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PubMed2026

Dual signal-enhanced immunochromatographic test strip based on Au@PtNPs: From sensitive detection of thiamethoxam to multiplex pesticide screening in vegetables.

Immunochromatographic test strip (ICTS) is a rapid analytical technique widely used in environmental and food detection owing to its merits of simple operation and short analysis time. Herein, three-dimensional nanoflower-structured gold‑platinum nanoparticles (Au@PtNPs) were synthesized via a seed-growth method. Compared with conventional gold nanoparticles (AuNPs), Au@PtNPs exhibited stronger signal intensity, excellent catalytic performance, and efficient antibody binding efficiency. Colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS were developed for the sensitive detection of thiamethoxam (THI) in vegetables. The limits of detection (LODs) for colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS quantitative analysis were 0.18 ng/mL and 0.093 ng/mL, respectively, representing approximately 3-fold and 6-fold improvement compared to AuNPs-ICTS (0.56 ng/mL). Furthermore, highly sensitive detection of multiple pesticide residues (chlorpyrifos, acetamiprid, and imidacloprid) was achieved by replacing the corresponding target antigens and antibodies, which further verified the universality of this immunochromatographic strategy.

Thiamethoxam↗
PubMed2026

Determinants of Nonspecific Response to Treatment in Randomized Controlled Trials of Major Depressive Disorder: A Narrative Review.

The design, conduct, and interpretation of double-blind randomized placebo-controlled clinical trials in major depressive disorder (MDD) are complicated by determinants of nonspecific response to treatment (NSRT). This narrative review provides a comprehensive overview of the determinants of NSRT in randomized controlled trials (RCTs) for MDD, including the placebo effect, factors related to measurement of the primary endpoint, the inclusion of misdiagnosed patients, the relapsing-remitting course of MDD, and factors related to functional unblinding. Potential strategies to reduce the impact of the determinants of NSRT and to improve the interpretation of RCT outcomes in MDD are also summarized. These strategies include use of centralized rating and standardized rater training, independent diagnostic confirmation, optimized site selection, minimizing financial incentives, exclusion of subjects participating in multiple clinical trials, exclusion of patients with unstable major depressive episode trajectories, and use of active placebo and alternative trial designs. Uniformity among experts in the definitions of determinants of NSRT and related concepts, as well as in strategies to address them, may facilitate progress in the development of novel treatments for MDD.

Humans↗
PubMed2026

Microglial modulation in general anesthesia: molecular.

General anesthetics profoundly alter brain function and consciousness, yet the mechanisms underlying these effects remain incompletely understood. Although traditional studies have primarily focused on neuronal targets, accumulating evidence suggests that microglia dynamically respond to anesthetic exposure and may participate in anesthesia-associated neurophysiological changes. Beyond their established immune functions, microglia are increasingly implicated in synaptic remodeling, metabolic regulation, neuronal activity surveillance, and neuron-glia communication. Recent studies indicate that different classes of anesthetic agents modulate microglial activity through diverse and context-dependent mechanisms involving inflammatory signaling, purinergic pathways, calcium dynamics, mitochondrial metabolism, and neural circuit interactions. These responses are associated with postoperative neurocognitive disorders, altered synaptic plasticity, and anesthesia-related changes in brain states. In this review, we summarize current evidence regarding the effects of volatile anesthetics, intravenous anesthetics, and analgesics on microglial function and discuss the molecular, functional, and circuit-level mechanisms underlying anesthesia-associated neuron-microglia interactions. We further highlight the dynamic and heterogeneous nature of microglial responses during anesthesia and discuss current limitations in the field, including the lack of temporally resolved and cell-specific approaches. Understanding these processes may provide insights into anesthesia-associated neurocognitive dysfunction and support the development of neuroimmune-targeted strategies in anesthesiology.

General anesthesia↗
PubMed2026

Deciphering CD8+ T cell exhaustion in human cancers through single-cell and spatial transcriptomics.

Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.

Humans↗
PubMed2026

Nephropathies Associated with Sickle Cell Trait and How to Study Them.

Sickle cell trait (SCT), which carries a single point mutation in the hemoglobin-β (HBB) gene, has long been considered a benign condition. However, epidemiological evidence challenges this assumption, revealing that individuals with SCT face an elevated risk of renal dysfunction. However, this field of study remains ill-defined as it has focused on sickle cell disease (SCD), where renal complications are severe. As SCT is more prevalent than SCD, consequences of nephropathies in this group translate into a substantial and largely unaddressed public health burden. Clinical data, primarily observational, implicate age and sex in the development of SCT-associated nephropathies. These manifestations span glomerular hyperfiltration, tubular damage, hematuria, renal papillary necrosis, renal medullary carcinoma, and progression to chronic kidney disease, all complications that cluster disproportionately in older male individuals. Despite this, the mechanistic basis of SCT nephropathy, the thresholds at which renal injury becomes clinically significant, and the optimal strategies for early identification and prevention remain inadequately defined. In vitro studies have primarily focused on SCD blood cell biology, with SCT receiving comparatively little attention. Humanized murine models (i.e., Berkeley and Townes) have recapitulated some SCT-associated renal phenotypes but need to be more fully characterized. This review aims to provide an overview of the biology of sickle cell trait nephropathies, the gaps in our knowledge, and the model systems we can use to fill those gaps.

Journal Article↗
PubMed2026

An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.

Population affinity estimation in forensic anthropology often involves the integration of multiple pieces of information, including visual (nonmetric) and metric data. This study examines how practitioners interpret and synthesize visual and metric information and their decision-making processes. A Qualtrics survey was developed using two cases: Case 1 presented clear nonmetric signal but ambiguous metric signal, while Case 2 showed more ambiguous nonmetric signal but clear metric signal. Practitioners were asked to estimate population affinity based on visual assessment, Fordisc data, and provide a final, integrated assessment. A total of 22 valid survey responses were received, with the majority of survey respondents reporting more than 10 years of forensic anthropology experience and holding a PhD degree. Results showed that there is substantial variability in Fordisc use and interpretation. Across both cases, participants synthesized conflicting visual and metric information, converged toward the stronger signal, and came to more consistent final estimates relative to the more ambiguous input. These findings highlight variability in practitioner decision-making but suggest that integration of nonmetric and metric information in population affinity estimation can moderate decision-making uncertainty. The results have implications for forensic anthropology education, training, and proficiency testing.

Humans↗
PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗
PubMed2025

The Association Between Child Maltreatment and Quality of Life: A Systematic Review and Meta-Analysis.

The association between child maltreatment (CM) and quality of life (QoL) has been widely examined in the past decade. In this study, we estimated the association between CM and QoL using a systematic review and meta-analysis. Articles were searched up to May 15, 2024, in both English databases (Web of Science, EMBASE, CINAHL, PsycINFO & PsycArticles, MEDLINE, Cochrane Library, PubMed, and Scopus) and Chinese databases (CNKI, Weipu, and Wanfang). The meta-analysis was performed by a random-effects model, using 43 studies comprising 130,884 participants. This study demonstrated that general CM had an adverse impact on QoL and its sub-dimensions, including physical, mental, psychosocial, and environmental QoL. Further analysis showed that the subtypes of CM also had negative impacts on the dimensions of QoL, except for mental QoL. Emotional maltreatment had stronger negative associations with QoL than other subtypes of CM, while neglect received relatively less attention. In addition, the association between CM and QoL was moderated by region, gender ratio, and measurement methods. The findings of this study suggest that CM is negatively associated with QoL. Future studies need to investigate the impact of neglect on QoL and develop tailored programs to improve the QoL of people who have suffered from CM.

Humans↗
PubMed2026

Evolutionary architecture and lineage-specific diversification of Forkhead box transcription factors in Perna viridis.

The Forkhead box (Fox) transcription factors are evolutionarily conserved regulators of development, cell cycle, and apoptosis across metazoans. This study provides the first comprehensive genome-wide analysis of the Fox gene family in the Asian green mussel (Perna viridis). We identified 28 Fox genes distributed across 10 chromosomes. Comparative analysis reveals the absence of the FoxI, FoxQ1, FoxR and FoxS subfamily, consistent with other bivalves and indicative of lineage-specific gene loss during molluscan evolution. Notably, gene duplications in the FoxAB, FoxD, FoxH, FoxN1-4, FoxQ2 and FoxQD subfamilies may reflect functional diversification associated with environmental adaptation. Exon-intron structural variability, including intron loss in several paralogues, suggests structural diversification and potential regulatory variation. Phylogenetic reconstruction confirmed the monophyly of core Fox classes while highlighting divergent expansion patterns in lophotrochozoans. Selection analyses showed strong purifying selection across duplicated Fox paralogs, supporting functional conservation after lineage-specific expansion. Gene Ontology enrichment linked Fox genes to stress response, apoptosis, and transcriptional regulation. By integrating phylogenetic, structural, and transcriptomic analyses, this study provides a genomic framework for understanding Fox gene organisation, evolution, and tissue-associated expression patterns in Perna viridis and establishes a comparative resource for future functional studies in bivalves.

Animals↗
PubMed2026

Messaging Strategies for Tobacco Prevention and Cessation Among People with Depression: A Scoping Review.

INTRODUCTION: Depression is strongly associated with higher tobacco use and lower quit rate; few communication campaigns have been designed with these mental health factors in mind. This scoping review compiles existing research on tobacco prevention and cessation messaging involving people with depression to identify gaps and opportunities for future message development. METHODS: Sources included PubMed, PsycINFO, Scopus, Academic Search Premier, and ProQuest Central (November - December 2024). The 55 studies included examined tobacco prevention or cessation messages and measured depression, depressive symptoms, or mental health as a primary outcome or analytic covariate. Study characteristics, target population, delivery format, message content, theoretical frameworks, outcomes, and gaps were extracted. RESULTS: RCTs made up half (51%) of the included studies, and most (78%) were conducted in the U.S. Nearly half (46%) required participants to have a mental health condition. Interventions most often used interactive (65.5%) or text-based (47.3%) communication and focused on tobacco cessation (89%) rather than vaping (9%). Common outcomes included feasibility or acceptability (37.7%) and point prevalence abstinence (37.7%). Mental health-specific messages showed mixed effectiveness. CONCLUSIONS: Despite progress in integrating mental health into tobacco messaging, targeted interventions for people with depression remain limited. Few studies tested long-term outcomes or used biochemical verification; many relied on untargeted generalized messaging.

Journal Article↗
PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗
PubMed2026

School-based sexual violence prevention: A systematic review.

PURPOSE: Sexual violence profoundly affects the health and development of children, adolescents, and young adults, representing a persistent challenge to public policy. This systematic review examined the effectiveness of school-based interventions aimed at prevention. METHODS: Eighteen randomized controlled trials published between 2012 and 2024 were retrieved from four major databases. The programs were implemented in primary, secondary, and higher education settings and targeted children, adolescents, and young adults. RESULTS: The results revealed improvements in knowledge and attitude, particularly regarding consent and awareness, whereas evidence supporting behavioral changes was less frequent and often limited. Methodological limitations, such as short follow-up periods and participant attrition, restricted the assessment of long-term outcomes. CONCLUSIONS: This review highlights the importance of multicomponent, participatory, and culturally sensitive approaches, along with the integration of digital tools and continuous evaluation systems, to strengthen the role of schools as safe and transformative spaces in the prevention of sexual violence. IMPLICATIONS AND CONTRIBUTIONS: This systematic review suggests that school-based interventions hold significant potential for the prevention of sexual violence. It identifies promising strategies and reinforces the importance of culturally sensitive, sustained, evidence-based approaches to ensure learning environments that are safe, protective, and promotive of gender equity.

Humans↗
PubMed2026

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

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

Acrylamide↗
PubMed2026

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↗
PubMed2026

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article↗
PubMed2026

Association of media use with sleep of children and adolescents: an umbrella review.

Adequate sleep is essential for child and adolescent development, driving extensive research across scientific disciplines. This umbrella review provides a comprehensive overview of existing evidence on media consumption and sleep and thereby lays the foundation for identifying key concepts and gaps. An inclusive systematic search for reviews reporting literature searches was conducted in 02/2021 and updated last in 09/2024. Methodological quality of the included reviews was assessed using AMSTAR-2. We included 84 reviews reporting on the association between media use and sleep in individuals aged 0-18 years. The field is dominated by reviews of low methodological quality, mainly including original cross-sectional studies with subjective measures in older children and adolescents. A total of 475 original articles were covered by the reviews; only 10 of them appeared in at least seven and at most nine reviews. Screen time generally had a negative impact on sleep, though evidence varied from very low to strong. Evidence for effects of conventional books on sleep remains inconclusive. High quality systematic reviews are needed to evaluate robust studies using objective measures of sleep and contemporary media use across all age groups up to adolescence and to explore the impact of non-digital media use on sleep, considering age and gender differences.

Humans↗
PubMed2026

Influencer-driven lifestyle and wellness framing of intoxicating hemp products may normalize youth cannabis use.

Hemp-derived intoxicating cannabis products (DICPs) have rapidly expanded across the U.S. marketplace and are increasingly promoted on social media platforms popular among youth. This commentary highlights emerging concerns about influencer-driven DICP promotion on Instagram, where intoxicating hemp and cannabis products are embedded within lifestyle, wellness, fitness, sobriety, harm-reduction, and entertainment narratives. In ongoing monitoring of Instagram posts from leading DICP brands, we observed influencer posts that featured young-looking creators, aspirational wellness imagery, humor, slang, fast-cut editing, mocktail-making scenes, and claims positioning DICPs as "hangover-free," safer, or substitutes for alcohol or other drug use. Such content may reduce perceived risk, increase product appeal, and normalize cannabis use, particularly when promotional posts resemble organic (non-promotional) peer-culture content rather than advertising. Existing platform guidelines and regulatory approaches may inadequately address this form of influencer marketing. Enforcement is more actionable when sponsorship is clearly disclosed; however, influencers often omit brand sponsorship disclosures entirely or use vague disclosures. The absence of a disclosure does not necessarily mean that a post is non-promotional. Platforms should develop policies and algorithm-assisted surveillance approaches that identify DICP influencer content using youth-oriented cues, lifestyle and wellness framing, brand tags or links, and unverified reduced-risk or therapeutic claims.

Humans↗
PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗