1.Expert Consensus on Clinical Application of Pingxuan Capsules
Yuer HU ; Yanming XIE ; Yaming LIN ; Yuanqi ZHAO ; Yihuai ZOU ; Mingquan LI ; Xiaoming SHEN ; Wei PENG ; Changkuan FU ; Yuanyuan LI
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(1):201-210
As a patented characteristic medicine of Yi ethnic minority, Pingxuan capsules have the effects of nourishing the liver and kidney, pacifying the liver, and subduing Yang. With the main indications of dizziness, headache, palpitations, tinnitus, insomnia, dreaminess, waist and knee soreness caused by liver-kidney deficiency and liver Yang upward disturbance, Pingxuan capsules are widely used in the treatment of posterior circulation ischemic vertigo, vestibular migraine, benign paroxysmal positional vertigo. However, the current knowledge is limited regarding the efficacy, syndrome differentiation, and safety of this medicine. On the basis of summarizing the experience of clinicians and the existing evidence, this study invites clinical experts of traditional Chinese and Western medicine, pharmaceutical experts, and methodological experts from relevant fields across China to conduct evidence-based evaluation of Pingxuan capsules. The evaluation follows the Specifications for the Development of Clinical Expert Consensus on Chinese Patent Medicines issued by the Standardization Office of the China Association of Chinese Medicine, and reaches 5 recommendations and 16 consensus suggestions. The consensus clarifies the clinical applications, efficacy, dose, course of treatment, combination of medicines, precautions, and contraindications of Pingxuan capsules in the treatment of vertigo and explains the safety of clinical application. This consensus is applicable to clinicians (traditional Chinese medicine, Western medicine, and integrated traditional Chinese and Western medicine) and pharmacists in tertiary hospitals, secondary hospitals, and community-level medical and health institutions across China, providing a reference for the rational use of Pingxuan capsules in the treatment of vertigo. It is hoped that the promotion of this consensus can facilitate the rational use of drugs in clinical practice, reduce the risk of drug use, and give full play to the advantages of Pingxuan capsules in the treatment of vertigo diseases. This consensus has been reviewed and published by the China Association of Chinese Medicine, with the number GS/CACM330-2023.
2.Guidelines for vaccination of kidney transplant candidates and recipients in China
Jian Zhang ; Jun Lin ; Weijie Zhang ; Xiaoming Ding ; Xiaopeng Hu ; Wujun Xue
Organ Transplantation 2025;16(2):177-190
In order to further standardize the vaccination of kidney transplant candidates and recipients in China, the Branch of Organ Transplantation of Chinese Medical Association has organized experts in kidney transplantation and infectious diseases. Based on the "Vaccination of Solid Organ Transplant Candidates and Recipients: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice", and in combination with the clinical reality of infectious diseases and vaccination after organ transplantation in China, as well as referring to relevant recommendations from home and abroad in recent years, these guidelines are formulated from aspects such as epidemiology, types of vaccines, vaccination principles, target population, and specific vaccine administration. The "Guidelines for Vaccination of Kidney Transplant Candidates and Recipients in China" aims to provide theoretical reference for medical workers in the field of kidney transplantation in China, regarding the vaccination of kidney transplant candidates and recipients. It is expected to better guide the vaccination of kidney transplant candidates and recipients, reduce the risk of postoperative infection, and improve survival outcomes.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
4.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
5.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
6.The application of surgical robots in head and neck tumors.
Xiaoming HUANG ; Qingqing HE ; Dan WANG ; Jiqi YAN ; Yu WANG ; Xuekui LIU ; Chuanming ZHENG ; Yan XU ; Yanxia BAI ; Chao LI ; Ronghao SUN ; Xudong WANG ; Mingliang XIANG ; Yan WANG ; Xiang LU ; Lei TAO ; Ming SONG ; Qinlong LIANG ; Xiaomeng ZHANG ; Yuan HU ; Renhui CHEN ; Zhaohui LIU ; Faya LIANG ; Ping HAN
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(11):1001-1008
7.PARylation promotes acute kidney injury via RACK1 dimerization-mediated HIF-1α degradation.
Xiangyu LI ; Xiaoyu SHEN ; Xinfei MAO ; Yuqing WANG ; Yuhang DONG ; Shuai SUN ; Mengmeng ZHANG ; Jie WEI ; Jianan WANG ; Chao LI ; Minglu JI ; Xiaowei HU ; Xinyu CHEN ; Juan JIN ; Jiagen WEN ; Yujie LIU ; Mingfei WU ; Jutao YU ; Xiaoming MENG
Acta Pharmaceutica Sinica B 2025;15(9):4673-4691
Poly(ADP-ribosyl)ation (PARylation) is a specific form of post-translational modification (PTM) predominantly triggered by the activation of poly-ADP-ribose polymerase 1 (PARP1). However, the role and mechanism of PARylation in the advancement of acute kidney injury (AKI) remain undetermined. Here, we demonstrated the significant upregulation of PARP1 and its associated PARylation in murine models of AKI, consistent with renal biopsy findings in patients with AKI. This elevation in PARP1 expression might be attributed to trimethylation of histone H3 lysine 4 (H3K4me3). Furthermore, a reduction in PARylation levels mitigated renal dysfunction in the AKI mouse models. Mechanistically, liquid chromatography-mass spectrometry indicated that PARylation mainly occurred in receptor for activated C kinase 1 (RACK1), thereby facilitating its subsequent phosphorylation. Moreover, the phosphorylation of RACK1 enhanced its dimerization and accelerated the ubiquitination-mediated hypoxia inducible factor-1α (HIF-1α) degradation, thereby exacerbating kidney injury. Additionally, we identified a PARP1 proteolysis-targeting chimera (PROTAC), A19, as a PARP1 degrader that demonstrated superior protective effects against renal injury compared with PJ34, a previously identified PARP1 inhibitor. Collectively, both genetic and drug-based inhibition of PARylation mitigated kidney injury, indicating that the PARylated RACK1/HIF-1α axis could be a promising therapeutic target for AKI treatment.
8.An improved reporter gene assay for evaluating the biological activity of recombinant human growth hormone.
Xiaoming ZHANG ; Heyang LI ; Ying HUANG ; Ping LV ; Lvyin WANG ; Kezheng XU ; Yi LI ; Xinyue HU ; Yue SUN ; Cheng-Gang LIANG ; Jing LI
Journal of Pharmaceutical Analysis 2025;15(5):101073-101073
Image 1.
9.Guidelines for clinical diagnosis and treatment of hypertension in kidney transplant recipients in China
Branch of Organ Transplantation of Chinese Medical Association ; Jian ZHANG ; Jun LIN ; Xiaopeng HU ; Xiaoming DING ; Ning LI ; Wujun XUE
Organ Transplantation 2024;15(4):509-532
To further standardize the diagnosis and treatment of hypertension after kidney transplantation in China,Branch of Organ Transplantation of Chinese Medical Association organized experts in kidney transplantation and cardiovascular diseases to formulate"Guidelines for Clinical Diagnosis and Treatment of Hypertension in Kidney Transplant Recipients in China"based on"Diagnosis and Treatment Specification for Hypertension after Solid Organ Transplantation in China(2019 edition)"in combination with clinical status of hypertension after organ transplantation in China,and referring to the latest guidelines for diagnosis and treatment of hypertension at home and abroad.This guideline was formulated to provide theoretical reference for medical practitioners in the field of kidney transplantation in China,aiming to better control adult hypertension after kidney transplantation,mitigate adverse outcomes and improve the quality of life.
10.Association of sleep duration and physical exercise with dyslipidemia in older adults aged 80 years and over in China
Bing WU ; Yang LI ; Lanjing XU ; Zheng ZHANG ; Jinhui ZHOU ; Yuan WEI ; Chen CHEN ; Jun WANG ; Changzi WU ; Zheng LI ; Ziyu HU ; Fanye LONG ; Yudong WU ; Xuehua HU ; Kexin LI ; Fangyu LI ; Yufei LUO ; Yingchun LIU ; Yuebin LYU ; Xiaoming SHI
Chinese Journal of Epidemiology 2024;45(1):48-55
Objective:To explore the impact of sleep duration, physical exercise, and their interactions on the risk of dyslipidemia in older adults aged ≥80 (the oldest old) in China.Methods:The study subjects were the oldest old from four rounds of Healthy Aging and Biomarkers Cohort Study (2008-2009, 2011-2012, 2014 and 2017-2018). The information about their demographic characteristics, lifestyles, physical examination results and others were collected, and fasting venous blood samples were collected from them for blood lipid testing. Competing risk model was used to analyze the causal associations of sleep duration and physical exercise with the risk for dyslipidemia. Restricted cubic spline (RCS) function was used to explore the dose-response relationship between sleep duration and the risk for dyslipidemia. Additive and multiplicative interaction model were used to explore the interaction of sleep duration and physical exercise on the risk for dyslipidemia.Results:The average age of 1 809 subjects was (93.1±7.7) years, 65.1% of them were women. The average sleep duration of the subjects was (8.0±2.5) hours/day, 28.1% of them had sleep duration for less than 7 hours/day, and 27.2% had sleep for duration more than 9 hours/day at baseline survey. During the 9-year cumulative follow-up of 6 150.6 person years (follow-up of average 3.4 years for one person), there were 304 new cases of dyslipidemia, with an incidence density of 4 942.6/100 000 person years. The results of competitive risk model analysis showed that compared with those who slept for 7-9 hours/day, the risk for dyslipidemia in oldest old with sleep duration >9 hours/day increased by 22% ( HR=1.22, 95% CI: 1.07-1.39). Compared with the oldest old having no physical exercise, the risk for dyslipidemia in the oldest old having physical exercise decreased by 33% ( HR=0.67, 95% CI: 0.57-0.78). The RCS function showed a linear positive dose-response relationship between sleep duration and the risk for hyperlipidemia. The interaction analysis showed that physical exercise and sleep duration had an antagonistic effect on the risk for hyperlipidemia. Conclusion:Physical exercise could reduce the adverse effects of prolonged sleep on blood lipids in the oldest old.

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