1.Association between dietary behavior and type 2 diabetes in the older adults aged 65 years and over in 18 longevity areas of China
Xuehua HU ; Yue CHEN ; Zenghang ZHANG ; Chen CHEN ; Yingli QU ; Xi MENG ; Jun WANG ; Zinan XU ; Zheng LI ; Sixin LIU ; Wenhui SHI ; Zhanhong XUE ; Fanye LONG ; Xiaoming SHI ; Yuebin LYU
Chinese Journal of Preventive Medicine 2025;59(5):588-596
Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.
2.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.
3.National clinical three-tiered surveillance and stratified precision detection report on respiratory infectious pathogens in 2024
Jingwen AI ; Jikui DENG ; Min DONG ; Xiaohong GAO ; Jiawei GENG ; Xiaoli HU ; Zhu JIN ; Hongyan LIU ; Yongzhong LI ; Xi LIU ; Yuanwang QIU ; Lihong QU ; Binhuang SUN ; Wei SONG ; Hongyu WANG ; Junping WANG ; Sen WANG ; Xiaoming XIONG ; Daokun YANG ; Liaoyun ZHANG ; Yanliang ZHANG ; Xianghong ZHOU ; Wenhong ZHANG
Chinese Journal of Infectious Diseases 2025;43(2):79-89
Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.
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.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
6.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.
7.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.
8.Diagnostic value of 18F-FDG PET/CT and bone marrow biopsy in evaluating common non-Hodgkin lymphoma with bone marrow infiltration
Bin HU ; Liu HE ; Yang LI ; Cheng GU ; Xiaoming ZHANG ; Lichun ZHENG
Journal of China Medical University 2025;54(5):437-441,447
Objective To evaluate the diagnostic value of positron emission tomography(PET)/computed tomography(CT)and bone marrow biopsy(BMB)for bone marrow infiltration in common non-Hodgkin lymphoma(NHL).Methods We retrospectively analyzed data from 197 patients with NHL and compared the diagnostic value of PET/CT and BMB for bone marrow infiltration.Differences in PET/CT parameters and serological test results were compared between PET/CT-positive and PET/CT-negative patients as well as between BMB-positive and BMB-negative patients.Results In patients with diffuse large B-cell lymphoma(DLBCL),the sensitivities of PET/CT and BMB for detecting bone marrow infiltration were 90.5%and 66.7%,and the specificities were 95.1%and 100.0%,respectively.In patients with follicular lymphoma(FL),the sensitivities were 63.6%and 81.8%,and the specificities were 98.1%and 100.0%,respec-tively.In patients with T-cell lymphoma(TCL),the sensitivities were 60.0%and 80.0%,and the specificities were 88.0%and 100.0%,respectively.Among patients with DLBCL and TCL,significant differences were observed in platelet count and lactate dehydrogenase levels between PET/CT-positive and PET/CT-negative patients(P<0.05).Conclusion PET/CT showed excellent diagnostic perfor-mance for evaluating bone marrow infiltration in DLBCL.PET/CT had limited sensitivity for FL and TCL and might serve as a supplemen-tary tool for BMB.Platelet count and lactate dehydrogenase levels may aid in the diagnosis of bone marrow infiltration in DLBCL and TCL.
9.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.
10.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.

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