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PubMed2026

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (ΣOPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated ΣOPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring↗

PubMed2026

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans↗

PubMed2026

A systematic review and meta-analysis of the late positive potential and internalizing psychopathology.

The present study leveraged the Hierarchical Taxonomy of Psychopathology (HiTOP) framework to conduct a systematic meta-analysis to determine the association between the late positive potential (LPP) index of emotional reactivity and internalizing psychopathology. PRISMA guidelines were followed. Articles were identified through PubMed, APA PsycInfo, and Web of Science online platforms in May 2025. Included articles examined associations between the LPP to positive and/or negative stimuli and internalizing psychopathology. Risk of bias and publication bias were assessed. Results were examined for individual disorders, distress and fear subfactors, and the internalizing spectrum using two approaches: standard analyses that examined aggregate effects and hierarchical analyses that examined direct and indirect relationships. We conducted moderator analyses for sample, task design, LPP quantification, and psychopathology measurement. We included 63 studies across 5,360 participants (Mage = 19.65, SD = 11.1; 58.7% female). In standard meta-analyses, depression was associated with a smaller LPP to positive stimuli (r = -.06, 95% confidence interval [CI; -.12, -.003]). Specific phobia was associated with a larger LPP to negative stimuli (r = .21, 95% CI [.02, .37]). Distress was associated with a smaller LPP to both positive (r = -.12) and negative (r = -.11) stimuli when measured via clinical interview, and fear was associated with a larger LPP to negative stimuli (r = .10, 95% CI [.03, .16]). Hierarchical analyses indicated that the depression results were specific to the disorder, whereas the fear disorder-level results were due to the higher order fear subfactor. The LPP demonstrates discriminant relationships with distress and fear disorders and subfactors. Results were largely robust against methodological factors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans↗

PubMed2026

The composition of the periostracum in the razor clam Sinonovacula constricta and the mantle's response to sulfide.

The razor clam Sinonovacula constricta inhabits sulfide-rich intertidal sediments and exhibits remarkable tolerance to this toxicant, yet the role of its periostracum in sulfide adaptation remains poorly understood. In this study, we investigated the composition and structure of the periostracum proteins, and the response of the mantle to sulfide stress. Scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed that the periostracum is approximately 10 μm thick and contains 1.43 wt% sulfur, and proteomic analysis further confirmed the presence of organic sulfur (Cys/Met-rich proteins), suggesting its involvement in sulfur deposition. Using LC-MS/MS, we identified 77 high-confidence proteins from the periostracum, which were classified into six functional categories: enzymes, framework proteins, immune-related proteins, calcium ion-related proteins, other proteins, and proteins with unknown functions. Phylogenetic analyses of representative proteins revealed bivalve-specific evolutionary patterns, with several proteins exclusively present in Bivalvia, such as Unknown protein 2 and 7, which possess signal peptides and low-complexity domains. For the sulfide exposure experiment, razor clams were subjected to three Na2S concentrations (0, 10, and 100 μM). qPCR analysis showed that, compared with the control group, Chitin-binding protein 3 and Tyrosinase were significantly upregulated in the mantle, peaking in the 100 μM group at 48 h (5677.84-fold and 157.20-fold, respectively), whereas Collagen and Cadherin 3 were generally suppressed. This study represents one of the most comprehensive proteomic profiles of the razor clam periostracum and highlights the mantle's potential role in sulfide tolerance, offering insights for sulfur-tolerant aquaculture breeding and bioremediation applications.

Animals↗

PubMed2026

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans↗

PubMed2026

Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Utero-placental calcium and magnesium ion channels: A systematic review of obstetric implications of their alterations.

Despite the established roles of calcium (Ca2+) and magnesium (Mg2+) in placental function and uterine contractility, limited information exists on how dysregulation of major ion channels contributes to poor pregnancy outcomes. We synthesized data on the consequences of Ca2+ and Mg2+ channelopathies in uterine and placental functions. Using PubMed, Wiley Online, AJOL, and Web of Science databases for article search, a systematic review of forty-nine papers published between 2000 and March 2026 was carried out and reported in accordance with the PRISMA 2020 guideline. Based on the PICO framework, eligible studies involving human, animal, and in vitro designs were chosen and subjected to narrative analysis. L-type and T-type voltage-gated Ca2+ channels, together with transient receptor potential channels, emerged as principal mediators of placental Ca2+ transport and myometrial contractility. Mechanosensitive Piezo1 channels mediate stretch-activated Ca2+ influx, while store-operated Ca2+ entry pathways involving STIM1-Orai1 sustain intracellular Ca2+ homeostasis. Potassium-Ca2+ coupling channels modulated membrane hyperpolarization and anti-labor effects, and intracellular regulators such as PMCA and RYR1 fine-tuned Ca2+ homeostasis. The Mg2+ transporters are essential for preserving Mg2+ homeostasis and regulating Ca2+-dependent excitability. Dysregulation of these ion channel systems was consistently linked to abnormal uterine contractility, preterm birth, preeclampsia, fetal growth restriction, and adverse pregnancy outcomes. Both Ca2+ and Mg2+ ion channelopathies represent both a potential therapeutic target and a mechanistic factor underlying key obstetric complications.

Female↗

PubMed2026

A complete hlyCABD-like RTX operon marks a virulence-associated subset of trh-positive Vibrio parahaemolyticus from Hangzhou Bay, China.

Vibrio parahaemolyticus remains a major cause of seafood-associated gastroenteritis, yet routine surveillance still relies largely on the canonical hemolysin markers thermostable direct hemolysin (tdh) and tdh-related hemolysin (trh). To determine whether this framework overlooks accessory virulence determinants in trh-positive lineages, we analyzed 193 V. parahaemolyticus isolates collected between 2022 and 2025 from clinical, environmental, and seafood-associated sources in the Hangzhou Bay region of China. Serotyping identified 45 serotypes, with O10:K4 predominating among clinical isolates. Both clinical and non-clinical populations showed open pan-genomes, although the non-clinical group carried a larger accessory gene pool. We identified a complete hlyCABD-like RTX operon in 10 trh-positive isolates with T3SS2-associated virulence backgrounds. These RTX-positive isolates were distributed across seven sequence types and three of five phylogenetic groups. This distribution was lineage-restricted but non-clonal. In the representative hybrid-assembled genome, the operon occurred within a mosaic genomic region containing additional virulence- and mobility-associated genes, indicating a composite pathogenicity island-like element. In the tested subset, RTX-positive isolates showed significantly greater hemolytic activity than RTX-negative trh-positive isolates. This significant difference was consistently observed in both plate-based and liquid assays, and within the RTX-positive subset, hlyA expression correlated with hemolytic activity, whereas the trh gene and the tlh (thermolabile hemolysin) gene did not. A complete hlyCABD-like RTX operon therefore identifies a hemolysis-associated subset of trh-positive V. parahaemolyticus and supports its further evaluation as an additional target for food safety surveillance.

Vibrio parahaemolyticus↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2026

Psychotherapy training in psychiatry: a systematic review and narrative synthesis on the supervision experiences of early-career psychiatrists.

BACKGROUND: Supervision is a fundamental component of psychotherapy training, transforming theoretical knowledge into clinical skills through real-world practice. Psychotherapy training practices vary widely between countries, training programs, and over time, including supervision. Our systematic review aimed to investigate and describe the experiences of psychotherapy supervision through early-career psychiatrists' (ECPs) views. METHODS: We systematically searched PubMed/MEDLINE, Scopus, and PubPsych for survey-based studies on ECPs' experiences of psychotherapy supervision during or after their psychiatry training and reported our findings according to the PRISMA guidelines. Of 32,877 articles screened, 29 articles were included. Each article underwent quality assessment, and results were synthesized narratively. RESULTS: Included articles published between 2000 and 2025, were from Europe (N = 16, 55.1%), the Americas (N = 5, 17.2%), Western Pacific (N = 4, 13.7%), South-East Asia (N = 2, 7%), Eastern Mediterranean (N = 1, 3.5%), and Africa (N = 1, 3.5%), with a total of 4691 participants. Supervision access rates ranged from 26.2% in Nigeria to 85.5% in Russia, with significant variation across countries and psychotherapy modalities. Most ECPs received 50-100 total hours of supervision, frequently delivered in weekly sessions. While formats, individual, group, or mixed, varied by country and training scheme, supervision was generally provided by a psychiatrist-psychotherapist. Common learning techniques included oral consultations and case discussions, followed by audio recordings or transcripts. The need to self-fund psychotherapy supervision costs was identified as a prominent barrier. CONCLUSIONS: Psychotherapy supervision is inconsistent globally, with barriers including supervisor availability and cost. There is a large implementation gap between recommendations and evaluated practice. Digital tools and competency-based frameworks may improve access and quality.

Humans↗

PubMed2026

Dual-tasking reveals severity-dependent reorganization of cortical beta energy landscapes in Parkinson's disease.

Dual-task impairment is a hallmark of Parkinson's disease (PD), yet the large-scale neural mechanisms underlying postural-motor interference remain poorly understood. In particular, it is unclear how cortical network dynamics reorganize across disease severity when postural control competes with concurrent task demands. This study investigated EEG-derived beta-band cortical energy landscapes in healthy older adults, early-stage PD, and mid-stage PD during single- and dual-task conditions. Dual-task behavioral cost increased with disease severity for concurrent manual performance (p < 0.001), whereas a quadratic pattern was observed for postural performance. Energy landscape analysis revealed severity-dependent reconfiguration of cortical beta dynamics. Dual-task-related landscape changes in effective network flexibility (ΔNeff), landscape geometry (ΔEvar and ΔGmag), and dominant low-energy attractor organization (ΔLow mass and ΔLow area) showed significant monotonic trends (p < 0.05), reflecting progressive constrained cortical network dynamics with advancing PD severity. In addition, dual-task-related landscape alterations were associated with clinical severity, as indexed by Hoehn and Yahr stage (|r| = 0.353-0.423, p = 0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r| = 0.333-0.455, p = 0.009-0.063). These findings demonstrate that dual-task demands induce severity-dependent reconfiguration of cortical beta energy landscapes in PD. Energy landscape geometry may capture systems-level neural constraints associated with dual-task susceptibility in PD, providing a physiologically grounded framework to characterize disease-related functional vulnerability.

Humans↗

PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2026

Characterization of the Immune Response after Oral Cholera Vaccination (OCV) and Effects of Mycophenolate Mofetil on Priming of this Immune Response-A Randomized, Placebo-Controlled Trial.

Mycophenolate mofetil (MMF) is an immunosuppressive drug widely used by solid organ transplant recipients. Although it is known that MMF suppresses immune responses, its exact effects on specific vaccinations have not been investigated yet. Mucosal vaccinations are increasingly used, such as a cholera vaccination consisting of two oral immunizations (oral cholera vaccination; OCV). This study aimed to investigate the specific immunosuppressive effects of MMF use during the first dose of OCV in a randomized, placebo-controlled trial in healthy volunteers. Moreover, the study aimed to characterize the immune response provoked by OCV in detail. This randomized, placebo-controlled, single-blind trial included 16 healthy volunteers, each receiving two doses of Dukoral® and an intranasal rechallenge. Outcome measures were serum antibody responses (IgA and IgG) and IgA levels in saliva. Additionally, peripheral blood mononuclear cells (PBMCs) of participants were investigated for ex vivo cytokine production and expression of tissue-specific homing markers after OCV. There were considerable serum IgA and IgG responses after vaccination. MMF-treated volunteers still showed a significant cholera antibody response, though data suggest a potential suppression by MMF without reaching statistical significance. There was no substantial IgA response in saliva. Investigation of PBMCs from OCV-treated participants showed a Th2 skewing with increased ex vivo production of TNF, IL-2, IL-5, IL-13, and IL-22 compared to the placebo group. Taken together, this study provides a framework for future clinical pharmacology studies building on OCV as a challenge model and for further investigation of specific effects of MMF on mucosal vaccination responses.

Humans↗

PubMed2026

Polygenic risk scores in major depressive disorder: A systematic review across diagnostic, treatment, course/severity, and subtype domains.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous across diagnostic, treatment-related, course/severity, and subtype domains. Polygenic risk score (PRS) studies have examined these domains, but differences in PRS sources, samples, methods, and endpoint definitions have fragmented the evidence. We synthesised findings and examined potential contributors to heterogeneity. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and Web of Science were searched for studies published from January 2016 through 25 November 2025. Result records were synthesised using SWiM, and certainty was assessed with an adapted GRADE framework. RESULTS: Sixty studies contributed 493 retained records; 450 were descriptively classified as positive, null, or reverse, although records were not independent. Positive findings accounted for 44/56 diagnostic, 61/273 treatment-related, 64/100 course/severity, and 14/21 subtype records. For MDD/depression-derived PRSs and case-control MDD status, all 10 contributing studies showed higher liability in cases (exploratory exact sign test p = 0.002; FDR q = 0.004). The same PRS group showed positive findings for overall depressive symptom severity (14/18), although the study-level test was imprecise (5/5 studies; p = 0.063). Pharmacological response/remission findings for these PRSs were mostly null or directionally mixed (10 positive, 18 null, and 9 reverse). Treatment-resistant depression (TRD) findings differed by operational definition. Atypical and psychotic subtype signals arose mainly from single-study PRS and endpoint contrasts. CONCLUSIONS: PRS evidence was clearest for MDD diagnostic status and showed a tentative pattern for overall symptom burden. Treatment and subtype findings were less consistent or less replicated. Larger, ancestrally diverse studies with standardised endpoints and transparent PRS methods are needed.

Humans↗

PubMed2026

Antennal transcriptome analysis of chemosensory proteins in the raspberry weevil, Aegorhinus superciliosus (Coleoptera: Curculionidae).

Aegorhinus superciliosus (Coleoptera: Curculionidae) is a polyphagous pest of economic importance in southern Chile, the chemical ecology of which remains poorly characterized. Across insect species, chemosensory proteins, including odorant receptors (ORs), gustatory receptors (GRs), ionotropic receptors (IRs), odorant-binding proteins (OBPs), chemosensory proteins (CSPs), and sensory neuron membrane proteins (SNMPs), mediate the detection of chemical cues involved in host selection, reproduction, and other ecologically relevant behaviors. In this study, the antennal transcriptome of adult A. superciliosus was sequenced and analyzed using a de novo RNA-seq approach. Three independent biological replicates per sex were used for RNA-seq, and the same number of independent biological replicates was used for RT-qPCR validation; sequencing yielded 147,409,936 high-quality reads after quality filtering. A total of 112 candidate chemosensory genes were identified, comprising 43 ORs, 34 OBPs, 10 CSPs, 18 IRs, 5 GRs, and 2 SNMPs. Phylogenetic analyses assigned these candidate proteins to established clades, providing a comparative framework for functional inference for ORs and OBPs. Sex- and tissue-biased expression analyses revealed that several ORs, including AsupOR4, AsupOR19, and AsupOBP13, exhibit antennal enrichment and sex-specific expression patterns. Notably, AsupOR19 and AsupOBP13 displayed strong female-biased expression. In addition, transcripts of selected ORs and OBPs were detected in non-antennal tissues, such as the rostrum and legs, suggesting potential functional versatility beyond canonical olfaction. Together, these findings represent the first molecular identification of the chemosensory repertoire of A. superciliosus. This study establishes a foundation for reverse chemical ecology approaches aimed at identifying behaviorally active volatile organic compounds (VOCs) toward environmentally sustainable strategies for integrated pest management.

Animals↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗