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.Association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40-89 in selected areas of China
Yufei LUO ; Yuan WEI ; Xiaochen WANG ; Yi ZHANG ; Wenli ZHANG ; Bing WU ; Zhengxiong YANG ; Xiaojie DONG ; Ruiting HAO ; Yifu LU ; Xiaoshuang FU ; Ziyue ZHU ; Ying ZHU ; Yuebin LYU ; Dongqun XU ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2024;58(6):839-846
Objective:To investigate the association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40 to 89 years in selected areas of China.Methods:The research was based on the survey of the impact of soil quality of agricultural land on human health in typical areas conducted in 2019-2020. A total of 5 600 middle-aged and older adults aged 40 to 89 years were included by using a multi-stage stratified random sampling method. Baseline characteristics of the subjects were collected and physical examinations were performed. Random midstream urine was collected to measure urinary cadmium and urinary creatinine and fasting venous blood was collected to measure the leukocyte count, neutrophil count, lymphocyte count, monocyte count and eosinophil count. The linear mixed effect model was used to analyse the association of urinary cadmium levels with leukocyte classification counts, and the dose-response relationship between them was analyzed by using the restricted cubic spline (RCS) function.Results:The age of the subjects was (63.17±12.02) years; 2 851 (50.91%) were males; and the M ( Q 1, Q 3) of urinary creatinine-corrected urinary cadmium levels was 2.69 (1.52, 4.69) μg/g·creatinine. After adjusting for confounding factors, the results of linear mixed effects model analysis showed that for each 1-unit increase in urinary creatinine-corrected urinary cadmium level, the percentage change [% (95% CI)] of leukocyte count and lymphocyte count was -1.70% (-2.61%, -0.79%) and -1.57% (-2.86%, -0.26%), respectively. RCS function showed a negative linear relationship between urinary creatinine-corrected urinary cadmium levels and leukocyte counts and lymphocyte counts, respectively (all Pnon-linear>0.05). Conclusion:Urinary cadmium levels are negatively associated with leukocyte count and lymphocyte count among middle-aged and older adults aged 40 to 89 years in selected areas of China.
5.A correlation study between T1ρ and T2 values of glenohumeral articular cartilage and rotator cuff injury
Yaqing YANG ; Wenjuan LIANG ; Guohua WANG ; Tianqi HAO ; Xiaoming HUANG
Journal of Practical Radiology 2024;40(6):957-960
Objective To quantitatively study the correlation between T1ρ and T2 values of glenohumeral articular cartilage and the degree of rotator cuff injury.Methods A total of 149 patients with rotator cuff injury and healthy volunteers were prospectively selected.All of them underwent MRI routine scanning and T1 ρ and T2 mapping sequences.The degree of rotator cuff injury was graded,and the T1ρ and T2 values of glenohumeral articular cartilage were measured to analyze their relationship.Results With the development of rotator cuff injury grading,the T1 ρ and T2 values of glenohumeral articular cartilage increased.There were statistically significant differences in T1ρ and T2 values of articular cartilage between the different grades of rotator cuff injury(P<0.001).Conclusion The injury of glenohumeral articular cartilage is aggravated with the severity of rotator cuff injury.The severity of rotator cuff injury can be evaluated by analyzing the T1 ρ and T2 values of glenohumeral articular cartilage.
6.The quantitative assessment value of the IDEAL-IQ sequence for knee osteoarthritis and surrounding soft tissue fat infiltration
Tianqi HAO ; Yamei WANG ; Guohua WANG ; Yaqing YANG ; Xiaoming HUANG
Journal of Practical Radiology 2024;40(8):1329-1333
Objective To explore the value of measuring infrapatellar fat pad(IPFP)and muscle fat fraction(FF)around the knee joint based on iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification(IDEAL-IQ)quantitative technology in patients with knee osteoarthritis(KOA)for the degree of KOA.Methods A total of 106 participants were included in this study.Participants were grouped based on Kellgren-Lawrence grading(KLG),divided into no KOA group,mild KOA group and severe KOA group.The IDEAL-IQ technology was used to measure FF values of IPFP and muscles around the knee joint,the correlation between FF values and KOA was analyzed,and its value in diagnosing KOA was evaluated.Results In severe KOA group and mild KOA group can be observed in the way of lower IPFP FF values and higher FF values muscles around the knee joint.The FF values of IPFP and part of the muscles around the knee joint[vastus medialis muscle(VM),vastus lateralis muscle(VL),semimembranosus(SE),sartorius(SA),medial head of gastrocnemius muscle(Gas(media)),lateral head of gastrocnemius muscle(Gas(lateral))]were correlated with the degree of KOA(r/rs=-0.708,0.737,0.567,0.468,0.280,0.491,0.378),the area under the curve(AUC)for diagnosing KOA were 0.850,0.950,0.842,0.759,0.692,0.763,and 0.725,respectively.Conclusion IDEAL-IQ sequence can quantitatively assess fat infiltration of IPFP and muscles around the knee joint in patients with KOA,and has certain potential to predict the development and severity of KOA.
7.Bowel Sounds Detection Method Based on ResNet-BiLSTM and Attention Mechanism
Yali HAO ; Xianrong WAN ; Congqing JIANG ; Xianghai REN ; Xiaoming ZHANG ; Xiang ZHAI
Chinese Journal of Medical Instrumentation 2024;48(5):498-504
Bowel sounds can reflect the movement and health status of the gastrointestinal tract.However,the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive.In order to better assist doctors in diagnosing bowel sounds and improve the reliability and efficiency of bowel sound detection,this study proposed a deep neural network model that combines a residual neural network(ResNet),a bidirectional long short-term memory network(BiLSTM),and an attention mechanism.Firstly,a large number of labeled clinical data was collected using the self-developed multi-channel bowel sound acquisition system,and the multi-scale wavelet decomposition and reconstruction method was used to preprocess the bowel sounds.Then,log Mel spectrogram features were extracted and sent to the network for training.Finally,the performance and effectiveness of the model were evaluated and verified by 10-fold cross-validation and an ablation experiment.The experimental results showed that the precision,recall,and F1 score of the model reached 83%,76%,and 79%,respectively,and it could effectively detect bowel sound segments and locate their start and end times,performing better than previous algorithms.This algorithm can not only provide auxiliary information for doctors in clinical practice but also offer technical support for further analysis and research of bowel sounds.
8.Association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40-89 in selected areas of China
Yufei LUO ; Yuan WEI ; Xiaochen WANG ; Yi ZHANG ; Wenli ZHANG ; Bing WU ; Zhengxiong YANG ; Xiaojie DONG ; Ruiting HAO ; Yifu LU ; Xiaoshuang FU ; Ziyue ZHU ; Ying ZHU ; Yuebin LYU ; Dongqun XU ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2024;58(6):839-846
Objective:To investigate the association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40 to 89 years in selected areas of China.Methods:The research was based on the survey of the impact of soil quality of agricultural land on human health in typical areas conducted in 2019-2020. A total of 5 600 middle-aged and older adults aged 40 to 89 years were included by using a multi-stage stratified random sampling method. Baseline characteristics of the subjects were collected and physical examinations were performed. Random midstream urine was collected to measure urinary cadmium and urinary creatinine and fasting venous blood was collected to measure the leukocyte count, neutrophil count, lymphocyte count, monocyte count and eosinophil count. The linear mixed effect model was used to analyse the association of urinary cadmium levels with leukocyte classification counts, and the dose-response relationship between them was analyzed by using the restricted cubic spline (RCS) function.Results:The age of the subjects was (63.17±12.02) years; 2 851 (50.91%) were males; and the M ( Q 1, Q 3) of urinary creatinine-corrected urinary cadmium levels was 2.69 (1.52, 4.69) μg/g·creatinine. After adjusting for confounding factors, the results of linear mixed effects model analysis showed that for each 1-unit increase in urinary creatinine-corrected urinary cadmium level, the percentage change [% (95% CI)] of leukocyte count and lymphocyte count was -1.70% (-2.61%, -0.79%) and -1.57% (-2.86%, -0.26%), respectively. RCS function showed a negative linear relationship between urinary creatinine-corrected urinary cadmium levels and leukocyte counts and lymphocyte counts, respectively (all Pnon-linear>0.05). Conclusion:Urinary cadmium levels are negatively associated with leukocyte count and lymphocyte count among middle-aged and older adults aged 40 to 89 years in selected areas of China.
9.Effect of Yudantong decoction on intestinal flora and intestinal barrier function in mice with cholestasis induced by α-naphthyl isothiocyanate
Xiaoming WU ; Qiang HE ; Linyi HOU ; Yan HU ; Xiaofang ZHEN ; Jing HAO ; Yan SHENG
Journal of Clinical Hepatology 2023;39(4):864-875
Objective To investigate the therapeutic effect of Yudantong decoction in mice with α-naphthyl isothiocyanate (ANIT)-induced cholestasis, as well as its targets and mechanism based on intestinal flora and intestinal barrier function. Methods A total of 24 C57BL/6 mice were randomly divided into control group, model group, Yudantong decoction group (YDTF group), and ursodeoxycholic acid (UDCA) group, with 6 mice in each group. The mice in the model group, the YDTF group, and the UDCA group were given ANIT 35 mg/kg/day by gavage on days 1, 4, 7, 10, and 13, and those in the YDTF group and the UDCA group were given Yudantong decoction or UDCA by gavage for 15 consecutive days; related samples were collected on day 16. Liver histopathology was observed, and liver function parameters were measured; immunohistochemistry was used to measure the protein expression levels of caspase-1, interleukin-1β (IL-1β), and FXR in the liver, and flow cytometry was used to measure the percentages of CD11b + , CD86 + , and CD45 + immune cells in the liver; 16S rDNA sequencing and information analysis were performed for fecal microorganisms; immunohistochemistry was used to measure the protein expression of the intestinal FXR/NLRP3 pathway, and immunofluorescence assay was used to measure the protein expression of intestinal E-cadherin and occludin. A one-way analysis of variance was used for comparison of continuous data with homogeneity of variance between multiple groups, and the least significant difference t -test was used for further comparison between two groups; the Welch test was used for comparison of data with heterogeneity of variance between multiple groups, and the Games-Howell test was used for further comparison between two groups. Results HE staining showed that the model group had partial hepatocyte fatty degeneration, massive necrosis of hepatocytes in hepatic lobules, damage of lobular structure, and massive inflammatory cell infiltration, and the YDTF group and the UDCA group had alleviation of hepatocyte fatty degeneration and hepatocyte necrosis in hepatic lobules, with a reduction in inflammatory cells. Compared with the control group, the model group had significantly higher serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP), total bilirubin (TBil), direct bilirubin (DBil), and total bile acid (TBA) (all P < 0.05); compared with the model group, the YDTF group had significant reductions in the serum levels of ALT, AST, GGT, ALP, TBil, DBil, and TBA (all P < 0.05), and the UDCA group had significant reductions in the serum levels of GGT, TBil, DBil, and TBA (all P < 0.05). Compared with the control group, the model group had significant increases in the levels of caspase-1 and IL-1β and a significant reduction in the expression of FXR in the liver (all P < 0.05); compared with the model group, the YDTF group had significant reductions in the levels of caspase-1 and IL-1β in the liver and the UDCA group had a significant reduction in the level of IL-1β in the liver, and both the YDTF group and the UDCA group had a significant increase in the expression level of FXR in the liver (all P < 0.05). The model group had a significant change in the composition of intestinal flora compared with the control group ( P < 0.05); there was a significant difference in the structure of intestinal flora between the YDTF group and the model group ( P < 0.05), and there was also a significant difference in the composition of intestinal flora between the UDCA group and the control/model groups ( P < 0.05). Compared with the control group, the model group had a significant increase in the abundance of intestinal Akkermansia muciniphila and a significant reduction in the abundance of Lactobacillus johnsonii (both P < 0.05); compared with the model group, both the YDTF group and the UDCA group had a significant reduction in the abundance of intestinal Akkermansia muciniphila , and the YDTF group had a significant increase in the abundance of Lactobacillus murinus , while the UDCA group had significant increases in the abundance of Lactobacillus murinus and Bifidobacterium pseudolongum (all P < 0.05). Compared with the control group, the model group had a significant reduction in the protein expression of intestinal FXR, a significant increase in the protein expression of intestinal NLRP3, and significant reductions in the expression of intestinal E-cadherin and occludin (all P < 0.05); compared with the model group, both the YDTF group and the UDCA group had a significant increase in the protein expression of intestinal FXR, a significant reduction in the protein expression of intestinal NLRP3, and significant increases in the expression of intestinal E-cadherin and occludin (all P < 0.05). Conclusion Yudantong decoction can alleviate liver injury in mice with ANIT-induced cholestasis, possibly by improving intestinal flora and enhancing intestinal barrier function.
10.Influence of NOD-like receptor thermal protein domain associated protein 6 on hepatic ischemia-reperfusion injury
Xiaoming AI ; Yong YAN ; Defeng SUN ; Hao WANG ; Zhiyuan HUA ; Yongping ZHOU
Chinese Journal of Hepatobiliary Surgery 2023;29(8):615-621
Objective:To observe the influence of NOD-like receptor thermal protein domain associated protein 6 (NLRP6) on hepatic ischemia-reperfusion injury (IRI), and elucidate the related mechanism.Methods:Thirty C57BL/6 mice with body weight of (18.80±1.99) g, were divided randomly into 5 groups, with 6 mice in each group: the mice that experienced only exploratory laparotomy were Sham group; that only underwent an operation to establish a hepatic IRI model were IRI group; that were treated with tail intravenous injection of clodronate (Clo) liposomes before the establishment of hepatic IRI model were Clo group; that received tail intravenous injection of clodronate liposomes and transfusion of bone marrow derived macrophages (BMDM) before the operation were Clo+ BMDM group; that received preoperative tail intravenous injection of clodronate liposomes and transfusion of BMDM with NLRP6 knockdown were Clo+ NLRP6-knockdown group. Real time quantitative polymerase chain reaction analysis (RT-PCR) and Western blot were performed to analyze the expressions of pyroptosis related proteins and factors. Simulate a hypoxia/reoxygenation (H/R) model in vitro, and set up experimental groups: lipopolysaccharide (LPS) + adenosine triphosphate (ATP), LPS+ ATP+ NLRP6-knockdown, H/R, and H/R+ NLRP6-knockdown. The changes of expressions of pyroptosis related proteins and factors were detected by RT-PCR and Western blot. Expression of NF-κB in vivo and in vitro was measured.Results:Compared with those in Sham group, protein expressions of NLRP6, NLRP3, Caspase-1, gasdermin D (GSDMD), IL-1β and IL-18 were remarkably increased in IRI group, but the levels of these proteins were dramatically decreased in Clo group with the exhaustion of macrophages in comparison with in IRI group, which were significantly different statistically (all P<0.05). The levels of these proteins were enhanced again in Clo+ BMDM group with the reconstruction of macrophages in contrast to those in Clo group, while the enhancements were more obvious in Clo+ NLRP6-knockdown group comparing to those in Clo+ BMDM group, with significant differences (all P<0.05). In vitro, pyroptosis rate for LPS+ ATP group was (16.39±1.06)%, which was lower than (27.34±2.79)% for LPS+ ATP+ NLRP6-knockdown group, with a statistical significance ( P<0.05). Meanwhile, pyroptosis rate for H/R group was (20.59±5.66)%, also much more reduced than (37.76±2.00)% for H/R+ NLRP6-knockdown group ( P<0.05). Expressions of NLRP3, Caspase-1, GSDMD, IL-1β, IL-18 and NF-κB p65 in LPS+ ATP+ NLRP6-knockdown group were more elevated than in LPS+ ATP group, and these indices were also more enhanced in H/R+ NLRP6-knockdown group than which in H/R group. Compared to the Sham group, expression of NF-κB p65 significantly increased in IRI group, which was reversed in Clo group, but enhanced again in Clo+ BMDM group and reached a peak in Clo+ NLRP6-knockdown group. Conclusions:Macrophage plays a critical role in immune response to hepatic IRI, wherein NLRP6 functions specifically. NLRP6 acts to suppress inflammation during hepatic IRI through regulating macrophage pyroptosis via inhibiting NF-κB.

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