Objective: To investigate the protective effects of Gouqizi (Lycii Fructus, GQZ)-Danshen (Salviae Miltiorrhizae Radix et Rhizoma, DS) against hydrogen peroxide (H2O2)-induced oxidative injury in 661W retinal photoreceptor cells and to explore whether these effects involve angiopoietin-like 4 (ANGPTL4). Methods: Liquid chromatography-mass spectrometry (LC-MS) was used to identify the major components of GQZ-DS aqueous extract. An H2O2-induced oxidative injury model was established in 661W cells. Working concentrations of H2O2 and GQZ-DS were determined using the cell counting kit-8 (CCK-8) assay. Cells were subjected to GQZ-DS, ANGPTL4 knockdown, or ANGPTL4 overexpression as indicated. Flow cytometry was used to analyze cell cycle distribution, apoptotic rate, and intracellular reactive oxygen species (ROS). Colorimetric determination of malondialdehyde (MDA) content and superoxide dismutase (SOD) activity using the thiobarbituric acid (TBA) method was performed. The protein expression level of ANGPTL4 was assessed by immunofluorescence. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to quantify the mRNA level of ANGPTL4. Western blot was used to detect the protein levels of ANGPTL4 and cleaved caspase-3. Results: LC-MS identified five major constituents in the GQZ-DS aqueous extract: 2-O-β-D-glucopyranosyl-L-ascorbic acid, rutin, D-galactose, salvianolic acid A, and tanshinone IIA. The CCK-8 method selected 300 μmol/L H2O2 as the oxidative stress condition for experiments, and 0.05 and 0.1 g/mL were selected as the low and high doses of GQZ-DS, respectively, for subsequent experiments. The intervention with H2O2 resulted in reduced cell viability, elevated ROS and MDA levels, decreased SOD activity, increased apoptotic rate, upregulated cleaved caspase-3 expression, and G0/G1 phase cell cycle arrest of 661W cells. Both low and high doses of GQZ-DS alleviated these alterations, with high dose exhibiting stronger protective effects (P < 0.05 or P < 0.01). GQZ-DS also downregulated ANGPTL4 expression at both the mRNA and protein levels. Following plasmid transfection of cells, the study further revealed that ANGPTL4 knockdown mitigated oxidative stress and apoptosis-related injury, whereas ANGPTL4 overexpression exacerbated these pathological changes. Moreover, GQZ-DS partially reversed the degree of cellular oxidative damage induced by ANGPTL4 overexpression. Conclusion GQZ-DS can alleviate the H2O2-induced oxidative injury of 661W retinal photoreceptor cells, and the effects are related to the down-regulation of ANGPTL4 expression.

Acute liver failure (ALF) is lack of broadly approved therapeutic strategy except liver transplantation. As a glycogen metabolic intermediate, UDP-glucose (UDP-G) has been considered to accelerate liver repairment. Nevertheless, the role of UDP-G and its receptor P2Y purinoceptor 14 (P2Y₁₄R) in ALF remains unknown. The present study aims to investigate the role and underlying mechanisms of UDP-G/P2Y₁₄R axis in ALF. In this study, hepatic P2Y₁₄R is significantly increased in TAA-induced and partial hepatectomy-induced ALF, while knockout of whole-body P2Y₁₄R aggravates liver failure, manifested by inhibiting β-Catenin-mediated liver regeneration. Consistently, P2Y₁₄R deficiency exhibits impaired liver regeneration in mice suffer partial hepatectomy. Importantly, only hepatocellular specific deletion of P2Y₁₄R (P2Y₁₄R ^flox/flox Alb ^cre/+ ) mice shows a similar phenomenon, rather than stellate cell specific deletion of P2Y₁₄R (P2Y₁₄R ^flox/flox Lrat ^cre/+ ) mice. Mechanistically, P2Y₁₄R induction regulates methylation of Dact-2 through CREB/DNMT3b signals in hepatocytes, subsequently inhibiting the expression of Dact-2 which is a stabilizer of β-Catenin degradation complex, leading to the activation of β-Catenin -mediated liver regeneration. Interestingly, the administration of exogenous UDP-G can accelerate liver regeneration and liver function recovery after partial hepatectomy in hepatocellular carcinoma mice. Together, the findings propose an unrecognized role of P2Y₁₄R in ALF and provide an effective adjuvant strategy for treatment of ALF.

Human papillomavirus (HPV) can cause various tumors such as cervical cancer in women. Further study of HPV infection and its pathogenic mechanism, as well as the development of vaccines and anti-tumor drugs, have been hindered due to the strong host specificity and tissue affinity of HPV, along with the challenges in in vitro culture and the lack of animal infection models. To advance the study of HPV infection and its pathogenic mechanism and to development better prevention and treatment measures, it is important to establish an animal model that closely resembles the infection and pathogenesis pathways in humans. This article reviews previous research on HPV-related animal models using mice, rabbits, macaques, and Drosophila, including infectious models, tumor models, and transgenic models, aiming to provide reference for the selection of appropriate animal models for HPV-related research.

Objective:To investigate the correlations between physical, psychological and social frailty in elderly patients with multimorbidity.Methods:This study utilized a mixed method. A questionnaire survey was conducted from February to June 2024, among elderly patients with multimorbidity attending 4 primary health care centers in urban Beijing selected by the convenience sampling method. The FRAIL Frailty Assessment Scale, WHO-5 Index of Well-Being Scale, and HALFT Scale were used to assess the patients′ physical, psychological, and social frailty, respectively. Spearman correlation analysis was used to analyze the correlation between different dimensions of frailty in elderly with multimorbidity. Logistic regression model was used to analyze the factors influencing physical, psychological and social frailty. The elderly with multimorbidity who were assessed to have at least 1 or more types of frailty in the quantitative study were selected for in-depth interviews in the form of online and offline combination. The topics of in-depth interview included the real experience of the different dimensions of frailty, the possible causes and the difficulties caused. The sample size was determined according to the principle of information saturation. Thematic analysis was used to summarize, code and analyze the interview data.Results:A total of 919 participants were included in the quantitative study, with a mean age of (74.09±6.03) years, 329(35.80%) were males and 590(64.20%) were females. The prevalence of physical, psychological, and social frailty was 17.85%(164/919), 21.44%(197/919), 11.21%(103/919), respectively. A total of 21 participants were included in the qualitative study, with a mean age (76.90±5.13)years, 5(23.81%) males and 16(76.19%) females. Spearman correlation analysis showed that physical and psychological frailty were moderately correlated ( r=0.311, P<0.001), psychological and social frailty were weakly correlated ( r=0.218, P<0.001), and physical and social frailty were weakly correlated ( r=0.267, P<0.001). Logistic regression analysis showed that the age, the number of multimorbidities, the psychological frailty and social frailty were the influencing factors for physical frailty (all P<0.05). The gender, number of multimorbidity, type of medication taken, physical frailty and social frailty were influencing factors of psychological frailty (all P<0.05). And age, number of multimorbidities, physical frailty and psychological frailty were influencing factors of social frailty (all P<0.05). A total of 3 themes were extracted through in-depth interviews, namely, "physical and psychological frailty are interrelated""physical and social frailty are interrelated", and "psychological and social frailty are interrelated". Conclusions:The physical, psychological, and social frailty in elderly patients with multimorbidity interacts with each other. Whereas the number of multimorbidities is a common risk factor for all three.

Objective:To analyze the current status, research hotspots, and development trends on the integration of primary care and prevention in China.Methods:This was a bibliometric analysis. Literature related to research on the integration of primary care and prevention in China was retrieved from CNIKI, Wanfang, VIP, Chinese Medical Journal Full Text Database, PubMed, and Web of Science for the period from January 1, 2015, to April 1, 2025. CiteSpace software was used to conduct a visual analysis of publication volume, authors and their collaborations, institutions, and keywords in the included literature.Results:A total of 292 domestic publications on the integration of primary healthcare and public health were analyzed. Research on primary healthcare-public health integration in China exhibited an overall upward trend from 2015 to 2025. Based on publication volume and temporal distribution, domestic research can be categorized into an exploratory phase (2015-2020) and a rapid development phase (2021-2025). The institutions publishing relevant research were predominantly universities and research centers, with a low institutional network density (0.013), indicating relative weak inter-institutional collaboration. The co-occurrence density among authors was 0.013 9. Collaboration predominantly occurred in small clusters, with limited cross-regional cooperation. Keywords that appeared frequently and had an intermediary centrality exceeding 0.1 included chronic diseases (0.40), public health (0.23),health management (0.18), and hypertension (0.17). Keyword clustering analysis showed that the top three categories mainly focused on public health, chronic diseases, and health management. Since 2024, emerging keywords with high burst intensity have included big data, health literacy, primary care hospitals, and infectious diseases.Conclusions:Research on the integration of medical and preventive care at the primary healthcare level in China has entered a stage of rapid development. Current research hotspots focus primarily on chronic disease management, the implementation status and barriers of primary healthcare and prevention integration models. Future research is expected to emphasize the application of intelligent technologies, and the enhancement of public health emergency response capacity.

Objective: To map the research hotspots, developmental trends, and existing challenges in the integration of artificial intelligence (AI) with multi-omics in traditional Chinese medicine (TCM) through comprehensive bibliometric analysis. Methods: China National Knowledge Infrastructure (CNKI), Wanfang Data, China Science and Technology Journal Database (VIP), Chaoxing Journal Database, PubMed, and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31, 2024. Eligible records were required to simultaneously address AI, TCM, and multi-omics. Quantitative and visual analyses of publication growth, core authorship networks, institutional collaboration patterns, and keyword co-occurrence were performed using Microsoft Excel 2021, NoteExpress v4.0.0, and Cite Space 6.3.R1. AI application modes in TCM multi-omics research were also categorized and summarized. Results: A total of 1 106 articles were enrolled (932 Chinese and 174 English). Publication output has increased continuously since 2010 and accelerated after 2016. Region-specific collaboration clusters were identified, dominated by Beijing University of Chinese Medicine, China Academy of Chinese Medical Sciences, Shanghai University of Traditional Chinese Medicine, and Nanjing University of Chinese Medicine. Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining. Research foci mainly ranked as follows: single herbs, herbal formulae, and disease-syndrome differentiation. Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present, utilized for processing omics data and uncovering latent patterns therein. The domain of TCM, in addition to investigating omics information procured through high-throughput technologies, also integrates data on traditional Chinese medicinal substances and clinical phenotypes, progressing towards joint analysis of multi-omics, high-dimensionality of data, and multi-modality of information. Deep learning approaches represent an emerging trend in the field.

Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and gouty arthritis (GA), is a prevalent inflammatory disease that significantly impacts quality of life. Natural products (NPs), derived from animals, plants, marine organisms, and microorganisms, have demonstrated beneficial effects in arthritis treatment both domestically and internationally. These natural compounds offer advantages in drug discovery due to their skeletal diversity, structural complexity, and multi-effect, multi-target, and low-toxicity properties compared to conventional small-molecule medicines. However, unclear mechanisms have hindered the development and clinical application of NPs. This review summarizes recent experimental studies from the past decade on natural medicine for arthritis treatment, emphasizing key NPs with therapeutic effects on OA, RA, and GA. It examines the effects and molecular mechanisms of NPs acting on different cells to treat arthritis. Furthermore, this review provides insights into the future prospects of NP research in this field, which is crucial for advancing NP-based arthritis treatments.
Humans ; Biological Products/therapeutic use* ; Animals ; Arthritis, Rheumatoid/drug therapy* ; Arthritis, Gouty/drug therapy* ; Arthritis/drug therapy* ; Osteoarthritis/drug therapy*

Aim To investigate the effect of hypobaric hypoxia on macrophage necroptosis and atherosclerotic plaque instability and explore the underlying mechanisms.Methods Mouse bone marrow-derived macrophages were i-solated and cultured,and divided into control group(21％oxygen concentration)and hypoxia group(3％oxygen concen-tration).After 48 hours,cell necroptosis was detected,and the expression of cell necroptosis related proteins was deter-mined by Western blot.Healthy male ApoE-/-mice were randomly divided into control group and hypobaric hypoxia group.After the intervention for 16 weeks,the plasma lipids and inflammatory cytokines were measured,the areas of ath-erosclerotic plaque and necrotic core were evaluated by HE staining.The content of plaque collagen was detected by Mas-son staining.The number of macrophages in the plaque and the expression of necrotic apoptosis related proteins were de-tected by immunohistochemical staining and Western blot.Results Hypoxia induced increased necrotic apoptosis of macrophages(P＜0.01),while necroptotic inhibitor necrostatin-1(Nec-1)reduced hypoxia induced cell death(P＜0.05);hypoxia leads to a decrease in the expression of adenosine deaminase acting on RNA 1(ADAR1)in macrophages(P＜0.01),and an increase in the expression of Z-DNA binding protein 1(ZBP1),phosphorylated receptor-interacting serine/threonine-protein kinase(p-RIPK3),and phosphorylated mixed lineage kinase domain-like protein(p-MLKL)(all P＜0.01).Compared with the control group,the plasma lipid levels of ApoE-/-mice in the hypobaric hypoxia group did not change significantly(P＞0.05),the plasma inflammatory cytokines(TNF-α,IL-1β,IL-6 and MCP-1)increased(all P＜0.05),the area of atherosclerotic plaque increased(P＜0.05),the area of plaque necrotic core increased,the content of plaque collagen decreased,the number of macrophages increased,the expression of ADAR1 decreased,and the expres-sion of ZBP1 and p-MLKL increased(all P＜0.01).Conclusion Hypobaric hypoxia causes the imbalance of A-DAR1/ZBP1 expression in macrophages,activates RIPK3/MLKL signaling pathway,promotes macrophage necroptosis,in-creases the area of plaque necrosis core,and leads to increase instability of atherosclerotic plaque.

Objective To evaluate the advantages of a real-time computer endoscopy-assisted system(EndoAngel)for colorectal lesions detection in colonoscopy.Methods 2 000 patients who underwent EndoAngel assisted colonoscopy and conventional colonoscopy were selected for the study in a single-center,self-controlled study.According to different examination methods,the patients were divided into artificial intelligence(AI)group and traditional colonoscopy group,each with 1 000 cases.The results were statistically analyzed and compared with the polyp detection rate and adenoma detection rate of the two groups using pathological diagnosis as the gold standard.Further subgroup analysis will be conducted based on the seniority of the operating physicians.Results AI group's polyp detection rate was higher(39.3％)than conventional colonoscopy group polyp detection rate(29.0％),with statistically significant difference(x2=23.59,P=0.000).Of these,the detection rates of hyperplastic polyps and adenomatous polyps were 19.1％and 25.2％,which were significantly higher than those of 12.4％and 20.8％in the conventional colonoscopy group,and the differences were statistically significant(x2=16.92,P=0.000;x2=5.46,P=0.019).Further subgroup analysis of the two groups by physician seniority,the polyp detection rate of AI low seniority group(36.6％)was higher than that of conventional colonoscopy low seniority group(20.40％),with a statistically significant difference(x2=32.20,P=0.000).Among them,the detection rates of hyperplastic polyp(17.8％)and adenomatous polyp(23.6％)in AI low seniority group were higher than those in the conventional colonoscopy low seniority group(12.8％vs 13.6％),and the differences were significant(x2=4.82,P=0.028;x2=16.51,P=0.000).There were no significant differences in adenomatous polyp detection rates between the two groups of senior physicians.Conclusion EndoAngel assisted system can improve the polyp detection rate of colonoscopy,especially for the effect of low seniority physicians is more significant.

Infectious diseases continue to pose a threat to global public health. Successive global shocks caused by emerging and re-emerging pathogens have continuously challenged existing surveillance systems, highlighting the urgent need to build efficient and precise pathogen surveillance networks. Pathogen genomic databases have been developed rapidly in recent two decades, significantly improving the molecular identification, evolutionary analysis, and transmission tracking of pathogens, and changing disease surveillance strategies and patterns. This paper summarizes the developmental history and current state of pathogen genomic databases, and discusses their applications in public health, including pathogen variation surveillance, emerging or suspected pathogen identification, and epidemiological tracing. Furthermore, this paper systematically analyzes the limitations and key challenges faced by current global health prevention and control system, and suggests the focus of the development of online pathogen databases to address existing shortcomings, ultimately improve global infectious disease surveillance and early warning