1.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.
2.Design of a modified tracheal intubation device and its application study in neurocritical patients
Guanyu WANG ; Yunxia CHEN ; Xiangrun KONG ; Ziheng GAO ; Mengli YANG ; Hao WANG ; Huali WANG ; Yingpu FENG
Chinese Journal of Nursing 2025;60(20):2557-2560
Objective To design and evaluate the clinical application efficacy of a novel bilateral-separation endotracheal tube fixation device and provide references for clinical practice.Methods Using convenient sampling,60 patients from the Neurological Intensive Care Unit of a tertiary-level hospital in Zhengzhou were selected from May to December 2024.Patients were randomly divided into an experimental group(n=30)and a control group(n=30).The experimental group utilized the novel bilateral-separation endotracheal tube fixation device,while the control group employed traditional bandage fixation methods.Differences in fixation time,tube displacement,and intubation duration were compared between the 2 groups.Results The experimental group demonstrated significantly shorter tube fixation times compared to the control group(P<0.05).However,no statistically significant differences were observed between the groups regarding intubation duration and tube displacement(P>0.05).Conclusion The novel bilateral-separation endotracheal tube fixation device can reduce tube fixation time for patients in neurological intensive care and enhance nurse satisfaction.Despite not showing advantages in preventing tube displacement,the device still presents promising potential for broad clinical application.
3.Metformin upregulates ABCA1 expression via inhibiting ubiquitin-proteasome system
Yunxia LIU ; Yan YANG ; Lei FAN ; Minjie WANG ; Lingze YU ; Tuya BAI ; Mengdi ZHANG ; Xiaoli LYU ; Jun LI ; Yuxia HU ; Feng GAO
Chinese Journal of Arteriosclerosis 2025;33(6):474-480
Aim To explore the potential mechanism of metformin on ATP-binding cassette transport A1(ABCA1)expression.Methods J774A.1 macrophages were treated with metformin and cycloheximide,and ABCA1 expression was determined by Western blot.His-tagged ABCA1 and HA-tagged Ub plasmids were co-transferred into HEK293 cells and stimulated with metformin.Co-immunoprecipitation(Co-IP)was used to test the binding ability of ABCA1 and ubiquitin.Candidate E3 ubiquitin-protein ligases(CE3)of ABCA1 were identified through Co-IP-based pro-teomics.The MIB1 plasmid was constructed and transferred into HEK293 cells,and Western blot was used to determine the effect of metformin and MIB1 on ABCA1 expression.Results Metformin increased the expression of ABCA1 in J774A.1 cells(P<0.01),and inhibited ABCA1 degradation(P<0.05).Metformin disrupted the binding of ABCA1 to ubiquitin(P<0.05).The proteins regulated by metformin in ABCA1 expression were primarily enriched in pathways re-lated to cell development,inflammation and immune defense.Metformin may upregulate ABCA1 protein expression via MIB1(P<0.05).Conclusion Metformin inhibits the degradation of ABCA1 by blocking the ubiquitin-proteasome system(UPS),and MIB1 might act as a candidate E3 ubiquitin-protein ligase(CE3)for ABCA1.
4.Vaccination willingness and its influencing factors for 23-valent pneumococcal polysaccharide vaccine among community-dwelling elderly in Xinzhuang Town, Shanghai
Xiaoli WANG ; Min LI ; Yan LU ; Yunxia YU ; Zhijun JIE
Chinese Journal of General Practitioners 2025;24(10):1212-1219
Objective:To investigate the vaccination rate of 23-valent pneumococcal polysaccharide vaccine (PPV23), identify determinants of vaccination willingness, and analyze barriers to vaccination among community-dwelling elderly in Xinzhuang Town of Shanghai Minhang District.Methods:This cross-sectional study was conducted in Xinzhuang Town of Shanghai Minhang District from November to December 2024. An online questionnaire was distributed via WeChat groups of neighborhood committees to community-dwelling elderly (aged≥60 years) using a convenience sampling method. The questionnaire covered basic demographic information, health status, knowledge and awareness about pneumonia and PPV23, attitudes toward PPV23 vaccination, and vaccination behavior. The χ2 test and multivariate logistic regression analysis were employed to identify factors influencing the PPV23 vaccination rate and willingness to vaccination among the elderly. Results:A total of 667 questionnaires were collected and 612 were valid (91.8%). Among 612 responders there were 223 males (36.44%) and 389 females (63.56%), and 304 (49.67%) aged 70-79 years. In all respondents, 185 (30.23%) had previously received PPV23, while 427 (69.77%) had not. Reasons for non-vaccination included unawareness of vaccine necessity (31.85%, 136/427), self-perceived good health (31.15%, 133/427), concerns about adverse reactions (21.08%, 90/427), and lack of physician recommendation (14.52%, 62/427). In all participants, 65.85%(403/612)expressed willingness for vaccination and 34.15%(209/612) did not have willingness. Factors significantly influencing vaccination willingness included negative perception of vaccine efficacy ( OR=2.750, 95% CI:1.077-7.023), concerns about adverse reactions ( OR=2.568, 95% CI:1.258-5.242), low awareness of pneumonia and PPV23 vaccine ( OR=11.608, 95% CI:4.177-32.258), perceived vaccination inconvenience ( OR=0.457, 95% CI:0.248-0.844), and belief in good health negating need ( OR=2.658, 95% CI:1.361-5.190) (all P<0.05). Conclusions:Suboptimal PPV23 vaccination rates and low willingness among community-dwelling elderly in Shanghai Xinzhuang Town are driven by knowledge gaps and perceptual barriers. Targeted interventions should prioritize physician engagement, accessible vaccination services, and public education addressing safety and efficacy concerns.
5.Relationship of peripheral blood phosphorylated Tau181 and Aβ42 levels with microstructure of white matter in elderly patients with dementia
Yunxia WANG ; Wangjun LI ; Tao WU ; Haotao LI
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(10):1367-1371
Objective To explore the relationship between peripheral blood levels of phosphoryla-ted Tau181(p-Tau181)and β-amyloid(Aβ)42 and microstructure of white matter in elderly pa-tients with different types of dementia.Methods A total of 64 elderly dementia patients admitted to our department between January 2022 and December 2023 were enrolled and according to dif-ferent types of dementia,they were divided into Alzheimer's disease(AD)group(38 cases)and vascular dementia(VaD)group(26 cases).Another 30 healthy individual taking physical examina-tion during the same period were subjected and served as control group.All participants under-went MRI examination and detection of peripheral blood indicators.The cognitive level[mini-mental state examination(MMSE),Montreal cognitive assessment(MoCA)],diffusion tensor imaging parameters in different white matter areas[fractional anisotropy(FA),mean diffusion coefficient(MD)[,and peripheral blood indicators(p-Tau181,Aβ42)were compared among the three groups.Spearman correlation analysis was applied to analyze the relationship between peripheral blood Tau181 and Aβ42 levels and microstructure of white matter in AD group and VaD group.Results The scores of MMSE and MoCA were significantly higher in the control group than the AD group and the VaD group(28.13±0.72 vs 11.25±2.37 and 10.98±2.59,27.84±0.62 vs 10.37±2.64 and 10.58±2.87,P<0.05).In the VaD group,the MD values of anterior and pos-terior horns of left and right lateral ventricles were obviously greater than the AD group and the control group,while the FA values were notably lower than the two groups(P<0.05).The levels of p-Tau181 and Aβ42 were remarkably higher in the AD group and the VaD group than the con-trol group,and the level of p-Tau181 was significantly higher and that of Aβ42 was significantly lower in the AD group than the VaD group(P<0.05).Spearman correlation analysis showed that in the VaD group,the peripheral blood level of p-Tau181 was positively correlated with the FA value and negatively with the MD value of brain white matter,while that of Aβ42 was negatively with the FA value and positively correlated with the MD value of brain white matter(P<0.01).Conclusion There are significant differences in microstructure damage of white matter and pe-ripheral blood levels of p-Tau181 and Aβ42 among elderly patients with different types of dementi-a,and the levels of the two indicators are correlated with the microstructure damage.Clinically,peripheral blood indicators can be applied to evaluate microstructure damage of white matter.
6.Status of allostatic load in patients with polycystic ovary syndrome and its influence on in vitro fertilization-embryo transfer outcomes
Jingxian CHENG ; Yunxia CAO ; Jiajun GUAN ; Jieyu WANG ; Chunyan WANG ; Guiying LUO ; Chang′e CHEN
Chinese Journal of Obstetrics and Gynecology 2025;60(9):732-740
Objective:To investigate the status of allostatic load (AL) in patients with polycystic ovary syndrome (PCOS) and its influence on the clinical outcomes of in vitro fertilization-embryo transfer.Methods:This was a prospective study. By using convenient sampling method, 421 patients with PCOS (PCOS group) and 372 control infertility patients (control group) in the Reproductive Center of the First Affiliated Hospital of Anhui Medical University from April 2022 to January 2024 were investigated for basic information, physical examination, laboratory examination and follow-up of clinical outcomes. The total score of AL was calculated using 16 related indicators of cardiovascular system, metabolic system and immune system, and AL>3 was used as the judgment criteria for the high level AL group and the low level AL group. The differences in general data, embryo development and clinical outcomes between the groups were compared.Results:There were 222 cases (52.7%, 222/421) in PCOS low level AL group and 199 cases (47.3%, 199/421) in PCOS high level AL group. There were 214 patients (57.5%, 214/372) in the control low level AL group and 158 patients (42.5%, 158/372) in the control high level AL group. Embryo development outcomes: number of oocytes retrieved (median: 12, 12, 19, 14, respectively; P<0.001), number of two pronuclei (median: 8, 7, 11, 8, respectively; P<0.001), number of fertilization (median: 9, 9, 13, 10, respectively; P<0.001), number of metaphase of meiosis Ⅱ oocytes (median: 9, 8, 13, 10, respectively; P<0.001), number of transferable embryos (median: 5, 5, 7, 6, respectively; P<0.001), number of high-quality embryos (median: 4, 3, 6, 5, respectively; P<0.001), gonadotropin(Gn) starting dosage (median: 150, 200, 150, 200 U, respectively; P<0.001), total dosage of Gn (median: 1 800, 2 075, 1 575, 2 025 U, respectively; P<0.001), duration of Gn used (median: 10, 10, 10, 10 days, respectively; P=0.027) in the control low level AL group, control high level AL group, PCOS low level AL group and PCOS high level AL group were significantly different. Pairings between groups showed that number of oocytes retrieved, number of two pronuclei, number of fertilization, number of metaphase of meiosis Ⅱ oocytes and number of transferable embryos in PCOS high level AL group were lower than those in PCOS low level AL group (all P<0.05); Gn starting dosage and total dosage of Gn in PCOS low level AL group were lower than those in the other three groups (all P<0.05); duration of Gn used in PCOS high level AL group was higher than that PCOS low level AL group ( P<0.05). Clinical outcomes: the control low level AL group, control high level AL group, PCOS low level AL group and PCOS high level AL group underwent fresh transplantation [27.4% (57/208), 24.4% (38/156), 15.1% (32/212), 17.1% (33/193), respectively; P=0.006] and the proportion of transplanted day 5 embryos [82.7% (172/208), 77.6% (121/156), 91.0% (193/212), 86.5% (167/193), respectively; P=0.018] were statistically significant. There were no significant differences in fertilization rate, biochemical pregnancy rate, clinical pregnancy rate, multiple pregnancy rate and early abortion rate among the four groups (all P>0.05). Conclusion:The high level of AL in PCOS patients may affect the outcomes of embryo development, and more attention should be paid to AL in PCOS patients to reduce stress.
7.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.
8.The mediating role of social support between anxiety and cancer pain behavior in radiotherapy patients with advanced colorectal cancer
Yunxia ZHANG ; Jialiang ZHOU ; Teng WANG ; Fuzheng ZHANG ; Jing WANG ; Jian ZHANG
Chinese Journal of Behavioral Medicine and Brain Science 2025;34(5):433-437
Objective:To investigate the relationship among social support, anxiety and cancer pain behavior in patients undergoing radiotherapy for advanced colorectal cancer, and to explore the mediating role of social support between anxiety and cancer pain behavior.Methods:A sample of 100 patients with advanced colorectal cancer admitted to the Oncology Radiotherapy Department of the Affiliated Hospital of Jiangnan University was recruited from March 2021 to March 2023. The hospital anxiety and depression scale (HADS), perceived social support scale (PSSS) and visual analogue scale (VAS) were utilized to assess patients' anxiety levels, individually perceived levels of social support and cancer pain intensity.The SPSS 25.0 software and AMOS 26.0 software were used for data analysis.Pearson correlation analysis was conducted to examine the relationships between these variables, and the Bootstrap method was employed to investigate the mediating role of social support in the relationship between anxiety and cancer pain behavior.Results:The patients' HADS anxiety score was (10.63±2.56), VAS pain score was (5.31±1.92), and PSSS social support score was (56.19±6.28). Pearson correlation analysis showed that anxiety was positively correlated with cancer pain behavior ( r=0.785, P<0.001), and social support was significantly correlated with both anxiety ( r=0.671) and cancer pain behavior ( r=0.672) (both P<0.001). Structural equation modeling indicated that social support partially mediated the relationship between anxiety and cancer pain behavior, with an indirect effect value of 0.177 (95% CI=0.033-0.287), accounting for 22.55%(0.177/0.785) of the total effect and the direct effect value was 0.608 (95% CI=0.287-0.642), accounting for 77.45%(0.608/0.785) of the total effect. Conclusion:Social support plays a mediating role in the effect of anxiety on cancer pain behavior in patients with advanced colorectal cancer undergoing radiotherapy. Enhancing social support can effectively alleviate anxiety in patients with advanced colorectal cancer undergoing radiotherapy, thereby alleviating cancer pain behavior, providing a theoretical basis for clinical comprehensive interventions.
9.Study on the Changes in Medical Expenses for Chronic Diseases in Shanxi Province from 2019 to 2022 Based on"SHA 2011"
Hong WANG ; Yunxia ZHANG ; Ying HAN
Chinese Health Economics 2025;44(4):56-60
Objective:To analyze the changes of chronic disease treatment cost in Shanxi,to clarify priorities in chronic disease prevention and control,and provide recommendations for optimizing chronic disease prevention policies.Methods:"SHA 2011"accounting framework was used to measure the change of chronic disease treatment costs.Results:The proportion of chronic diseases in treatment cost remained at about 70%.The proportion of chronic disease treatment cost in general hospital is the highest.The proportion of chronic disease treatment expenses of 45-59 years old is second only to that of 60-74 years old.The proportion of treatment expenses for circulatory diseases should be kept above 25%;the main sources of financing is social medical insurance.Conclusion:The avoidable hospitalization cost of chronic diseases is high.The cost of chronic disease treatment is becoming younger.The health financing structure of chronic diseases tends to be reasonable.In order to further improve the prevention and control effect of chronic diseases and the efficiency of the use of chronic disease resources in Shanxi,it is necessary to improve the effectiveness of key policies,reduce the incidence of chronic diseases;improve the medical insurance reimbursement policy,optimize the use of inpatient services;strengthen the urban medical alliances,guide key groups to seek medical treatment reasonably;optimize the financial compensation and medical insurance payment policy,and improve the multi-channel financing mechanism
10.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.

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