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Particulate air pollution and transportation noise frequently co-occur, but their combined molecular effects are poorly defined. We used data-independent acquisition (DIA) LC-MS/MS proteomics to profile lung, brain, and heart from male C57BL/6J mice exposed for 3 days to NIST SRM 1648a urban particulate matter (PM), aircraft noise (NOISE), PM + NOISE, or control conditions. The exposure model is the acute co-exposure paradigm previously characterized with orthogonal functional, redox, and inflammatory endpoints by Kuntic et al. The lung was the dominant responsive organ. PM + NOISE produced the broadest pulmonary response and the strongest induction of immune and macrophage-associated proteins, including acute-phase, particle-handling, interferon-linked, and phagosome-associated markers. This immune signal was accompanied by NADPH oxidase and iron-handling components, altered epithelial barrier markers, and endothelial and extracellular-matrix perturbation. The principal pulmonary modules agreed with orthogonal endpoints previously measured in the parent exposure experiment, including pulmonary NOX-2 and HO-1 protein, in situ reactive oxygen species formation, Cd68 and Mcp-1 transcripts, circulating cytokines, increased systolic blood pressure, impaired endothelium-dependent relaxation of the aorta, and cerebral and retinal arteriolar microvascular dysfunction. Brain and heart responses were lower in amplitude and involved selective redox, neuronal, contractile, metabolic and matrix-associated programs. Observed-versus-expected analyses showed that most stress-responsive proteins scaled proportionally, whereas a smaller set enriched for ribosome, RNA-processing, and chromatin functions was constrained. Integration with transcriptomic data showed strong mRNA-protein concordance in lung and greater transcript-protein divergence in brain and heart. Acute co-exposure therefore increases early pulmonary immune-redox burden without uniform additive escalation across molecular systems.

The antibiotics used in veterinary medicine accumulate in agricultural soils, where their persistence selects for antibiotic-resistance genes (ARGs). Soil fungi possess diverse metabolic enzyme systems and substantial potential for antibiotic biodegradation, but how temperature shapes fungal community succession and the functional pathways involved in antibiotic removal remains poorly understood. Herein, soils with histories of no fertilizer and organic fertilizer application (UF and OF, respectively) were spiked with 21 tetracyclines, quinolones and sulfonamides at approximately 2 mg kg^-1 per compound and incubated for 18 months at natural (NT; monthly mean of approximately 15 °C, ranging from -5.6 °C to 28.1 °C), constant (CT, 20 °C), and low (LT, 4 °C) temperatures. Dissipation kinetics were combined with fungal community and metagenomic profiling, co-occurrence networks, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-residual correlations. Dissipation was slower in OF (total-antibiotic half-life [DT₅₀] of 22-58 d) than in UF (DT₅₀ of 18-44 d). Temperature exerted a stronger effect, with dissipation fastest at NT (DT₅₀ of 18-22 d) and slowest at LT (DT₅₀ of 44-58 d); ARGs followed the same trend, declining less than the parent compounds and least of all at LT. Temperature restructured the fungal community (PERMANOVA, P ≤ 0.018), chiefly by replacing taxa rather than by nested loss. Fungal-assigned KEGG pathways were inversely correlated with residual antibiotic concentrations (Spearman's ρ = -0.34 to -0.54, P < 0.05) and fell into three candidate functional modules: antibiotic capture and transport, oxidative transformation, and intracellular transformation. Across all temperatures the community retained a capture-and-transport core, for which no significant temperature contrast was detected, whereas oxidative and intracellular transformation were both less abundant at LT. Temperature therefore influences soil antibiotic dissipation by reshaping fungal community structure and redistributing annotated potential among complementary fungal functions. Accounting for this temperature dependence can improve bioremediation strategies for antibiotic-contaminated agricultural soils.

Ammonium ions (NH₄⁺), owing to their abundance, low cost, and environmental friendliness, have emerged as promising non-metallic charge carriers for next-generation aqueous energy storage systems. However, the lack of suitable electrode materials has so far hindered their practical application. In this study, we report the development of a high-entropy multimetallic electrode material comprising uniformly dispersed Mn, Fe, Co, Ni, and Cu species on a conductive graphitized nitrogen-doped carbon framework. This engineered electrode enables high-performance symmetric NH₄⁺-ion supercapacitors. The multi-metal doping strategy significantly increases the density of electroactive sites, reduces NH₄⁺ diffusion barriers, and enhances structural stability. The optimized electrodes deliver a high specific capacitance of 836 F g^-1 at 1 A g^-1 and demonstrate excellent cycling performance, retaining 97.2% of their initial capacity and nearly 100% Coulombic efficiency after 50,000 cycles in a three-electrode system. Moreover, the assembled symmetric devices achieve energy densities exceeding 53 Wh kg^-1 at a power density of 891 W kg^-1. Density functional theory calculations confirm that the synergistic interaction among multiple metal centers optimizes NH₄⁺ adsorption and charge distribution, accounting for the superior electrochemical performance.

Accurate cortisol monitoring is essential for stress assessment and health management, yet reliable quantification remains challenging because signal fluctuations and matrix effects can compromise the performance of conventional single-mode immunosensors. Herein, we developed a fluorescence-colorimetric (FL-CL) dual-modal immunosensor based on a CuMOF-PEI@AuNPs@HRP (CPA) immunoreceptor for cortisol determination. The integrated sensing architecture generates correlated fluorescence and colorimetric responses from the same recognition event, which are combined through a normalized dual-signal output to improve calibration reliability. Under optimized conditions, the proposed sensor exhibited a detection limit of 0.22 ng/mL and a linear range of 3.1-200 ng/mL, covering physiologically relevant cortisol concentrations in saliva. Compared with single-modal assays and commercial kits, the proposed platform demonstrates enhanced sensitivity, improved correlation, good stability, and batch reproducibility. By integrating signal amplification, dual-modal readout, and simplified immunoreceptor fabrication within a single sensing platform, this work provides a reliable strategy for cortisol monitoring and offers potential for extension to other biomarker detection systems.

Antibiotic residues in environmental matrices pose escalating threats to ecosystems and human health, creating demand for rapid detection. Here, we present a portable smartphone-integrated bifunctional sensor based on Fe-CDs that enables sequential colorimetric and fluorescent detection of ampicillin (Amp) and tetracycline (TC). The Fe-CDs, synthesized via a one-pot hydrothermal process, exhibit stable fluorescence and intrinsic peroxidase-mimicking activity. Ampicillin inhibits the Fe-CDs nanozyme-catalyzed TMB/H₂O₂ chromogenic reaction via •OH consumption, allowing visual colorimetric quantification. Meanwhile, tetracycline strongly quenches the fluorescent signal of Fe-CDs through an inner filter effect, enabling a sensitive fluorescence readout. This bifunctional assay achieves high sensitivity (LOD as low as ∼0.012 μg/mL for Amp and 0.005 μg/mL for TC). By incorporating Fe-CDs onto paper test strips and analyzing with smartphone cameras, the platform allows real-time, rapid quantification of antibiotics in complex matrices. In manure samples, the sensor's results (recoveries ∼94.4-104.8%) agree well with LC-MS/MS measurements, underscoring its accuracy and robustness. Overall, the portable bifunctional Fe-CDs sensor provides a sensitive, field-deployable tool for environmental antibiotic surveillance.

Objective: Non-suicidal self-injury (NSSI) is prevalent among university students and represents a critical public health concern. This cross-sectional study investigated the prevalence of NSSI and its associated factors among freshmen at a university in central China. Using network analysis, we further examined the interrelationships among NSSI and three protective psychological constructs: resilience, cognitive reappraisal, and social problem-solving.

Methods: A cross-sectional survey was conducted among 3616 freshmen. After data screening, 2862 valid responses were included in the final analysis. Participants completed validated scales measuring NSSI, cognitive reappraisal, psychological resilience, and social problem-solving. SPSS 27.0 was used to perform logistic regression and group comparisons. Network analysis was performed in R to examine the interrelations and centrality of psychological constructs.

Results: The prevalence of NSSI among freshmen was 24.1%. Psychological resilience, cognitive reappraisal, and social problem-solving ability showed a significant stepwise decrease across NSSI severity groups (p < 0.001). Logistic regression showed that cognitive reappraisal, psychological resilience, social problem-solving ability, and rural household registration were negatively associated with NSSI, whereas male gender was positively associated with NSSI. Network analysis further revealed that cognitive reappraisal exhibited relatively high betweenness centrality within the network comprising resilience and social problem-solving subsystems. Within this network, toughness, strength, and avoidant problem-solving showed the highest node strength, whereas strength and negative problem orientation exhibited elevated betweenness centrality.

Limitations: The cross-sectional design and the single-institution sample preclude causal inferences and limit the generalizability of the present findings.

Conclusion: Cognitive reappraisal, psychological resilience, and social problem-solving ability were independently and negatively correlated with NSSI severity. Network analysis provided complementary insights into the structural relationships among these variables, identifying cognitive reappraisal as a central node within this network.

Background: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce.

Methods: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD.

Results: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (β = -0.45; 95%CI[-0.70, -0.19]; FDR-p = 0.003) and verbal memory (β = -0.45; 95%CI[-0.72, -0.18]; FDR-p = 0.003). Significant time × group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances.

Conclusions: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.