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 and prospect of artificial intelligence and population pharmacokinetics in personalized medication after organ transplantation
Shuai HE ; Huiying ZONG ; An’an LI ; Penglin ZHOU ; Rui GAO ; Xichao WU ; Yanjiao ZHU ; Yan LI
China Pharmacy 2025;36(14):1813-1818
Artificial intelligence (AI) and population pharmacokinetics (PPK) technologies have demonstrated significant potential in the personalized medication of immunosuppressants after organ transplantation, enabling precise prediction of drug dosages. This article provides a comprehensive review of the application status of AI and PPK in the individualized administration of immunosuppressants after organ transplantation, focuses on monitoring blood drug concentration, predicting efficacy/adverse reactions, and establishing individualized dosing models for organ transplant recipients after immunosuppressant administration, and analyzes and compares the application characteristics of different methods in different organ transplant patients as well as the integration and future development of AI and PPK technologies. AI and PPK technologies can not only significantly reduce the dependence on human resources, but also greatly improve the level of individualized treatment of immunosuppressants after organ transplantation, and reduce the discomfort and burden caused by frequent blood concentration monitoring to patients.
5.Efficacy and safety of CDK4/6 inhibitors combined with endocrine therapy for HR+/HER2− advanced or metastatic breast cancer: A network meta-analysis
Yanjiao PU ; Hui LI ; Wei CHEN ; Xueyu DUAN ; Chunmei CHEN ; Rui WU ; Xuechang WANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(06):830-838
Objective To compare the efficacy and safety of different cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy (ET) for the treatment of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2−) advanced or metastatic breast cancer. Methods Randomized controlled trials (RCTs) on CDK4/6i for the treatment of HR+/HER2− metastatic or advanced breast cancer were retrieved from databases including PubMed, EMbase, Web of Science, The Cochrane Library, CNKI, Wanfang, VIP, and SinoMed, with the search period ranging from database inception to August 2023. Bayesian network meta-analysis was conducted using R 4.2.0 software. Results A total of 18 RCTs from 25 articles, involving 8 031 patients and 11 treatment regimens, were included. There was no significant difference in progression-free survival (PFS) or overall survival (OS) among different CDK4/6i+ET combinations. The highest cumulative probability for PFS was observed with dalpiciclib (DAL)+fulvestrant (FUL), while ribociclib (RIB)+FUL ranked first for OS. In terms of efficacy, abemaciclib (ABE)+aromatase inhibitors (AI) and ABE+FUL ranked first in objective response rate and clinical benefit rate, respectively. Regarding safety, statistically significant difference in grade 3-4 adverse events was observed among certain types of CDK4/6i (P<0.05). Conclusion Current evidence suggests that CDK4/6i+ET is superior to ET alone for the treatment of HR+/HER2− advanced/metastatic breast cancer. Different CDK4/6i+ET combinations demonstrate comparable or similar efficacy; however, the incidence of adverse reactions is higher with combination therapy. Treatment regimens should be selected based on individual conditions.
6.Research progress on the lipid-lowering mechanisms and clinical application of GLP-1 receptor agonists
Yanjiao ZHU ; Rui GAO ; Huiying ZONG ; An’an LI ; Penglin ZHOU ; Shuai HE ; Xichao WU ; Yan LI
China Pharmacy 2025;36(20):2615-2620
Glucagon-like peptide-1 (GLP-1) receptor agonists are a novel class of antidiabetic drugs that also possess lipid- lowering and cardiovascular protective effects, with liraglutide and semaglutide being their representative medications. Based on a systematic literature search, this review summarizes the lipid-lowering mechanisms by which liraglutide and semaglutide exert direct effects on the liver and kidney (regulating autophagy, key lipid metabolism pathways, reverse cholesterol transport, etc.), direct actions on adipose tissue (affecting adipocyte proliferation and differentiation, expression of lipid metabolism proteins, and gene transcription), activation of sympathetic pathways through the central nervous system, and modulation of the gut microbiota. Additionally, it summarizes the clinical evidence of their lipid-lowering effects in populations with type 2 diabetes mellitus, overweight individuals, and others. These findings indicate that GLP-1 receptor agonists exert lipid-lowering effects by acting on multiple tissues or systems, providing crucial evidence for further elucidating the molecular mechanisms of these drugs in lipid regulation and exploring potential new ideas for their clinical applications.
7.Ameliorative effect and mechanism of curcumin on diabetes model rats with depression
Hongyan ZHANG ; Yuping ZHANG ; Yanjiao ZHANG ; Jingjing ZHENG ; Rui BIAN ; Wenhui LI ; Weidong REN
China Pharmacy 2024;35(8):942-947
OBJECTIVE To study the ameliorative effect and potential mechanism of curcumin on diabetes model rats with depression based on cAMP response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) signaling pathway. METHODS The diabetes model rat with depression was established by high fat and high sugar diet+intraperitoneal injection of streptozotocin+chronic unpredictable stress-induced depression. The successfully modeled rats were randomly divided into model group, positive control group (0.18 g/kg metformin and 1.8 mg/kg fluoxetine, gavage), curcumin low-dose and high-dose groups (30, 60 mg/kg, gavage) and curcumin high-dose+CREB inhibitor group [60 mg/kg curcumin (gavage)+5 mg/kg CREB inhibitor 666-15 (intraperitoneal injection)], with 12 rats in each group. Another 12 healthy rats were selected as the normal group. Each group was given a corresponding intervention for 4 weeks, the fasting blood glucose level of rats was detected, and the depression of rats was assessed. The levels of corticosterone (CORT) and inflammatory factors [tumor necrosis factor-α (TNF-α), interleukin- 1β (IL-1β), IL-6] in serum, and the levels of norepinephrine (NE) and 5-hydroxytryptamine (5-HT) in hippocampal tissue were determined. The pathological changes and neuronal apoptosis were observed in the hippocampal tissue of rats in each group; the expression levels of CREB, BDNF mRNA and protein in hippocampal tissue were detected. RESULTS Compared with the normal group, the hippocampal tissue of rats in the model group was severely damaged, and neurons were scattered, while the fasting blood glucose, the forced swimming immobility time, the tail suspension immobility time, serum levels of CORT, TNF-α, IL-1β and IL-6, and neuron apoptosis indexes were all increased or prolonged significantly (P<0.05). The levels of NE and 5-HT, the number of surviving neurons, and the expression levels of CREB and BDNF mRNA and protein in hippocampal tissue were decreased significantly (P<0.05). Compared with the 的model group, the damage to hippocampal tissue was relieved in the positive control group and curcumin groups, while the above indexes were improved significantly (P<0.05). The improvement effect of curcumin high-dose group was better than that of curcumin low-dose group (P<0.05). CREB inhibitor could significantly reverse the ameliorative effect of high-dose curcumin on the model rats (P<0.05). CONCLUSIONS Curcumin can improve the depression of diabetes model rats with depression, and relieve neuronal damage and inflammatory response, the mechanism of which may be associated with activating CREB/BDNF signaling pathway.
8.Orthodontic correction of an adult patient with closed deep overbite using clear aligners:A case report
Shuoyi HUI ; Lei WANG ; Zhiwei WANG ; Yanjiao LI ; Fang JIN
Journal of Practical Stomatology 2024;40(2):281-284
An adult female presented with severe closed overbite,class Ⅱ skeletal and dental malocclusion,low angle and straight face.Helped with the clear aligners,the class Ⅱ dental malocclusion was corrected by maxillary molars distalization,the occlusion of anterior teeth were opened by posterior teeth extention and anterior teeth intrusion,and finally a balanced occlusion and an ideal smile line were obtained.
9.Survey on monkeypox knowledge awareness, risk perception and vaccination intention in men who have sex with men in five cities in northeast China
Lingling LI ; Mengjie HAN ; Fan LYU ; Houlin TANG ; Jie YANG ; Wei ZHANG ; Jinrui ZHANG ; Caidong SUN ; Yanjiao CUI ; Yang ZHENG ; Fangfang CHEN
Chinese Journal of Epidemiology 2024;45(1):128-133
Objective:To understand the monkeypox knowledge awareness, risk perception and vaccination intention in men who have sex with men (MSM) in five cities in northeast China.Methods:A cross-sectional study was conducted by using electronic questionnaire in MSM selected by convenience sampling in five cities in northeast China (Shenyang, Panjin, Changchun, Harbin and Jiamusi) from June 28 to July 8, 2023 by local centers for disease control and prevention and MSM communities. The sample size was estimated to be 220. Information about their demographics, monkeypox-related knowledge awareness, perceived concern about epidemic risk perception, and monkeypox vaccination intention were collected. Logistic regression model was used to analyze related factors for MSM's monkeypox vaccination intention.Results:In 355 MSM, 63.9% (227/355) had monkeypox vaccination intentions, and 55.5% (197/355) had high awareness of monkeypox related knowledge with a mean knowledge awareness score of 3.7±1.5. MSM with education level of high-school and above (a OR=1.93, 95% CI:1.01-3.69), higher knowledge awareness score (a OR=1.19, 95% CI:1.02-1.40) and higher risk perception of monkeypox infection (a OR=1.82, 95% CI:1.15-2.88), were more willing to receive monkeypox vaccination. The main reasons for willingness to receive monkeypox vaccine were preventing monkeypox (86.3%, 196/227) and worrying about appearance being affected (62.1%, 141/227). The main reasons for unwillingness for the vaccination included concerns about vaccine safety (53.1%, 68/128), clinical progression of AIDS being affected (46.1%, 59/128) and efficacy of antiretroviral therapy being affected (44.5%, 57/128). Conclusions:The levels of knowledge awareness and vaccine intentions still need to be improved among MSM in five cities of northeast China. It is necessary to improve the awareness of monkeypox and intention of monkeypox vaccination, promote protected sex behavior and self-assessment of infection risk, reduce vaccine hesitancy and increase monkeypox vaccination intention in MSM in 5 cities in northeast China.
10.Construction of an"Internet+Traditional Chinese Medicine nursing"service capability evaluation index system based on the three-dimensional quality structure model
Yanjiao HU ; Yan LI ; Shimiao LUO ; Tao ZOU ; Meizhu DING
Chinese Journal of Nursing 2024;59(15):1818-1823
Objective To construct an evaluation index system of"Internet+Traditional Chinese Medicine nursing"service capability,in order to provide references for the standardized and effective evaluation of"Internet+Traditional Chinese Medicine nursing"service capability.Methods Literature analysis and semi-structured interview method were adopted,and three-dimensional quality structure model was used as the theoretical framework to initially construct the"Internet+Traditional Chinese Medicine nursing"service capability evaluation index item pool.From July to 0ctober 2022,the Delphi method was used to conduct 2 rounds of consultation with 16 experts from Guangdong Province,to evaluate the enthusiasm,authority,degree of opinion concentration and degree of opinion coordination of the experts in the correspondence consultation,and the weight of the index system was determined with the combination of chromatography analysis.Results 2 rounds of expert letter consultation were conducted.The questionnaire recovery rates were 100%,and the authority coefficients were 0.844 and 0.834,respectively.Kendall coordination coefficients were 0.161 and 0.110,respectively(P<0.001).The first level indexes of the index system are structure evaluation,process evaluation and outcome evaluation.There were 3 first-level evaluation indicators,14 second-level evaluation indicators and 57 third-level evaluation indicators.Conclusion The evaluation index is scientific and practical,and it is carried out around the Internet+Traditional Chinese Medicine nursing capability,which provides a certain reference for the effective evaluation of the service capability of"Internet+Traditional Chinese Medicine nursing".

Result Analysis
Print
Save
E-mail