Metabolic associated fatty liver disease （MAFLD） is a chronic liver disease closely associated with metabolic syndrome， characterized by a complex pathogenesis involving genetic， environmental， and lifestyle factors. Recent studies have shown significant disparities in the prevalence rate and clinical features of MAFLD across different racial and ethnic groups， and such disparities might be associated with various factors such as genetic background， environmental factors， socioeconomic disparities， and metabolic profiles. This article reviews the latest research advances in racial and ethnic differences in MAFLD in China and globally， discusses its potential pathogenic mechanisms and clinical significance， proposes future research directions and interventional measures， and emphasizes the critical need to enhance MAFLD screening and preventive health education in multiethnic populations.

Background Fine particulate matter (PM_2.5) monitoring stations may generate missing data for a certain period of time due to various factors. This data loss will adversely affect air quality assessment and pollution control decision-making. Objective To propose an inverse distance weighted (IDW) spatiotemporal interpolation method based on particle swarm optimization (PSO) to interpolate and fill missing PM_2.5 spatiotemporal sequence data and increase interpolation accuracy. Methods An interpolation experiment was designed into two parts. The first part used hourly PM_2.5 observational data from four moments on January 1, 2017 in the Yangtze River Delta region. The second part employed daily PM_2.5 observational data from the first 10 d of January 2017 in the Beijing-Tianjin-Hebei region. Interpolation accuracy was evaluated using four metrics: root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean relative error (MRE). Results IDW spatiotemporal interpolation method optimized with PSO significantly improved the accuracy of filling missing PM_2.5 spatiotemporal sequence data. In the hourly-scale experiment conducted in the Yangtze River Delta region, compared to a distance index of 2, the accuracy metrics RMSE, MAE, MAPE, and MRE generated by the proposed method improved on average by 0.17 μg·m⁻³, 0.27 μg·m⁻³, 0.17%, and 0.01%, respectively. The PM_2.5 spatial field maps generated for four moments based on this method clearly illustrated the spatiotemporal distribution characteristics of hourly PM_2.5 concentrations in the Yangtze River Delta region. In the daily-scale experiment conducted in the Beijing-Tianjin-Hebei region, the PSO-optimized distance index outperformed the traditional method, with interpolation accuracy improvements of approximately 0.215 μg·m⁻³, 0.283 μg·m⁻³, 0.174%, and 0.014%, respectively. Furthermore, the seasonal PM_2.5 spatial field maps generated by this method revealed the spatiotemporal distribution characteristics of PM_2.5 concentrations in the Beijing-Tianjin-Hebei region across different seasons, further validating the effectiveness and applicability of this method. Conclusion The IDW spatiotemporal interpolation method optimized with PSO is highly accurate and reliable for interpolating the missing data in the Yangtze River Delta region and the Beijing-Tianjin-Hebei region, providing valuable insights for air pollution control and public health protection.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

OBJECTIVE To assess the cost-effectiveness of durvalumab combined with chemotherapy as a first-line treatment for advanced biliary tract cancer from the perspective of the Chinese healthcare system. METHODS Using data from the TOPAZ-1 clinical trial， a three-state Markov model comprising progression-free survival （PFS）， progressive disease （PD） and death was developed， with a cycle length of 21 days and a 10-year time horizon. Patients in the observation group received durvalumab in combination with gemcitabine and cisplatin， whereas those in the control group received placebo plus the same chemotherapy regimen. The evaluation indexes were quality-adjusted life year （QALY） and the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） threshold was set at three times the 2024 Chinese per capita gross domestic product （GDP） （287 247 yuan/QALY）. The sensitivity analyses， along with scenario analyses， were performed. RESULTS In the base-case analysis， the ICER of observation group compared to control group was 1 166 344.46 yuan/QALY， far exceeding the WTP threshold， indicating that the regimen was not cost-effective. One-way sensitivity analysis identified the PD state utility， discount rate， cost of durvalumab， and PFS state utility as the main drivers of ICER variation. Probabilistic sensitivity analysis showed that， at the above WTP threshold， the probability of the acceeptance of this regimen was 0， further supporting the robustness of the base-case findings. In the scenario analysis， inclusion of a patient assistance program reduced the ICER to 235 885.16 yuan/ QALY， below the above WTP threshold， suggesting cost-effectiveness under this assistance program. However， when applying a regional WTP threshold set at three times the per capita GDP （158 475 yuan/QALY） of Gansu Province （the province with the lowest GDP in China in 2024）， the ICER remained above the threshold， indicating that the regimen was not cost-effective at the regional level. CONCLUSIONS At current pricing， durvalumab plus chemotherapy as a first-line treatment for advanced biliary tract cancer is not cost-effective in China. Although the introduction of a patient assistance program can substantially reduce the ICER and achieve cost-effectiveness at a WTP threshold set at three times the 2024 per capita GDP of China， due to limited affordability in low-income areas， the program remains not cost-effective.

Utilizing network pharmacology, molecular docking, and cellular experimental validation, this study delved into the therapeutic efficacy and underlying mechanisms of matrine in combating senescence. Databases were utilized to predict targets related to the anti-senescence effects of matrine, resulting in the identification of 81 intersecting targets for matrine in the treatment of senescence. A protein-protein interaction(PPI) network was constructed, and key targets were screened based on degree values. Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed on the key targets to elucidate the critical pathways involved in the anti-senescence effects of matrine. Molecular docking was conducted between matrine and key targets. A senescence model was established using human umbilical vein endothelial cells(HUVECs) induced with hydrogen peroxide(H_2O_2). Following treatment with varying concentrations of matrine(0.5, 1, and 2 mmol·L~(-1)), cell viability was assessed by using the CCK-8. SA-β-galactosidase staining was employed to observe the positive rate of senescent cells. Flow cytometry was utilized to measure the apoptosis rate. Real-time quantitative PCR(RT-PCR) was utilized to measure the mRNA expression of apoptosis-related cysteine peptidase 3(CASP3), albumin(ALB), glycogen synthase kinase 3β(GSK3B), CD44 molecule(CD44), and tumor necrosis factor-α(TNF-α). Western blot was performed to detect the protein expression of tumor protein p53(p53), cyclin-dependent kinase inhibitor 1A(p21), cyclin-dependent kinase inhibitor 2A(p16), and retinoblastoma tumor suppressor protein(pRb) in the senescence signaling pathway, p38 protein kinase(p38), c-Jun N-terminal kinase(JNK), and extracellular regulated protein kinases(ERK) in the mitogen-activated protein kinase(MAPK) pathway, and phosphatidylinositol 3-kinase(PI3K) and protein kinase B(Akt) in the PI3K/Akt signaling pathway. The experimental results revealed that matrine significantly increased the viability of HUVECs(P<0.05), decreased the positive rate of senescent cells and the apoptosis rate(P<0.05), and reduced the mRNA expression levels of CASP3, ALB, GSK3B, CD44, and TNF-α(P<0.05). It also inhibited the protein expression of p53, p21, p16 and pRb in the senescence signaling pathway(P<0.05), upregulated the protein expression of p-PI3K/PI3K and p-Akt/Akt(P<0.05), and downregulated the protein expression of p-p38/p38, p-JNK/JNK, and p-ERK/ERK(P<0.05). Collectively, these findings suggest that matrine exerts an inhibitory effect on HUVECs senescence, and its mechanism involves the modulation of the senescence signaling pathway, MAPK pathway, and PI3K/Akt signaling pathway to suppress cell apoptosis and inflammation.
Humans ; Matrines ; Quinolizines/chemistry* ; Alkaloids/chemistry* ; Human Umbilical Vein Endothelial Cells/cytology* ; Cellular Senescence/drug effects* ; Network Pharmacology ; Molecular Docking Simulation ; Signal Transduction/drug effects* ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Apoptosis/drug effects* ; Drugs, Chinese Herbal/pharmacology*

With the growing awareness of public health, the value and importance of traditional Chinese medicine(TCM) resources have become increasingly prominent. Despite the undeniable significance of TCM in medical treatment and healthcare, the protection, development, and utilization of TCM resources still face numerous challenges. Under the traditional model, the development and utilization of TCM resources heavily rely on manual labor and empirical decision-making, which not only leads to inefficiencies and high costs but also causes serious issues such as unstable drug quality and imbalances in market supply and demand. In the current era of rapid advancements in artificial intelligence(AI) and technology, AI has emerged as a new engine to address many challenges and difficulties throughout the entire TCM resource industry chain. By leveraging AI technology, intelligent management, precise production, and optimized utilization of TCM resources can be achieved, thereby improving efficiency, reducing costs, ensuring stable quality, and balancing market supply and demand. This article primarily explores the application of AI technology in the entire TCM resource industry chain from different perspectives and provides an in-depth analysis of the future development of AI in the TCM industry. It holds significant importance and value in promoting the intelligent development of the TCM sector and facilitating the healthy development of the entire TCM resource industry chain.
Artificial Intelligence ; Medicine, Chinese Traditional/economics* ; Humans ; Drugs, Chinese Herbal/economics* ; Drug Industry

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

Drug toxicity is closely related to both clinical drug safety and new drug development. Therefore, it is vital to understand the mechanisms of drug toxicity fully and to use appropriate research models with advanced technologies. Zebrafish has become an important vertebrate animal model for high-throughput drug screening and toxicity assessment. At the same time, zebrafish has an intact biological complexity, reflecting the whole organism's toxicity, which gives it an advantage over other high-throughput models in toxicity studies. Despite the gradual increase in toxicity studies utilizing zebrafish, a comprehensive and systematic review of the underlying mechanisms and new techniques is still lacking. This review aims to analyze common toxicity mechanisms in zebrafish models, such as oxidative stress, endoplasmic reticulum stress, inflammation, and apoptosis, and macroscopic changes in biological processes like lipid metabolism disorders and neurotransmitter expression abnormalities. It also introduces new technologies applied in toxicity assessment, such as gene editing, novel fluorescence imaging technology, 3D imaging technology, and novel automated technology for high-throughput screening, such as fish capsules. In addition, it also summarizes the advantages and disadvantages of the model. By doing so, it will provide new suggestions for the development and improvement of the model, make it better serve the toxicity study of clinical drugs and provide a more comprehensive perspective for drug toxicity study, thus promoting the development of the field of drug toxicity study.

Objective:A comparison was made between the predictive efficacy of the Padua Score and the simplified Assessment Scheme Recommended by Chinese experts (hereinafter referred to as the Simplified Method) for the risk assessment of venous thromboembolism (VTE) in medical inpatients, aiming to provide a reference for the clinical selection of appropriate risk assessment tools.Methods:A retrospective cohort study was conducted, selecting 42 257 internal medicine inpatients discharged from Peking University Shenzhen Hospital between May 1, 2021, and April 30, 2022, using a convenience sampling method. Data collected included general information upon admission, VTE-related information, occurrences of VTE during hospitalization, and results from the two assessment tools. The predictive efficacy of the tools was evaluated by plotting ROC curves and calculating AUC, sensitivity, specificity, positive predictive value, negative predictive value, and predictive accuracy.Results:Among 42 257 patients, there were 21 065 male and 21 192 female participants, aged (55.04 ± 15.17) years old. The incidence rate of VTE among medical inpatients was 2.24% (948/42 257). The AUC for Padua Score and the Simplified Method in medical patients were 0.735 (95% CI 0.717-0.753) and 0.582 (95% CI 0.561-0.602), respectively. Sensitivities were 49.4% and 18.2%, specificities were 89.6% and 98.1%, positive predictive values were 9.9% and 17.7%, negative predictive values were 98.7% and 98.1%, and predictive accuracy were 88.7% and 96.3%, respectively. The departments with the highest incidence rates of VTE during hospitalization were rehabilitation medicine, emergency, neurology, geriatrics, and respiratory medicine. Within these departments, the AUC values for the Padua Score and the Simplified Method were as follows: 0.864 and 0.612, 0.782 and 0.653, 0.792 and 0.664, 0.850 and 0.551, 0.867 and 0.664, respectively. Conclusions:The Padua Score demonstrated better predictive efficacy compared to the Simplified Method. However, the Simplified Method had more accessible assessment criteria and could serve as an initial VTE risk screening tool in emergency situations or when complete data are not available.