1.Clinical Efficacy of Tangning Tongluo Tablets for Nonproliferative Diabetic Retinopathy
Fuwen ZHANG ; Junguo DUAN ; Wen XIA ; Tiantian SUN ; Yuheng SHI ; Shicui MEI ; Xiangxia LUO ; Xing LI ; Yujie PAN ; Yong DENG ; Chuanlian RAN ; Hao CHEN ; Li PEI ; Shuyu YANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(3):132-139
		                        		
		                        			
		                        			ObjectiveTo observe the clinical efficacy and safety of Tangning Tongluo tablets in the treatment of nonproliferative diabetic retinopathy (DR). MethodsFourteen research centers participated in this study, which spanned a time interval from September 2021 to May 2023. A total of 240 patients with nonproliferative DR were included and randomly assigned into an observation group (120 cases) and a control group (120 cases). The observation group was treated with Tangning Tongluo tablets, and the control group with calcium dobesilate capsules. Both groups were treated for 24 consecutive weeks. The vision, DR progression rate, retinal microhemangioma, hemorrhage area, exudation area, glycosylated hemoglobin (HbA1c) level, and TCM syndrome score were assessed before and after treatment, and the safety was observed. ResultsThe vision changed in both groups after treatment (P<0.05), and the observation group showed higher best corrected visual acuity (BCVA) than the control group (P<0.05). The DR progression was slow with similar rates in the two groups. The fundus hemorrhage area and exudation area did not change significantly after treatment in both groups, while the observation group outperformed the control group in reducing the fundus hemorrhage area and exudation area. There was no significant difference in the number of microhemangiomas between the two groups before treatment. After treatment, the number of microhemangiomas decreased in both the observation group (Z=-1.437, P<0.05) and the control group (Z=-2.238, P<0.05), and it showed no significant difference between the two groups. As the treatment time prolonged, the number of microhemangiomas gradually decreased in both groups. There was no significant difference in the HbA1c level between the two groups before treatment. After treatment, the decline in the HbA1c level showed no significant difference between the two groups. The TCM syndrome score did not have a statistically significant difference between the two groups before treatment. After treatment, neither the TCM syndrome score nor the response rate had significant difference between the two groups. With the extension of the treatment time, both groups showed amelioration of TCM syndrome compared with the baseline. ConclusionTangning Tongluo tablets are safe and effective in the treatment of nonproliferative DR, being capable of improving vision and reducing hemorrhage and exudation in the fundus. 
		                        		
		                        		
		                        		
		                        	
2.Research Progress on Human Umbilical Cord Mesenchymal Stem Cells in the Treatment of Knee Osteoarthritis
Jin GONG ; Jinjin ZHANG ; Lili CHEN ; Hui WANG ; Yanchao XING
Medical Journal of Peking Union Medical College Hospital 2025;16(1):75-82
Knee osteoarthritis (KOA) is a prevalent degenerative joint disease characterized by synovial inflammation, cartilage loss. Often manifesting as joint pain and limited mobility, it severely affects the quality of life of patients. Traditional treatment methods such as pharmacological injections and surgical interventions primarily aim to alleviate symptoms but have limited effects on cartilage repair. Human umbilical cord mesenchymal stem cells (hUC-MSCs), due to their anti-inflammatory and chondrogenic capabilities, is considered a new hope for the treatment of KOA. This article synthesizes the latest research findings from both domestic and international sources to discuss the theoretical basis for the clinical application of hUC-MSCs in treating KOA, clinical study design, and efficacy evaluation. It also addresses the challenges in the clinical application of hUC-MSCs and explores future directions, in the hope of providing feasible theoretical support for the treatment of KOA with hUC-MSCs.
3.Blood management strategy for massive transfusion patients in frigid plateau region
Haiying WANG ; Jinjin ZHANG ; Lili CHEN ; Xiaoli SUN ; Cui WEI ; Yongli HUANG ; Yingchun ZHU ; Chong CHEN ; Yanchao XING
Chinese Journal of Blood Transfusion 2025;38(2):268-273
		                        		
		                        			
		                        			 [Objective] To explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×1012/L, Hb 106 g/L, HCT 30.40%, PLT 115.00×109/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×1012/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×109/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.
		                        		
		                        		
		                        		
		                        	
4.NAD+ Ameliorates Endothelial Dysfunction in Hypertension via Activation of SIRT3/IDH2 Signal Pathway
Yumin QIU ; Xi CHEN ; Jianning ZHANG ; Zhangchi LIU ; Qiuxia ZHU ; Meixin ZHANG ; Jun TAO ; Xing WU
Journal of Sun Yat-sen University(Medical Sciences) 2025;46(1):70-80
		                        		
		                        			
		                        			ObjectiveTo investigate the effect of nicotinamide adenine dinucleotide on vascular endothelial injury in hypertension and its molecular mechanism. MethodsC57BL/6J mice were randomly divided into saline group (Saline) and hypertension group (Ang Ⅱ, which were infused with Ang Ⅱ via subcutaneously implanted osmotic pumps), and supplemented daily with nicotinamide mononucleotide (300 mg/kg), a precursor of NAD+. Blood pressure, endothelial relaxation function and pulse wave velocity were measured after 4 weeks. Wound healing assay and adhesion assay were used to evaluate the function of endothelial cells in vitro. mtROS levels were detected by immunofluorescence staining. RT-PCR was used to detect the mRNA expression of mtDNA, SIRT3 and isocitrate dehydrogenase 2 (IDH2). 8-hydroxy-2'-deoxyguanosine levels were detected by enzyme-linked immunosorbent assay. The protein expression levels of p-eNOS, eNOS, SIRT3 and IDH2 were detected by Western blot. ResultsNMN supplementation reduced blood pressure (P<0.001) and improved endothelial function and arterial stiffness (P<0.001) in hypertensive mice. In vitro, NMN improved endothelial function in AngII-stimulated endothelial cells (P<0.05) and attenuated mitochondrial oxidative stress levels (P<0.001). Mechanistically, NMN elevated SIRT3 activity (P<0.001), which subsequently enhanced IDH activity (P<0.001) and reduced oxidative stress levels in endothelial cells. Conversely, knockdown of IDH2 would reverse the effect of SIRT3 in improving endothelial function (P<0.001). ConclusionNAD+ lowers blood pressure and enhances vascular function in hypertension by reducing the level of oxidative stress in endothelial cells through activation of the SIRT3/IDH2 signal pathway. 
		                        		
		                        		
		                        		
		                        	
5.Analysis of clinical infection characteristics of multidrug-resistant organisms in hospitalized patients in a tertiary sentinel hospital in Shanghai from 2021 to 2023
Qi MAO ; Tenglong ZHAO ; Xihong LYU ; Zhiyuan GU ; Bin CHEN ; Lidi ZHAO ; Xifeng LI ; Xing ZHANG ; Liang TIAN ; Renyi ZHU
Shanghai Journal of Preventive Medicine 2025;37(2):156-159
		                        		
		                        			
		                        			ObjectiveTo understand the infection characteristics of multidrug-resistant organisms (MDROs) in hospitalized patients in a tertiary sentinel hospital in Shanghai, so as to provide an evidence for the development of targeted prevention and control measures. MethodsData of MDROs strains and corresponding medical records of some hospitalized patients in a hospital in Shanghai from 2021 to 2023 were collected, together with an analysis of the basic information, clinical treatment, underlying diseases and sources of sample collection. ResultsA total of 134 strains of MDROs isolated from hospitalized patients in this hospital were collected from 2021 to 2023 , including 63 strains of methicillin-resistant Staphylococcus aureus (MRSA), 57 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), and 14 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP). Of the 134 strains, 30 strains were found in 2021, 47 strains in 2022 and 57 strains in 2023. The male-to-female ratio of patients was 2.05∶1, with the highest percentage (70.90%) in the age group of 60‒<90 years. The primary diagnosis was mainly respiratory disease, with lung and respiratory tract as the cheif infection sites. There was no statistically significant difference in the distribution of strains between different genders and infection sites (P>0.05). However, the differences in the distribution of strains between different ages and primary diagnosis were statistically significant (P<0.05). Patients who were admitted to the intensive care unit (ICU), had urinary tract intubation, were not artery or vein intubated, were not on a ventilator, were not using immunosuppresants or hormones, and were not applying radiotherapy or chemotherapy were in the majority. There was no statistically significant difference in the distribution of strains for whether received radiotherapy or chemotherapy or not (P>0.05), while the differences in the distribution of strains with ICU admission history, urinary tract intubation, artery or vein intubation, ventilator use, and immunosuppresants or hormones use or not were statistically significant (all P<0.05). The type of specimen was mainly sputum, the hospitalized ward was mainly comprehensive ICU, the sampling time was mainly in the first quarter throughout the year, the number of underlying diseases was mainly between 1 to 2 kinds, the application of antibiotics ≥4 kinds, and those who didn’t receive any surgery recently accounted for the most. There were statistically significant differences in the distribution of strains between different specimen types, wards occupied and history of ICU stay (P<0.05), but no statistically significant difference in the distribution of strains between different sampling times, number of underlying diseases and types of antibiotics applied (P>0.05). ConclusionThe situation of prevention and control on MDROs in this hospital is still serious. Focus should be placed on high-risk factors’ and infection monitoring and preventive measures should be strengthened to reduce the incidence rate of MDROs infection. 
		                        		
		                        		
		                        		
		                        	
6.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
		                        		
		                        			 Objective:
		                        			Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. 
		                        		
		                        			Methods:
		                        			Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). 
		                        		
		                        			Results:
		                        			LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. 
		                        		
		                        			Conclusion
		                        			Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.	 
		                        		
		                        		
		                        		
		                        	
7.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
		                        		
		                        			 Objective:
		                        			Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. 
		                        		
		                        			Methods:
		                        			Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). 
		                        		
		                        			Results:
		                        			LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. 
		                        		
		                        			Conclusion
		                        			Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.	 
		                        		
		                        		
		                        		
		                        	
8.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
		                        		
		                        			 Objective:
		                        			Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. 
		                        		
		                        			Methods:
		                        			Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). 
		                        		
		                        			Results:
		                        			LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. 
		                        		
		                        			Conclusion
		                        			Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.	 
		                        		
		                        		
		                        		
		                        	
9.Effect of Different Time Interventions of Yangxin Tongmai Formula (养心通脉方) on DNA Methylation in Rat Models of Premature Coronary Heart Disease with Blood Stasis Syndrome
Xing CHEN ; Zixuan YU ; Shumeng ZHANG ; Yanjuan LIU ; Shuangyou DENG ; Ying WANG ; Lingli CHEN ; Jie LI
Journal of Traditional Chinese Medicine 2025;66(11):1165-1173
		                        		
		                        			
		                        			ObjectiveTo observe the effect of Yangxin Tongmai Formula (养心通脉方) by midnight-noon ebb-flow administration method for rat models of premature coronary heart disease (PCHD) with blood stasis syndrome, and to explore the possible mechanism of action from the perspective of DNA methylation differential gene expression. MethodsThere were 3 SD rats in each of the blank group, model group and Yangxin Tongmai Formula group, and the rats in the model group and Yangxin Tongmai Formula group were fed with high-fat chow plus vitamin D3 by gavage plus isoproterenol hydrochloride by subcutaneous injection to construct rat models of PCHD with blood stasis syndrome. After successful modelling, rats in Yangxin Tongmai Formula group were gavaged with 18 g/(kg‧d) of Yangxin Tongmai Formula, and rats in blank group and the model group were gavaged with 4 ml/(kg‧d) of 0.9% NaCl solution, and serum samples of rats in each group were collected for DNA methylation sequencing after 3 weeks to screen for the relevant DNA methylation differentiation genes. In addition, rats with successful modelling of PCHD with blood stasis were randomly divided into model group, Yangxin Tongmai Formula with midnight-noon ebb-flow administration method group [18 g/(kg‧d) of Yangxin Tongmai Formula was gavaged twice in the heart channel period (12:00) and pericardium channel period (20:00)], the Yangxin Tongmai Formula control group [18 g/(kg‧d) of Yangxin Tongmai Formula was gavaged twice at 8:00 and 18:00] and the Atorvastatin Calcium group [atorvastatin calcium tablets solution 1.8 mg/(kg‧d) at the same intervention time as that in Yangxin Tongmai Formula control group], and set up a blank group of 8 rats in each group. The model group and blank group were gavaged with 0.9% NaCl solution 4 ml/(kg‧d) for the same time as the Yangxin Tongmai Formula control group. After 3 weeks of gavage, the blood lipids [including total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL)] levels of rats in each group were detected; the HE staining of myocardial tissues and thoracic aorta was used to observe the pathomorphological changes; the levels of serum inflammation indexes [tumour necrosis factor alpha (TNF-alpha), lipopolysaccharide (LPS), and interleukin 10 (IL-10)] were detected; immunoprecipitation-realtime fluorescence quantitative PCR was used to detect the relative expression of cardiac tissue screening differential genes. ResultsThe genes screened for differentially methylated regions were calmodulin 2 (Calm2), calcium voltage-gated channel subunit α1s (Cacna1s), and phospholipase Cβ1 (Plcb1). Compared with the blank group, rats in the model group showed elevated levels of TC, LDL, TNF-α and LPS, and decreased levels of HDL and IL-10 (P<0.05 or P<0.01); HE staining showed obvious swelling of myocardial fibres, accompanied by a large number of inflammatory cell infiltration, and thickening of the inner wall of the aortic vessels with internal wall damage, which was visible as a large number of lipid cholesterol crystals and obvious inflammatory cell infiltration. Compared with the model group, the TC, LDL, TNF-α and LPS contents of rats in the Yangxin Tongmai Formula with midnight-noon ebb-flow administration method group, the Yangxin Tongmai Formula control group, and the atorvastatin calcium group all reduced, and the contents of HDL and IL-10 all elevated (P<0.05), with the improvement of myocardial tissue damage and the reduction of inflammatory infiltration, and the improvement of the damage of the inner lining of the thoracic aorta and the reduction of lipid infiltration. Compared with Yangxin Tongmai Formula control group, LDL, TNF-α and LPS contents reduced, and IL-10 contents increased in the midnight-noon ebb-flow administration method group (P<0.05). Compared with the model group, the relative expression of Calm2 and Plcb1 genes decreased and the relative expression of Cacna1s gene increased in Yangxin Tongmai Formula control group and the midnight-noon ebb-flow administration method group (P<0.05); compared with the Yangxin Tongmai Formula control group, the relative expression of Calm2 gene decreased and the relative expression of Cacna1s gene increased in the midnight-noon ebb-flow administration method group (P<0.05). ConclusionThe intervention of Yangxin Tongmai Formula in the heart channel period (12:00) and pericardium channel period (20:00) was more effective in improving the blood lipid level, inhibiting inflammation, and improving myocardial tissue damage in rats of PCHD with blood stasis syndrome, and Calm2 and Cacna1s genes may be the key targets of Yangxin Tongmai Formula in intervening the blood stasis syndrome of PCHD. 
		                        		
		                        		
		                        		
		                        	
10.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
		                        		
		                        			 Objective:
		                        			Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. 
		                        		
		                        			Methods:
		                        			Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). 
		                        		
		                        			Results:
		                        			LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. 
		                        		
		                        			Conclusion
		                        			Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.	 
		                        		
		                        		
		                        		
		                        	
            
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