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Ecological momentary assessment studies on food craving among healthy adults: A systematic review.

Ecological Momentary Assessment (EMA) can capture the dynamic nature of food craving in free-living conditions, addressing limitations of laboratory and retrospective reporting methods. This systematic review synthesized findings from EMA studies to characterize 1) methodological features, 2) the temporal dynamics of food craving, and 3) the relationship between craving and eating behaviors. A systematic search of PubMed and PsycINFO databases was conducted following PRISMA guidelines. The review included 23 studies that utilized EMA designs to assess food craving repeatedly in daily life among healthy adults. Most studies employed EMA protocols that prompted participants to respond at pre-specified time points and utilized single-item craving measures. Most craving measures (71%) lacked specificity regarding the type of food craved. Results revealed a consistent positive within-person association between hunger and food craving. Conversely, associations between stress/negative affect and craving were inconsistent, varying by individual traits and context. Momentary food craving appeared to predict subsequent eating outcomes. Evidence suggested food craving may be a dynamic, transient state that co-fluctuates with hunger, functioning as a proximal antecedent to food intake. However, reliance on non-specific food craving measures and EMA protocols prompting at fixed schedules limits the granular understanding of craving mechanisms. Future research requires refining food craving measurement and incorporating randomized prompting within predefined windows, or participant-initiated sampling triggered by specific events (e.g., eating occasion), to better characterize food craving dynamics in relation to eating behaviors.

Humans

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans

Integrative analysis of transcriptome and DNA methylome dynamics during caudal fin regeneration in silver pomfret (Pampus argenteus).

Caudal fin regeneration in teleost fish is a complex, multi-stage process involving coordinated molecular and cellular changes. While the role of epigenetic regulation particularly DNA methylation has been studied in model freshwater species such as zebrafish, its contribution to regeneration in marine teleosts remains largely unexplored. In this study, we integrated transcriptomic and DNA methylomic data to characterize the temporal dynamics of gene expression and methylation during caudal fin regeneration in the silver pomfret (Pampus argenteus). Using RNA-sequencing and reduced representation bisulfite sequencing (RRBS) at three biologically critical time points 1, 3, and 7 days post-amputation (dpa), we characterized the spatiotemporal molecular landscape of caudal fin regeneration. These time points capture the key transitional phases of wound healing and inflammation (1 dpa), blastema formation and progenitor proliferation (3 dpa), and regenerative outgrowth with tissue remodeling (7 dpa), enabling robust detection of the major molecular programs underlying epimorphic regeneration. Concurrently, CG-methylome analysis identified thousands of dynamically changing differentially methylated regions (DMRs). A strong global inverse correlation was observed between promoter methylation and gene expression. Integrative analysis pinpointed key regeneration genes (fgf20a, msxb, sox9b) whose expression was associated with dynamic methylation changes in their promoters or gene bodies. We conclude that DNA methylation is a dynamic and key regulatory layer that acts in concert with transcriptional reprogramming to coordinate tissue regeneration, providing new insights into the epigenetic mechanisms underlying complex regenerative processes in teleosts.

Animals

An RPA-assisted homogeneous electrochemical DNA sensor for on-site eDNA detection toward early warning of crown-of-thorns starfish outbreaks.

Crown-of-thorns starfish (COTS) outbreaks seriously threaten coral reef ecosystems, while conventional monitoring approaches are time-consuming and often lack sufficient sensitivity for early warning. Existing electrochemical DNA sensors usually require complex electrode-surface immobilization procedures, which can lead to uneven probe distribution, significant steric hindrance, and poor stability. Meanwhile, the low concentration of environmental DNA (eDNA) in marine environments further complicates detection. To overcome these challenges, this study developed a homogeneous electrochemical DNA sensor assisted by recombinase polymerase amplification (RPA) for COTS eDNA detection. Target DNA was first amplified by RPA, and the amplification products were then hybridized in solution with capture probe (CP)-modified magnetic beads (MB) and biotin-labeled signal probe (SP) to form sandwich-structured MB complexes. These complexes were subsequently magnetically enriched and immobilized on the electrode surface for electrochemical signal readout. Under optimized conditions, the sensor displayed a linear response to COTS genomic DNA from 3.77 fg/μL to 1 ng/μL, with an LOD of 2.02 fg/μL and an LOQ of 3.77 fg/μL. The sensor was applied to Xisha Islands samples, and the results agreed with droplet digital PCR (ddPCR) (P > 0.05), demonstrating its potential for sensitive and reliable on-site COTS eDNA detection.

Animals

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

Sex- and development-specific transcriptomic profiling of venom and silk genes in the wolf spider Pardosa astrigera provides insights into ecological adaptation and predatory strategies.

Spider venom and silk glands are two major secretory systems that contribute to prey capture, defense, and reproduction, but their sex- and development-specific molecular regulation in wandering wolf spiders remains poorly understood. Here, the transcriptome of Pardosa astrigera, an important agricultural natural enemy in China, revealed significant sex- and development-associated molecular differentiation among adult females, adult males, and spiderlings. A total of 100,025 unigenes were obtained, of which 23,852 were functionally annotated, providing a comprehensive transcriptomic resource for this species. Differential expression patterns showed marked variation among groups, with 531, 1792, and 832 DEGs detected in PAF vs PAS, PAM vs PAS, and PAF vs PAM, respectively. These genes were mainly associated with metabolic, oxidation-reduction, cuticle development, MAPK signaling, and lysosome pathways. Fifteen co-expression modules revealed distinct expression patterns. The turquoise, pink, yellow, and red modules were development-related, whereas the blue module was male-biased. Venom- and spidroin-related genes were distributed across multiple modules, suggesting coordinated regulation. Overall, 42 venom peptides, 21 venom proteins, and 11 spidroins were identified. Representative genes showed strongly biased expression, including spiderling-biased U3_Pp1a and U5_Pp1e, female-biased U4_Pp1a, and male-biased SMase D_108750 and PaTuSp_108466. These findings reveal sex- and development-biased expression patterns of venom- and silk-related candidate genes in P. astrigera and may provide molecular insights into ecological adaptation and predatory strategies in wandering wolf spiders.

Animals

Clonal haematopoiesis of indeterminate potential and epigenetic age acceleration: Systematic review and meta-analysis.

Clonal haematopoiesis of indeterminate potential (CHIP) represents somatic mutations in haematopoietic stem cells that drive clonal expansion. Epigenetic age acceleration (EAA), estimated from DNA methylation (DNAm) clocks, may capture age-related changes in haematopoiesis. This systematic review and meta-analysis was conducted to synthesise evidence on associations between CHIP and EAA and explore shared biological mechanisms that may underlie this relationship. Six databases were searched from January 1, 2011, to June 6, 2025, adhering to PRISMA 2020. Random-effects meta-analyses were performed. Five studies comprising 7483 individuals (ages 55-79, 67.1% female) assessing associations between CHIP and DNAm clocks were included. Across studies, CHIP individuals had higher EAA than no-CHIP individuals, and larger clones were associated with higher EAA. Meta-analysis of three cross-sectional studies (n = 6946) showed that CHIP had higher EAA versus no-CHIP for Horvath1Age IEAA (mean difference, MD=2.84 years, 95% confidence interval, CI: 1.49-4.19), HannumAge EEAA (MD=2.31 years, 95% CI: 1.14-3.49), PhenoAge (MD=1.84 years, 95% CI: 0.96-2.71), and GrimAge (MD=1.20 years, 95% CI: 0.80-1.61). Both DNMT3A- and TET2-mutated CHIP were associated with higher EAA with TET2-mutated CHIP showing larger effect sizes and more consistent associations than DNMT3A-mutated CHIP across DNAm clocks tested. Higher EAA may also act as an effect modifier for morbidity and mortality in CHIP. Larger longitudinal studies are needed to verify a temporal relationship and determine whether EAA provides incremental prognostic value for morbidity and mortality in CHIP.

Humans

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny

Integrated photoelectrocatalytic reduction and oxidation processes to achieve efficient degradation of fluoxetine in pharmaceutical wastewater.

Fluorinated organic compounds have been frequently detected in aquatic environments, with the widespread use of fluorinated drugs. The existing processes of urban sewage treatment plants are difficult to completely remove these pollutants containing the persistent C-F bonds. In this work, an integrated system of UV-activated sulfite and UV-assisted electrochemical oxidation was innovatively constructed for efficient degradation of fluoxetine. For the UV-activated sulfite unit system, when the sulfite dosage was 0.5 mmol/L and the initial pH was about 10, the defluorination efficiency of 5 mg/L fluoxetine wastewater under nitrogen atmosphere was about 98 %. Subsequently, the UV-assisted electrochemical oxidation unit system was employed to treat the reduced wastewater mentioned above. When the sodium chloride dosage was 25 mmol/L, the initial pH was about 5, and the current density was 30 mA/cm2, the total organic carbon (TOC) removal of the wastewater arrived at 65 %. Active species capture experiments and ESR tests confirmed that hydrated electrons, hydroxyl, and chlorine radicals were the main components for the efficient degradation of fluoxetine. According to the analysis of Fukui function and HPLC-MS, the degradation pathway of pollutants was proposed including defluorination and mineralization. Meanwhile, the toxicity of intermediates was predicted using the ECOSAR program. In addition, the verification test of actual wastewater treatment indicated that the defluorination and TOC removal efficiency of fluorouracil by the integrated system were similar to those for fluoxetine. This work provided a new approach for the efficient degradation of fluorinated organic pollutants in pharmaceutical wastewater.

Fluoxetine

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques

Measuring Coping Strategies in Daily Life: A Systematic Review of Experience Sampling Methodology and Daily Diary Studies.

Advances in daily diary methods and experience sampling method (ESM) have improved the study of coping strategies in daily life and their role in shaping health and well-being. In this review, we examine study designs, measurement approaches, and analytical practices used to investigate coping in natural contexts. We performed a systematic review of studies published before 5 December 2025 that used daily diary or ESM to measure coping strategies over multiple days or moments. Studies were examined with regard to sampling schemes, assessment frequency and duration, measurement of coping strategies, incorporation of stressor appraisals, and analytic techniques used to model coping processes. Fifty-five studies met the inclusion criteria. Results indicated that 80% employed end-of-day diary designs, generally lasting 1-3 weeks, whereas higher-frequency ESM protocols were less common and ranged 2-14 days. Coping strategies were often assessed using abbreviated or single-item measures, frequently adapted from established questionnaires. Many studies incorporated appraisals such as perceived stressor intensity or controllability, enabling tests of coping flexibility. Multilevel modelling was the dominant analytic approach, allowing researchers to distinguish within-person dynamics from between-person differences. However, analyses were predominantly concurrent, and temporally ordered models remained comparatively rare. Overall, the literature demonstrates substantial progress in capturing coping in everyday contexts, yet heterogeneity in measurement and limited use of temporal modelling constrain cumulative knowledge about the temporal links between coping and psychological and physiological health outcomes. Future research would benefit from greater alignment between theoretical assumptions, assessment strategies, and analytic methods.

Humans

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic

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&#xa0;<&#xa0;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 (&#x394;Neff), landscape geometry (&#x394;Evar and &#x394;Gmag), and dominant low-energy attractor organization (&#x394;Low mass and &#x394;Low area) showed significant monotonic trends (p&#xa0;<&#xa0;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|&#xa0;=&#xa0;0.353-0.423, p&#xa0;=&#xa0;0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r|&#xa0;=&#xa0;0.333-0.455, p&#xa0;=&#xa0;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

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5&#x200b; concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

Humans