1.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
2.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
3.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
4.Expert consensus on evaluation index system construction for new traditional Chinese medicine(TCM) from TCM clinical practice in medical institutions.
Li LIU ; Lei ZHANG ; Wei-An YUAN ; Zhong-Qi YANG ; Jun-Hua ZHANG ; Bao-He WANG ; Si-Yuan HU ; Zu-Guang YE ; Ling HAN ; Yue-Hua ZHOU ; Zi-Feng YANG ; Rui GAO ; Ming YANG ; Ting WANG ; Jie-Lai XIA ; Shi-Shan YU ; Xiao-Hui FAN ; Hua HUA ; Jia HE ; Yin LU ; Zhong WANG ; Jin-Hui DOU ; Geng LI ; Yu DONG ; Hao YU ; Li-Ping QU ; Jian-Yuan TANG
China Journal of Chinese Materia Medica 2025;50(12):3474-3482
Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards*
;
Humans
;
Consensus
;
Drugs, Chinese Herbal/therapeutic use*
;
Surveys and Questionnaires
5.An intelligent model for classifying supraventricular tachycardia mechanisms based on 12-lead wearable electrocardiogram devices
Hongsen WANG ; Lijie MI ; Yue ZHANG ; Lan GE ; Jiewei LAI ; Tao CHEN ; Jian LI ; Xiangmin SHI ; Jiancheng XIU ; Min TANG ; Wei YANG ; Jun GUO
Journal of Southern Medical University 2024;44(5):851-858
Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.
6.An intelligent model for classifying supraventricular tachycardia mechanisms based on 12-lead wearable electrocardiogram devices
Hongsen WANG ; Lijie MI ; Yue ZHANG ; Lan GE ; Jiewei LAI ; Tao CHEN ; Jian LI ; Xiangmin SHI ; Jiancheng XIU ; Min TANG ; Wei YANG ; Jun GUO
Journal of Southern Medical University 2024;44(5):851-858
Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Development and validation of a stromal-immune signature to predict prognosis in intrahepatic cholangiocarcinoma
Yu-Hang YE ; Hao-Yang XIN ; Jia-Li LI ; Ning LI ; Si-Yuan PAN ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Peng-Cheng WANG ; Chu-Bin LUO ; Rong-Qi SUN ; Jia FAN ; Jian ZHOU ; Zheng-Jun ZHOU ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2024;30(4):914-928
Background:
Intrahepatic cholangiocarcinoma (ICC) is a highly desmoplastic tumor with poor prognosis even after curative resection. We investigated the associations between the composition of the ICC stroma and immune cell infiltration and aimed to develop a stromal-immune signature to predict prognosis in surgically treated ICC.
Patients and methods:
We recruited 359 ICC patients and performed immunohistochemistry to detect α-smooth muscle actin (α-SMA), CD3, CD4, CD8, Foxp3, CD68, and CD66b. Aniline was used to stain collagen deposition. Survival analyses were performed to detect prognostic values of these markers. Recursive partitioning for a discrete-time survival tree was applied to define a stromal-immune signature with distinct prognostic value. We delineated an integrated stromal-immune signature based on immune cell subpopulations and stromal composition to distinguish subgroups with different recurrence-free survival (RFS) and overall survival (OS) time.
Results:
We defined four major patterns of ICC stroma composition according to the distributions of α-SMA and collagen: dormant (α-SMAlow/collagenhigh), fibrogenic (α-SMAhigh/collagenhigh), inert (α-SMAlow/collagenlow), and fibrolytic (α-SMAhigh/collagenlow). The stroma types were characterized by distinct patterns of infiltration by immune cells. We divided patients into six classes. Class I, characterized by high CD8 expression and dormant stroma, displayed the longest RFS and OS, whereas Class VI, characterized by low CD8 expression and high CD66b expression, displayed the shortest RFS and OS. The integrated stromal-immune signature was consolidated in a validation cohort.
Conclusion
We developed and validated a stromal-immune signature to predict prognosis in surgically treated ICC. These findings provide new insights into the stromal-immune response to ICC.
9.Predictive value of the proportion of hibernating myocardium in total perfusion defect on reverse remodeling in patients with HFrEF underwent coronary artery bypass graft.
Yao LU ; Jian CAO ; En Jun ZHU ; Ming Xin GAO ; Tian Tian MOU ; Ying ZHANG ; Xiao Fen XIE ; Yi TIAN ; Ming Kai YUN ; Jing Jing MENG ; Xiu Bin YANG ; Yong Qiang LAI ; Ran DONG ; Xiao Li ZHANG
Chinese Journal of Cardiology 2023;51(4):384-392
Objective: To evaluate the predictive value of the proportion of hibernating myocardium (HM) in total perfusion defect (TPD) on reverse left ventricle remodeling (RR) after coronary artery bypass graft (CABG) in patients with heart failure with reduced ejection fraction (HFrEF) by 99mTc-methoxyisobutylisonitrile (MIBI) single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) combined with 18F-flurodeoxyglucose (FDG) gated myocardial imaging positron emission computed tomography (PET). Methods: Inpatients diagnosed with HFrEF at the Cardiac Surgery Center, Anzhen Hospital of Capital Medical University from January 2016 to January 2022 were prospectively recruited. MPI combined with 18F-FDG gated PET was performed before surgery for viability assessment and the patients received follow-up MPI and 18F-FDG gated PET at different stages (3-12 months) after surgery. Δ indicated changes (post-pre). Left ventricular end-systolic volume (ESV) reduced at least 10% was defined as RR, patients were divided into reverse remodeling (RR+) group and the non-reverse group (RR-). Binary logistic regression analysis was used to identify predictors of RR. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated to assess the cut-off value for predicting RR. Additionally, we retrospectively enrolled inpatients with HFrEF at the Cardiac Surgery Center, Anzhen Hospital of Capital Medical University from January 2021 to January 2022 as the validation group, who underwent MPI and 18F-FDG gated PET before surgery. Echocardiography was performed before CABG and after CABG (3-12 months). In the validation group, the reliability of obtaining the cut-off value for the ROC curve was verified. Results: A total of 28 patients with HFrEF (26 males; age (56.9±8.7) years) were included in the prospective cohort. HM/TPD was significantly higher in the RR+ group than in the RR- group ((51.8%±17.9%) vs. (35.7%±13.9%), P=0.016). Binary logistic regression analysis revealed that HM/TPD was an independent predictor of RR (Odds ratio=1.073, 95% Confidence interval: 1.005-1.145, P=0.035). ROC curve analysis revealed that HM/TPD=38.3% yielded the highest sensitivity, specificity, and accuracy (all 75%) for predicting RR and the AUC was 0.786 (P=0.011). Meanwhile, a total of 100 patients with HFrEF (90 males; age (59.7±9.6) years) were included in the validation group. In the validation group, HM/TPD=38.3% predicted RR in HFrEF patients after CABG with the highest sensitivity, specificity and accuracy (82%, 60% and 73% respectively). Compared with the HFrEF patients in the HM/TPD<38.3% group (n=36), RR and cardiac function improved more significantly in the HM/TPD≥38.3% group (n=64) (all P<0.05). Conclusions: Preoperative HM/TPD ratio is an independent factor for predicting RR in patients with HFrEF after CABG, and HM/TPD≥38.3% can accurately predict RR and the improvement of cardiac function after CABG.
Male
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Humans
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Middle Aged
;
Aged
;
Stroke Volume
;
Heart Failure
;
Fluorodeoxyglucose F18
;
Retrospective Studies
;
Reproducibility of Results
;
Prospective Studies
;
Coronary Artery Bypass
;
Ventricular Dysfunction, Left
;
Tomography, Emission-Computed, Single-Photon
;
Perfusion
;
Myocardium
10.Mechanism of protective effect of resveratrol on poor ovarian response in mice.
Jian-Heng HAO ; Yue-Meng ZHAO ; Hai-Jun WANG ; Yu-Xia CAO ; Ying LAN ; Lai-Xi JI
China Journal of Chinese Materia Medica 2023;48(21):5888-5897
This study aims to investigate the therapeutic effects and potential mechanisms of resveratrol(Res) on poor ovarian response(POR) in mice. The common target genes shared by Res and POR were predicted by network pharmacology, used for Gene Ontology(GO) annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment, and then validated by animal experiments. The mice with regular estrous cycle after screening were randomized into normal, POR, and low-and high-dose(20 and 40 mg·kg~(-1), respectively) Res groups. The normal group was administrated with an equal volume of 0.9% sodium chloride solution by gavage, and the mice in other groups with tripterygium glycosides suspension(50 mg·kg~(-1)) by gavage for 2 weeks. After the modeling, the mice in low-and high-dose Res groups were treated with Res by gavage for 2 weeks, and the mice in normal and POR groups with an equal volume of 0.9% sodium chloride solution by gavage. Ovulation induction and sample collection were carried out on the day following the end of treatment. Vaginal smears were collected for observation of the changes in the estrous cycle, the counting of retrieved oocytes, and the measurement of ovarian wet weight and ovarian index. The enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of anti-mullerian hormone(AMH), follicle-stimulating hormone(FSH), estradiol(E_2), and luteinizing hormone(LH) in the serum. The ovarian tissue morphology and granulosa cell apoptosis were observed by hematoxylin-eosin(HE) staining and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL), respectively. Western blot was employed to determine the protein levels of phosphatidylinositol 3-kinase(PI3K), protein kinase B(AKT), forkhead box O(FOXO) 3a, hypoxia-inducible factor(HIF)-1α, B-cell lymphoma-2(Bcl-2), and Bcl-2-associated X protein(Bax). A total of 222 common targets shared by Res and POR were collected. GO annotation indicated that these targets were mainly involved in oxidative stress response. KEGG enrichment analysis revealed that Res can intervene in POR via PI3K/AKT, HIF-1, and FOXO signaling pathways. Animal experiments showed that the model group had higher rate of estrous cycle disorders, lower number and poorer morphology of normally developed follicles at all levels, more atretic follicles, higher apoptosis of ovarian granulosa cells, lower number of retrieved oocytes, lower ovarian wet weight and ovarian index, higher serum levels of FSH and LH, lower levels of AMH and E_2, higher expression levels of HIF-1α, FOXO3a and Bax, and lower expression levels of PI3K, AKT, and Bcl-2 in the ovarian tissue than the normal group. Compared with the POR group, low-and high-dose Res decreased the rate of estrous cycle disorders, improved the follicle number and morphology, reduced atretic follicles, promoted the apoptosis of ovarian granulosa cells, increased retrieved oocytes, ovarian wet weight and ovarian index, and lowered serum FSH and LH levels. Moreover, Res down-regulated the expression levels of HIF-1α, FOXO3a and Bax, and up-regulated the expression levels of PI3K, AKT and Bcl-2 in the ovarian tissue. In summary, Res can inhibit apoptosis and mitigate poor ovarian response in mice by regulating the PI3K/AKT/FOXO3a and HIF-1α pathways.
Female
;
Mice
;
Animals
;
Proto-Oncogene Proteins c-akt/metabolism*
;
Resveratrol/pharmacology*
;
bcl-2-Associated X Protein
;
Phosphatidylinositol 3-Kinases/metabolism*
;
Sodium Chloride
;
Follicle Stimulating Hormone
;
Proto-Oncogene Proteins c-bcl-2

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