Objective: To investigate the status of condom use and its influencing factors among men who have sex with men (MSM), so as to provide a basis for improving condom utilization rates and AIDS prevention and control in this population. Methods: From May to October 2024, a snowball sampling method was employed to recruit MSM in Songjiang District, Shanghai Municipality. Self-administered questionnaires were used to collect data on demographic characteristics, AIDS-related knowledge, sexual behaviors, pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), and condom use in the past six months. Multivariable logistic regression model was used to analyze the influencing factors for consistent condom use. Results: A total of 921 MSM were surveyed, with a median age of 29.00 (interquartile range, 9.00) years. Among them, 697 (75.68%) were aware of AIDS-related knowledge, 826 (89.69%) expressed willingness to use PrEP, and 835 (90.66%) were willing to use PEP. Additionally, 787 (85.45%) MSM reported their age at first homosexual intercourse as ≥18 years, while 519 (56.35%) reported consistent condom use in the past six months. Multivariable logistic regression analysis revealed that MSM who were aware of AIDS-related knowledge (OR=0.582, 95% CI: 0.423-0.801), willing to use PrEP (OR =0.611, 95% CI: 0.385-0.969), and whose age at first homosexual intercourse was <18 years (OR=0.480, 95% CI: 0.330-0.700) were less likely to consistent use condoms. Conclusion The proportion of consistent condom use among the MSM remains relatively low, which is primarily associated with AIDS-related knowledge, willingness to use PrEP, and the age at first homosexual intercourse.

Objective To analyze the global pattern, long-term trends, and regional and population heterogeneity in the burden of 375 diseases and injuries and 88 risk factors from 1990 to 2023 using data from the Global Burden of Disease Study 2023 (GBD 2023). Methods Publicly available GBD 2023 estimates were extracted for incidence, deaths, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life years (DALYs), and age-standardized rates at the global level and by socio-demographic index (SDI), GBD region, age group, and sex. Descriptive analysis, ranking comparison, stratified analysis, and trend analysis were performed, and 95% uncertainty interval was used to assess the stability of estimates. Results In 2023, non-communicable diseases were the leading contributor to global DALYs, accounting for 64.39% of DALYs across the three major disease and injury groups (communicable, maternal, neonatal, and nutritional diseases, non-communicable diseases, and injuries), and also had the highest age-standardized DALYs rate. From 1990 to 2023, age-standardized DALYs rates declined for three major disease and injury groups, with estimated annual percentage changes of −2.69%, −0.78%, and −1.47%, respectively. Cardiovascular diseases ranked first by both DALYs and deaths in 2023, whereas respiratory infections and tuberculosis ranked first by incidence. Non-communicable diseases were the leading cause of disease burden across all SDI strata. As the SDI level declined, the burden of communicable, maternal, neonatal, and nutritional diseases, as well as injuries, increased markedly. Behavioral and metabolic risks remained the main contributors to attributable deaths and DALYs. Conclusion From 1990 to 2023, the global burden of disease continues to shift toward non-communicable diseases; however, some regions still face a double burden of infectious, maternal and child, injury-related, and chronic diseases. Integrating deaths, DALYs, YLLs, YLDs, and risk-attributable burden helps identify priority areas for prevention and resource allocation across regions and populations.

Background Antibiotics are frequently detected in aquatic environments, posing potential threats to ecological systems and public health. Objective To characterize antibiotic contamination in source water in Wuhan, evaluate the removal efficiency of conventional drinking water treatment processes, identify potential pollution sources, and assess ecological risks, thereby providing evidence to support water safety management. Methods A total of 34 source water samples and paired finished water samples were collected. Twenty-seven target antibiotics were analyzed via solid-phase extraction coupled with high-performance liquid chromatography-tandem mass spectrometry. Total antibiotic concentrations and the relative contributions of individual antibiotics were calculated for each sampling site. Differences in removal performance across seasons and waterworks scales were further assessed. Antibiotic pairs with co-occurrence frequencies of ≥ 10 were included in Spearman’s rank correlation analysis to explore co-occurrence patterns. Potential sources were inferred according to their approved clinic and veterinary uses. For ecological risk assessment, predicted no-effect concentrations were derived from chronic toxicity values for fish, Daphnia, green algae, and mysid obtained from the ECOSAR database. Risk quotients (RQ) were calculated using both the median and the 95th percentile concentrations to characterize typical and high-end ecological toxicity. Results Seventeen antibiotics were detected in the source water. Lincosamides, macrolides, and sulfonamides were frequently detected, with detection frequencies exceeding 50%. Although quinolones were detected less frequently (2.94%-38.24%), they exhibited episodic high concentrations; the 95th percentile concentration of cinoxacin (CNX) reached 365.73 ng·L⁻¹. The mean total antibiotic concentration was 1.79 times higher in the wet season (105.97 ng·L⁻¹) than in the dry season (59.21 ng·L⁻¹). The contribution of quinolones increased markedly from 0.87% in the dry season to 43.10% in the wet season. Except for flumequine (FQ), ofloxacin (OFX), enoxacin (ENX), and clarithromycin (CLR), the median removal rates of the remaining antibiotics by conventional treatment processes all exceeded 80%. Ten antibiotics achieved complete removal (100%) in the wet season, compared with 4 antibiotics in the dry season. The median removal rate of CLR declined with decreasing waterworks scale, from 67.92% in large-scale plants to –1.96% in medium-scale plants and –71.25% in small-scale plants. Apparent negative removal was observed for sulfadiazine (SDZ), FQ, OFX, and CLR, with OFX exhibiting the highest frequency of negative removal events (n=14). Correlation analysis revealed significant positive correlations between sulfonamides and macrolides (ρ=0.52-0.83), indicating mixed influences from livestock farming and domestic wastewater. Lincomycin (LIN) was positively correlated with sulfamethoxazole (SMX), but negatively correlated with the aforementioned antibiotic network, suggesting a predominantly human medical source. Based on median concentrations, the ecological risk of individual antibiotics was negligible. However, the cumulative risk to Daphnia reached a low level (RQ > 0.01), with sulfonamides contributing more than 70% of this risk. Based on the 95th percentile concentrations, bost individual and cumulative risks of quinolones to fish and Daphnia increased to low levels, with quinolones contributing more than 55% of the total risk. Conclusion Antibiotics are commonly detected in source water in Wuhan, and conventional drinking water treatment dose not completely eliminate all target compounds. Quinolones, despite their relatively low detection frequencies, occur at episodically high concentrations and pose low risks to fish and Daphnia under high-end exposure scenarios, warranting priority control. The coexistence of human-use and veterinary-use antibiotics reflects diverse pollution sources and highlights the need for coordinated multi-source pollution control.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Objective To clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

ObjectiveIn nature, objects cast shadows due to illumination, forming the basis for stereoscopic perception. Birds need to adapt to changes in lighting (meaning they can recognize stereoscopic shapes even when shadows look different) to accurately perceive different three-dimensional forms. However, how neurons in the key visual brain area in birds handle these lighting changes remains largely unreported. In this study, pigeons (Columba livia) were used as subjects to investigate how neurons in pigeon’s ventrolateral mesopallium (MVL) represent stereoscopic shapes consistently, regardless of changes in lighting. MethodsVisual cognitive training combined with neuronal recording was employed. Pigeons were first trained to discriminate different stereoscopic shapes (concave/convex). We then tested whether and how light luminance angle and surface appearance of the stereoscopic shapes affect their recognition accuracy, and further verify whether the results rely on specify luminance color. Simultaneously, neuronal firing activity of neurons was recorded with multiple electrode array implanted from the MVL during the presentation of difference shapes. The response was finally analyzed how selectively they responded to different stereoscopic shapes and whether their selectivity was affected by the changes of luminance condition (like lighting angle) or surface look. Support vector machine (SVM) models were trained on neuronal population responses recorded under one condition (light luminance angle of 45°) and used to decode responses under other conditions (light luminance angle of 135°, 225°, 315°) to verify the invariance of responses to different luminance conditions. ResultsBehavioral results from 6 pigeons consistently showed that the pigeons could reliably identify the core 3D shape (over 80% accuracy), and this ability wasn’t affected by changes in light angle or surface appearance. Statistical analysis of 88 recorded neurons from 6 pigeons revealed that 83% (73/88) showed strong selectivity for specific 3D shapes (selectivity index>0.3), and responses to convex shapes were consistently stronger than to concave shapes. These shape-selective responses remained stable across changes in light angle and surface appearance. Neural patterns were consistent under both blue and orange lighting. The decoding accuracy achieves above 70%, suggesting stable responses under different conditions (e.g., different lighting angles or surface appearance). ConclusionNeurons in the pigeon MVL maintain a consistent neural encoding pattern for different stereoscopic shapes, unaffected by illumination or surface appearance. This ensures stable object recognition by pigeons in changing visual environments. Our findings provide new physiological evidence for understanding how birds achieve stable perception (“invariant neural representations”) while coping with variations in the visual field.

Alcoholic liver disease(ALD), a major cause of chronic liver disease worldwide, poses a serious threat to human health. Despite the availability of various drugs for treating ALD, their efficacy is often uncertain, necessitating the search for new therapeutic approaches. Traditional Chinese medicine polysaccharides have garnered increasing attention in recent years due to their versatility, high efficiency, and low side effects, and they have demonstrated significant potential in preventing and treating ALD. Emerging studies have suggested that these polysaccharides exert their therapeutic effects through multiple mechanisms, including the inhibition of oxidative stress and the regulation of lipid metabolism, gut microbiota, and programmed cell death. This review summarizes the recent research progress in the pharmacological effects and regulatory mechanisms of traditional Chinese medicine polysaccharides in treating ALD, aiming to provide a scientific basis and theoretical support for their application in the prevention and treatment of ALD.
Humans ; Liver Diseases, Alcoholic/metabolism* ; Polysaccharides/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Oxidative Stress/drug effects* ; Medicine, Chinese Traditional ; Gastrointestinal Microbiome/drug effects* ; Lipid Metabolism/drug effects*

The Baihe Dihuang Decoction(BDD) is a representative traditional Chinese medicine formula that has been used to treat depression. This study employed metabolomics and network pharmacology to investigate the mechanism of BDD in the treatment of depression. Fifty male Sprague-Dawley(SD) rats were randomly assigned to the normal control group, model group, fluoxetine group, and high-and low-dose BDD groups. A rat model of depression was established through chronic unpredictable mild stress(CUMS), and the behavioral changes were detected by forced swimming test and open field test. Metabolomics technology was used to analyze the metabolic profiles of serum and hippocampal tissue to screen differential metabolites and related metabolic pathways. Additionally, network pharmacology and molecular docking techniques were used to investigate the key targets and core active ingredients of BDD in improving metabolic abnormalities of depression. A "component-target-metabolite-pathway" regulatory network was constructed. BDD could significantly improve depressive-like behavior in CUMS rats and regulate 12 differential metabolites in serum and 27 differential metabolites in the hippocampus, involving tryptophan metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, alanine, aspartate, and glutamate metabolism, tyrosine metabolism, and purine metabolism. Verbascoside, isorbascoside, and regaloside B were the key active ingredients for improving metabolic abnormalities in depression. Epidermal growth factor receptor(EGFR), protooncogene tyrosine-protein kinase(SRC), glycogen synthase kinase 3β(GSK3β), and androgen receptor(AR) were the key core targets for improving metabolic abnormalities of depression. This study offered a preliminary insight into the mechanism of BDD in alleviating metabolic abnormalities of depression through network regulation, providing valuable guidance for its clinical use and subsequent research.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Depression/genetics* ; Antidepressive Agents/chemistry* ; Network Pharmacology ; Hippocampus/drug effects* ; Humans ; Molecular Docking Simulation ; Behavior, Animal/drug effects* ; Disease Models, Animal