Search Results (1,353)

The geochemistry of karstic paddy soils significantly influences Cd bioavailability and its accumulation by rice. However, there is limited research on Cd translocation and accumulation in rice, grown in paddy soil with elevated CaO and Zn levels. Addressing this, a field-based study in Hanyuan County, Sichuan Province, China, examined the Cd distribution and translocation patterns across the soil–root–straw–grain continuum, aiming to elucidate how elevated CaO and Zn levels regulate Cd accumulation in grains. The geochemical characterization of the soil revealed elevated concentrations of cadmium (Cd), calcium oxide (CaO), and zinc (Zn), with mean values of 2.12 ± 2.93 mg/kg, 5.77 ± 5.80 wt.%, and 359 ± 472 mg/kg, respectively. The sequential extraction results (by Tessier) demonstrated that the distribution of Cd followed the general order: residual > Fe-Mn oxide-bound ≈ exchangeable ≈ carbonate-bound > organic matter-bound. The exchangeable Cd content ranged from 0.063 to 0.93 mg/kg, accounting for up to 21.4% of the total Cd on average. The correlation analysis, Bioconcentration Factor (BCF), and Transfer Factor (TF) of Cd in different rice tissues, and structural equation modeling (SEM) revealed that elevated CaO and Zn levels in soil exhibit synergistic effects in inhibiting Cd accumulation in grains. Specifically, the CaO in soil reduces the Cd bioavailability by the formation of carbonate-bound specie (CdF2), thereby inhibiting Cd uptake by roots. In rice tissues, Zn could limit Cd translocation, particularly from roots to straws. Consequently, the regional rice Cd exceedance rate (25.8%) was significantly lower than that reported for other similar karst soils in China (over 50%). Full article

Background/Objectives: Antibody-dependent cellular cytotoxicity relies on the interaction between the Fc region of immunoglobulin G1 (IgG1) and the CD16a receptor. While removal of core fucosylation on Fc and introduction of the DFTE mutation set (S239D, H268F, S324T, I332E) are known to enhance CD16a binding, the detailed contributions of these engineered sites in solution remain incompletely defined. Methods: Here, we employed 1 µs molecular dynamics simulations to map, at atomic resolution, the interaction networks stabilizing pre-formed Fc-CD16a complexes, including afucosylated Fc-wild-type, DFTE-engineered, Fc-fucosylated, and asymmetrically engineered Fc variants. Results: Our results show that only S239D, present on both Fc chains, and H268F on chain A consistently contribute to stabilizing the CD16a interface, while I332E does not form persistent interactions. Glycan–protein contacts are primarily intrachain, with transient interchain glycan–glycan interactions not contributing significantly to complex stability. Fucosylation on Fc significantly reduces binding stability by disrupting peripheral interactions and critical glycan-mediated contacts. Notably, the asymmetric Fc variant, in which the two heavy chains carry distinct sets of substitutions, retains high-affinity binding despite lacking S239D and carrying core fucose, through a novel hydrophobic cluster and reinforced peripheral electrostatic interactions. Conclusions: Altogether, these findings provide a quantitative framework for how targeted mutations and fucose modifications remodel Fc-CD16a interactions, offering insights for the rational design of next-generation therapeutic antibodies. Full article

Background/Objectives: Extranodal NK/T-cell lymphoma, nasal type (ENKTCL-NT), is a rare and extremely aggressive subtype of non-Hodgkin lymphoma that most frequently involves the nasal cavity and upper aerodigestive tract. Primary isolated oral manifestation is exceptionally uncommon and may mimic odontogenic or infectious diseases, delaying diagnosis. We report a case of ENKTCL-NT presenting initially as a destructive oral lesion without sinonasal involvement at diagnosis. Methods: A 32-year-old man with progressive palatal ulceration underwent clinical and imaging assessment (panoramic radiography and staging ^18F-FDG PET–CT) and repeated biopsies. Diagnosis was established using histopathology (H&E), immunohistochemistry (T-cell markers and cytotoxic profile), EBV detection by EBER in situ hybridization, and T-cell receptor gamma (TCRG) gene rearrangement analysis. Results: The lesion presented as a hemorrhagic, ulcerative palatal destruction covered by pseudomembranous exudate and was complicated by fungal infection, periostitis, and severe dental inflammatory foci, contributing to diagnostic delay. Histopathological examination revealed extensive necrosis with a dense atypical lymphoid infiltrate; angiocentric and angiodestructive growth was identified in one biopsy specimen. Tumor cells expressed T-cell markers (CD2, CD3, CD5, CD7; heterogeneous) and cytotoxic markers (TIA-1) and showed CD30 and CD56 positivity, with EBV positivity confirmed by EBER in situ hybridization. Molecular analysis demonstrated monoclonal TCRG rearrangement, and Ki-67 indicated high proliferative activity. Initial PET–CT demonstrated an intensely FDG-avid, locally invasive lesion without distant organ involvement. The patient was treated with L-asparaginase-based SMILE chemotherapy followed by radiotherapy (50 Gy), achieving marked initial clinical improvement and partial metabolic response; however, systemic relapse subsequently occurred with refractory disease despite salvage therapy and immunotherapy. Conclusions: This case highlights the substantial diagnostic challenge posed by isolated oral extranodal NK/T-cell lymphoma, nasal type, which may closely mimic benign inflammatory or infectious conditions and lead to significant diagnostic delay. Persistent, progressive, or therapy-resistant oral ulcerations should prompt early consideration of hematologic malignancy. Timely biopsy with comprehensive immunophenotyping, EBV testing, and close multidisciplinary collaboration are essential for accurate diagnosis and may contribute to earlier diagnosis and improved patient outcomes in these rare and atypical presentations. Full article

Change detection in remote sensing imagery is crucial for monitoring temporal variations in surface characteristics; nevertheless, it presents significant challenges owing to indistinct boundaries, limited semantic differentiation, and inadequate incorporation of multi-scale contextual information. To solve these problems, we propose EIMDGNet (Edge-Induced and Multi-Dimensional Grouped Difference Network), a novel architecture that enhances boundary representation and cross-scale feature interaction for accurate and robust change detection. EIMDGNet adopts a dual-branch ResNet18 backbone to extract multi-scale features from bi-temporal images, capturing both fine spatial detail and high-level semantic context. To improve boundary awareness and reduce pseudo-change interference, we introduce the Edge-Induced Differential Multi-Dimensional Group Enhancement Module (EID-MDGEM). This module enriches fine-grained spatial features through grouped pooling across spatial and channel dimensions, enabling precise localization of change contours. Within EID-MDGEM, the Edge Feature Enhancement Module (EFEM) integrates a parameter-free attention mechanism to generate edge-saliency maps, highlighting true change regions while suppressing background noise and irrelevant variations. To further enhance semantic consistency across feature scales, we design the Multi-Scale Hierarchical Progressive Fusion Module (MSHPM). This component employs a bottom-up progressive strategy to hierarchically integrate low-level spatial details with high-level semantic abstractions, thus increasing the continuity and completeness of detected change regions. By tightly coupling edge-aware enhancement with multi-scale hierarchical fusion, EIMDGNet effectively addresses major obstacles in change detection, including boundary ambiguity, inconsistent scale information, and feature misalignment. We evaluated EIMDGNet on five remote sensing change detection datasets: LEVIR-CD, DSIFN-CD, S2Looking, CLCD-CD and GVLM-CD. Our method consistently outperformed state-of-the-art approaches, achieving 91.49% F1 and 82.93% IoU on LEVIR-CD, 77.32% F1 and 69.39% IoU on DSIFN-CD, the highest 49.19% IoU and 99.20% OA on S2Looking, 81.65% F1 and 72.91% IoU on CLCD-CD, and 85.49% F1 and 76.08% IoU on GVLM-CD. These results demonstrate the superior accuracy and robustness of EIMDGNet across diverse change detection scenarios. Full article

Background/Objectives: Meals eaten at movie theaters may have acute, negative health effects due to high refined sugar and moderate sodium content. We aimed to characterize the cardiometabolic response to movie-theater-style meals independently (fasting) and after high-fat meal consumption. Methods: Participants (N = 10; 5M/5F; 18–45 y) completed two meal trials (randomized). At both trials, participants ate a movie-theater-style meal (popcorn, candy, and soda; 884 kcal, 150 g sugar, and 700 mg sodium). At one trial, the movie theater meal was consumed while fasting (Fasting Trial). At the other trial, a high-fat meal (820 kcal; 56 g fat) was consumed 3.5 h prior to the movie theater meal (Fed Trial). Blood was collected (0, 0.5, 1, 2, 3, and 4 h) and endothelial function (i.e., flow-mediated dilation or FMD) was assessed (0, 2, and 4 h) at both trials. Serum metabolic markers (glucose, insulin, triglycerides, and HDL-C) and biomarkers of intestinal permeability (sCD14 and LBP) were measured. Mixed-model ANOVAs (meal × time) and change scores (Δ) were used to compare responses between trials. Results: At both trials, glucose, insulin, and triglycerides increased, while HDL-C decreased (p_time’s ≤ 0.05). ΔInsulin (p = 0.02), but not Δglucose, was higher at Fasting versus Fed. Peak glucose (range = 86–178 mg/dL) and insulin (range = 28.3–307.6 mU/L) were highly variable between participants across trials. Absolute and percent FMD tended to decrease, regardless of trial (p_time’s ≥ 0.08). Conclusions: Overall, the movie theater meal impacted a number of cardiometabolic factors when consumed independently and after a high-fat meal, although there was notable inter-individual variability. Full article

Milk is a primary source of vital nutrients and bioactive components fundamental to the growth and development of both newborn animals and humans. Produced by economically significant livestock species (including cattle, buffaloes, goats, sheep and camels), milk is a complex matrix rich in caseins, vitamins, fats, and proteins. Beyond its classical nutritional profile, milk serves as a pivotal vehicle for milk-derived extracellular vesicles (mEVs). These specialized food-derived EVs (fEVs) exert pleiotropic effects that resonate with the One Health paradigm, linking animal well-being and human nutrition to broader ecosystem stability. mEVs offer unique advantages, such as high biocompatibility and gastrointestinal stability, also rendering them potential therapeutic tools as drug delivery systems. However, challenges remain regarding the standardization of mEVs and the variability of their molecular cargo. This review provides a comprehensive comparative analysis of mEVs across a diverse taxonomic range, including bovines, water buffaloes, yaks, camels, goats, pigs, horses, donkeys, and humans, highlighting their distinct functional signatures. Indeed, a critical issue in mEV research is the isolation process: recommendations to minimize contamination from milk fat globules and casein micelles (which can cover EV signals) are given. Finally, current detection methods and instrumentation, with a specific focus on advancing flow cytometry (FC) approaches are discussed. Key insights include the use of conventional FC (with fluorescence triggering, the necessity of rigorous controls and calibration, and the utility of bead-based assays to overcome resolution limits) and imaging flow cytometry (IFC). In both technical approaches, the application of different EV generic fluorescent markers and the strategic selection of tetraspanins (i.e., CD9, CD63, CD81), is mandatory: we emphasize that selecting the correct antibody clones and accounting for inter-species cross-reactivity are essential steps for ensuring the accuracy and reproducibility of mEV research across mammalian species. Full article

This study aims to establish an origin identification method for Scutellariae radix that integrates multidimensional quality indicators and machine learning algorithms, enabling accurate and rapid traceability of Scutellariae radix medicinal materials from four production areas: Hebei (HB), Shanxi (SX), Shaanxi (SAX), and Chengde (CD). The study collected a total of 43 batches of Scutellariae radix samples from the aforementioned origins. It systematically measured 12 key quality indicators covering flavonoids, physicochemical parameters, chromaticity values, and biological activity. These specifically include four flavonoid components: baicalin, wogonoside, baicalein, and wogonin; three physicochemical parameters: moisture content, ash content, and alcohol-soluble extract; four chromaticity values: L*, a*, b*, and ΔE; and in vitro anti-inflammatory activity (IC₅₀ value for NO clearance). On the basis of these parameters, in this study there were five machine learning models constructed based on the following algorithms and methods: Random Forest (RF), Extreme Learning Machine (ELM), Backpropagation Neural Network (BP), and Radial Basis Function Neural Network (RBF). A comparative analysis was conducted to evaluate the origin identification performance of each model. The results indicate significant differences (p < 0.05) in the contents of baicalin, wogonoside, L*, a*, b*, ΔE, and alcohol-soluble extract among Scutellariae radix from different origins. The comparative analysis of four machine learning models reveals that RF outperforms ELM, BP, and RBF in multiclass classification, achieving a test accuracy of 75% and consistent precision, recall, and F1-score of 79.17%. In contrast, the three neural networks attain only 66.67% test accuracy, with RBF showing high precision but low recall, ELM delivering moderate performance, and BP performing poorly. These results underscore the strength of ensemble methods like RF in small-sample settings, where they mitigate overfitting and enhance generalization, whereas neural networks struggle with limited data. We therefore recommend RF for deployment under current data constraints and suggest future work should focus on data expansion, especially for under-performing classes, along with hyperparameter tuning to further improve classification. Full article

Background: Family caregivers of intensive care unit (ICU) patients face a double burden: the psychological toll of critical illness and the economic and occupational disruptions that often accompany prolonged caregiving. While prior research has examined caregiver distress, few studies have systematically integrated economic, psychological and spiritual domains over long-term follow-up. Methods: This study presents a cross-sectional analysis conducted at long-term follow-up examining economic, occupational, psychological, and spiritual correlates among family caregivers of former ICU patients. From an initial cohort of 189 caregivers, 92 participated in a five-year follow-up, completing validated psychometric instruments (SCL-90-R, SpREUK, CD-RISC-10, Heartland Forgiveness, F-COPES). Multivariate regression models were used to identify predictors of psychological and spiritual outcomes, while cluster analysis explored heterogeneity in caregiver profiles. Results: Job loss emerged as a strong predictor of anxiety and hostility, while reduced working hours showed a protective association against depression and anxiety. Financial burden was less consistently associated with psychopathology. Spirituality demonstrated an ambivalent pattern of correlational associations: while dimensions such as trust and reflection were linked to adaptive coping, higher levels of spiritual engagement were also associated with elevated depressive symptoms, suggesting a reactive rather than purely protective role. Resilience and coping resources (e.g., reframing, forgiveness, personal competence) mitigated distress, whereas neuroticism amplified vulnerability. Cluster analysis revealed three distinct caregiver subgroups: a high-burden cluster (severe psychopathology and economic strain), a moderate cluster with mixed spiritual and psychological engagement and a resilient cluster with minimal burden. Conclusions: This study highlights that economic stressors are not peripheral but central drivers of caregiver distress and that spirituality, although valued, may operate in both adaptive and maladaptive ways. Tailored interventions must integrate financial protection, psychological support and sensitive spiritual care to address the multidimensional reality of ICU caregiving. Full article

Background and Aim: Sarcopenia is increasingly recognized as a clinically significant complication of inflammatory bowel disease (IBD), influencing both medical management and surgical outcomes. Accurate and accessible diagnostic tools are essential for assessing muscle mass and function in this population. The iliopsoas (IP) muscle has traditionally been used as a marker of sarcopenia, but its deep anatomical location requires skilled operators. Conversely, the diaphragm (DM), being more superficial, may serve as a more feasible surrogate. This study aimed to assess the correlation between IP- and DM-derived ultrasound indices in patients with IBD and to explore their association with sarcopenia risk. Methods: This prospective single-center study enrolled 353 IBD patients (Crohn’s disease [CD] and ulcerative colitis [UC]). Overall, 57 patients had a SARC-F score ≥ 4 and underwent intestinal ultrasound (US). The transverse diameter of the right IP muscle was measured in triplicate, and the psoas-to-height ratio (PMTH, mm/m) was calculated. Diaphragm thickness was assessed during inspiration and expiration, and the diaphragm-to-height ratio was derived. Pearson correlation, Bland–Altman analysis and multivariable regression (adjusted for age and sex) were performed to test associations. Results: The mean IP diameter was 28.40 mm (28.82 mm in males, 27.02 mm in females), with a mean PMTH of 16.62 mm/m. Diaphragm thickness was 20.4 ± 5.0 mm at inspiration and 10.7 ± 3.5 mm at expiration, yielding a mean difference of 9.7 ± 3.4 mm. The diaphragm-to-height ratio was 0.59 ± 0.21 mm/m. Pearson correlation revealed a moderate positive association between PMTH and the diaphragm index (r = 0.3568, p < 0.05). Bland–Altman analysis disclosed a symmetrical distribution. Multivariable regression confirmed that the diaphragm index increased linearly with PMTH (β = 0.018, 95% CI 0.005–0.030; p = 0.008). Neither age nor sex significantly affected the results. Conclusions: Muscle ultrasound is a reliable and reproducible method for evaluating sarcopenia in IBD. The diaphragm, due to its superficial anatomical location and ease of measurement, shows a significant correlation with psoas muscle parameters and may serve as a practical surrogate marker in clinical practice. Larger multicenter studies are warranted to validate these findings. Full article

Semiconductor defect inspection is frequently hindered by data scarcity and the resulting class imbalance in supervised learning. This study proposes a CycleGAN-based data augmentation pipeline designed to synthesize realistic defective CD-SEM images from abundant normal patterns, incorporating a quantitative quality control mechanism. Using an ADI CD-SEM dataset, we conducted a sensitivity analysis by cropping original 1024 × 1024 micrographs into 512 × 512 and 256 × 256 inputs. Our results indicate that increasing the effective defect-area ratio is critical for improving generative stability and defect visibility. To ensure data integrity, we applied a screening protocol based on the Structural Similarity Index (SSIM) and a median absolute deviation noise metric to exclude low-fidelity outputs. When integrated into the training of XceptionNet classifiers, this filtered augmentation strategy yielded substantial performance gains on a held-out test set, specifically improving the Recall and F1 score while maintaining a near-ceiling AUC. These results demonstrate that controlled CycleGAN augmentation, coupled with objective quality filtering, effectively mitigates class imbalance constraints and significantly enhances the robustness of automated defect detection. Full article

Background: n-3 PUFA derived from marine sources, including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), exhibit potential for breast cancer prevention. In contrast, higher dietary intakes of n-6 PUFA, such as linoleic acid (LA), have been implicated in promoting mammary tumourigenesis. However, there is a need for further exploration into how n-3 PUFA influence breast cancer development in comparison to different amounts and sources of LA. Objective: The purpose of this study was to compare the effects of n-3 PUFA-enriched diets versus n-6 PUFA diets differing in LA content, including corn oil (50% LA) and safflower oil (70% LA), on mammary tumour development in a HER2+ breast cancer model. Methods: Using the HER2+ breast cancer MMTV-neu(ndl)YD5 transgenic mouse model, this study determined the effects of: (1) 10% w/w corn oil (CO, n-6 PUFA, n = 14), (2) 10% w/w safflower oil (SO, n-6 PUFA, n = 14), (3) 3% w/w menhaden oil + 7% w/w CO (3% FO 7% CO, n-3 PUFA, n = 12), and (4) 3% w/w menhaden oil + 7% w/w SO (3% FO 7% SO, n-3 PUFA, n = 14) on puberty onset, tumour incidence, tumour volume, and tumour number in utero until 20 weeks of age. Results: Mice fed the n-3 PUFA-enriched diets showed a lower trajectory of tumour development compared to the n-6 PUFA diets, although the differences for palpated tumour volume and number over time reached significance only between the 10% CO and 3% FO 7% CO groups. This suggests that high LA content in CO may represent a threshold for promoting tumour growth whereby further LA content marginally influences additional tumour development. Exposure to the CO n-6 PUFA diet further resulted in earlier onset of puberty compared to the n-3 PUFA-enriched diet containing CO. To investigate the underlying mechanisms, a qPCR analysis of mammary glands and tumour tissue revealed that the n-3 PUFA diets downregulated the expression of pro-tumourigenic immune markers, including CD206 and F4/80 in the mammary glands and the cannabinoid receptor CB2 in tumours, compared to the n-6 PUFA diets. Conclusions: These findings indicate that the presence of dietary n-3 PUFA plays a key role in modulating mammary tumour development, which may be further influenced by the underlying n-6 PUFA background. The associated changes in immune markers suggest that n-3 PUFA exert anticancer effects in part by shifting the tumour immune microenvironment toward an anti-tumour phenotype and modulating cannabinoid receptor signalling. Collectively, this work informs future human studies investigating the role of dietary fat composition in breast cancer risk. Full article

Detecting minute defects, such as spurs on the surface of a Printed Circuit Board (PCB), is extremely challenging due to their small size (average size < 20 pixels), sparse features, and high dependence on circuit topology context. The original Mosaic data augmentation method faces significant challenges with semantic adaptability when dealing with such tasks. Its unrestricted random cropping mechanism easily disrupts the topological structure of minute defects attached to the circuits, leading to the loss of key features. Moreover, a splicing strategy without domain constraints struggles to simulate real texture interference in industrial settings, making it difficult for the model to adapt to the complex and variable industrial inspection environment. To address these issues, this paper proposes a Context-aware and Domain-consistent Mosaic (CD-Mosaic) augmentation algorithm. This algorithm abandons pure randomness and constructs an adaptive augmentation framework that synergizes feature fidelity, geometric generalization, and texture perturbation. Geometrically, an intelligent sampling and dynamic integrity verification mechanism, driven by “utilization-centrality”, is designed to establish a controlled sample quality distribution. This prioritizes the preservation of the topological semantics of dominant samples to guide feature convergence. Meanwhile, an appropriate number of edge-truncated samples are strategically retained as geometric hard examples to enhance the model’s robustness against local occlusion. For texture, a dual-granularity visual perturbation strategy is proposed. Using a homologous texture library, a hard mask is generated in the background area to simulate foreign object interference, and a local transparency soft mask is applied in the defect area to simulate low signal-to-noise ratio imaging. This strategy synthesizes visual hard examples while maintaining photometric consistency. Experiments on an industrial-grade PCB dataset containing 2331 images demonstrate that the YOLOv11m model equipped with CD-Mosaic achieves a significant performance improvement. Compared with the native Mosaic baseline, the core metrics mAP@0.5 and Recall reach 0.923 and 86.1%, respectively, with a net increase of 8.3% and 8.8%; mAP@0.5:0.95 and AP_small, which characterize high-precision localization and small target detection capabilities, are improved to 0.529 (+3.0%) and 0.534 (+3.3%), respectively; the comprehensive metric F1-score jumps to 0.903 (+6.2%). The experiments prove that this method effectively solves the problem of missed detections of industrial minute defects by balancing sample quality and detection difficulty. Moreover, the inference speed of 84.9 FPS fully meets the requirements of industrial real-time detection. Full article

Aiming at the differences in spatial spectral attributes between forested land and cultivated land on remote sensing images, and the deficiencies of existing remote sensing change detection methods that are difficult to capture fine edge structures and distinguish pseudo changes, this paper introduces an Edge Enhanced Hierarchical Dual Gated Change Detection (EHDCD) model for forested land and cultivated land, aiming to meet the demand for representing the complex features of these two land types. The model designs an Edge Enhanced Channel Attention Module (EECA) to strengthen the edge recognition ability and suppress the noise interference; proposes a High-Low Level Dynamic Adaptation Strategy (HiLo) to realize the balanced expression of detail information and semantic features; and constructs a Dual Gated Feature Compensation Module (DGFM) to effectively reduce the misdetection rate of change detection. Experiments show that the F1 scores of the model on the self-constructed forest and agricultural dataset FC-CD and public datasets CLCD and SYSU-CD reach 89.06%, 83.37%, and 85.06%, respectively, which can more accurately support the dynamic monitoring applications of forest land and cropland. Full article

Thermoregulatory dysfunction is a major pathophysiological consequence of aging, affecting many elderly individuals. Growth hormone secretagogue receptor (GHSR) regulates energy homeostasis and immune function. We previously showed that global GHSR deletion improves thermogenic adaptation of brown adipose tissue (BAT) in aging, but the responsible cell type remained unclear. GHSR is expressed in macrophages, and its expression in macrophages increases with aging. Here, we studied myeloid-specific Ghsr-deleted male mice (LysM-Cre; Ghsr^f/f denoted as “KO”) to assess their metabolic and immune responses to cold stress at young and old ages. Old mice showed impaired thermogenesis, marked by reduced core body temperature under 4 °C cold exposure, a blunted cold-induced increase in glucose levels, reduced BAT mass, and increased infiltration of pro-inflammatory CD38⁺ macrophages in BAT. In contrast, KO mice exhibited enhanced cold tolerance in both young and old mice. Notably, aged KO mice showed preserved BAT mass and a pronounced shift in resident macrophages toward an anti-inflammatory state. Consistently, aged KO mice showed reduced pro-inflammatory markers (Ccl2, Nos2) and increased expression of the thermogenic gene Ppargc1a and UCP1 protein under cold exposure. Together, these findings demonstrate that macrophage GHSR drives age-associated pro-inflammatory remodeling of BAT, and that its deletion promotes an immune environment favorable for thermogenic activation. Thus, targeting macrophage GHSR may offer a new therapeutic strategy to restore thermogenesis and enhance thermal resilience in aging. Full article

Potentially toxic element (PTE) contamination in topsoil poses non-negligible risks to both the ecological environment and public safety. This study integrated multiple methods to conduct geochemical analyses and assess the presence of PTEs in topsoils of an urban area. The findings show that the average concentrations of PTEs were as follows: 8.21 mg/kg for As, 0.23 mg/kg for Cd, 92.26 mg/kg for Cr, 0.22 mg/kg for Hg, 35.99 mg/kg for Pb, 37.83 mg/kg for Cu, 42.85 mg/kg for Ni, and 111.99 mg/kg for Zn. Zn exhibited the highest mean concentration among PTEs in the topsoil, followed by Cr and Ni, while all PTEs exceeded their background levels. Utilizing the positive matrix factorization (PMF) model, four distinct sources of PTEs were quantitatively determined: F1, representing industrial emissions, had the highest contribution rate (30.73%) and mainly provided Cr and Ni; F2, representing agricultural activities, ranked second with a contribution rate of 23.31%. The Nemerow geo-accumulation index (NI) varied between 0.26 and 2.07 (mean = 0.73), with over 88% of the samples classified as slightly polluted; the potential ecological risk index (PERI) was in the range of 119.98–511.07 (mean = 158.95), with more than 95% classified within the low-to-moderate ecological risk range; and the soil environmental capacity index (PI) ranged from 0.47 to 1.40, with an average value of 1.0. These results suggest that the pollution level of and potential ecological risk posed by PTEs are low overall, reflecting a robust soil carrying capacity and minimal adverse effects on the ecosystem. In addition, the hazards of PTEs to public health were quantified based on the human health risk assessment framework. The potential health risks posed by PTEs fell into the acceptable range for both children and adults. Notably, elevated risk values were predominantly observed in the southern portion of the study area, with arsenic (As) being the principal contributor. Full article