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Metabolic dysfunction-associated steatotic liver disease (MASLD) has garnered considerable attention globally. Changing lifestyles, over-nutrition, and physical inactivity have promoted its development. MASLD is typically accompanied by obesity and is strongly linked to metabolic syndromes. Given that MASLD prevalence is on the rise, there is an urgent need to elucidate its pathogenesis. Hepatic lipid accumulation generally triggers lipotoxicity and induces MASLD or progress to metabolic dysfunction-associated steatohepatitis (MASH) by mediating endoplasmic reticulum stress, oxidative stress, organelle dysfunction, and ferroptosis. Recently, significant attention has been directed towards exploring the role of gut microbial dysbiosis in the development of MASLD, offering a novel therapeutic target for MASLD. Considering that there are no recognized pharmacological therapies due to the diversity of mechanisms involved in MASLD and the difficulty associated with undertaking clinical trials, potential targets in MASLD remain elusive. Thus, this article aimed to summarize and evaluate the prominent roles of lipotoxicity, ferroptosis, and gut microbes in the development of MASLD and the mechanisms underlying their effects. Furthermore, existing advances and challenges in the treatment of MASLD were outlined.

Nano and microplastics (NPs/MPs) have received widespread attention in recent years. Because of their large specific surface area and hydrophobicity, NPs/MPs can adsorb various organic contaminants. This article gives a brief review of the sorption behavior of organic contaminants to NPs/MPs, summarizes the possible sorption mechanisms, and analyzes the influencing factors in the environment on the sorption behavior and mechanisms of NPs/MPs. The main mechanisms of sorption of organic contaminants to NPs/MPs are partitioning, surface sorption (hydrogen bonding, π–π interaction, electrostatic interaction, and van der Waals force), and pore filling. The sorption behavior of organic contaminants to NPs/MPs is not only affected by the properties of the NPs/MPs and the organic contaminants, but also by the solution chemistry, such as the pH, ionic strength, and dissolved organic matter.

Aquatic ecosystems worldwide are increasingly affected by human activities, with urbanization representing a major source of environmental stress. Channelization and flow depletion are key stressors in urban aquatic ecosystems. However, the combined effects of these factors on benthic macroinvertebrate and fish communities in urban rivers remain poorly understood. We examined the ecological impacts of channelization and flow depletion on benthic macroinvertebrates and fish in four urban rivers in Beijing, China: the natural high-flow Yongding River, the natural low-flow Gaojinggou River, the artificial high-flow Yongding River Diversion Channel, and the artificial low-flow Renmin Channel. By analyzing community composition, diversity, biomass, and water quality parameters, we assessed how river type (natural vs. artificial) and flow conditions (high vs. low) shape macroinvertebrate and fish communities across these urban rivers. Results showed that artificial channels had higher water temperatures, lower pH and DO, and higher concentrations of COD, NH 4 + , TP, fluorides, and sulfides compared to natural rivers, with flow depletion intensifying these effects. Both macroinvertebrate and fish community compositions varied significantly between river types and flow conditions. Channelization and flow depletion significantly reduced species richness, Shannon-Wiener diversity, and biomass in both macroinvertebrates and fish. Furthermore, we found a significant interaction between river type and flow depletion, as revealed by two-way ANOVA, with macroinvertebrate and fish communities in natural rivers being more sensitive to flow reductions than artificial channels. Redundancy analyses (RDAs) revealed that total phosphorus (TP) was the primary driver of macroinvertebrate community variation (contributing 23.6%), while DO played a crucial role in fish assemblages (contributing 20.6%). These findings underscore the significant impacts of channelization and flow depletion on urban river ecosystems, highlighting the vulnerability of natural rivers to flow depletion. Our study calls for urgent implementation of integrated management strategies to mitigate hydrological alterations, restore natural flow regimes, and reduce nutrient inputs, thereby enhancing the ecological resilience of urban aquatic ecosystems.

Excessive nitrogen has been discharged into natural environments due to anthropogenic activities, leading to numerous negative impacts on natural ecosystems worldwide and becoming a global environmental issue. Therefore, effective removal of nitrogenous contaminants from natural ecosystems is crucial for the protection of both ecological sustainability and human interests. In this study, a strain of Enterobacter cloacae GW6 was newly isolated from natural estuarine sediment. This strain could utilize ammonium, nitrite and nitrate, with removal efficiencies of 99.60%, 93.73% and 98.79%, and the maximum removal rates of 39.96, 40.39 and 44.65 mg/L/h, respectively. Importantly, Strain GW6 showed excellent simultaneous heterotrophic nitrification and aerobic denitrification (HN-AD) capability with the maximum TN removal rate of 35.27 mg/L/h, which is greater than those of many other HN-AD bacteria reported previously, indicating that Strain GW6 was suitable for the efficient nitrogen removal in aquatic ecosystems with high ammonium, nitrite and nitrate concentrations. The detection of functional genes amoA , hao , napA , nirK and nosZ from Strain GW6 further confirmed its HN-AD capability. Strain GW6 exhibited strong nitrogen removal capability across a wide range of environmental conditions, which makes it a promising candidate as a HN-AD bacterium for the effective biological treatment of nitrogen contamination and eutrophication in natural aquatic ecosystems, thereby contributing to better environmental protection.

Cathepsin B (CatB) is a cysteine proteolytic enzyme widely expressed in various cells and mainly located in the lysosomes. It contributes to the pathogenesis and development of many diseases. However, the role of CatB in viral myocarditis (VMC) has never been elucidated. Here we generated the VMC model by intraperitoneal injection of coxsackievirus B3 (CVB3) into mice. At day 7 and day 28, we found CatB was significantly activated in hearts from VMC mice. Compared with the wild-type mice receiving equal amount of CVB3, genetic ablation of CatB (Ctsb-/-) significantly improved survival, reduced inflammatory cell infiltration, decreased serum level of cardiac troponin I, and ameliorated cardiac dysfunction, without altering virus titers in hearts. Conversely, genetic deletion of cystatin C (Cstc-/-), which markedly enhanced CatB levels in hearts, distinctly increased the severity of VMC. Furthermore, compared with the control, we found the inflammasome was activated in the hearts of wild-type mice with VMC, which was attenuated in the hearts of Ctsb-/- mice but was further enhanced in Cstc-/- mice. Consistently, the inflammasome-initiated pyroptosis was reduced in Ctsb-/- mice hearts and further increased in Cstc-/- mice. These results suggest that CatB aggravates CVB3-induced VMC probably through activating the inflammasome and promoting pyroptosis. This finding might provide a novel strategy for VMC treatment.

The railway hub with multiple stations has been more common with the expansion of the railway network. It is imperative to investigate the utilization of multiple stations to meet the travel demand of urban residents. This paper focuses on railway hubs and abstracts the division of labor among multiple stations as an optimization of train routing problem. A mixed integer linear programming model is constructed to minimize the total cost of trains and passengers, with the number of stops, capacity of railway lines and station tracks, and passenger demand of traffic zones considered as constraints. A case study based on a multi-station railway hub is implemented to evaluate the effectiveness of the optimization model. Compared with the other two scenarios, the total cost of the optimization results is reduced by 0.1% and 2.7%. Meanwhile, the proposed optimization scheme also achieves a more balanced and efficient utilization of railway line and station track capacity. Furthermore, the research also proposes several operationally feasible recommendations for railway department to support making division of labor scheme for railway hubs.

This study explores the safety problems of hydrogen leakage and explosion in hydrogen fuel cell buses through Computational Fluid Dynamics simulations. The research investigates the diffusion behavior of hydrogen in the passenger cabin depending on the leakage position and flow rates, identifying a stratified, constant-concentration layer formed at the top of the cabin. Leakage near the rear wall of the vehicle provided the highest hydrogen concentration, while at higher flow rates, the diffusive process accelerated the spreading of flammable hydrogen concentrations. Hydrogen ignition simulations showed a fast internal pressure increase and secondary explosions outside the vehicle. Thermal hazards in the cases were higher than overpressure. The research’s additional analysis of ignition timing and source location shows that overpressure peaked initially with delayed ignition but declined afterward, while rear-ignited flames exhibited the farthest high-temperature hazard range at 10.88 m. These findings are fundamental for giving insight into hydrogen behavior in confined spaces and thus guiding risk assessment and emergency response planning for the development of safety protocols in hydrogen fuel cell buses, contributing to the safer implementation of hydrogen energy in public transportation.

MicroRNAs (miRs) serve a key role in carcinogenesis. miR-148a-3p has been demonstrated to act as a tumor suppressor in several tumors, such as epithelial ovarian cancer and esophageal cancer. However, to the best of our knowledge, the role of miR-148a-3p in cervical cancer remains unclear. In the present study, the expression levels of miR-148a-3p measured by reverse transcription-quantitative PCR were significantly decreased in cervical cancer tissues compared with that in normal cervical tissues. Furthermore, overexpression of miR-148a-3p markedly suppressed the proliferation of cervical cancer cells. The luciferase reporter assay demonstrated that DNA methyltransferase 1 (DNMT1) was the target gene of miR-148a-3p and that its expression measured by western blotting was inhibited by miR-148a-3p in cervical cancer cells. Correlation analysis highlighted that the expression levels of the undifferentiated embryonic cell transcription factor-1 (UTF1) were negatively associated with the expression levels of DNMT1 in cervical cancer tissues. Furthermore, DNMT1 knockdown increased the expression of UTF1 and decreased the methylation level of UTF1 promoter. These data demonstrated the expression levels of UTF1 were regulated by DNMT1 methylation in cervical cancer cells. Collectively, the results of the present study suggested that miR-148a-3p may inhibit the proliferation of cervical cancer cells by regulating the expression levels of DNMT1/UTF1, which provides potential therapeutic targets for cervical cancer.

Long-term effects of occupational polycyclic aromatic hydrocarbons (PAHs) on biological aging are unclear. A prospective cohort study was conducted from 2019 to 2023, involving 610 coke oven workers and 454 control workers from a water treatment plant. Biological age was calculated using the Klemera and Doubal method (KDM-BA) based on 12 clinical biomarkers, and aging acceleration (KDM-Accel) was derived. Group-based trajectory modeling (GBTM) was employed to identify distinct aging trajectories over five time points. The associations between eleven urinary mono-hydroxylated PAH metabolites (measured via HPLC-MS) and both KDM-Accel and aging trajectories were assessed using multiple linear regression and multivariable logistic regression, respectively. GBTM identified three distinct aging trajectories: slow aging (14.86%), moderately accelerated aging (59.14%), and rapidly accelerated aging (26%). Higher concentrations of urinary Σ-OHPAHs (sum of all metabolites), 1-hydroxypyrene (1-OHPyr), and 2-hydroxyphenanthrene (2-OHPhe) were significantly associated with increased KDM-Accel. A natural log-unit increase in Σ-OHPAHs and 1-OHPyr was associated with a 0.029-year and 0.028-year increase in KDM-Accel, respectively. Workers in the highest tertile (T3) of Σ-OHPAHs exposure had a 61.2% increased odds (OR = 1.612, 95% CI 1.093–2.376) of being in the rapidly accelerated aging trajectory compared to those in the lowest tertile (T1). Similar positive dose-response relationships were observed. Occupational exposure to PAHs, as specifically indicated by elevated levels of urinaryΣ-OHPAHs, 1-OHPyr, and 2-OHPhe, is correlated with accelerated biological aging and a heightened probability of a rapid aging trajectory. Therefore, enhanced protection measures and early intervention strategies are necessary.

Hydroponic lettuce was prone to pest and disease problems after transplantation. Manual identification of the current growth status of each hydroponic lettuce not only consumed time and was prone to errors but also failed to meet the requirements of high-quality and efficient lettuce cultivation. In response to this issue, this paper proposed a method called YOLO-EfficientNet for identifying the growth status of hydroponic lettuce. Firstly, the video data of hydroponic lettuce were processed to obtain individual frame images. And 2240 images were selected from these frames as the image dataset A. Secondly, the YOLO-v8n object detection model was trained using image dataset A to detect the position of each hydroponic lettuce in the video data. After selecting the targets based on the predicted bounding boxes, 12,000 individual lettuce images were obtained by cropping, which served as image dataset B. Finally, the EfficientNet-v2s object classification model was trained using image dataset B to identify three growth statuses (Healthy, Diseases, and Pests) of hydroponic lettuce. The results showed that, after training image dataset A using the YOLO-v8n model, the accuracy and recall were consistently around 99%. After training image dataset B using the EfficientNet-v2s model, it achieved excellent scores of 95.78 for Val-acc, 94.68 for Test-acc, 96.02 for Recall, 96.32 for Precision, and 96.18 for F1-score. Thus, the method proposed in this paper had potential in the agricultural application of identifying and classifying the growth status in hydroponic lettuce.