BACKGROUND:Lysosomal storage diseases,as a group of rare genetic metabolic disorders,exhibit complex pathogenesis often leading to dysfunction of cells,tissues,and organs.Current therapeutic approaches have certain limitations.Stem cell transplantation,as an emerging treatment method,offers new options for patients with lysosomal storage diseases.OBJECTIVE:To review the mechanisms of action of stem cells in regulating lysosomes for the treatment of lysosomal storage diseases and explore the feasibility of traditional Chinese medicine in treating such diseases,providing new insights for the treatment of lysosomal storage diseases with stem cells.METHODS:Relevant literature from 2010 to 2024 was searched in CNKI and PubMed databases using keywords"stem cells,lysosomal storage disease,lysosome"in English and Chinese.Ultimately,78 articles were included for review and analysis.RESULTS AND CONCLUSION:(1)Stem cells treat lysosomal storage diseases by regulating lysosomes primarily through three aspects:regulating stem cell differentiation and replacement,improving intercellular communication and the microenvironment,and enhancing lysosomal enzyme expression through gene editing.(2)Stem cells have achieved significant effects in the treatment of some lysosomal storage diseases,such as Niemann-Pick disease,mucopolysaccharidoses,Gaucher disease,and metachromatic leukodystrophy.(3)The procedure for stem cell transplantation needs further optimization.Adverse reactions post-transplantation urgently need to be addressed,and the efficiency and safety of gene-modified stem cells also need to be further improved.In the future,more research on the treatment of lysosomal storage diseases with traditional Chinese medicine is required to reveal the relevant mechanisms for the treatment of lysosomal storage diseases with traditional Chinese medicine.

BACKGROUND:Lysosomal storage diseases,as a group of rare genetic metabolic disorders,exhibit complex pathogenesis often leading to dysfunction of cells,tissues,and organs.Current therapeutic approaches have certain limitations.Stem cell transplantation,as an emerging treatment method,offers new options for patients with lysosomal storage diseases.OBJECTIVE:To review the mechanisms of action of stem cells in regulating lysosomes for the treatment of lysosomal storage diseases and explore the feasibility of traditional Chinese medicine in treating such diseases,providing new insights for the treatment of lysosomal storage diseases with stem cells.METHODS:Relevant literature from 2010 to 2024 was searched in CNKI and PubMed databases using keywords"stem cells,lysosomal storage disease,lysosome"in English and Chinese.Ultimately,78 articles were included for review and analysis.RESULTS AND CONCLUSION:(1)Stem cells treat lysosomal storage diseases by regulating lysosomes primarily through three aspects:regulating stem cell differentiation and replacement,improving intercellular communication and the microenvironment,and enhancing lysosomal enzyme expression through gene editing.(2)Stem cells have achieved significant effects in the treatment of some lysosomal storage diseases,such as Niemann-Pick disease,mucopolysaccharidoses,Gaucher disease,and metachromatic leukodystrophy.(3)The procedure for stem cell transplantation needs further optimization.Adverse reactions post-transplantation urgently need to be addressed,and the efficiency and safety of gene-modified stem cells also need to be further improved.In the future,more research on the treatment of lysosomal storage diseases with traditional Chinese medicine is required to reveal the relevant mechanisms for the treatment of lysosomal storage diseases with traditional Chinese medicine.

ObjectiveTo investigate the distribution characteristics and correlation of paired oral and esophageal microbiota in patients with esophageal squamous cell carcinoma （ESCC）. MethodsA total of 46 pathologically confirmed ESCC patients were enrolled， and oral swabs and cancerous tissue samples were collected. The microbial composition was analyzed using 16S rRNA gene sequencing， and bioinformatics methods were employed to compare the microbiota diversity， compositional differences， and correlations between the two sites. ResultsThe Alpha diversity of the oral microbiota in ESCC patients was significantly higher than that of their esophageal microbiota， though the overall community structure was similar between the two sites. LEfSe analysis revealed that Spirochaetes， Prevotella， Catonella， Enterococcus， Fusobacterium periodonticum， Veillonella parvula， Capnocytophaga sputigena， and Neisseria subflava were significantly enriched in ESCC tumor tissues. In contrast， Actinobacteria， Proteobacteria， Streptococcus， Neisseria， Haemophilus， Streptococcus mitis， Haemophilus parainfluenzae， Porphyromonas gingivalis， Haemophilus haemolyticus， and Prevotella tannerae were significantly enriched in the oral cavity. Correlation analysis demonstrated significant associations between the two sites at taxonomic levels such as Spirochaetes， Treponema， Granulicatella elegans， Neisseria macacae， Treponema amylovorum， Fusobacterium periodonticum， and Neisseria meningitidis （P<0.05）. ConclusionThe oral and esophageal microbiota in ESCC patients exhibit both distinct differences and similarities. Oral microbiota may influence the esophageal microenvironment through migration or local immune modulation.

Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the "monarch, minister, assistant, envoy" compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.
Artificial Intelligence ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Drug Synergism

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Dendritic cells (DCs) serve as the primary antigen-presenting cells in autoimmune diseases, like rheumatoid arthritis (RA), and exhibit distinct signaling profiles due to antigenic diversity. Type II collagen (CII) has been recognized as an RA-specific antigen; however, little is known about CII-stimulated DCs, limiting the development of RA-specific therapeutic interventions. In this study, we show that CII-stimulated DCs display a preferential gene expression profile associated with migration, offering a new perspective for targeting DC migration in RA treatment. Then, saikosaponin D (SSD) was identified as a compound capable of blocking CII-induced DC migration and effectively ameliorating arthritis. Optineurin (OPTN) is further revealed as a potential SSD target, with Optn deletion impairing CII-pulsed DC migration without affecting maturation. Function analyses uncover that OPTN prevents the proteasomal transport and ubiquitin-dependent degradation of C-C chemokine receptor 7 (CCR7), a pivotal chemokine receptor in DC migration. Optn-deficient DCs exhibit reduced CCR7 expression, leading to slower migration in CII-surrounded environment, thus alleviating arthritis progression. Our findings underscore the significance of antigen-specific DC activation in RA and suggest OPTN is a crucial regulator of CII-specific DC migration. OPTN emerges as a promising drug target for RA, potentially offering significant value for the therapeutic management of RA.

Objective:To explore the expression of chemokine ligand 1(CCL1)in oral squamous cell carcinoma(OSCC)and its effect on the proliferation,migration and invasion of human oral tongue squamous cell carcinoma cells(HSC-4).Methods:28 OSCC tissue samples and clinical characteristic data of patients were collected at the Affiliated Stomatological Hospital of Southwest Medical University between January 2018 and June 2020,as well as 10 normal gingival tissue samples removed during the extraction of impacted teeth.OSCC cells HSC-4 were cultured routinely and divided into the control group(without virus),the NC group(transfected with control lentiviral vector),the shCCL1 group(transfected with knockdown CCL1 lentiviral vector),and the CCL1 group(culture medium containing 60 ng/mL CCL1 recombinant protein).Immunohistochemistry and WB were used to detect the expression of CCL1 in OSCC tissues and cells,and analyze the correlation between its expression level and the clinical features of patients.qPCR,CCK-8 assay,plate cloning assay,cell scratch test,Transwell assay and flow cytometry were used to detect the expression of CCL1 mRNA,the proliferation,migration and invasion abilities and the apoptosis of HSC-4 cells respectively.Results:CCL1 protein was highly expressed in OSCC tissues and HSC-4 cells(all P<0.01)and its expression was related to the clinical stage of tumors(P<0.05).The expression of CCL1 in HSC-4 cells was successfully knocked down(P<0.000 5).Knocking down the expression of CCL1 could inhibit the proliferation(P<0.05 or P<0.01),migration and invasion(all P<0.05)of HSC-4 cells,and promote its apoptosis(all P<0.05).CCL1 recombinant protein treatment resulted in the opposite effects(P<0.05,P<0.01,P<0.000 1).Conclusion:CCL1 is highly expressed in OSCC and its expression is correlated with the clinical stage of OSCC.CCL1 may take part in regulating the proliferation,migration,invasion and apoptosis of HSC-4 cells.

Objective lt aims to identify key issues in the current informatization development of internal control over revenue and expenditure in public hospitals.The findings are intended to serve as a reference for deepening this informatization effort.Methods Following the steps and requirements of content analysis method,it involved a semi-quantitative analysis of policies and expert interviews to establish an analytical framework.Two researchers uti-lized NVivo 15 software to analyze the policy and articles.The analysis results were quantified statistically,and key is-sues were summarized.Results lt developed a content analysis framework comprising 5 primary categories and 17 secondary categories.Based on this framework,326 analytical units extracted from 81 articles were categorized and statistically analyzed.Key problems corresponding to each secondary category were summarized.Conclusion To ad-dress five key issues,it proposes a five-dimensional solution including:building a digital foundation to integrate busi-ness systems;establishing a Master Data Management platform to dismantle data silos;developing flexible ap-proval mechanismsfor medical emergencies;deploying an Al risk control hub for precise payment interception,and implementing zero-trust architecture to enhance e-bill anti-counterfeiting-ultimately forming a business-finance-in-tegrated,data-and-Al-driven,proactively secured internal control system covering budget formulation to fund su-pervision.

To explore the application of sequential analysis in post-market safety dynamic surveillance of vaccines. Under the dynamic monitoring data of vaccines post-market approval, this research introduces the fundamental principles of maximizing sequential probability ratio test (MaxSPRT) and Bayesian sequential analysis, employing R software. Through an example of dynamic safety monitoring data of vaccines post-market approval, we analyze using the MaxSPRT and Bayesian sequential analysis. The MaxSPRT identified a safety signal in week 4 ( P<0.05), while Bayesian sequential analysis indicated that the 95% highest density interval for the RR value at week 4 is 1.13-3.27, suggesting the first appearance of a safety signal at week 4. The MaxSPRT and Bayesian sequential analysis effectively leverage continuously accumulating dynamic monitoring data, thereby serving as a valuable method for post-market safety surveillance of vaccines.

Objective: To analyze the occupational health literacy (OHL) level and its influencing factors among key populations in the tertiary industry in Lu'an City, Anhui Province, so as to provide a basis for developing targeted health interventions and improving regional occupational health policies. Methods: A stratified cluster random sampling method was employed to select five categories of key populations from the tertiary industry in Lu'an City as study subjects from August to September 2024. Data on gender, age, education level, and OHL were collected through the National OHL Monitoring Questionnaire for Key Populations. The OHL levels were analyzed, and influencing factors of OHL levels among key populations were analyzed using a multivariable logistic regression model. Results: A total of 1 243 individuals were surveyed, comprising 700 (56.32%) males and 543 (43.68%) females. The median age was 42.00 (interquartile range, 17.00) years. There were 609 individuals with OHL, and the OHL level was 48.99%. The OHL levels in fundamental knowledge of occupational health protection, healthy work styles and behaviors, knowledge of occupational health laws, and basic skills for occupational health protection were 84.71%, 60.34%, 43.93%, and 37.09%, respectively. Multivariable logistic regression analysis showed that educational level (primary school and below, OR=0.149, 95%CI: 0.064-0.344; junior high school, OR=0.340, 95%CI: 0.184-0.629; high school, OR=0.408, 95%CI: 0.230-0.723), average monthly personal income (3 000-<5 000 yuan, OR=1.655, 95%CI: 1.092-2.508; 5 000-<7 000 yuan, OR=2.195, 95%CI: 1.302-3.699; ≥7 000 yuan, OR=2.062, 95%CI: 1.016-4.183), employer nature (private enterprises, OR=2.992, 95%CI: 1.569-5.443), and industry category (education, OR=3.423, 95%CI: 1.407-8.327; courier / food delivery services, OR=0.459, 95%CI: 0.268-0.787; healthcare, OR=7.539, 95%CI: 3.255-17.461) were statistically associated with the OHL level among key population. Conclusion The OHL level among key population in the tertiary industry of Lu'an City can be further enhanced, with educational level, average monthly personal income, employer nature, and industry category identified as the primary influencing factors.