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In Situ Hybridization and RT-PCR Detection of Nervous Necrosis Virus in Fourfinger Threadfin, Eleutheronema tetradactylum, in Taiwan.

Between April and July 2020, suspected outbreaks of nervous necrosis virus (NNV) infection were observed in fourfinger threadfin (Eleutheronema tetradactylum) fingerling hatcheries in Pingtung County, southern Taiwan. Affected fish exhibited spiral swimming behaviour and abdominal distension, resulting in mortality rates between 50% and 100%. Histopathological examination showed severe vacuolation in the brain and ocular tissues, with large oval and/or irregular basophilic cytoplasmic inclusion bodies in the brain. Phylogenetic analysis of the viral replicase (RNA1) and capsid protein (RNA2) genes revealed high nucleotide sequence identities among the isolates in this study, with sequence similarity rates of 96.9%-99% for RNA1 and 98.2%-99.0% for RNA2 compared to RGNNV reference strains available in the NCBI GenBank database. This is the first detection of betanodavirus in fourfinger threadfin in Taiwan, using RT-PCR and ISH. A positive correlation between elevated water temperatures and disease severity indicates the need for year-round surveillance and genomic analysis to clarify the epidemiology of FTNNV. The data suggest that infected eggs may facilitate the vertical transmission of Betanodavirus. Crucially, utilising virus-free broodstock, alongside routine health screening and environmental control, is essential for mitigating NNV risks in fourfinger threadfin aquaculture.

Animals

Dispositional optimism and open-label placebo responses in hair cortisol concentrations and psychological distress-A randomized controlled trial.

Open-label placebo (OLP) treatments show beneficial effects on various health-related outcomes, but studies investigating OLP effects on physiological measures remain scarce. This randomized controlled trial examined the effect of a 4-week OLP intervention on psychological distress and hair cortisol concentrations (HCC) in 202 healthy university students preparing for mandatory oral exams and whether dispositional optimism moderates the OLP effects. Participants were randomly assigned to an OLP or control group. Psychological distress was repeatedly assessed via negative affect, test anxiety, and subjective stress. HCC was measured before and within the intervention. Treatment expectations were additionally examined in interaction with optimism. Results show that OLPs significantly reduced psychological distress and HCC compared to the controls. Optimism moderated the OLP effect on HCC, with less optimistic individuals demonstrating the strongest reduction, independent of expectation. Optimism did not moderate OLP effects in psychological distress. However, the OLP effect on psychological distress depended on the three-way interaction of group, optimism, and expectation. The results suggest that OLPs alleviate the psychophysiological impact of a real-life stressor and indicate that optimism and expectation differently shape psychological and physiological OLP responses. These findings are discussed within the framework of the interactionist perspective.

Humans

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology

Transcranial Magnetic Stimulation for Patients with Exposure Therapy Resistant Obsessive-Compulsive Disorder (TETRO): Study Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a disabling mental disorder, characterized by obsessions, compulsions, and substantial morbidity. Approximately 50% of adults with OCD fail to achieve satisfactory outcomes from first-line treatments, such as exposure therapy with response prevention (ERP), with or without medication. This leads to chronic social, educational, and occupational impairment. While invasive procedures such as deep brain stimulation are available for severe, treatment-refractory cases, a need remains for less invasive alternatives. Repetitive transcranial magnetic stimulation (rTMS), a noninvasive intervention, shows promise in reducing OCD symptoms. Unlike in depression, rTMS is not yet reimbursed for OCD in the Dutch healthcare system. OBJECTIVE: This study examines the efficacy and cost-effectiveness of low-frequency (1Hz) rTMS targeting the presupplementary motor area (pre-SMA) compared to sham rTMS as an adjuvant treatment to ERP in adults with OCD with inadequate response to first-line treatment. METHODS: A total of 250 adults with OCD will be enrolled in this multicenter randomized controlled trial. Participants will be randomly assigned to ERP combined with either active or sham 1Hz rTMS over the pre-SMA. Treatment is administered 4 times weekly for at least 5 weeks (20 rTMS-ERP sessions), with optional extension of 1 to 2 weeks, up to 28 rTMS-ERP sessions. Clinical assessments occur at baseline, weekly during treatment, posttreatment, and at 3, 6, and 12 months follow-up. Participants undergo pre- and posttreatment (functional) (MRI) scans, including a symptom provocation task. Blood sampling takes place pre- and posttreatment and at 3-month follow-up. The primary outcome is OCD severity at posttreatment, as measured by the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Secondary outcomes include functional improvement, quality of life, and societal costs. Pretreatment symptom profiles, genotype, and brain network topology will be analyzed as predictors of response and relapse risk. Pre-to-post treatment change in blood-based and magnetic resonance (MR)-based neuroplasticity markers will help explore differential mechanisms between ERP alone and combined rTMS-ERP. We expect that the verum rTMS protocol will be cost-effective compared to sham-rTMS. RESULTS: Recruitment started in April 2022, and as of February 2026, 201 participants have been enrolled. Posttreatment assessments are projected to be completed in December 2026, with final one-year follow-up evaluations anticipated by the end of 2027. CONCLUSIONS: To our knowledge, this study is the first adequately powered randomized controlled trial examining efficacy, cost-effectiveness, and mechanism of action of rTMS for OCD as adjuvant therapy to ERP. In case of efficacy and/or cost-effectiveness, it will pave the way for rTMS as insured health care for adults with OCD in the Netherlands, and possibly other European countries. Furthermore, this trial will provide insight into the mechanisms of treatment response to intensive ERP, with and without adjunctive rTMS, as well as potential side effects, individual variability, and long-term outcomes in adults with OCD.

Humans

Behind the Curtain of Care. Nurses' Experiences Providing Care to Consumers With Alcohol and Other Drug Issues: A Qualitative Scoping Review.

AIM: To scope and synthesise qualitative literature relating to nurses' experiences of providing care to consumers with alcohol and other drug issues and explore how meaning is constructed in practice. DESIGN: Scoping review. METHODS: A scoping review was conducted following Arksey and O'Malley's framework. Findings were analysed using thematic analysis. DATA SOURCES: Systematic searches were conducted between September and November 2025 across Medline, Emcare, CINAHL and Google Scholar, using controlled vocabulary and keywords relevant to nurses' experiences of providing care to consumers with alcohol and other drug issues. RESULTS: Twenty-four studies from 12 countries were included. Seven themes were identified: emotional aspects of care, education, training and skills in practice, the spectrum of stigma, ethical issues in professional practice, navigating pain management, limited support, and how meaning is constructed in practice. CONCLUSION: Nurses' experiences of providing care to consumers with alcohol and other drug issues are shaped by multiple intersecting factors influencing care delivery and professional practice. Further research is needed to examine how workplace culture, language and interpersonal interactions influence healthcare experiences, and inform education, service development and support needs. REPORTING METHOD: Reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

alcohol and other drugs

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots

The cold case of state transition 7 (stt7) mutants of Chlamydomonas reinhardtii, solved by whole-genome sequencing.

The process of State Transitions (ST) corresponds to an STT7 kinase-driven redistribution of the transmembrane LHCII antenna proteins between Photosystem II (PSII) and Photosystem I (PSI), which results from changes in their phosphorylation state. For the past two decades, two LHCII-kinase mutants, stt7-1 and stt7-9, have been instrumental in the study of STs in Chlamydomonas reinhardtii, the former being a null mutant for the kinase but quasi-sterile in crosses, while the latter, although fertile, has a leaky phenotype. Using long-read sequencing, this study further characterized the genetic lesions of the stt7 mutant strains through whole-genome reconstruction and de novo chromosome assembly. In addition, two new stt7 null mutants were generated, one derived by crosses from the original stt7-1 and one obtained by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) technology. This work provides a comprehensive genomic characterization of the original stt7-1 null mutant, revealing extensive chromosomal rearrangements and high levels of aneuploidy, associated with increased cell size and meiotic dysfunction. Reassessment of their physiology and genetic backgrounds highlights the need for caution in interpreting genetic information. We thus produced more reliable null mutants for the LHCII-kinase, amenable to genetic crosses for the study of STs in a variety of genetic backgrounds.

Chlamydomonas reinhardtii

Prevalence of Breastfeeding in Infants With Down Syndrome: A Systematic Review and Meta-Analysis.

AIM: To estimate the prevalence of breastfeeding-overall, exclusive, partial and depending on infants' age-in infants with Down syndrome, and to investigate associated factors. METHODS: A systematic literature search was conducted in Medline, Cochrane Library, Web of Science, Embase, CINAHL and SciELO up to 1 August 2024. Original articles that estimated the prevalence of breastfeeding in infants with Down syndrome, written in French, English or Spanish, were included. Study quality was assessed using the Joanna Briggs Institute (JBI) scale. Meta-analyses were performed for breastfeeding outcomes and meta-regression explored heterogeneity. The review was registered in PROSPERO (CRD42021278019). RESULTS: Twenty-six studies (3463 infants) were included. The estimated prevalence of overall breastfeeding regardless of duration was 71.6% (95% CI [60.3; 80.7]; 25 studies, 3351 infants) with high heterogeneity, I2 = 94%. The estimated prevalence of exclusive breastfeeding was 38.4% (95% CI [22.4; 57.3]; 10 studies, 1099 infants). No factor assessed in meta-regression was significantly associated with overall breastfeeding. CONCLUSION: The estimated breastfeeding prevalence in infants with Down syndrome is similar to that reported in the general population, despite high heterogeneity. Further studies using standardised methodology to assess breastfeeding barriers and facilitators in the context of Down syndrome would allow us to improve support for breastfeeding.

Humans

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence

The combination of morphogenic regulators BABY BOOM and GRF-GIF improves maize transformation efficiency and promotes leaf regeneration.

Transformation is an indispensable tool for plant genetics and functional genomics. Although stable transformation in maize is no longer a major obstacle, there remains a need for accessible and efficient methods for academic laboratories. Here, we present the GGB system, a rapid and efficient approach optimized for immature embryo transformation in B104 and other maize lines. This system combines two distinct morphogenetic regulators, the wheat GRF4-GIF1 chimera and the maize BABY BOOM (BBM) transcription factor (hence the name "GGB") with a modified QuickCorn protocol, enabling regeneration of transformed maize plantlets in c. 2 months with an efficiency 7-fold higher than when compared to either morphogenic factor used in isolation. Expression of both regulators did not significantly affect development, eliminating the need to excise them after regeneration. However, transmission of the transgenic GGB construct through pollen was significantly reduced, potentially aiding transgenic line containment. We show that the GGB system is adaptable for CRISPR-Cas9 editing and reporter line generation. Furthermore, stable GGB transformants exhibited high leaf regeneration capacity via somatic embryogenesis. RNA-seq time-course profiling of GGB leaf cultures identified additional factors that could promote regeneration and led to the discovery of asparagine and trehalose as additional media components that significantly enhanced leaf regeneration.

Zea mays

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans

Plant species identification by genome skimming across the vascular plant tree of life.

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing <&#x2009;25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (<&#x2009;25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

DNA Barcoding, Taxonomic

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (&#x2265;54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

Humans

Biliary Cirrhosis in Myhre Syndrome: The First Case Report of Liver Transplantation and a Review of Reported Hepatic Findings.

Myhre syndrome is a rare autosomal-dominant disorder caused by gain-of-function pathogenic variants in SMAD4 and is now recognized as a progressive multisystem fibrotic disease. Although transforming growth factor-&#x3b2; (TGF-&#x3b2;) signaling plays a central role in hepatic fibrogenesis, hepatobiliary involvement in Myhre syndrome has not been systematically evaluated. We report the first case of Myhre syndrome complicated by rapidly progressive biliary cirrhosis requiring liver transplantation in a 15-year-old male with a confirmed SMAD4 p.Ile500Val variant. Following an infectious episode, the patient developed severe cholestasis with imaging and histopathologic findings consistent with fibro-obliterative cholangiopathy, ultimately necessitating living donor liver transplantation. A systematic review of 55 published reports comprising 217 patients with Myhre syndrome revealed that hepatic evaluation was rarely performed and that previously reported liver abnormalities were mild and secondary, most commonly related to right heart dysfunction or metabolic disease, with no prior cases of progressive biliary fibrosis. This case suggests that dysregulated SMAD4-TGF-&#x3b2; signaling may predispose selected organs to fibro-obliterative injury and that infection-driven inflammation may act as a critical trigger for hepatic fibrosis in Myhre syndrome, expanding the recognized spectrum of organ involvement in this disorder.

Humans