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.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.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.Application research of PGT in blocking the inheritance of novel mutations in the PKHD1 gene in autoso-mal recessive polycystic kidney disease pedigrees
Ning WANG ; Yan HAO ; Dawei CHEN ; Zhiguo ZHANG ; Dan KUANG ; Qing ZHANG ; Yiqi YING ; Zhaolian WEI ; Ping ZHOU ; Yunxia CAO
The Journal of Practical Medicine 2024;40(7):1006-1010
Objective To investigate the application value of single nucleotide polymorphism(SNP)linkage analysis based on next-generation sequencing(NGS)technology in preimplantation genetic testing(PGT)of families with autosomal recessive polycystic kidney disease(ARPKD).Methods A family with ARPKD was selected,where the female member had a pregnancy ultrasound revealing polycystic kidney in the fetus.Genetic testing showed compound heterozygous mutations of the polycystic kidney/polycystic liver disease 1 gene(PKHD1),c.10444C>T(paternal)and c.4303del(maternal),with the c.4303del mutation being reported for the first time.Targeting the coding region of the PKHD1 gene,335 high-density tightly linked SNP sites were selected in the upstream and downstream 2M regions using multiplex polymerase chain reaction(PCR)and NGS.The couple′s SNP risk haplotypes carrying gene mutations were constructed.After in vitro fertilization,blastocyst culture was performed.Trophoblastic cells obtained from the biopsy were subjected to whole-genome amplification,and NGS was used for linkage analysis and low-depth chromosomal aneuploidy screening of the embryos.Sanger sequencing was used to verify the results of embryo linkage analysis.Results Among the 6 biopsied embryos,4 were mutation-free and euploid,1 exhibited heterozygous for the mutation and mosaic while another unstable sequencing data,making it impossible to judge.One of the mutation-free and developmentally healthy euploid embryos was implanted into the maternal uterus,resulting in the full-term delivery of a healthy baby.Conclusion Application of NGS-based SNP linkage analysis in PGT can effectively blocking the vertical transmission of ARPKD within families,while avoiding abortion issues caused by aneuploid embryos.This study is also the first PGT report target-ing the PKHD1 gene c.4303del mutation.
5.Construction and Verification of a Risk Prediction Model for Death From Dissection Rupture in Patients With Acute Aortic Dissection During Emergency Treatment
Zhixin ZHANG ; Tao LIANG ; Yanmin YANG ; Chen ZHANG ; Yunxia HAO ; Yanjuan ZHANG ; Rui ZHAO ; Ran PANG ; Jing YANG
Chinese Circulation Journal 2024;39(9):903-909
Objectives:To explore the risk factors for death from ruptured acute aortic dissection during emergency treatment,construct and validate a risk prediction model for death from ruptured acute aortic dissection during emergency treatment. Methods:A total of 301 cases of acute aortic dissection patients who were admitted to Chinese Academy of Medical Sciences Fuwai Hospital from January 2018 to August 2021 were included in this study.Patients were divided into survival subgroup(n=239)and death subgroup(n=62)according to whether dissection rupture occurred in the acute stage of the disease.Univariate and multivariate analyses were performed.Logistic regression analysis was used to establish the risk prediction model.The Hosmer-Lemeshow test was conducted to assess the model's goodness of fit,and the receiver operating characteristic curve(ROC curve)was used to evaluate the model's predictive performance.A prospective validation was performed on 129 cases of acute aortic dissection patients admitted to our hospital's emergency department from September 2021 to September 2022. Results:Among the 301 cases of acute aortic dissection patients,there were 62 cases of rupture and death,with an incidence rate of 20.6%.The results of multivariate analysis showed that age(OR=1.066,95%CI:1.034-1.099),type A dissection(OR=0.045,95%CI:0.006-0.364),history of hypertension(OR=0.377,95%CI:0.167-0.850),and concomitant hypotension(OR=4.424,95%CI:1.467-13.340)were determinants of deaths.The model formula was Z=-5.624+0.064×age-0.976×history of hypertension(yes=1,no=0)-3.104×type(Type A=0,Type B=1)+1.487×concomitant hypotension(yes=1,no=0).The Hosmer-Lemeshow test result showed χ2=9.328,df=8,P=0.315,the area under the ROC curve was 0.874,sensitivity was 79.0%,specificity was 81.6%,and the maximum Youden index was 0.606.The model validation result showed that the area under the ROC curve was 0.722,sensitivity was 73.7%,specificity was 69.1%,and accuracy was 89.9%. Conclusions:Age,history of hypertension,dissection type,and combined hypotension are predictors of the risk prediction model for death from dissection rupture in patients with acute aortic dissection during emergency treatment.The model constructed in this study has good predictive performance,which can provide reference for medical staffto quickly identify high-risk patients for death from ruptured acute aortic dissection and timely predictive measures could be highlighted in indicated cases.
6.Development of a droplet digital polymerase chain reaction assay for the sensitive detection of total and integrated HIV-1 DNA
Lin YUAN ; Zhiying LIU ; Xin ZHANG ; Feili WEI ; Shan GUO ; Na GUO ; Lifeng LIU ; Zhenglai MA ; Yunxia JI ; Rui WANG ; Xiaofan LU ; Zhen LI ; Wei XIA ; Hao WU ; Tong ZHANG ; Bin SU
Chinese Medical Journal 2024;137(6):729-736
Background::Total human immunodeficiency virus (HIV) DNA and integrated HIV DNA are widely used markers of HIV persistence. Droplet digital polymerase chain reaction (ddPCR) can be used for absolute quantification without needing a standard curve. Here, we developed duplex ddPCR assays to detect and quantify total HIV DNA and integrated HIV DNA.Methods::The limit of detection, dynamic ranges, sensitivity, and reproducibility were evaluated by plasmid constructs containing both the HIV long terminal repeat (LTR) and human CD3 gene (for total HIV DNA) and ACH-2 cells (for integrated HIV DNA). Forty-two cases on stable suppressive antiretroviral therapy (ART) were assayed in total HIV DNA and integrated HIV DNA. Correlation coefficient analysis was performed on the data related to DNA copies and cluster of differentiation 4 positive (CD4 +) T-cell counts, CD8 + T-cell counts and CD4/CD8 T-cell ratio, respectively. The assay linear dynamic range and lower limit of detection (LLOD) were also assessed. Results::The assay could detect the presence of HIV-1 copies 100% at concentrations of 6.3 copies/reaction, and the estimated LLOD of the ddPCR assay was 4.4 HIV DNA copies/reaction (95% confidence intervals [CI]: 3.6-6.5 copies/reaction) with linearity over a 5-log 10-unit range in total HIV DNA assay. For the integrated HIV DNA assay, the LLOD was 8.0 copies/reaction (95% CI: 5.8-16.6 copies/reaction) with linearity over a 3-log 10-unit range. Total HIV DNA in CD4 + T cells was positively associated with integrated HIV DNA ( r = 0.76, P <0.0001). Meanwhile, both total HIV DNA and integrated HIV DNA in CD4 + T cells were inversely correlated with the ratio of CD4/CD8 but positively correlated with the CD8 + T-cell counts. Conclusions::This ddPCR assay can quantify total HIV DNA and integrated HIV DNA efficiently with robustness and sensitivity. It can be readily adapted for measuring HIV DNA with non-B clades, and it could be beneficial for testing in clinical trials.
7.Effect of vitamin D drops combined with insulin aspart in the treatment of gestational diabetes mellitus and its influence on serum 1, 25(OH) 2D 3 and RBP4 levels
Yunxia LI ; Qian GAO ; Yan ZHANG ; Xinmiao GE ; Yaqin HAO ; Bing WANG
Journal of Chinese Physician 2023;25(8):1181-1186
Objective:To investigate the clinical efficacy of vitamin D drops combined with insulin aspart in the treatment of gestational diabetes mellitus (GDM), and the effect of vitamin D drops on the serum levels of 1, 25 dihydroxyvitamin D 3 [1, 25(OH) 2D 3] and retinol binding protein 4 (RBP4). Methods:A total of 94 GDM patients admitted to the Baoding Second Central Hospital from March 2019 to March 2021 were selected and randomly divided into an observation group and a control group with 47 cases each using a random number table method. The control group received subcutaneous injection of insulin aspartate for treatment, while the observation group received oral vitamin D drops for treatment. After 4 weeks of continuous treatment, the blood glucose control effect and adverse reactions were observed in both groups. The glucose metabolism indicators of the two groups were compared before and after treatment, including fasting blood glucose (FPG), 2-hour postprandial blood glucose (2-hour PG), insulin resistance index (HOMA-IR), and pancreatic islets β Cell Function Index (HOMA-β) and serum levels of 1, 25(OH) 2D 3, RBP4, lipoprotein related phospholipase A2 (Lp-PLA2), and vascular cell adhesion molecule-1 (VCAM-1). All patients were followed up until the end of pregnancy, and Statistical analysis was conducted on the adverse outcomes of two groups of mothers and infants. Results:The time to reach the standard for FPG and 2-hour PG in the observation group, as well as the time for both to reach the standard were significantly shorter than those in the control group (all P<0.05). There was no statistically significant difference in the incidence of dawn phenomenon and hypoglycemia between the observation group and the control group (all P>0.05). After treatment, FPG and 2-hour PG in both groups were significantly reduced compared to those before treatment (all P<0.05); However, after treatment, there was no statistically significant difference between the groups (all P>0.05). Compared with before treatment, HOMA-IR in both groups significantly decreased (all P<0.05), All HOMA- β significantly increased (all P<0.05); And the improvement was more significant in the observation group (all P<0.05). After treatment, the serum levels of 1, 25(OH) 2D 3 in the observation group significantly increased compared to that before treatment ( P<0.05), but there was no significant change in the control group before and after treatment ( P>0.05). After treatment, the levels of serum RBP4, Lp-PLA2, and VCAM-1 in both groups significantly decreased compared to those before treatment (all P<0.05); After treatment, the serum levels of RBP4, Lp-PLA2, and VCAM-1 in the observation group were lower than those in the control group (all P<0.05). The incidence of adverse maternal and neonatal outcomes in the observation group was 14.9%(7/47) and 10.6%(5/47), respectively, which were lower than those in the control group [34.0%(16/47) and 27.7%(13/47)] (all P<0.05). There were 8 cases of hypoglycemia in 94 patients (3 in the observation group and 5 in the control group), and no other adverse events occurred. Conclusions:The combination of vitamin D drops and insulin aspartate in the treatment of GDM can safely, effectively, quickly, and steadily control patients′ blood sugar, improve IR and pancreatic islets β The effect of cell function on reducing the incidence of adverse maternal and fetal outcomes may be related to increasing serum 1, 25(OH) 2D 3 levels and down-regulating the expression levels of serum RBP4, Lp-PLA2, and VCAM-1.
8.Clinical outcomes of preimplantation genetic testing of vitrification⁃thawing blastocysts
Dan Kuang ; Yan Hao ; Dawei Chen ; Zhiguo Zhang ; Qing Zhang ; Yiqi Yin ; Ning Wang ; Ping Zhou ; Zhaolian Wei ; Yunxia Cao
Acta Universitatis Medicinalis Anhui 2023;58(8):1380-1386
Objective :
To analyze the data related to the clinical outcome of preimplantation genetic testing (PGT)
for double frozen , double biopsied blastocysts and double frozen , once biopsied blastocysts , in order to expand the existing data and provide some guidance for the clinical value and safety of PGT for frozen⁃thawed embryos .
Methods :
Retrospective analysis was made on the 38 PGT cycles of frozen⁃thawed blastocysts . According to the frequency of biopsy , cases in the study were divided into two groups : double frozen , double biopsy ( DFDB) group and double frozen , single biopsy ( DFSB) group . The freezing method was vitrification .
Results :
There were 24 patients in DFDB group , 34 blastocysts were not diagnosed in the last PGT cycle , 32 blastocysts survived after thawing , and the survival rate of thawed blastocysts was 94. 12% . After the second biopsy of these 32 blastocysts , genetic testing was performed , and all of them were definitely diagnosed , including 15 normal blastocysts (46. 88% ) and 17 abnormal blastocysts (53 . 13% ) . There were 14 patients in DFSB . The remaining 50 blastocysts in the last ICSI cycle were thawed and all blastocysts survived after thawing . Biopsy of these 50 blastocysts and genetic analysis showed that 47 blastocysts were diagnosed , including 9 normal blastocysts (18 . 00% ) , 28 abnormal blastocysts (56. 00% ) , 10 mosaic blastocysts (20. 00% ) , and 3 undiagnosed blastocysts (6. 00% ) . In DFDB group and DFSB group , 8 patients and 5 patients transferred the normal blastocystswhich all survivedafter thawing . There were 5 clinical pregnancies and 3 clinical pregnancies , respectively . One healthy live birth was obtained respectively in each group .
Conclusion
Acceptable pregnancy rate can be obtained whatever DFSB or DFDB blastocyst , which is
of clinical value . However , due to the small sample size , we need to expand the sample size to further explore its
safety .
9.Construction and evaluation of bundle nursing program for prevention of mechanical circulatory support infection after heart transplantation
Fan LU ; Feifei ZHUANG ; Rong WU ; Yunxia HAO ; Yan MA ; Chen ZHANG
Chinese Journal of Modern Nursing 2022;28(32):4555-4560
Objective:To construct a bundle nursing program to prevent mechanical circulatory support infection after adult heart transplantation.Methods:This study followed the process of formulating the bundle nursing program, determined the theme of bundle nursing and established a multidisciplinary support system. Based on literature research and theoretical analysis, a preliminary strategy draft was prepared. Delphi method was used to conduct two rounds of expert consultation for 16 experts, and calculate the weight of each item. Combined with expert opinions and pilot feedback, the final draft of bundle nursing program for prevention of mechanical circulation support infection after adult heart transplantation was finally formed.Results:The final bundle nursing program for prevention of mechanical circulation support infection after adult heart transplantation included 4 first-level indexes and 7 second-level items, and the importance and clinical applicability of each item were more than 3.50. The positivity of the experts was high, the authority coefficient was 0.73 and 0.87, and the coordination coefficient was 0.216 and 0.125, respectively ( P<0.05) . Conclusions:The bundle nursing program constructed in this study to prevent mechanical circulation support infection after adult heart transplantation is scientific and practical. Further confirmatory research will be carried out to provide evidence for the prevention of mechanical circulation support infection after heart transplantation.
10.Status and influencing factors of incontinence-associated dermatitis among elderly inpatients in 52 hospitals nationwide
Qixia JIANG ; Dan KUANG ; Jing WANG ; Jingping HAO ; Gailin HAO ; Yajuan WENG ; Yumei LI ; Haiyan LIU ; Shiming HUANG ; Bo LI ; Yunxia LUO ; Suling SHI ; Haihua GUO ; Yuxuan BAI
Chinese Journal of Modern Nursing 2022;28(21):2843-2849
Objective:To explore the status and influencing factors of incontinence-associated dermatitis among elderly inpatients in 52 hospitals nationwide, and to analyze the nursing of elderly inpatients with incontinence, so as to provide a reference for clinical intervention.Methods:On March 31, 2021, convenience sampling was used to select 14 675 elderly inpatients from 52 hospitals across the country as the research object. The self-designed Incontinence-associated Dermatitis Questionnaire for Elderly Inpatients was used to collect general demographic data, health status, incontinence, and skin nursing. Binomial Logistic regression was used to investigate the influencing factors of incontinence-associated dermatitis in elderly inpatients.Results:Among 14 675 elderly inpatients, the prevalence rates of xerosis cutis, incontinence and incontinence-associated dermatitis were 38.78% (5 691/14 675) , 11.06% (1 623/14 675) and 1.91% (280/14 675) , respectively. The prevalence of mild, moderate and severe incontinence-associated dermatitis were 1.27% (186/14 675) , 0.55% (81/14 675) , and 0.09% (13/14 675) , respectively. Among the nursing of 1 623 elderly inpatients with incontinence, the items with low implementation rate were the use neutral lotion to clean skin (14.17%, 230/1 623) , use of skin protectant after moisturizing (17.68%, 287/1 623) , moisturizing after cleansing the skin (28.90%, 469/1 623) . The results of binomial Logistic regression analysis showed that xeroderma, fecal incontinence, urinary and fecal incontinence, ≥2 kinds of combined medication, and hospital stay >30 days were risk factors for incontinence-associated dermatitis in elderly inpatients.Conclusions:The risk factors of incontinence-associated dermatitis in elderly inpatients mainly include xerosis cutis, type of incontinence, ≥2 kinds of combined medication, and hospital stay >30 days.


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