1.Neuroblastoma risk decreased by NSUN3 rs7653521 C>T polymorphism in Chinese children.
Meng LI ; Xinxin ZHANG ; Lei LIN ; Lei MIAO ; Haiyan WU ; Chunlei ZHOU ; Jing HE
Chinese Medical Journal 2025;138(17):2204-2206
2.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.
3.COCKROACH SURVEILLANCE IN LANZHOU FROM 2016 TO 2023
Ying ZHANG ; Jing ZUO ; Qing-Ming SHI ; Zi-Peng LI ; Wen-Juan BA ; Zhi-Qing LI ; Ai-Miao LIAO ; Jing-Jing YU ; Guo-Jing BAO ; Xing LI ; Jun GAN ; Xiao-Lei YE
Acta Parasitologica et Medica Entomologica Sinica 2025;32(2):119-122
Objective To investigate the population composition,seasonal dynamics,and infestation levels of cockroaches in Lanzhou,China,and to provide information for the scientific development of cockroach control strategies.Methods Monitoring was conducted at three locations using the sticky trap method.Habitats included farm product markets,catering establishments,hotels,hospitals,and residential areas.Results From 2016 to 2023,the average cockroach density was 0.77 insects per board,with an average infestation rate of 10.84%.Blattella germanica was the dominant species.Seasonal density of cockroaches showed an approximately unimodal distribution,peaking in September.The highest average density and infestation rates were observed in farm product markets.Conclusions Cockroach density and infestation levels in Lanzhou remained relatively low.A comprehensive prevention and control strategy focusing on environmental management in key areas should be implemented according to the seasonal fluctuations.
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.Exploration of Traditional Chinese Medicine Interventions for Inflammation-to-Tumor Transition in Cervical High-Risk Human Papillomavirus Infection from the Perspective of Damp-Heat Accumulation Resulting into Toxin
Yu-Xi MIAO ; Gen-Ping ZENG ; Pei-Yin LI ; Xi-Jing LU ; Song-Ping LUO ; Lei ZENG
Journal of Guangzhou University of Traditional Chinese Medicine 2024;41(9):2472-2478
Inflammation-to-tumor transition is one of the important mechanisms by which the cervical high-risk human papillomavirus(HR-HPV)infection develops into cervical cancer.Persistent cervical HR-HPV infection is an important cause of cervical cancer,and the focal uncontrolled inflammatory microenvironment caused by persistent cervical HR-HPV infection is the underlying mechanism of cervical cancer.The macroscopic and microscopic pathological process of inflammation-to-tumor transition is consistent with the pathogenesis evolution of damp-heat accumulation resulting into toxin in traditional Chinese medicine(TCM):the accumulation of damp-heat is the driving factor of inflammation-to-tumor transition,long-term retention of damp-heat leading to spleen deficiency and liver depression contributes to the characteristics of pathogenesis evolution,and long-term retention of damp-heat toxin causes the disorder of liver and spleen and then blood stasis accumulates in the cervical orifice,which eventually becomes cancer toxin.The process of inflammation-to-tumor transition caused by persistent cervical HR-HPV infection is due to the pathological factors of damp,heat,deficiency and toxin in TCM.Therefore,the regulation of inflammatory microenvironment caused by persistent cervical HR-HPV infection is the key approach to the prevention and treatment of cervical cancer.For the treatment of cervical cancer,methods of clearing heat and drying dampness,strengthening the spleen and soothing the liver are the key therapies.By intervention with the proper pathogen-eliminating methods and with simultaneous regulation of the interior and exterior,the process of inflammation-to-tumor transition can be interrupted.The exploration of inflammation-to-tumor transition caused by persistent cervical HR-HPV infection from the perspective of damp-heat accumulation resulting into toxin will provide thoughts for the prevention and treatment of cervical cancer with TCM and for Chinese medicine in intervening inflammation-to-tumor transition.
6.Construction and validation of the predictive model for intensive care unit and in-hospital mortality risk in patients with traumatic brain injury
Miao LU ; Jing ZHANG ; Sai XIN ; Jiaming ZHANG ; Lei ZHENG ; Yun ZHANG
Chinese Journal of Trauma 2024;40(5):420-431
Objective:To construct a predictive model for intensive care unit (ICU) and in-hospital mortality risk in patients with traumatic brain injury (TBI) and validate its performance.Methods:A retrospective cohort study was conducted to analyze the clinical data of 3 907 patients with TBI published until May 2018 in the eICU Collaborative Research Database v2.0 (eICU-CRD v2.0), including 2 397 males and 1 510 females, aged 18-92 years [63.0(43.0, 79.0)years]. According to whether the patients died in ICU or at hospital stay, they were divided into ICU survival group ( n=3 575) and ICU mortality group ( n=332), and hospital survival group ( n=3 413) and hospital mortality group ( n=494). The general data, admission diagnosis, laboratory tests, therapeutic interventions, and clinical outcomes were extracted as variables of interest. Univariate analysis and multivariate Logistic regression analysis were conducted on both the survival groups and the mortality groups to identify the independent risk factors that affect ICU and in-hospital mortality in TBI patients, based on which a Logistic regression prediction model was constructed and represented by Nomograms. The extracted dataset was randomly divided into training set ( n=2 735) and validation set ( n=1 172) with a ratio of 7∶3, and was applied for internal validation of the of the predictive model. Meanwhile, the data of TBI patients in the MIMIC-III v1. 4 database were extracted for external validation of the predictive model. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used for discriminability evaluation of the model, and the Hosmer-Lemeshow (H-L) goodness of fit test and calibration curve were used for calibration evaluation of the model. Results:The statistically significant variables identified in the univariate analysis were included in the multivariate logistic regression analysis of ICU mortality and in-hospital mortality risk. The results revealed that acute physiology and chronic health evaluation IV (APACHE IV) score ( OR=1.04, 95% CI 1.03, 1.04, P<0.01), Glasgow coma scale (GCS) ( OR=0.66, 95% CI 0.59, 0.73, P<0.01), cerebral hernia formation ( OR=6.91, 95% CI 3.13, 15.26, P<0.01), international normalized ratio (INR) ( OR=1.33, 95% CI 1.09, 1.62, P<0.01), use of hypertonic saline ( OR=0.45, 95% CI 0.21 0.94, P<0.05), and use of vasoactive agents ( OR=2.19, 95% CI 1.36, 3.52, P<0.01) were independent risk factors for ICU mortality in TBI patients. The age (with 10 years as a grade) ( OR=1.28, 95% CI 1.17, 1.40, P<0.01), APACHE IV score ( OR=1.03, 95% CI 1.02, 1.04, P<0.01), GCS ( OR=0.75, 95% CI 0.71, 0.80, P<0.01), cerebral hernia formation ( OR=6.44, 95% CI 2.99, 13.86, P<0.01), serum creatinine level ( OR=1.07, 95% CI 1.01, 1.15, P<0.05), INR ( OR=1.49, 95% CI 1.20, 1.85, P<0.01), use of hypertonic saline ( OR=0.41, 95% CI 0.21, 0.80, P<0.01), and use of vasoactive agents ( OR=2.27, 95% CI 1.46, 3.53, P<0.01) were independent risk factors of in-hospital mortality of TBI patients. Based on the forementioned independent risk factors for ICU mortality, the model equation was constructed: Logit P (ICU)=7.12+0.03×"APACHE IV score"-0.42×"GCS"+1.93×"cerebral hernia formation"+0.28×"INR"-0.81×"use of hypertonic saline"+0.79×"use of vasoactive agents". Based on the forementioned independent risk factors for in-hospital mortality, the model equation was constructed: Logit P (in-hospital)=2.75+0.25×"age"(with 10 years as a grade)+0.03×"APACHE IV score"-0.28×"GCS"+1.86×"cerebral hernia formation"+0.07×"serum creatinine level"+0.40×"INR"-0.90×"use of hypertonic saline"+0.82×"use of vasoactive agents". In the prediction model for ICU mortality, the AUC of the training set and validation set was 0.95 (95% CI 0.94, 0.97) and 0.91 (95% CI 0.87, 0.95). The result of H-L goodness of fit test of the training set was P=0.495 with the average absolute error in the calibration curve of 0.003, while the result of H-L goodness of fit test of the validation set was P=0.650 with the average absolute error in the calibration curve of 0.012. In the prediction model for in-hospital mortality, the AUC of the training set and validation set was 0.91 (95% CI 0.89, 0.93) and 0.91(95% CI 0.88, 0.94). The result of H-L goodness of fit test of the training set was P=0.670 with the average absolute error in the calibration curve of 0.006, while the result of H-L goodness of fit test of the validation set was P=0.080 with the average absolute error in the calibration curve of 0.021. In the external validation set of ICU mortality risk, the AUC of the prediction model was 0.88 (95% CI 0.86, 0.90), while the result of H-L goodness of fit test was P=0.205 with the average absolute error in the calibration curve of 0.031. In the external validation set of in-hospital mortality risk, the AUC of the prediction model was 0.88 (95% CI 0.85, 0.91), while the result of H-L goodness of fit test was P=0.239 with the average absolute error in the calibration curve of 0.036. The internal and external validation of the model indicated that both the prediction models for ICU and in-hospital mortality had good discriminability and calibration. Conclusion:The ICU mortality prediction model constructed by APACHE IV score, GCS, cerebral hernia formation, use of hypertonic saline, vasoactive agents use of and INR, and the in-hospital mortality prediction model constructed by age grading, APACHE IV score, GCS, cerebral hernia formation, serum creatinine level, hypertonic saline use of, use of vasoactive agents and INR can predict the mortality risk of TBI patients well.
7.A survey report on the status of emergency radiology in China
Jing WANG ; Zheng MIAO ; Qi YANG ; Lei ZHANG ; Hao WANG ; Huishu YUAN ; Haoran SUN ; Wei JIANG ; Yuan TIAN ; Mingyang LI ; Yaning WANG ; Zhaoyi MA ; Huimao ZHANG
Chinese Journal of Radiology 2024;58(6):661-666
Objective:To investigate the application status of emergency radiology in China, and to provide data support for the standardized development, scientific management and big data research of emergency radiology.Methods:From August 12th to October 19th, 2022, a questionnaire survey was conducted through WeChat"Questionnaire Star"to send targeted questionnaires to investigate the relevant data of the current status of emergency radiology in China, mainly including digital radiography (DR) and computed tomography (CT). This study was initiated by the Chinese Emergency Radiology Database Collaboration Group, and comprehensively investigated emergency imaging personnel, equipment, workload, critical value reporting process, and artificial intelligence (AI) application status.Results:There were 123 hospitals in the study. The survey showed that emergency DR/CT reports were mainly completed by residents and above (69.1%). There were 21 DR brands, 10 CT brands and 8 MR brands used for emergency imaging examinations. The median number of DR examinations in tertiary hospitals and secondary hospitals investigated from January to June 2022 was 4 642 and 2 015 cases respectively, and the median number of CT examinations was 16 512 and 3 762 cases respectively. The average single-shift workload of DR in the emergency radiology department during the day and night shift in tertiary hospitals was mainly ≤20 copies and 21-50 copies, and the average single-shift workload of CT in the emergency radiology department during the day and night shift was mainly 21-50 copies and 51-100 copies, while the average single-shift workload of DR/CT in the emergency radiology department during the day/night shift in secondary hospitals was mainly ≤20 copies. In terms of critical value reporting process, 74.8% of emergency imaging doctors and 84.6% of emergency imaging technicians took the way of phone/text message to notify the clinical doctor or the patients′ family. The overall deployment rate of AI in emergency imaging was about 60.2%. 75% of the respondents believed that in the future, AI can improve emergency radiology work from aspects such as emergency screening, aided diagnosis and process optimization.Conclusions:The emergency medical imaging mainly based on DR and CT has the current situations such as generally low seniority of doctors, diverse brands of imaging equipments, large volume of examinations and intense workload per doctor, especially in tertiary hospitals, and dependence on traditional means for critical value reporting. At present, AI is emerging in the field of emergency imaging, and there is still a long way to go to play the huge potential of AI in the intelligent whole process of emergency imaging in the future.
8.A third dose of inactivated vaccine augments the potency, breadth, and duration of anamnestic responses against SARS-CoV-2.
Zijing JIA ; Kang WANG ; Minxiang XIE ; Jiajing WU ; Yaling HU ; Yunjiao ZHOU ; Ayijiang YISIMAYI ; Wangjun FU ; Lei WANG ; Pan LIU ; Kaiyue FAN ; Ruihong CHEN ; Lin WANG ; Jing LI ; Yao WANG ; Xiaoqin GE ; Qianqian ZHANG ; Jianbo WU ; Nan WANG ; Wei WU ; Yidan GAO ; Jingyun MIAO ; Yinan JIANG ; Lili QIN ; Ling ZHU ; Weijin HUANG ; Yanjun ZHANG ; Huan ZHANG ; Baisheng LI ; Qiang GAO ; Xiaoliang Sunney XIE ; Youchun WANG ; Yunlong CAO ; Qiao WANG ; Xiangxi WANG
Protein & Cell 2024;15(12):930-937
9.Efficacy and safety of BTK inhibitor combined with bendamustine and rituximab in the first-line treatment of chronic lymphocytic leukemia/small lymphocytic lymphoma.
Shu Chao QIN ; Rui JIANG ; Ye Qin SHA ; Jing Yan QIU ; Hong Ling MI ; Yi MIAO ; Wei WU ; Li WANG ; Lei FAN ; Wei XU ; Jian Yong LI ; Hua Yuan ZHU
Chinese Journal of Hematology 2023;44(2):158-161
10.Effect of the area under the curve of carboplatin dosage on therapeutic efficacy and safety in Chinese patients with epithelial ovarian cancer
Wei JING ; Lei WANG ; Lu HAN ; Min LI ; Xue ZHOU ; Miao GUO ; Qiling LI
Journal of Xi'an Jiaotong University(Medical Sciences) 2023;44(2):243-250
【Objective】 To retrospectively analyze the average carboplatin dosage and calculate the area under the curve (AUC) using the Calvert formula in first-line chemotherapy in patients with epithelial ovarian cancer in The First Affiliated Hospital of Xi’an Jiaotong University so as to evaluate the effect of the AUC difference in the Chinese population on therapeutic efficacy and safety. 【Methods】 We enrolled patients who underwent first-line chemotherapy with paclitaxel and carboplatin 3-week regimen in our hospital from January 1, 2012 to January 1, 2022. According to the median of AUC, the patients were divided into high-dose group and low-dose group. The overall response rate (ORR), disease control rate (DCR), progression free survival (PFS), overall survival (OS), and the incidence of adverse events (AEs) were compared. 【Results】 A total of 153 patients were enrolled in this study and the median AUC of carboplatin was 3.981 (range 2.314-5.446). Only 10.46% patients (16/153) had an AUC above 5. There were 77 patients with the AUC<4. There were 76 patients with AUC≥4. No significant difference was observed in baseline characteristics between the two groups (P>0.05). The ORR in the low-dose group and the high-dose group was 59.74% and 57.89%, respectively, and the DCR was 87.01% and 85.53%, respectively. The median PFS of the two groups was 14 and 15.5 months, respectively, and the median OS was 50 and 55 months, respectively. None of the above outcomes were statistically different between the two groups (P>0.05). The two groups showed significant differences in the incidence of anemia, neutropenia, and thrombocytopenia (P<0.05). The incidence of nausea and vomiting, grade 1-2 diarrhea or constipation, and grade 1-2 fever showed significant differences (P<0.05). In addition, the incidence of dose limiting toxicity (DLT), including grade 4 thrombocytopenia and febrile neutropenia (FN), was significantly increased in the high-dose group (P<0.05). 【Conclusion】 Compared with the recommended AUC 5-6 of carboplatin abroad, the actual carboplatin dosage in the first-line chemotherapy for patients with epithelial ovarian cancer was generally insufficient in our hospital. There was no difference in therapeutic efficacy between the patients with AUC<4 and AUC≥4. However, considering the increased risk of some AEs and DLT in the high-dose group, it is not recommended to increase the carboplatin AUC blindly.

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