1.Herbal Textual Research on Cynanchi Atrati Radix et Rhizoma in Famous Classical Formulas
Xiaoqi JING ; Minna GUO ; Haihua WANG ; Juan LI ; Fusheng ZHANG ; Zhilai ZHAN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(4):208-216
This article systematically reviews and verifies the name, origin, production area, quality evaluation, harvesting, processing and other aspects of Cynanchi Atrati Radix et Rhizoma(CARR) by consulting relevant ancient and modern literature, in order to provide a basis for the development and utilization of famous classical formulas containing this herb. Through textual research, Baiwei has been the official name for CARR, though it also bears alternative names such as Chuncao, Popo Zhenxianbao, Longdan Baiwei. The mainstream base is the roots and rhizomes of Cynanchum atratum. Historical records indicate primary producing areas include Shandong, Anhui, Jiangsu, Shaanxi and Shanxi. Since the late Ming dynasty, varieties from Juxian, Yishui and Rizhao in Shandong have been highly regarded as authentic, commonly known as eastern Baiwei. Since modern times, its quality has been summarized as fine, slender, and straight fibrous roots, pale yellow exterior, whiter interior, and dryness with easy breakability are considered superior. The harvesting time before the Song dynasty was on the third day of the third lunar month, but after the Song dynasty, harvesting was possible in both spring and autumn. The initial processing methods of CARR in ancient times included drying in the shade, removing Lu(the little rhizomes which are on tap of roots), and removing mustaches, modern methods involve washing and sun-drying. During the Northern and Southern dynasties, processing methods included steaming. In the Song dynasty, drying and light stir-frying were predominant, while wine washing emerged in the Ming dynasty. Modern practices primarily involve using raw, stir-frying or honey processing. Regarding the medicinal properties of CARR, both ancient and modern texts agree it has a bitter and salty taste and is non-toxic. Records prior to the Qing dynasty predominantly describe its nature as extremely cold, while mainstream herbal texts after the Qing dynasty generally characterize it as cold. Before the Ming dynasty, there were no records of its meridian tropism. It was not until the Qing dynasty that it was recorded in the lung meridian. Modern records mainly refer to the stomach, liver, and kidney meridians. Throughout history, its main functions have been to clear heat, diuresis, nourish Yin, and replenish essence, primarily treating Yin deficiency and fever syndrome. Based on the research results, it is suggested that when developing famous classical formulas containing CARR, the dried roots and rhizomes of C. atratum can be selected as its medicinal source. If there are no specific processing requirements, raw products can be selected as medicine. If the processing requirements are specified, corresponding processed products can be selected as medicine according to the original formula requirements.
2.Altered Lymphocyte Subsets in Perioperative Cancer Patients Before and After Septic Shock: Characteristics and Prognostic Implications
Miao WEI ; Lili YANG ; Xiaoyan LI ; Huifang LYU ; Yan DUAN
Medical Journal of Peking Union Medical College Hospital 2026;17(1):86-97
To investigate the changes in peripheral blood immune cells before and after the onset of septic shock in patients with malignant tumors, and to analyze the relationship between these immune cells and patient prognosis. A retrospective study was conducted, enrolling perioperative tumor patients who were transferred to the intensive care unit (ICU) due to septic shock at Shanxi Provincial Cancer Hospital between October 2018 and December 2019.Changes in lymphocyte counts and subsets were compared before and after septic shock (measured prior to septic shock onset and within 72 hours after onset).A multivariate Logistic regression model was used to analyze the relationship between these immune indicators and the 28-day mortality risk in tumor patients following septic shock. A total of 47 tumor patients transferred to the ICU due to septic shock were included.There were 32 males and 15 females, with a mean age of (63.9±11.2) years.Gastrointestinal tumors were the most common tumor type (76.60%, 36/47), and abdominal/pelvic infection (65.96%, 31/47) was the primary source of infection.Within 28 days after ICU transfer, 12 patients died and 35 survived. Compared to pre-septic shock levels, lymphocyte counts significantly decreased after septic shock[530(300, 830) cells/μL Perioperative tumor patients experience acute depletion of peripheral blood lymphocyte subsets following septic shock.Among various immune indicators, regulatory T cell count serves as an independent predictor of short-term mortality risk.Evaluating baseline immune function in such patients may help optimize treatment strategies and improve overall prognosis.
3.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
4.Discussion on the generative principles and moral cognitive capacity of artificial life
Chinese Medical Ethics 2026;39(1):12-21
Artificial life is the goal pursued by cognitive philosophy, cognitive science, and artificial intelligence, yet its realization has consistently encountered challenge. The generative mechanisms of artificial life include self-organization, emergence, and agency, all of which are difficult to precisely grasp in the cognitive paradigm. Evolutionary biology demonstrates that natural life possesses extraordinary adaptability. For artificial artifacts, the way to endow them with life-like characteristics involves first transforming them into self-organizing systems with emergence, and then evolving them into embodied agents possessing agency and moral cognitive capacity. This process reveals the functional and informational properties of artificial life, manifesting its adaptive representational character.
5.Application of Recombinant Collagen in Biomedicine
Huan HU ; Hong ZHANG ; Jian WANG ; Li-Wen WANG ; Qian LIU ; Ning-Wen CHENG ; Xin-Yue ZHANG ; Yun-Lan LI
Progress in Biochemistry and Biophysics 2025;52(2):395-416
Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.
6.Assocation of family environment and depressive symptoms among primary and secondary school students in Shanxi province
YANG Yang, YANG Le, QU Hongfei, YAO Dianrui, LI Zhenhao, GUO Dan
Chinese Journal of School Health 2025;46(1):86-91
Objective:
To explore the assocation of the family environment and depressive symptoms among primary and middle school students, so as to provide suggestions for further maximizing the utility of family environment in the growth of primary and secondary school students, as well as prevention and intervention of depressive symptoms among children and adolescents.
Methods:
From June to July 2024, through a multistage cluster random sampling method, 8 800 primary and middle school students aged 10 to 18 from 36 schools in 3 cities (Datong, Lvliang, Linfen) in Shanxi Province. A self designed questionnaire was used to conduct a family environment survey, including family socioeconomic conditions, family structure, family parenting behavior, family member health behavior, etc; and the depression symptoms of primary and secondary school students were investigated by Patient Health Questionnaire-9. The χ 2 test and binary Logistic regression to method were used to analyze the association of the family environment with depressive symptoms among primary and secondary school students, and to analyze gender and urban-rural heterogeneity in this association.
Results:
The detection rate of depressive symptoms among primary and middle school students was 46.7% ( n = 4 111 ). Among them, the detection rates of depressive symptoms for male and female students were 45.7% and 47.7% respectively, and the detection rates for rural and urban students were 48.0% and 44.9% respectively. The results of binary Logistic regression model showed that in the family environment, factors such as the father s education level (junior high school: OR =0.84), self assessed family socio economic status (average: OR =0.78, good: OR =0.80), parental support and understanding (yes: OR = 0.55 ), family atmosphere (harmonious: OR =0.66), living arrangement (living only with father or mother: OR =1.31, living with parents and grandparents: OR =1.19), and family rearing style (combining punishment and reward: OR =1.42, punishment only: OR =1.25) were related to depressive symptoms in primary and middle school students in Shanxi Province ( P <0.05). From the perspective of gender heterogeneity, the living arrangement (living only with father or mother: OR =1.67, others: OR =1.67) had a statistically significant association with depressive symptoms in male students ( P <0.05). From the perspective of urban rural heterogeneity, the living arrangement (living only with father or mother: OR =1.38) had a statistically significant association with depressive symptoms in rural primary and middle school students ( P <0.05).
Conclusions
The family environment has an important impact on depressive symptoms in primary and middle school students. Family functioning should be fully exerted to prevent depressive symptoms in primary and middle school students.
7.Risk Identification Model of Coronary Artery Stenosis Constructed Based on Random Forest
Yongfeng LV ; Yujing WANG ; Leyi ZHANG ; Yixin LI ; Na YUAN ; Jing TIAN
Journal of Sun Yat-sen University(Medical Sciences) 2025;46(1):138-146
ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years,diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province, were continuously enrolled. Logistic regression,back propagation neural network (BPNN), and random forest(RF)algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity (TPR), specificity (TNR), accuracy (ACC), positive predictive value (PV+), negative predictive value (PV-), area under subject operating characteristic curve (AUC), and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression,BPNN,and RF models were 75.76%, 74.30%, and 93.70%, while ACC values were 74.05%, 72.30%, and 79.49%, respectively. The AUC values were:logistic regression 0.739 9; BPNN 0.723 1; RF 0.752 2. Manifestations such as chest pains,abnormal ST segments on ECG,ventricular premature beats with hypertension, atrial fibrillation, regional wall motion abnormalities(RWMA) by color echocardiography, aortic regurgitation(AR), pulmonary insufficiency (PI), family history of cardiovascular diseases,and body mass index(BMI)were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.
8.Association between lifestyle and cardiovascular-metabolic risk factor aggregation in a young and middle-aged male occupational population
Baoyi LIANG ; Lyurong LI ; Yingjun CHEN ; Lingxiang XIE ; Gaisheng LIU ; Liuquan JIANG ; Lu YU ; Qingsong CHEN
Journal of Environmental and Occupational Medicine 2025;42(4):385-391
Background Unhealthy lifestyle behaviors may be associated with an increased risk of cardiometabolic risk factor aggregation (CMRF≥ 2), and few studies have focused on the correlation between the two in occupational populations. Objective To investigate the current status of CMRF≥2 and the compliance of healthy lifestyle in male occupational personnel, explore the effect of lifestyle on cardiometabolic risk, and provide reference for formulating healthy behavior promotion strategies and reducing cardiometabolic risk in occupational populations. Methods The study subjects were selected from male workers who completed occupational health examinations at an occupational disease prevention and control hospital in Shanxi Province from May to December 2023, and
9.Value of third lumbar skeletal muscle mass index in predicting the prognosis of patients with acute-on-chronic liver failure
Yewen HAN ; Jing LI ; Ninghui ZHAO ; Jia YAO ; Juan WANG
Journal of Clinical Hepatology 2025;41(4):698-702
ObjectiveTo investigate the value of third lumbar skeletal muscle mass index (L3-SMI) in predicting the long-term prognosis of patients with acute-on-chronic liver failure (ACLF), and to provide a useful tool for prognostic scoring of ACLF patients. MethodsA retrospective analysis was performed for the data of 126 patients who underwent abdominal computed tomography (CT) scanning and were diagnosed with ACLF in Shanxi Bethune Hospital from December 2017 to December 2021, including clinical indicators, biochemical parameters, and model for end-stage liver disease (MELD) score, and L3-SMI was calculated. The independent-samples t test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data between groups. The receiver operating characteristic (ROC) curve was used to assess the diagnostic value of L3-SMI and other variables (MELD score and Child-Pugh score), and the DeLong test was used for comparison of the area under the ROC curve (AUC). ResultsAmong the 126 patients enrolled, 44 (35%) died within 2 years and 82 (65%) survived. Compared with the survival group, the death group had significantly higher age, incidence rate of ascites, international normalized ratio, MELD score, and Child-Pugh score (all P<0.05) and a significantly lower value of L3-SMI [38.40 (35.95 — 46.29) cm²/m² vs 44.19 (40.20 — 48.58) cm²/m², Z=-2.855, P=0.004]. L3-SMI had an AUC of 0.720 in predicting 2-year mortality in ACLF patients, with a sensitivity of 63.6% and a specificity of 80.5%, and a combination of L3-SMI, MELD score, and Child-Pugh score had a significantly better AUC than a combination of MELD score and Child-Pugh score in predicting 2-year mortality (0.809 vs 0.757, Z=2.015, P<0.05). ConclusionL3-SMI has a high predictive value for the prognosis of ACLF patients, and the combination of L3-SMI、MELD score and Child-Pugh score has a higher predictive value for ACLF patients, and the inclusion of L3-SMI or sarcopenia in the conventional prognostic scores of ACLF patients may increase the ability to predict disease progression.
10.Research Advances in Tetraspanins in Colorectal Cancer
Chengwei LIU ; Kunyang WANG ; Zhen HU ; Yaoping LI
Cancer Research on Prevention and Treatment 2025;52(5):361-367
The tetraspanins are closely associated with the development and therapeutic prognosis of colorectal tumors. These proteins play a role in cell proliferation, metastasis, and invasion, regulate apoptosis and autophagy of colorectal tumor cells. affect immune escape by releasing exosomes, intervening the epithelial-mesenchymal transition process, and altering the tumor microenvironment, and enhance tumor stemness through specific pathways. This paper reviews the mechanisms and current research regarding the status of tetraspanins in colorectal cancer, aiming to improve early diagnosis and providing valuable insights for treatment strategies.


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