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Meta-analysis of source identification and apportionment in soil: A systematic review of analytical procedures, receptor modeling, and environmental applications.

Soil pollution poses significant risks to ecosystems and human health, necessitating accurate source identification and apportionment to guide mitigation strategies. This systematic review evaluates the application of Positive Matrix Factorization (PMF) and other receptor models in soil pollution studies, focusing on analytical procedures, tracer indicators, and environmental applications. This review aims to provide a comprehensive framework for conducting soil source apportionment studies, aiding policymakers in designing effective, region-specific environmental management strategies by compiling global trends and methodological insights. The study addresses sampling protocols, emphasizing representativeness and quality control. Data from 500 peer-reviewed publications highlight the dominance of research in China, Eastern Europe, and South Asia, with agricultural soils being the most frequently studied. Key findings reveal that traffic emissions (20.8 %) and industrial activities (19.4 %) are the primary global contributors to soil contamination, with regional variations such as coal combustion in cold climates and agricultural inputs in developing regions. Policy recommendations include stricter industrial regulations, sustainable agricultural practices, and targeted remediation efforts based on source-specific risks.

Soil Pollutants

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii

Self-healing materials for food packaging: Design principles, activation mechanisms and implications for food safety.

Self-healing materials (SHMs), originally developed to restore mechanical integrity, have recently attracted growing interest in food packaging. By autonomously repairing physical damage, SHMs help preserve packaging integrity, barrier performance, food safety, and shelf-life during storage and transportation. This review summarizes recent advances in the design principles, activation mechanisms, material systems and food packaging applications of SHMs. Key healing strategies, including microencapsulation, dynamic covalent bond exchange, reversible non-covalent interactions and responsiveness to external stimuli such as temperature, pH, and humidity, are discussed. Representative material systems, including biopolymer-based films, hydrogels, nanocomposites, and stimuli-responsive polymers are evaluated with respect to their relevance to packaging animal-derived foods, fruits, and vegetables. Performance evaluation methods, sustainability implications, and food-contact safety concerns are addressed. Despite promising healing efficiency and mechanical resilience, challenges remain regarding production cost, food-grade safety, migration risks, trigger compatibility and stability under fluctuating environmental conditions. Future research should focus on scalable manufacturing, standardized evaluation protocols, repeated damage-healing safety assessment, regulatory compliance, and integration with intelligent packaging technologies.

Food Packaging

Flux rewiring enables native D-glucosamine production in Escherichia coli.

D-Glucosamine is an industrially important amino sugar used in pharmaceuticals, nutraceuticals, and functional materials, yet its production remains dominated by chemical extraction from chitinous biomass, raising sustainability and allergen concerns. Escherichia coli natively synthesizes D-glucosamine directly from D-glucose through endogenous metabolism, revealing an underutilized amino sugar biosynthetic capability. Building on this native pathway, D-glucosamine production was enhanced through targeted genetic modifications and systematic optimization of nitrogen metabolism and cultivation conditions, reaching 9.2 g L-1 under shake-flask conditions. This work extends a phosphorylation-dephosphorylation strategy previously developed for neutral rare sugars to amino sugar biosynthesis, demonstrating the broader applicability of this metabolic design principle. Phosphatase identity emerged as a key control point for product formation: YbiV was the most effective phosphatase for selective D-glucosamine production, whereas alternative phosphatases redirected flux toward D-sedoheptulose. This enzyme-dependent flux partitioning further enabled tunable co-production of D-glucosamine and D-sedoheptulose. Native amino sugar biosynthesis in E. coli provides a controllable framework for producing chemically distinct sugars through endogenous metabolism and establishes a generalizable strategy for engineering amino sugar and other nitrogen-containing metabolite biosynthesis.

Escherichia coli

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants

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

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

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

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

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

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

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

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

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

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

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