1.Establishment and optimization of combined model of influenza and wind-heat syndrome in mice
Xiaoyan ZHANG ; Miao XIE ; Qishuai HU ; Xinxin FENG ; Yutao WANG ; Xin ZHAO ; Yanli LIANG ; Linyang CHEN ; Zifeng YANG
Acta Laboratorium Animalis Scientia Sinica 2025;33(8):1105-1115
Objective To establish a mouse model of H1N1 influenza wind-heat syndrome by combining climate intervention with influenza virus nasal drops.Methods Seventy-two BALB/c mice were divided randomly into nine groups:a Control group,wind-heat(FR)groups(FR-3Day,FR-5Day),and Model groups(1LD-3Day,2LD-3Day,3LD-3Day,1LD-5Day,2LD-5Day,2LD-5Day,3LD-5Day)(n=8 mice per group).Mice in the Control group were housed in a normal environment,while mice in the FR and Model groups were kept in wind-heat conditions for 7 d.Mice in the Model groups received nasal PR8 influenza virus infection on the 8th day,and mice in the Control and FR heat groups received equal amounts of physiological saline nasal drops.After virus challenge,each group was housed in a normal environment and samples were taken on days 3 and 5.The appearance of the mice was observed and recorded and the lung index,routine blood parameters,lung tissue pathology,serum interleukin(IL)-6 levels,and virus titers were detected in each group based on their behavioral status,stools,and body temperature.Results After 7 d of wind-heat intervention,mice in the FR groups showed no significant abnormalities in terms of appearance,stools,body temperature,routine blood parameters,or lung tissue pathology compared with the Control group.The appearance,lung index,red blood cell count,hemoglobin,hematocrit,pathological result,and body temperature in the Model groups worsened progressively with increasing time and toxin dosage,while the neutrophil percentage,lymphocyte percentage,virus titer,and serum IL-6 levels peaked on day 3 after viral attack,for the same viral dose,and then decreased slightly on day 5.Conclusions PR8 nasal drops and 7 d of wind-heat climate intervention can be used to establish a mouse model of influenza wind-heat syndrome.
2.A machine learning-based model for predicting the risk of diabetic kidney disease in type 2 diabetes mellitus
Tingting LI ; Peng SU ; Jinbo CHEN ; Xiaoyan HE ; Yi CAO ; Xin ZHANG ; Qingling TANG ; Xubin MIAO ; Xiaohua LIANG ; Dong MA
Chinese Journal of Diabetes 2025;33(4):241-247
Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853~0.891,0.865~0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.
3.Expert consensus on non-surgical treatment for acute lateral ankle sprain (version 2025)
Hui CHE ; Wenge DING ; Shiming FENG ; Xueping GU ; Qinwei GUO ; Jianchao GUI ; Yinghui HUA ; Yuefeng HAO ; Qinglin HAN ; Bo HU ; Xiaojun LIANG ; Guoping LI ; Yunxia LI ; Qi LI ; Yanlin LI ; Xin MA ; Jun MA ; Xudong MIAO ; Jianzhong QIN ; Xiaodong QIN ; Xu SUN ; Kefu SUN ; Weidong SONG ; Dai SHI ; Zhongmin SHI ; Youlun TAO ; Xu WANG ; Youhua WANG ; Liheng WANG ; Anli WANG ; Aiguo WANG ; Weidong WU ; Yajun XU ; Weidong XU ; Renjie XU ; Yongsheng XU ; Tengbo YU ; Lianqi YAN ; Xiaodong YUAN ; Yuan ZHU ; Mingzhu ZHANG ; Hongtao ZHANG ; Xintao ZHANG ; Xiaofei ZHENG
Chinese Journal of Trauma 2025;41(6):517-529
Acute lateral ankle sprain (ALAS) is one of the most common sport injuries, with high incidence, recurrence and disability rates. Currently, exercise rehabilitation-based non-surgical treatment is the primary management approach for ALAS. However, there remain improper practices such as excessive immobilization or uncontrolled activity, which contribute to recurrent sprains and chronic ankle instability, significantly impairing patients′ athletic function and quality of life. To standardize the non-surgical management of ALAS, improve the cure rates, and reduce the recurrence and disability rates, Chinese Sports Rehabilitation Medicine Training Project of Chinese Medical Association, Foot and Ankle Basics and Orthopedics Group, Orthopedic Branch of Chinese Medical Doctor Association, and Sports Medicine Branch of Jiangsu Medical Association organized relevant experts to formulate Expert consensus on non-surgical treatment for acute lateral ankle sprain ( version 2025), following the principles of scientific vigor, practicality, and innovation. Thirteen recommendations were proposed for standardized treatment protocols across different healing phases, aiming to provide references for standard management of ALAS and improve the therapeutic outcomes.
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.Prevalence and risk factors of training-related abdominal injuries: A multicenter survey study.
Chuan PANG ; Wen-Quan LIANG ; Gan ZHANG ; Ting-Ting LU ; Yun-He GAO ; Xin MIAO ; Zhi-Da CHEN ; Yi LIU ; Wen-Tong XU ; Hong-Qing XI
Chinese Journal of Traumatology 2025;28(4):301-306
PURPOSE:
This study aims to identify the prevalence and risk factors of military training-related abdominal injuries and help plan and conduct training properly.
METHODS:
This questionnaire survey study was conducted from October 2021 to May 2022 among military personnel from 6 military units and 8 military medical centers and participants' medical records were consulted to identify the training-related abdominal injuries. All the military personnel who ever participated in military training were included. Those who refused to participate in this study or provided an incomplete questionnaire were excluded. The questionnaire collected demographic information, type of abdominal injury, frequency, training subjects, triggers, treatment, and training disturbance. Chi-square test and t-test were used to compare baseline information. Univariate and multivariate regression analyses were used to explore the risk factors associated with military training-related abdominal injuries.
RESULTS:
A total of 3058 participants were involved in this study, among which 1797 (58.8%) had suffered training-related abdominal injuries (the mean age was 24.3 years and the service time was 5.6 years), while 1261 (41.2%) had no training-related abdominal injuries (the mean age was 23.1 years and the service time was 4.3 years). There were 546 injured patients (30.4%) suspended the training and 84 (4.6%) needed to be referred to higher-level hospitals. The most common triggers included inadequate warm-up, fatigue, and intense training. The training subjects with the most abdominal injuries were long-distance running (589, 32.8%). Civil servants had the highest rate of abdominal trauma (17.1%). Age ≥ 25 years, military service ≥ 3 years, poor sleep status, and previous abdominal history were independent risk factors for training-related abdominal injury.
CONCLUSION
More than half of the military personnel have suffered military training-related abdominal injuries. Inadequate warm-up, fatigue, and high training intensity are the most common inducing factors. Scientific and proper training should be conducted according to the factors causing abdominal injuries.
Humans
;
Military Personnel
;
Risk Factors
;
Prevalence
;
Male
;
Abdominal Injuries/etiology*
;
Female
;
Adult
;
Surveys and Questionnaires
;
Young Adult
6.Clinical Applications of Circulating Tumor DNA in Response Evaluation and Relapse Monitoring of Primary Mediastinal Large B-Cell Lymphoma.
Lu PAN ; Xin-Miao JIANG ; Yan TENG ; Ning WANG ; Ling HUANG ; Han-Guo GUO ; Si-Chu LIU ; Xiao-Juan WEI ; Fei-Li CHEN ; Zhan-Li LIANG ; Wen-Yu LI
Journal of Experimental Hematology 2025;33(2):407-415
OBJECTIVE:
To explore the clinical significance of circulating tumor DNA (ctDNA) in response evaluation and relapse monitoring for patients with primary mediastinal large B-cell lymphoma (PMBCL).
METHODS:
The clinical characteristics, efficacy and survival of 38 PMBCL patients in our hospital from January 2010 to April 2020 were retrospectively analyzed. The ctDNA monitoring was conducted by targeted next-generation sequencing (NGS).
RESULTS:
Among the 38 patients, 26 cases were female, and 32 cases were diagnosed with Ann Arbor stage I-II. The 5-year overall survival (OS) rate and progression-free survival (PFS) rate were 74.7% and 61.7%, respectively. Males and those with high aaIPI scores (3 points) had a relatively poor prognosis. The NGS results of 23 patients showed that STAT6 (65.2%), SOCS1 (56.5%), and TNFAIP3 (56.5%) were the most common mutated genes. Patients with stable disease (SD)/progressive disease (PD) exhibited enrichment in cell cycle, FoxO, and TNF signaling pathways. A total of 29 patients underwent end-of-treatment PET/CT (EOT PET/CT), and 16 of them received ctDNA monitoring with 12 negative. Among 6 patients with EOT PET/CT positive (Deauville 4), 4 underwent ctDNA monitoring, and 3 of them were negative, being still in continuous remission without any subsequent anti-tumor therapy.
CONCLUSION
CtDNA may be combined with PET/CT to assess efficacy, monitor relapse, and guide treatment of PMBCL.
Humans
;
Circulating Tumor DNA/blood*
;
Female
;
Mediastinal Neoplasms
;
Male
;
Retrospective Studies
;
High-Throughput Nucleotide Sequencing
;
Prognosis
;
Lymphoma, Large B-Cell, Diffuse/genetics*
;
Middle Aged
;
Adult
;
Aged
;
Neoplasm Recurrence, Local
;
Mutation
7.Additional role of low-density lipoprotein cholesterol on the risk of osteoporosis in men with or without coronary heart disease: a real-world longitudinal study.
Jing ZENG ; Zi-Mo PAN ; Ting LI ; Ze-Yu CHEN ; Xiao-Yan CAI ; Mei-Liang GONG ; Xin-Li DENG ; Sheng-Shu WANG ; Nan LI ; Miao LIU ; Chun-Lin LI
Journal of Geriatric Cardiology 2025;22(2):219-228
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.
8.A machine learning-based model for predicting the risk of diabetic kidney disease in type 2 diabetes mellitus
Tingting LI ; Peng SU ; Jinbo CHEN ; Xiaoyan HE ; Yi CAO ; Xin ZHANG ; Qingling TANG ; Xubin MIAO ; Xiaohua LIANG ; Dong MA
Chinese Journal of Diabetes 2025;33(4):241-247
Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853~0.891,0.865~0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.
9.Establishment and optimization of combined model of influenza and wind-heat syndrome in mice
Xiaoyan ZHANG ; Miao XIE ; Qishuai HU ; Xinxin FENG ; Yutao WANG ; Xin ZHAO ; Yanli LIANG ; Linyang CHEN ; Zifeng YANG
Acta Laboratorium Animalis Scientia Sinica 2025;33(8):1105-1115
Objective To establish a mouse model of H1N1 influenza wind-heat syndrome by combining climate intervention with influenza virus nasal drops.Methods Seventy-two BALB/c mice were divided randomly into nine groups:a Control group,wind-heat(FR)groups(FR-3Day,FR-5Day),and Model groups(1LD-3Day,2LD-3Day,3LD-3Day,1LD-5Day,2LD-5Day,2LD-5Day,3LD-5Day)(n=8 mice per group).Mice in the Control group were housed in a normal environment,while mice in the FR and Model groups were kept in wind-heat conditions for 7 d.Mice in the Model groups received nasal PR8 influenza virus infection on the 8th day,and mice in the Control and FR heat groups received equal amounts of physiological saline nasal drops.After virus challenge,each group was housed in a normal environment and samples were taken on days 3 and 5.The appearance of the mice was observed and recorded and the lung index,routine blood parameters,lung tissue pathology,serum interleukin(IL)-6 levels,and virus titers were detected in each group based on their behavioral status,stools,and body temperature.Results After 7 d of wind-heat intervention,mice in the FR groups showed no significant abnormalities in terms of appearance,stools,body temperature,routine blood parameters,or lung tissue pathology compared with the Control group.The appearance,lung index,red blood cell count,hemoglobin,hematocrit,pathological result,and body temperature in the Model groups worsened progressively with increasing time and toxin dosage,while the neutrophil percentage,lymphocyte percentage,virus titer,and serum IL-6 levels peaked on day 3 after viral attack,for the same viral dose,and then decreased slightly on day 5.Conclusions PR8 nasal drops and 7 d of wind-heat climate intervention can be used to establish a mouse model of influenza wind-heat syndrome.
10.Expert consensus on non-surgical treatment for acute lateral ankle sprain (version 2025)
Hui CHE ; Wenge DING ; Shiming FENG ; Xueping GU ; Qinwei GUO ; Jianchao GUI ; Yinghui HUA ; Yuefeng HAO ; Qinglin HAN ; Bo HU ; Xiaojun LIANG ; Guoping LI ; Yunxia LI ; Qi LI ; Yanlin LI ; Xin MA ; Jun MA ; Xudong MIAO ; Jianzhong QIN ; Xiaodong QIN ; Xu SUN ; Kefu SUN ; Weidong SONG ; Dai SHI ; Zhongmin SHI ; Youlun TAO ; Xu WANG ; Youhua WANG ; Liheng WANG ; Anli WANG ; Aiguo WANG ; Weidong WU ; Yajun XU ; Weidong XU ; Renjie XU ; Yongsheng XU ; Tengbo YU ; Lianqi YAN ; Xiaodong YUAN ; Yuan ZHU ; Mingzhu ZHANG ; Hongtao ZHANG ; Xintao ZHANG ; Xiaofei ZHENG
Chinese Journal of Trauma 2025;41(6):517-529
Acute lateral ankle sprain (ALAS) is one of the most common sport injuries, with high incidence, recurrence and disability rates. Currently, exercise rehabilitation-based non-surgical treatment is the primary management approach for ALAS. However, there remain improper practices such as excessive immobilization or uncontrolled activity, which contribute to recurrent sprains and chronic ankle instability, significantly impairing patients′ athletic function and quality of life. To standardize the non-surgical management of ALAS, improve the cure rates, and reduce the recurrence and disability rates, Chinese Sports Rehabilitation Medicine Training Project of Chinese Medical Association, Foot and Ankle Basics and Orthopedics Group, Orthopedic Branch of Chinese Medical Doctor Association, and Sports Medicine Branch of Jiangsu Medical Association organized relevant experts to formulate Expert consensus on non-surgical treatment for acute lateral ankle sprain ( version 2025), following the principles of scientific vigor, practicality, and innovation. Thirteen recommendations were proposed for standardized treatment protocols across different healing phases, aiming to provide references for standard management of ALAS and improve the therapeutic outcomes.

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