sample Mendelian randomization (MR) was performed using genome-wide association study (GWAS) data. Network toxicology, molecular docking, and molecular dynamics simulation were applied to screen for core targets. In vivo experiments, transcriptome sequencing, Western blot (WB), and ELISA were conducted for mechanistic validation. RESULTS: MR confirmed a causal link between circulating PP levels and an elevated risk of gallstones (P&#x202f;<&#x202f;0.05), with AKT1 identified as the key target. In mice, PP aggravated gallstone formation by activating the AKT1-NF-&#x3ba;B-CXCL1 pathway, enhancing hepatic inflammation and neutrophil extracellular traps (NETs) formation; these effects were reversed by AKT inhibition. CONCLUSION: PP promotes gallstone formation via the AKT1-NF-&#x3ba;B-CXCL1-NETs axis. Our findings highlight PP as an environmental risk factor for gallstones, providing novel insights into their prevention and targeted therapy.

Animals

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans

Genome-wide scans reveal candidate genes associated with wing morph differentiation in Tetrix japonica.

Wing dimorphism is an important dispersal-related trait in insects, but its genomic basis remains poorly understood in pygmy grasshoppers. Here, we integrated genome-wide single-nucleotide polymorphism (SNP) analyses, population structure inference, selection scans, and functional annotation to investigate genomic differentiation between long- and short-winged Tetrix japonica. Principal component analysis (PCA), ADMIXTURE, and phylogenetic analyses revealed weak genome-wide separation between morphs, indicating differentiation on a largely shared genetic background. Genome-wide scans based on the fixation index (FST), nucleotide diversity ratios, and Tajima's D, using 50-kb non-overlapping windows and empirical top-5% outlier thresholds, identified multiple candidate regions across seven chromosomes. The broader long- and short-winged candidate sets spanned 9.35&#xa0;Mb and 9.37&#xa0;Mb and directly overlapped 82 and 77 genes, respectively. Candidate genes were associated with signaling/hormone regulation, membrane transport, metabolism, cytoskeletal organization, extracellular matrix structure, and development. Short-winged candidate genes were significantly enriched for ABC-type transporter activity and ATP hydrolysis activity. Because all individuals originated from a single laboratory-maintained population with weak genome-wide structure, these regions should be regarded as candidate loci from a screening-stage analysis that require validation in independent populations and by functional assays, rather than as confirmed targets of selection.

Animals