1.Mechanism of Colquhounia Root Tablets against diabetic kidney disease via RAGE-ROS-PI3K-AKT-NF-κB-NLRP3 signaling axis.
Ming-Zhu XU ; Zhao-Chen MA ; Zi-Qing XIAO ; Shuang-Rong GAO ; Yi-Xin YANG ; Jia-Yun SHEN ; Chu ZHANG ; Feng HUANG ; Jiang-Rui WANG ; Bei-Lei CAI ; Na LIN ; Yan-Qiong ZHANG
China Journal of Chinese Materia Medica 2025;50(7):1830-1840
This study aimed to explore the therapeutic mechanisms of Colquhounia Root Tablets(CRT) in treating diabetic kidney disease(DKD) by integrating biomolecular network mining with animal model verification. By analyzing clinical transcriptomics data, an interaction network was constructed between candidate targets of CRT and DKD-related genes. Based on the topological eigenvalues of network nodes, 101 core network targets of CRT against DKD were identified. These targets were found to be closely related to multiple pathways associated with type 2 diabetes, immune response, and metabolic reprogramming. Given that immune-inflammatory imbalance driven by metabolic reprogramming is one of the key pathogenic mechanisms of DKD, and that many core network targets of CRT are involved in this pathological process, receptor for advanced glycation end products(RAGE)-reactive oxygen species(ROS)-phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT)-nuclear factor-κB(NF-κB)-NOD-like receptor family pyrin domain containing 3(NLRP3) signaling axis was selected as a candidate target for in-depth research. Further, a rat model of DKD induced by a high-sugar, high-fat diet and streptozotocin was established to evaluate the pharmacological effects of CRT and verify the expression of related targets. The experimental results showed that CRT could effectively correct metabolic disturbances in DKD, restore immune-inflammatory balance, and improve renal function and its pathological changes by inhibiting the activation of the RAGE-ROS-PI3K-AKT-NF-κB-NLRP3 signaling axis. In conclusion, this study reveals that CRT alleviates the progression of DKD through dual regulation of metabolic reprogramming and immune-inflammatory responses, providing strong experimental evidence for its clinical application in DKD.
Animals
;
Diabetic Nephropathies/metabolism*
;
Receptor for Advanced Glycation End Products/genetics*
;
NF-kappa B/genetics*
;
Signal Transduction/drug effects*
;
Rats
;
NLR Family, Pyrin Domain-Containing 3 Protein/genetics*
;
Proto-Oncogene Proteins c-akt/genetics*
;
Drugs, Chinese Herbal/administration & dosage*
;
Male
;
Phosphatidylinositol 3-Kinases/genetics*
;
Reactive Oxygen Species/metabolism*
;
Humans
;
Plant Roots/chemistry*
;
Rats, Sprague-Dawley
;
Tablets/administration & dosage*
2.Clinical and genetic characteristics of osteopetrosis in children.
Min WANG ; Ao-Shuang JIANG ; Cheng-Lin ZHU ; Jie WANG ; Ya-Ping WANG ; Shan GAO ; Yan LI ; Tian-Ping CHEN ; Hong-Jun LIU ; Jian WANG
Chinese Journal of Contemporary Pediatrics 2025;27(5):568-573
OBJECTIVES:
To study the clinical and genetic characteristics of osteopetrosis (OPT) in children.
METHODS:
A retrospective analysis was performed on the clinical data of 14 children with OPT. Whole-exome sequencing was used to detect pathogenic genes, and clinical phenotypes and genotypic features were summarized.
RESULTS:
Among the 14 children (10 males and 4 females), the median age at diagnosis was 8 months. Clinical manifestations included systemic osteosclerosis (14 cases, 100%), anemia (12 cases, 86%), infections (10 cases, 71%), thrombocytopenia (9 cases, 64%), hepatosplenomegaly (8 cases, 57%), and developmental delay (5 cases, 36%). Malignant osteopetrosis (MOP) cases had lower platelet counts, creatine kinase isoenzyme, and serum calcium levels, but higher white blood cell counts, lactate dehydrogenase, and alkaline phosphatase levels compared to non-MOP cases (P<0.05). Genetic testing identified 15 variants in 12 patients, including 8 variants in the CLCN7 gene (53%), 6 in the TCIRG1 gene (40%), and 1 in the TNFRSF11A gene (7%). Three novel CLCN7 variants were identified: c.2351G>C, c.1215-43C>T, and c.1534G>A. All four patients with TCIRG1 variants exhibited MOP clinical phenotypes. Of the seven patients with CLCN7 variants, 4 presented with intermediate OPT, 2 with benign OPT, and 1 with MOP.
CONCLUSIONS
Clinical phenotypes of OPT in children are heterogeneous, predominantly involving CLCN7 and TCIRG1 gene variants, with a correlation between clinical phenotypes and genotypes.
Humans
;
Osteopetrosis/genetics*
;
Male
;
Female
;
Infant
;
Child, Preschool
;
Retrospective Studies
;
Vacuolar Proton-Translocating ATPases/genetics*
;
Child
;
Chloride Channels/genetics*
;
Mutation
;
Receptor Activator of Nuclear Factor-kappa B
3.Influence of Outdoor Light at Night on Early Reproductive Outcomes of In Vitro Fertilization and Its Threshold Effect: Evidence from a Couple-Based Preconception Cohort Study.
Wen Bin FANG ; Ying TANG ; Ya Ning SUN ; Yan Lan TANG ; Yin Yin CHEN ; Ya Wen CAO ; Ji Qi FANG ; Kun Jing HE ; Yu Shan LI ; Ya Ning DAI ; Shuang Shuang BAO ; Peng ZHU ; Shan Shan SHAO ; Fang Biao TAO ; Gui Xia PAN
Biomedical and Environmental Sciences 2025;38(8):1009-1015
4.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
5.Pathophysiological classification and clinical characteristics of hyperuricemia
Le YAN ; Shuang LIU ; Zhiwei CAO ; Ronger GU ; Shaoling YANG ; Hang SUN ; Qi CHEN ; Cuiling ZHU ; Haibing CHEN
Chinese Journal of Endocrinology and Metabolism 2025;41(8):627-633
Objective:To explore the clinical and biochemical characteristics of patients with hyperuricemia according to different pathophysiological subtypes. This may facilitate rapid identification of each subtype in clinical settings and provide evidence for personalized urate-lowering treatment.Methods:Patients diagnosed with hyperuricemia at the Department of Endocrinology and Metabolism, Tenth People′s Hospital of Tongji University between October 2015 and January 2024 were included. Based on 24-h urinary uric acid excretion(UUE) and the fractional excretion of uric acid(FEUA), patients were classified into four subtypes: renal uric acid underexcretion type(RUE), renal uric acid overload type(ROL), combined type and renal normal type. Clinical and biochemical variables-including sex, age, BMI, smoking history, comorbidities, blood glucose, and serum uric acid-were analyzed. Binary logistic regression was used to identify factors associated with each subtype.Results:Among 2 073 patients with hyperuricemia, 55.8% were RUE type, 6.9% were ROL type, 31.3% were combined type and 6.0% were renal normal type. RUE type had lower blood glucose levels and fewer cases of diabetes [ OR=0.685(95% CI 0.478-0.980), P<0.05]. ROL type showed a higher incidence of tophi, positively correlated with smoking history [ OR=1.672(95% CI 1.009-2.771), P<0.05], and negatively correlated with serum uric acid levels [ OR=0.994(95% CI 0.990-0.998), P=0.001]. Combined type had the youngest onset age, shortest disease duration, and the fewest comorbidities, and was associated with higher BMI [ OR=1.035(95% CI 1.001-1.070), P<0.05]. Renal normal type had the oldest age of onset, the highest proportion of female patients and comorbidities, and was associated with lower serum uric acid levels[ OR=0.994(95% CI 0.989-0.998), P=0.007], higher BMI[ OR=1.064(95% CI 1.003-1.129), P<0.05], and increased tophi incidence[ OR=2.261(95% CI 1.206-4.237), P=0.011]. Conclusion:Each pathophysiological subtype of hyperuricemia exhibits distinct clinical and biochemical characteristics, which may serve as useful references for subtype identification and personalized management in clinical practice.
6.Sedentary behavior patterns and related factors in patients with stable schizophrenia
Huijie LU ; Ping DONG ; Yanbo WANG ; Shuang ZHOU ; Qiuliang XU ; Longmei ZHU ; Yan JIN ; Fang WANG
Chinese Journal of Psychiatry 2025;58(11):843-850
Objective:To investigate the status of sedentary behavior and its influencing factors among inpatients with stable schizophrenia, providing empirical evidence for developing interventions to reduce sedentary behavior.Methods:A cross-sectional survey design was used to prospectively collect clinical data from 166 inpatients with stable schizophrenia (97 males, 69 females, mean age 56.4±8.4 years) hospitalized at the Shanghai Mental Health Center affiliated with Shanghai Jiao Tong University School of Medicine from February 2024 to May 2024. Sedentary behavior time was assessed using the Sedentary Behavior Questionnaire (SBQ), daily step count was measured via pedometers, and negative schizophrenic symptoms were evaluated using the Scale for the Assessment of Negative Symptoms (SANS). Patients were divided into a non-sedentary behavior group (≥5 000 steps/day, 66 cases) and a sedentary behavior group (<5 000 steps/day, 100 cases). Clinical variables were compared between the two groups, and binary logistic regression was used to identify influencing factors of sedentary behavior.Results:Stable inpatients with schizophrenia exhibited high levels of sedentary behavior, with an average daily sedentary time of (8.03±2.33) hours and a median daily step count of 3 352 (1 258-5 506) steps. Significant differences were observed between sedentary and non-sedentary behavior groups in Age ( t=-2.38),hospitalization duration ( Z=-1.53),blunted affect ( t=-8.37),poverty of thought ( t=-2.45),avolition ( t=-2.45),impoverished interests/social engagement ( t=-2.41),abdominal obesity ( χ2=9.18),and open vs. restricted hospital/wards environment ( χ2=8.88)(all P<0.05). Binary logistic regression analysis identified that hospital/wards environment ( OR=0.314, 95 %CI: 0.125-0.787),hospitalization duration ( OR=1.001, 95 %CI: 1.000-1.001),and the negative symptom of blunted affect ( OR=3.256, 95 %CI: 1.960-5.407)(all P<0.05) were significantly influencing factors for sedentary behavior in patients with stable schizophrenia. Conclusion:Hospitalized patients with stable schizophrenia exhibit high levels of sedentary behavior. Hospital/wards environment and blunted affect are significant factors influencing sedentary behavior.
7.Mendelian randomization analysis reveals genetic associations between pancreatic cancer and its risk factors
Shuang LI ; Ben LIU ; Wei XIANG ; An YAN ; Wenzhe GAO ; Hongwei ZHU ; Xiao YU
Chinese Journal of Hepatobiliary Surgery 2025;31(10):762-767
Objective:To clarify the genetic associations between obesity, diabetes, smoking, non-alcoholic fatty liver disease, acute and chronic pancreatitis, and pancreatic cancer risk.Methods:Summary data from genome-wide association studies (GWAS) of individuals of European descent were used. Obesity, alcohol consumption, diabetes, and acute and chronic pancreatitis data for the UK population were obtained from the GWAS catalog, while alcohol consumption, non-alcoholic fatty liver disease, occasional smoking, and regular smoking data were obtained from the UK biobank. Pancreatic cancer-related data for the Finnish population were sourced from the latest R11 version of the Finnish database. Two-sample Mendelian randomization (MR) analysis was conducted on the associations between the aforementioned risk factors and pancreatic cancer using five MR methods, primarily inverse variance weighting. The robustness of the results was assessed through Q heterogeneity tests, pleiotropy tests, MR-PRESSO analysis, and reverse MR analysis.Results:Obesity showed a significant positive association with pancreatic cancer risk ( OR=1.407, 95% CI: 1.100-1.714, P=0.030), and the results were robust based on Q heterogeneity tests, pleiotropy tests, MR-PRESSO, and reverse MR analysis (all P>0.05). However, no significant associations were found between pancreatic cancer risk and alcohol consumption ( P=0.330), heavy drinking ( P=0.382), type 1 diabetes ( P=0.674), type 2 diabetes ( P=0.825), occasional smoking ( P=0.607), regular smoking ( P=0.758), non-alcoholic fatty liver disease ( P=0.287), acute pancreatitis ( P=0.336), or chronic pancreatitis ( P=0.545). Conclusion:This study further confirms the strong genetic association between obesity and increased pancreatic cancer risk.
8.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
9.Pathophysiological classification and clinical characteristics of hyperuricemia
Le YAN ; Shuang LIU ; Zhiwei CAO ; Ronger GU ; Shaoling YANG ; Hang SUN ; Qi CHEN ; Cuiling ZHU ; Haibing CHEN
Chinese Journal of Endocrinology and Metabolism 2025;41(8):627-633
Objective:To explore the clinical and biochemical characteristics of patients with hyperuricemia according to different pathophysiological subtypes. This may facilitate rapid identification of each subtype in clinical settings and provide evidence for personalized urate-lowering treatment.Methods:Patients diagnosed with hyperuricemia at the Department of Endocrinology and Metabolism, Tenth People′s Hospital of Tongji University between October 2015 and January 2024 were included. Based on 24-h urinary uric acid excretion(UUE) and the fractional excretion of uric acid(FEUA), patients were classified into four subtypes: renal uric acid underexcretion type(RUE), renal uric acid overload type(ROL), combined type and renal normal type. Clinical and biochemical variables-including sex, age, BMI, smoking history, comorbidities, blood glucose, and serum uric acid-were analyzed. Binary logistic regression was used to identify factors associated with each subtype.Results:Among 2 073 patients with hyperuricemia, 55.8% were RUE type, 6.9% were ROL type, 31.3% were combined type and 6.0% were renal normal type. RUE type had lower blood glucose levels and fewer cases of diabetes [ OR=0.685(95% CI 0.478-0.980), P<0.05]. ROL type showed a higher incidence of tophi, positively correlated with smoking history [ OR=1.672(95% CI 1.009-2.771), P<0.05], and negatively correlated with serum uric acid levels [ OR=0.994(95% CI 0.990-0.998), P=0.001]. Combined type had the youngest onset age, shortest disease duration, and the fewest comorbidities, and was associated with higher BMI [ OR=1.035(95% CI 1.001-1.070), P<0.05]. Renal normal type had the oldest age of onset, the highest proportion of female patients and comorbidities, and was associated with lower serum uric acid levels[ OR=0.994(95% CI 0.989-0.998), P=0.007], higher BMI[ OR=1.064(95% CI 1.003-1.129), P<0.05], and increased tophi incidence[ OR=2.261(95% CI 1.206-4.237), P=0.011]. Conclusion:Each pathophysiological subtype of hyperuricemia exhibits distinct clinical and biochemical characteristics, which may serve as useful references for subtype identification and personalized management in clinical practice.
10.Sedentary behavior patterns and related factors in patients with stable schizophrenia
Huijie LU ; Ping DONG ; Yanbo WANG ; Shuang ZHOU ; Qiuliang XU ; Longmei ZHU ; Yan JIN ; Fang WANG
Chinese Journal of Psychiatry 2025;58(11):843-850
Objective:To investigate the status of sedentary behavior and its influencing factors among inpatients with stable schizophrenia, providing empirical evidence for developing interventions to reduce sedentary behavior.Methods:A cross-sectional survey design was used to prospectively collect clinical data from 166 inpatients with stable schizophrenia (97 males, 69 females, mean age 56.4±8.4 years) hospitalized at the Shanghai Mental Health Center affiliated with Shanghai Jiao Tong University School of Medicine from February 2024 to May 2024. Sedentary behavior time was assessed using the Sedentary Behavior Questionnaire (SBQ), daily step count was measured via pedometers, and negative schizophrenic symptoms were evaluated using the Scale for the Assessment of Negative Symptoms (SANS). Patients were divided into a non-sedentary behavior group (≥5 000 steps/day, 66 cases) and a sedentary behavior group (<5 000 steps/day, 100 cases). Clinical variables were compared between the two groups, and binary logistic regression was used to identify influencing factors of sedentary behavior.Results:Stable inpatients with schizophrenia exhibited high levels of sedentary behavior, with an average daily sedentary time of (8.03±2.33) hours and a median daily step count of 3 352 (1 258-5 506) steps. Significant differences were observed between sedentary and non-sedentary behavior groups in Age ( t=-2.38),hospitalization duration ( Z=-1.53),blunted affect ( t=-8.37),poverty of thought ( t=-2.45),avolition ( t=-2.45),impoverished interests/social engagement ( t=-2.41),abdominal obesity ( χ2=9.18),and open vs. restricted hospital/wards environment ( χ2=8.88)(all P<0.05). Binary logistic regression analysis identified that hospital/wards environment ( OR=0.314, 95 %CI: 0.125-0.787),hospitalization duration ( OR=1.001, 95 %CI: 1.000-1.001),and the negative symptom of blunted affect ( OR=3.256, 95 %CI: 1.960-5.407)(all P<0.05) were significantly influencing factors for sedentary behavior in patients with stable schizophrenia. Conclusion:Hospitalized patients with stable schizophrenia exhibit high levels of sedentary behavior. Hospital/wards environment and blunted affect are significant factors influencing sedentary behavior.

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