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Underground engineering rock masses are significantly affected by stress redistribution induced by mining or adjacent engineering disturbances, leading to initial damage accumulation in coal-rock masses. Under sustained geostress, these masses exhibit pronounced time-dependent creep behavior, posing serious threats to long-term engineering stability. Dynamic loading effects triggered by adjacent mining activities (manifested as medium strain-rate loading) further exacerbate damage evolution and significantly influence creep characteristics. In this study, coal samples with identical initial damage were prepared, and graded loading creep tests were conducted at rates of 0.005 mm·s−1 (50 microstrains·s−1), 0.01 mm·s−1 (100 microstrains·s−1), 0.05 mm·s−1 (500 microstrains·s−1), and 0.1 mm·s−1 (1000 microstrains·s−1) to systematically analyze the coupled effects of loading rate on creep behavior. Experimental results demonstrate that increased loading rates markedly shorten creep duration, with damage rates during the acceleration phase showing nonlinear surges (e.g., abrupt instability at 0.1 mm·s−1 (1000 microstrains·s−1)). Based on experimental data, an integer-order viscoelastic-plastic creep model incorporating stress-dependent viscosity coefficients and damage correlation functions was developed, fully characterizing four behaviors stages: instantaneous deformation, deceleration, steady-state, and accelerated creep. Optimized via the Levenberg–Marquardt algorithm, the model achieved correlation coefficients exceeding 0.96, validating its accuracy. This model clarifies the impact mechanisms of loading rates on the long-term mechanical behavior of initially damaged coal samples, providing theoretical support for stability assessment and hazard prevention in underground engineering.

Rural greywater management is a critical global challenge due to the lack of centralized treatment in dispersed communities. This study aimed to characterize the pollution characteristics and bacterial community structure of samples from four greywater collection tanks in eastern China using high-throughput sequencing and absolute quantification of the 16S rRNA gene. Pollution characteristics showed spatial heterogeneity: chemical oxygen demand ranged from 19.8 to 272.5 mg/L, total nitrogen from 8.6 to 16.4 mg/L, and dissolved oxygen from 1.3 to 5.3 mg/L. Dissolved greenhouse gases also varied, with N2O reaching 103.6 ppmv and CH4 up to 50.4 ppmv. Based on the estimated absolute abundance of 16S rRNA gene copies, we found that the bacterial communities were dominated by Pseudomonadota, Actinomycetota, Bacteroidota, and Bacillota. Key genera such as Acinetobacter, Pseudomonas, and unclassified Enterobacteriaceae were positively correlated with nitrate, suggesting their potential association with denitrification and potential N2O production. The methanotrophic genus Methyloparacoccus was enriched in a tank with high dissolved organic carbon. Co-occurrence network analysis revealed that core taxa like unclassified Paracoccaceae and Limnohabitans function as module hubs, maintaining community stability. These findings reveal associations between bacterial taxa, pollutant transformation, and greenhouse gas emissions in rural greywater and provide fundamental insights to support the development of low-carbon, resource-oriented treatment technologies.

The differentiated responses of biological groups to environmental change are central to river ecosystem management; however, the shared and distinct environmental selection processes that shape their spatial patterns remain understudied. We investigated two adjacent rivers with contrasting environmental conditions and applied eDNA metabarcoding to characterize the eukaryotic plankton and fish communities. The alpha diversity showed no significant river-to-river difference for either group, but beta diversity differed strongly, indicating high spatial turnover. Both groups exhibited distance–decay relationships, which were stronger in plankton, whose community assembly was mainly stochastic; in contrast, fish assembly was predominantly deterministic. Community variation in both groups was significantly associated with physical and chemical factors—electrical conductivity (EC), the potential of hydrogen (pH), water temperature (WT), dissolved oxygen (DO), chemical oxygen demand (COD), and biochemical oxygen demand (BOD5)—while plankton also responded to nutrient variables, including total phosphorus (TP), total nitrogen (TN), and ammonium nitrogen (NH4-N). Collectively, our results emphasize differential environmental selection across biological groups and provide a basis for designing targeted river restoration and water quality improvement strategies.

With the increasing depth of coal resource extraction, the creep characteristics of gangue backfill in deep backfill mining are crucial for the long-term deformation of rock strata. Existing research predominantly focuses on the instantaneous deformation response of either the backfill alone or the strata movement, lacking systematic studies that reflect the long-term time-dependent deformation characteristics of the strata-backfill system. This study addresses gangue–roof composite specimens with varying gangue particle sizes. Utilizing physical similarity ratio theory, graded loading confined compression creep experiments were designed and conducted to investigate the effects of gangue particle size and moisture content on the creep behavior of the gangue–roof composites. A fractional-order creep constitutive model for the gangue–roof composite was established, and its parameters were identified. The results indicate the following: (1) The creep of the gangue–roof composite exhibits two-stage characteristics (initial and steady-state). Instantaneous strain decreases with increasing particle size but increases with higher moisture content. Specimens reached their maximum instantaneous strain under the fourth-level loading, with values of 0.358 at a gangue particle size of 10 mm and 0.492 at a moisture content of 4.51%. (2) The fractional-order creep model demonstrated a goodness-of-fit exceeding 0.98. The elastic modulus and fractional-order coefficient showed nonlinear growth with increasing particle size, revealing the mechanism of viscoplastic attenuation in the gangue–roof composite. The findings provide theoretical support for predicting the time-dependent deformation of roofs in deep backfill mining.

Anterior gradient‐2 (AGR2) is crucial to breast cancer progression. However, its role in the tumor immune microenvironment remains unclear. RNA sequencing expression profiles and associated clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. The AGR2 expression patterns were verified using clinical samples of breast cancer. Based on single‐cell transcriptomic data, AGR2 expression patterns were identified and cell communication analysis was carried out. Furthermore, the roles of AGR2 in breast tumor progression were explored by a series of functional experiments. We found that DNA methylation was an important mechanism for regulating the expression patterns of AGR2. Patients with AGR2 low expression displayed an immune “hot” and immunosuppressive phenotype characterized by high abundance of tumor immune cell infiltration and increased enrichment scores for transforming growth factor‐β (TGF‐β) and epithelial–mesenchymal transition pathways, whereas patients with AGR2 high expression showed an opposite immunologic feature with a lack of immune cell infiltration, suggestive of an immune “cold” and desert phenotype. Moreover, single‐cell analysis further revealed that AGR2 in malignant cells alters cell–cell interactions by coordinating cytokine–chemokine signaling and immune infiltration. Notably, two immunotherapy cohorts revealed that AGR2‐coexpressed genes could serve as prognostic indicators of patient survival. In conclusion, AGR2 could promote breast cancer progression by affecting the tumor immune microenvironment. Patients with AGR2 low expression could be suitable for combination treatment with immune checkpoint inhibitor agents and TGF‐β blockers. Therefore, this study provides a theoretical foundation for developing a strategy for personalized immunotherapy to patients with breast cancer. AGR2 in malignant cells regulates cell‐cell communication by coordinating cytokine‐chemokine signaling and immune infiltration. AGR2 could affect tumor immune microenvironment and thus promoted the progression of breast cancer.

Background and objectiveSystemic sclerosis (SSc) is an immune-mediated rheumatic disease characterized by fibrosis and vascular lesions. Interstitial lung disease is an early complication of SSc and the main cause of death from SSc. Although baricitinib shows good efficacy in a variety of connective tissue diseases, its role in systemic sclerosis-related interstitial lung disease (SSc-ILD) is unclear. The objective of our study was to explore the effect and mechanism of baricitinib in SSc-ILD.MethodsWe explored crosstalk between the JAK2 and TGF-β1 pathways. In vivo experiments, SSc-ILD mice model were constructed by subcutaneous injection of PBS or bleomycin (7.5 mg/kg) and intragastric administration of 0.5% CMC-Na or baricitinib (5 mg/kg) once every two days. We used ELISA, qRT‒PCR, western blot and immunofluorescence staining to evaluate the degree of fibrosis. In vitro experiments, we used TGF-β1 and baricitinib to stimulate human fetal lung fibroblasts (HFLs) and assessed protein expression by western blot.ResultsThe vivo experiments showed that baricitinib notably alleviated skin and lung fibrosis, decreased the concentration of pro-inflammatory factors and increased those of the anti-inflammatory factors. Baricitinib affected the expression of TGF-β1 and TβRI/II inhibitiing JAK2. In the vitro experiments, following the culture of HFLs with baricitinib or a STAT3 inhibitor for 48 h, the expression levels of TβRI/II decreased. Conversely, with successful inhibition of TGF-β receptors in HFLs, JAK2 protein expression decreased.ConclusionsBaricitinib attenuated bleomycin-induced skin and lung fibrosis in SSc-ILD mice model by targeting JAK2 and regulating of the crosstalk between the JAK2 and TGF-β1 signaling pathways.

The administration of mRNA-based tumour vaccines is considered a promising strategy in tumour immunotherapy, although its application against kidney renal clear cell carcinoma (KIRC) is still at its infancy stage. The purpose of this study was to identify potential antigens and to further select suitable patients for vaccination. Gene expression data and clinical information were retrieved from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. GEPIA2 was used to evaluate the prognostic value of selected antigens. The relationship of antigens presenting cell infiltration with antigen expression was evaluated by TIMER, and immune subtypes were determined using unsupervised cluster analysis. Tumour antigens LRP2 and DOCK8, which are associated with prognosis and tumour-infiltrating antigen-presenting cells, were identified in KIRC. A total of six immune subtypes were identified, and patients with immune subtype 1–4 (IS1–4) tumours had an immune ‘cold’ phenotype, a higher tumour mutation burden, and poor survival. Moreover, these immune subtypes showed significant differences in the expression of immune checkpoint and immunogenic cell death modulators. Finally, the immune landscape of KIRC revealed the immune-related cell components in individual patients. This study suggests that LRP2 and DOCK8 are potential KIRC antigens in the development of mRNA vaccines, and patients with immune subtypes IS1–4 are suitable for vaccination.

Precise and sensitive methods for the simultaneous determination of different classes of antibiotics, including sulphonamides, fluoroquinolones, macrolides, tetracyclines, and trimethoprim in surface water, sediments, and fish muscles were developed. In water samples, drugs were extracted with solid-phase extraction （SPE） by passing 1000 mL of water through hydrophilic lipophilic balanced （HLB） SPE cartridges. Sediment samples were solvent-extracted, followed by tandem SPE （strong anion exchange （SAX） ＋ HLB） clean-ups. Fish muscles were extracted by a mixture of acetonitrile and citric buffer （80：20, v/v） solution, and cleaned by SPE. Liquid chromatography-tandem mass spectrometry （LC-MS/ MS） with multiple reaction monitoring （MRM） detection was employed to quantify all compounds. The recoveries for the antibiotics in the spiked water, sediment, and fish samples were 60.2%-95.8%, 48.1%-105.3%, and 59.8%- 103.4%, respectively. The methods were applied to samples taken from Dianchi Lake, China. It showed that concentrations of the detected antibiotics ranged from limits of quantification （LOQ） to 713.6 ng- L1 （ofloxacin） in surface water and from less than LOQ to 344.8 μg·kg-1 （sulphamethoxazole） in sediments. The number of detected antibiotics and the overall antibiotic concentrations were higher in the urban area than the rural area, indicating the probable role of livestock and human activities as important sources of antibiotic contamination. In fish muscles, the concentration of norfioxacin was the highest （up to 38.5 μg·kg-1）, but tetracyclines and macrolides were relatively low. Results showed that the methods were rapid and sensitive, and capable of determining several classes of antibiotics from each of the water, sediment, and fish matrices in a single run.

The accumulation and clearance of amyloid-β (Aβ) peptides play a crucial role in the pathogenesis of Alzheimer's disease (AD). The (re)discovery of meningeal lymphatic vessels in recent years has focused attention on the lymphatic clearance of Aβ and has become a promising therapeutic target for such diseases. However, there is a lack of small molecular compounds that could clearly regulate meningeal lymphatic drainage to remove Aβ from the brain. We investigated the effect of borneol on meningeal lymphatic clearance of macromolecules with different molecular weights (including Aβ) in the brain. To further investigate the mechanism of borneol regulating meningeal lymphatic drainage, immunofluorescence staining, western blotting, ELISA, RT-qPCR, and Nitric Oxide assay kits were used. The cognitive function of AD mice after borneol treatment was evaluated using two behavioral tests: open field (OF) and Morris water maze (MWM). This study discovered that borneol could accelerate the lymphatic clearance of Aβ from the brain by enhancing meningeal lymphatic drainage. Preliminary mechanism analysis revealed that borneol could improve the permeability and inner diameter of lymphatic vessels, allowing macromolecules to drain into the cervical lymph nodes (CLNS) and then be transported to the lymphatic circulation. To speed up the clearance of macromolecules, borneol also stimulated lymphatic constriction by lowering the level of nitric oxide in the meninges. In addition, borneol stimulated lymphangiogenesis by increasing the levels of FOXC2, VEGFC, and LYVE-1 in the meninges, which promoted the clearance rates of macromolecules. Borneol improved meningeal lymphatic clearance not only for Aβ but also for other macromolecular polymers (molecular weight in the range of 2 KD - 45 KD. Borneol ameliorated cognitive deficits and alleviated brain Aβ burden in Aβ-injected mice. Our findings not only provide a strategy to regulate lymphatic clearance pathways of macromolecules in the brain, but also new targets and ideas for treating neurodegenerative diseases like AD. Furthermore, our findings indicate that borneol is a promising therapeutic drug for AD.

The microbial community structure of sediments in the Bahe River Basin, China was studied using a high-throughput sequencing platform and PCR amplification to investigate the pattern changes in microbial communities in urban rivers affected by anthropogenic activities and their environmental driving mechanisms. The results demonstrated that the average total nitrogen and total phosphorus in the sediments were 524 and 734 mg/kg, respectively. The T, COD and NH4+-N of the water and the moisture content of the sediments has significantly impacted on the microbial community structure. Twenty microbial species with a relative abundance > 1% in the sediments of the river were observed, accounting for 95–99% of the total microbial community. The primary species were Proteobacteria (13.86–69.14%), Firmicutes (1.45–58.33%), Chloroflexi (3.68–26.18%), Actinobacteria (2.7–21.51%), Acidobacteria (0.73–16.36%), Bacteroides (1.53–14.11%), and Thermodesulfobacteria (0.1–8.9%), accounting for over 90% of the total microbial community. At the class level, the primary species were γ-proteobacteria, Alphaproteobacteria, Anaerolineae, Bacillus, Bacteroidota, Actinobacteriota, and Clostridia, accounting for over 70% of the total microbial community. Our results provide direct evidence for a link between microbial community structure and environment factors. This evidence demonstrates that sediment microorganisms can be applied to evaluate urban rivers pollution levels, which can provide a scientific basis for pollution control and management in the urban river affected by human activities.