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.Expression of peroxiredoxin 4 in oral squamous cell carcinoma and its effects on cancer cell proliferation, migration, and invasion
GENG Hua ; LI Lei ; YANG Jie ; LIU Yunxia ; CHEN Xiaodong
Journal of Prevention and Treatment for Stomatological Diseases 2025;33(4):278-288
Objective:
To investigate the expression of peroxiredoxin 4 (PRDX4) in oral squamous cell carcinoma (OSCC) and its effect on the proliferation, migration, and invasion of OSCC cells.
Methods:
The Cancer Genome Atlas(TCGA) database was used to analyze the expression of PRDX4 in OSCC. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western Blot (WB) were used to detect the mRNA and protein expression of PRDX4 in OSCC cell lines and normal oral mucosal epithelial cells. PRDX4 was knocked down in CAL-27 cells and divided into two groups: the si-PRDX4 group and si-NC group. SCC-9 cells overexpressing PRDX4 were divided into two groups: the PRDX4 overexpression group (transfected with pcDNA3.1-PRDX4 plasmid) and the vector group (the control group; transfected with pcDNA3.1-NC plasmid). A cell counting kit-8 (CCK-8) and plate colony formation assay were used to detect cell proliferation. Transwell assay and cell scratch test were used to detect cell invasion and migration ability. WB was used to detect the effects of knockdown or overexpression of PRDX4, p38MAPK agonist or inhibitor on the expression of p38MAPK-related signaling pathway proteins, and epithelial mesenchymal transition proteins in OSCC cells.
Results:
PRDX4 was highly expressed in OSCC tissues and cell lines. The results of qRT-PCR and WB showed that PRDX4 was highly expressed in OSCC cell lines compared with normal oral mucosal epithelial cells. The CCK-8 assay showed that the si-PRDX4 group had significantly lower OD values than the si-NC group at 24, 48, and 72 h (P<0.05). The PRDX4 overexpression group had a significantly higher OD value than the vector group at 24, 48, and 72 h (P<0.05). The plate colony formation assay showed that the si-PRDX4 group had a significantly lower number of colonies than the si-NC group (P<0.05). The number of colonies formed in the PRDX4 overexpression group was significantly higher than that in the vector group (P<0.05). The cell scratch test showed that the wound healing area of the si-PRDX4 group was less than that of the si-NC group (P<0.05). The scratch healing area of the PRDX4 overexpression group was significantly higher than that of the vector group (P<0.05). The Transwell invasion assay showed that the number of transmembrane cells in the si-PRDX4 group was lower than that in the si-NC group (P<0.05). The number of transmembrane cells in the PRDX4 overexpression group was significantly higher than that in the vector group (P<0.05). The WB results showed that knockdown and overexpression of PRDX4 could downregulate and upregulate the expression of the p38MAPK signaling pathway and epithelial-mesenchymal transition related proteins, respectively, and the addition of p38MAPK agonist and inhibitor could significantly reverse the expression of related proteins.
Conclusion
PRDX4 is highly expressed in OSCC. Knocking down the expression of PRDX4 in OSCC cells can downregulate the expression of p38 MAPK signal axis and EMT-related signal proteins, thereby inhibiting the proliferation, migration, invasion, and epithelial-mesenchymal transition of cells.
3.Analyzing the quality control evaluation results of occupational health examination institutions in Guizhou Province in 2022
Mei YANG ; Dongxia LI ; Yunxia AO ; Jun LI ; Hourui MA
China Occupational Medicine 2025;52(1):71-75
Objective To understand the status of quality control in occupational medical examination (OME) institutions in Guizhou Province. Methods A total of 124 registered OME institutions actively conducting OME in Guizhou Province were selected as the study subjects using the judgment sampling method. The evaluation was conducted by on-site document reviews, practical skill assessments, and investigation of OME practices for quality evaluation and analyzing their quality control performance. Results The public institutions accounted for 71.0% with a 41.5% of OME workload, while private institutions accounted for 29.0% with a 58.5% of OME workload among these 124 OME institutions. The overall pass rate for quality evaluation of OME institutions was 16.9% (21/124), with a total of 1 296 items failed to pass the quality evaluation. Among the unqualified items, organizational structure, quality control management systems, OME quality control, and information reporting accounted for 15.2%, 21.7%, 52.8%, and 10.3%, respectively. The unqualified rate of quality assessment items of OME institutions was 24.5% (1 296/5 288), and the unqualified rate was lower in public institutions compared with private institutions (22.4% vs 29.3%, P<0.01). The rates of the three key unqualified items, including chest radiography conclusion evaluation, audiogram calculation and conclusion evaluation, and blood lead comparison were 9.8%, 74.8% and 71.4%, respectively. The rates of unqualified audiometry operation test and chief physician theory test were 74.8% and 9.7%, respectively. Conclusion The quality of OME institutions in Guizhou Province requires continuous improvement, particularly in enhancing the abilities of audiometry operation, calculating audiogram results and conducing right conclusion, and blood lead inter-laboratory comparision.
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.Factors influencing carbapenem-resistant gram-negative bacillus infection in elderly patients in the intensive care unit of a general hospital in Yangpu District, Shanghai, 2019‒2023
Wen ZHU ; Qingfeng SHI ; Yi LIANG ; Junping YU ; Yunxia LI ; Chao WENG ; Renyi ZHU
Shanghai Journal of Preventive Medicine 2025;37(6):467-475
ObjectiveTo analyze the characteristics and influencing factors of elderly hospitalized patients with carbapenem-resistant gram-negative bacillus (CRO) infection in the intensive care unit (ICU) of a gradeⅡ level A general hospital in Yangpu District of Shanghai, and to provide scientific basis for the prevention and control of hospital-acquired CRO infection in such hospitals. MethodsThe clinical data of elderly ICU patients (age ≥60 years) from January 2019 to December 2023 were retrospectively collected. A total of 122 cases with hospital-acquired CRO infection were used as the case group, and a total of 68 cases with carbapenem-sensitive gram-negative (CSO) infection were used as the control group. The clinical characteristics of the two groups were analyzed, and univariate analysis and logistic regression analysis were performed for screening for possible influencing factors on hospital-acquired CRO infection. ResultsThe main pathogens of CRO infection were carbapenem-resistant Acinetobacter baumannii (CRAB) (53 cases, 43.44%) and carbapenem-resistant Klebsiella pneumoniae (CRKP) (46 cases, 37.70%), and 17 patients (13.93%) had more than two types of CRO infection. Among the CRO infection, the main sites were lower respiratory tract infection (58 cases, 47.54%), ventilator-associated pneumonia (21 cases, 17.21%), and catheter-associated urinary tract infections (16 cases, 13.11%). The incidence rate of poor prognosis was higher in the CRO infection group (54.10%) than that in the CSO infection group (36.76%) (P=0.021). The results of univariate analysis showed that male, history of hospitalization within three months, chronic respiratory disease, hypoproteinemia, anemia, and history of invasive procedures prior to infection, including indwelling central venous catheter, invasive mechanical ventilation, urinary catheter, gastric tube placement and parenteral nutrition, in addition, heparin anticoagulation, the use of broad-spectrum penicillin, third-generation cephalosporins, fluoroquinolones, carbapenems, carbapenems combined with fluoroquinolones, carbapenems combined with glycopeptides, use of ≥3 antibiotics and long time of antibiotic use prior to infection were all associated with the CRO infection (P<0.05). The results of logistic regression analysis showed that use of carbapenems (OR=7.739, 95%CI: 2.226‒26.911), ≥3 types of antibiotics (OR=6.307, 95%CI: 1.674‒23.754), invasive mechanical ventilation (OR=4.082, 95%CI: 1.795‒9.281), urinary catheter (OR=3.554, 95%CI: 1.074‒11.758), and comorbid hypoproteinemia (OR=4.741, 95%CI: 2.039‒11.022) and diabetes (OR=3.245, 95%CI: 1.344‒7.839) were positively correlated with the risk of CRO infection. ConclusionConcurrent use of carbapenems with multiple other antibiotics, as well as the use of invasive mechanical ventilation, urinary catheter, and comorbid hypoproteinemia and diabetes, may be associated with an increased influencing of CRO infection. More attention should be paid to the prevention and control of infection in elderly patients with the above-mentioned risk factors, and active screening of drug-resistant bacteria should be strengthened. Besides, the rational use of broad-spectrum antibiotics such as carbapenems, avoiding unnecessary invasive operations, and paying attention to patient nutrition and blood glucose control all can reduce the incidence of CRO infection and help to improve clinical outcomes.
7.Application of standardized family in pediatric clinical teaching
Binbin YANG ; Yueling ZHU ; Wei LI ; Zhigang GAO ; Yunxia HONG
Chinese Journal of Medical Education Research 2024;23(3):332-337
Standardized patient (SP) has been widely used for medical teaching and assessment in medical colleges at home and abroad. Pediatric consultations are mostly directed toward parents, so in pediatric education, SP is usually referred to as standardized family (Sfam), which is trained to portray the patient's family members. At present, the development of Sfam in pediatric teaching in China is relatively slow. Based on the characteristics of pediatric teaching, the paper summarizes the necessity of Sfam, the application of different types of Sfam, the integration of Sfam with other clinical teaching methods, and the value of Sfam in pediatric teaching, and also discusses the future direction and prospects of Sfam combined with artificial intelligence in pediatric teaching. After years of development, Sfam has been proved to be an effective teaching model. We hope this paper can help more pediatric clinical educators gain a deeper understanding of the Sfam teaching method, and promote the application of Sfam in pediatric teaching to maximize its role in advancing the development of pediatric education.
8.Intratumoral and peritumoral radiomics based on diffusion weighted imaging for predicting histological grade of breast cancer
Yaxin GUO ; Yunxia WANG ; Yiyan SHANG ; Huanhuan WEI ; Menglu HAI ; Xiaodong LI ; Meiyun WANG ; Hongna TAN
Chinese Journal of Interventional Imaging and Therapy 2024;21(3):160-165
Objective To observe the value of intratumoral and peritumoral radiomics based on diffusion weighted imaging(DWI)for predicting histological grade of breast cancer.Methods Preoperative DWI data of 700 patients with single breast cancer diagnosed by pathology were retrospectively analyzed.The patients were divided into training set(n= 560,including 381 of grade Ⅰ+Ⅱ and 179 of grade Ⅲ)and test set(n=140,including 95 of grade Ⅰ+Ⅱ and 45 of grade Ⅲ)at the ratio of 8∶2.Intratumoral ROI(ROIintra)was manually delineated on DWI,which was automatically expanded by 3 mm and 5 mm to decline peritumoral ROI(ROIperi,including ROI3 mm and ROI5 mm),then intratumoral-peritumoral ROI(ROIintra+3 mm,ROIintra+5 mm)were obtained.The optimal radiomics features were extracted and screened,and the radiomics model(RM)for predicting the histological grade of breast cancer were constructed.Receiver operating characteristic curves were drawn,and the areas under the curve(AUC)were calculated to evaluate the predictive efficacy of each model.Calibration curve method was used to evaluate the calibration degree,while decision curve analysis(DCA)was performed to explore the clinical practicability of each model.Results AUC of RMintra,RM+3 mm,RM+5mm,RMintra+3 mm and RMintra+5 mm was 0.750,0.724,0.749,0.833 and 0.807 in training set,while was 0.723,0.718,0.736,0.759 and 0.782 in test set,respectively.In training set,significant differences of AUC was found(all P<0.01),while in test set,no significant difference of AUC was found among models(all P>0.05).The calibrations of models were all high.DCA showed that taken 0.02-0.88 as the threshold,the clinical net benefit of RMintra+per were greater in training set,while taken 0.40-0.72 as the threshold,the clinical net benefit of RMintra+per was greater in test set.Conclusion Both DWI intratumoral and peritumoral radiomics could effectively predict histological grade of breast cancer.Combination of intratumoral and peritumoral radiomics was more effective.
9.Analysis of pregnancy outcomes after transplantation of frozen-thawed embryo transfer in PCOS patients
Huifen XIANG ; Pin ZHANG ; Zuying XU ; Zhenran LIU ; Yue HUANG ; Yuting HUANG ; Qiong WU ; Yiran LI ; Rong LI ; Yunxia CAO
Acta Universitatis Medicinalis Anhui 2024;59(4):684-689
Objective To investigate the factors influencing the pregnancy outcomes during frozen-thawed embryo transfer(FET)cycles in patients with polycystic ovary syndrome(PCOS).Methods A retrospective analysis was conducted on patients'data from 882 FET cycles.According to the pregnancy outcome,the patients were divided into non-implantation group(Group A),abortion group(Group B1)and live birth group(Group B2).Clinical data and laboratory parameters were compared among the three groups,and ordered Logistic regression analysis was used to study the factors influencing pregnancy outcomes after FET.Patients were also divided into four groups(C1-C4)based on the number of high-quality embryos obtained(0-3,4-6,7-10,≥11),and their clinical data and laboratory parameters were compared.Results The clinical pregnancy rate,live birth rate,and miscar-riage rate in the 882 treatment cycles were 71.09%(627/882),61.68%(544/882),and 13.24%(83/627),respectively.Single-factor analysis showed significant differences in body mass index(BMI),infertility type,hu-man chorionic gonadotropin(hCG)day estradiol(E2)level,number of retrieved oocytes,and number of high-quality embryos among Groups A,B1,and B2(P<0.05).Further multiple Logistic regression analysis revealed that BMI(OR=1.046,95%CI:1.001-1.093,P=0.044)and a history of previous pregnancy(OR=1.417,95%CI:1.030-1.950,P=0.032)were independent risk factors for successful FET in PCOS patients,while an in-creased number of high-quality embryos was an independent protective factor for successful pregnancy.Based on the results of Group B2,compared to Group A,OR=0.920,95%CI:0.880-0.962,P=0.000;compared to Group B1,OR=0.923,95%CI:0.862-0.988,P=0.022.Compared with the other three groups(C1-C3),the total amount of gonadotropin(Gn)in the C4 group was the lowest and the number of oocytes obtained was the high-est(P<0.05).Multiple comparisons showed that Group C4 had lower BMI,follicle-stimulating hormone(FSH),very low-density lipoprotein(vLDL)levels,a higher luteinizing hormone and follicle-stimulating hormone(LH/FSH)ratio compared to Group C1(P<0.05).Group C4 had lower fasting insulin(FINS)and homeostasis model assessment of insulin resistance(HOMA-IR)levels compared to Group C3,and higher high-density lipoprotein-cholesterol(HDL-C)and apolipoprotein A1(Apo A1)levels compared to Groups C2 and C3(P<0.05).Con-clusion BMI,the history of previous pregnancy and the number of high-quality embryos were both independent factors for predicting pregnancy outcomes in PCOS patients undergoing FET cycles.Patients with a higher number of high-quality embryos have a higher clinical pregnancy rate during FET cycles.
10.Correlation between the expression of hsa_circ_0001785 in triple negative breast cancer and the efficacy of neoadjuvant chemotherapy
Ming LI ; Yunxia LIU ; Liping WANG ; Lixin DUAN ; Jingjing BI
Journal of Clinical Surgery 2024;32(11):1157-1160
Objective To investigate the correlation between the expression of hsa_circ_0001785 in triple negative breast cancer(TNBC)and the efficacy of neoadjuvant chemotherapy(NAC).Methods A total of 129 patients with triple negative breast cancer who were admitted to our hospital from October 2021 to February 2023 were regarded as the study group,and 125 patients with benign breast lesions who underwent surgery in our hospital were served as the control group.The influencing factors of NAC efficacy in TNBC patients were analyzed by multivariate logistic regression model;receiver operating characteristic(ROC)curve was applied to analyze the predictive value of hsa_circ_0001785 level for NAC efficacy in triple negative breast cancer patients.Results Compared with the control group(1.05±0.16),the expression level of hsa_circ_0001785 in the study group(2.47±0.39)increased(P<0.05);compared with the effective group(2.34±0.35),the expression level of hsa_circ_0001785 in the ineffective group(3.48±0.56)increased(P<0.05);hsa_circ_0001785 was highly expressed in triple negative breast cancer patients with tumor diameter>2 cm,lymph node metastasis and high tissue grade(P<0.05);high expression of hsa_circ_0001785,tumor diameter>2 cm,occurrence of lymph node metastasis and high histological grade were risk factors for NAC efficacy in triple negative breast cancer patients(P<0.05).Hsa_circ_0001785 level has certain predictive value for NAC efficacy in TNBC patients.Conclusion Hsa_circ_0001785 is highly expressed in triple negative breast cancer,and the level of hsa_circ_0001785 has a certain predictive value for the efficacy of NAC in patients.


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