Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

BACKGROUND: Early control of low-density lipoprotein cholesterol (LDL-C) is crucial for reducing the progress of cardiovascular disease. However, its additional role to the risk of primary osteoporosis in men with coronary heart disease was inconclusive. Our study aims to determine the association of LDL-C and its trajectories for osteoporosis risk in the middle-aged and aged men of China. METHODS: The retrospective cohort study of 1546 men aged 69.74 ± 11.30 years conducted in Beijing, China from 2015 to 2022. And the incidence of primary osteoporosis was annually recorded. LDL-C trajectories were further identified by latent class growth model using repeated measurements of LDL-C. The association of baseline LDL-C for osteoporosis was estimated using hazard ratio (HR) with 95% CI in Cox proportional hazard model, while mean level and trajectories of LDL-C for osteoporosis were evaluated using odds ratio (OR) with 95% CI in logistic regression model. RESULTS: During the median 6.2-year follow-up period, 70 men developed primary osteoporosis. The higher level of baseline LDL-C (HR = 1.539, 95% CI: 1.012-2.342) and mean LDL-C (OR = 2.190, 95% CI: 1.443-3.324) were associated with higher risk of osteoporosis in men with coronary heart disease after adjusted for covariates. Compared with those in the LDL-C trajectory of low-stable decrease, participants with medium-fluctuant trajectory, whose longitudinal LDL-C started with a medium LDL-C level and appeared an increase and then decrease, were negatively associated with osteoporosis risk (OR = 2.451, 95% CI: 1.152-5.216). And participants with initially high LDL-C level and then a rapid decrease demonstrated a tendency towards reduced risk (OR = 0.718, 95% CI: 0.212-2.437). CONCLUSIONS Elevated LDL-C level and its long-term fluctuation may increase the risk of primary osteoporosis in men. Early controlling a stable level of LDL-C is also essential for bone health.

Objective:To explore the clinical phenotype and genetic characteristics of four patients with Phelan-McDermid syndrome (PMS) due to variants of SHANK3 gene. Methods:Four patients diagnosed with PMS at Guangzhou Women and Children′s Medical Center Liuzhou Hospital from January 2020 to January 2025 were selected as the study subjects. Clinical data of the patients were collected. Peripheral venous blood samples were collected from each patient for the extraction of genomic DNA, followed by whole-exome sequencing (WES) and validation by Sanger sequencing. Pathogenicity of candidate variants was rated based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), and multiple bioinformatic tools were used to assess the pathogenic effects of the variants. The study was approved by the Ethics Committee of the Guangzhou Women′s and Children′s Medical Center Liuzhou Hospital (Ethics No. 2025-007).Results:All four patients had exhibited language delay and intellectual disability (IQ 35 ~ 65). Some also presented with autism spectrum disorder and schizophrenia, albeit with significant phenotypic heterogeneity. All patients were found to harbor deletions of 22q13.33 region, ranging from 55.46 kb to 112.64 kb, primarily involving the SHANK3 gene. Conclusion:PMS is typically caused by deletions or mutations of the SHANK3 gene. The clinical manifestations are diverse, with developmental delay and intellectual disability being the most common. Accurate diagnosis requires integration of genetic testing and standardized clinical assessment. Genetic screening for suspected patients and at-risk pregnant women is recommended to facilitate their genetic counseling.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

OBJECTIVE: To explore the clinical phenotype and genetic characteristics of four patients with Phelan-McDermid syndrome (PMS) due to variants of SHANK3 gene. METHODS: Four patients diagnosed with PMS at Guangzhou Women and Children's Medical Center Liuzhou Hospital from January 2020 to January 2025 were selected as the study subjects. Clinical data of the patients were collected. Peripheral venous blood samples were collected from each patient for the extraction of genomic DNA, followed by whole-exome sequencing (WES) and validation by Sanger sequencing. Pathogenicity of candidate variants was rated based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), and multiple bioinformatic tools were used to assess the pathogenic effects of the variants. The study was approved by the Ethics Committee of the Hospital (Ethics No. 2025-007). RESULTS: All four patients had exhibited language delay and intellectual disability (IQ 35 ~ 65). Some also presented with autism spectrum disorder and schizophrenia, albeit with significant phenotypic heterogeneity. All patients were found to harbor deletions of 22q13.33 region, ranging from 55.46 Kb to 112.64 Kb, primarily involving the SHANK3 gene. CONCLUSION PMS is typically caused by deletions or mutations of the SHANK3 gene. The clinical manifestations are diverse, with developmental delay and intellectual disability being the most common. Accurate diagnosis requires integration of genetic testing and standardized clinical assessment. Genetic screening for suspected patients and at-risk pregnant women is recommended to facilitate their genetic counseling.
Child ; Humans ; Chromosome Deletion ; Chromosome Disorders/genetics* ; Chromosomes, Human, Pair 22/genetics* ; Exome Sequencing ; Nerve Tissue Proteins/genetics* ; Phenotype

With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.

Objective:To examine the effect of cumulative hemoglobin A 1c (HbA 1c) levels and insulin dosage on insulin resistance (IR)-related metabolic disturbances in newly diagnosed patients with type 1 diabetes (T1D). Methods:This retrospective cohort study included T1D patients admitted to the Second Xiangya Hospital of Central South University from November 2015 to March 2023. Clinical data collected comprised age, sex, disease duration, insulin dosage, body mass index, waist circumference, blood pressure, HbA 1c levels, islet autoantibodies, and fasting blood lipid profiles. IR-related metabolic disturbances assessed were overweight, obesity, central obesity, hypertension, and dyslipidemia. Cox regression and cluster analyses were applied to assess the influence of cumulative HbA 1c and insulin dosage on these metabolic disturbances. Results:A total of 235 patients were included, with 97 males (41.3%) and 138 females (58.7%). The median age was 19.8 (13.3, 31.1) years, and the median follow-up duration was 30.8 (20.8, 45.6) months. During follow-up, 41.6% (72/173) of patients developed IR-related metabolic disturbances. Multivariate Cox regression analysis revealed that a cumulative HbA 1c ≥60 mmol/mol was an independent risk factor for any IR-related metabolic disturbance [ HR (95% CI): 1.739 (1.067-2.835) ] and for triglyceride abnormalities [ HR (95% CI): 3.277 (1.176-9.127)]. Additionally, a cumulative insulin dosage ≥0.5 U·kg -1·d -1 was identified as an independent risk factor for overweight, obesity, or central obesity [ HR (95% CI): 2.374 (1.059-5.323)]. Cluster analysis further identified that patients with higher levels of cumulative HbA 1c and insulin dosage, particularly those with adolescent-onset diabetes, had the highest likelihood of developing hypertension ( HR=2.460, 95% CI 1.008-6.005), overweight/obesity/central obesity ( HR=2.707, 95% CI 1.062-6.900), triglyceride abnormalities ( HR=5.495, 95% CI 1.842-16.391), high-density lipoprotein cholesterol abnormalities ( HR=11.054, 95% CI 4.107-29.751), and any IR-related metabolic disturbance ( HR=5.833, 95% CI 2.602-13.077). Conclusions:Elevated cumulative HbA 1c and insulin dosage levels in T1D patients are associated with an increased risk of developing IR-related metabolic disturbances. These findings underscore the urgent need for novel therapeutic strategies tailored to this population.

Objective:To investigate the effect of a blended teaching mode based on medical knowledge graph and artificial intelligence (AI) teaching assistant on students' learning effectiveness and systematic thinking ability in teaching of pathogens and immunology.Methods:A controlled experimental design was employed, involving 114 clinical medical students ("5+3" integrated) enrolled in 2023 at Tianjin Medical University. They were divided into experimental group ( n=57) and control group ( n=57) based on their classes. A blended online-offline teaching mode based on medical knowledge graph and AI teaching assistant was used in the experimental group, and a blended online-offline teaching mode based on the online resources of this course was used in control group. Teaching effectiveness was assessed by comparing the scores of four chapter quizzes and the final exam between the two groups, as well as by analyzing student questionnaire responses. Data were analyzed using t test and χ2 test. Results:The experimental group achieved significantly higher scores in all four chapter quizzes and the final exam compared to the control group [(78.77±19.65) vs. (69.47±22.95), (84.56±14.02) vs. (76.49±16.20), (81.89±13.60) vs. (73.13±16.52), (81.56±21.28) vs. (73.16±16.27), (69.75±13.30) vs. (64.10±14.93), all P<0.05]. The questionnaire survey showed that 74.07% students ( n=40) believed that this blended teaching model stimulated their learning interest, 74.07% ( n=40) students believed that this blended teaching model enhanced their learning initiative, 81.48% ( n=44) students believed that this blended teaching model could help them construct the relationship between the old and new knowledge and thus improved memory retention, and 81.48% students b( n=44) elieved that this blended teaching model helped them integrate and summarize knowledge and construct systematic knowledge framework to improve their learning effectiveness. Conclusions:The blended teaching mode based on medical knowledge graph and AI teaching assistant is beneficial for cultivating students' systematic thinking ability and is helpful to improve their learning efficiency and effectiveness.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the effect of a blended teaching mode based on medical knowledge graph and artificial intelligence (AI) teaching assistant on students' learning effectiveness and systematic thinking ability in teaching of pathogens and immunology.Methods:A controlled experimental design was employed, involving 114 clinical medical students ("5+3" integrated) enrolled in 2023 at Tianjin Medical University. They were divided into experimental group ( n=57) and control group ( n=57) based on their classes. A blended online-offline teaching mode based on medical knowledge graph and AI teaching assistant was used in the experimental group, and a blended online-offline teaching mode based on the online resources of this course was used in control group. Teaching effectiveness was assessed by comparing the scores of four chapter quizzes and the final exam between the two groups, as well as by analyzing student questionnaire responses. Data were analyzed using t test and χ2 test. Results:The experimental group achieved significantly higher scores in all four chapter quizzes and the final exam compared to the control group [(78.77±19.65) vs. (69.47±22.95), (84.56±14.02) vs. (76.49±16.20), (81.89±13.60) vs. (73.13±16.52), (81.56±21.28) vs. (73.16±16.27), (69.75±13.30) vs. (64.10±14.93), all P<0.05]. The questionnaire survey showed that 74.07% students ( n=40) believed that this blended teaching model stimulated their learning interest, 74.07% ( n=40) students believed that this blended teaching model enhanced their learning initiative, 81.48% ( n=44) students believed that this blended teaching model could help them construct the relationship between the old and new knowledge and thus improved memory retention, and 81.48% students b( n=44) elieved that this blended teaching model helped them integrate and summarize knowledge and construct systematic knowledge framework to improve their learning effectiveness. Conclusions:The blended teaching mode based on medical knowledge graph and AI teaching assistant is beneficial for cultivating students' systematic thinking ability and is helpful to improve their learning efficiency and effectiveness.