1.The in vitro and in vivo inhibitory effects of metformin on esophageal squamous cell carcinoma cells
Shan LIU ; Meng HU ; Zhuo ZHANG ; Fei XIONG ; Pingshang WU ; Xueman LI
China Pharmacy 2025;36(17):2113-2119
OBJECTIVE To explore the in vitro and in vivo inhibitory effects and mechanism of metformin on the malignant biological behavior of esophageal squamous cell carcinoma (ESCC) cells by the hypoxia inducible factor-1α (HIF-1α)/interleukin-8 (IL-8) signaling pathway. METHODS Human ESCC TE1 cells were assigned into blank group, metformin low-, medium-, and high-dose groups (0.5, 1, 2 mmol/L), IDF-11774 (HIF-1α inhibitor) group (20 μmol/L), and high-dose metformin+HIF-1α activator dimethyloxalylglycine (DMOG) group. After 24 h treatment, cell proliferation [measured by the positive rate of 5-ethynyl- 2′-deoxyuridine (EdU) and optical density at 450 nm (OD450 value)], apoptosis, invasion and migration as well as mRNA expressions of proliferating cell nuclear antigen (PCNA), Bcl-2 interacting mediator of cell death (Bim), migration and invasion enhancer 1 (MIEN1), and matrix metalloproteinase-9 (MMP-9), and protein expressions of HIF-1α and IL-8 in the cells were detected. The xenograft tumor model of nude mice was established. Thirty nude mice were randomly divided into blank group, metformin low-, medium-, and high-dose groups (i.g. administration of metformin 62.5, 125, 250 mg/kg+i.p. administration of equal volume of normal saline), IDF-11774 group (i.g. administration of 50 mg/kg IDF-11774+i.p. administration of equal volume of normal saline) and high-dose metformin+DMOG group (i.g. administration of metformin 250 mg/kg+i.p. administration of DMOG 250 mg/kg), with 5 mice in each group. They were given relevant medicine, once a day, for 4 consecutive weeks; the mass and volume of the tumor and protein expressions of HIF-1α and IL-8 in the tumor tissue were determined. RESULTS The EdU positive rate, OD450 value, cell invasion number, scratch healing rate, mRNA expressions of PCNA, MIEN1 and MMP-9, protein expressions of HIF-1α and IL-8, as well as the mass and volume of transplanted tumors and protein expressions of HIF-1α and IL-8 in tumor tissues were decreased by metformin in concentration/dose-dependent manner (P<0.05). Additionally,metformin increased the apoptosis rate and mRNA expression of Bim in cells (P<0.05). The trend of changes in corresponding indicators in the IDF-11774 group was consistent with that in the metformin groups, whereas DMOG could significantly attenuate the aforementioned effects of high-concentration/high-dose metformin (P<0.05). CONCLUSIONS Metformin can inhibit the proliferation, invasion, migration of TE1 cells, and tumor growth of nude mice, and induce cell apoptosis, the mechanism of which may be related to the inhibition of HIF-1α/IL-8 signaling pathway.
2.Research status of risk prediction model of post-endoscopic retrograde cholangiopancreatography pancreatitis
Zhe-Yu ZHU ; Yi-Yu HU ; Peng CHEN ; Fei-Fan WU ; Si-Yu WANG ; Wei-Min WANG ; Chun-Mu MIAO ; Yun-Bing WANG ; Xiong DING
Journal of Regional Anatomy and Operative Surgery 2024;33(12):1105-1109
Post-endoscopic retrograde cholangiopancreatography pancreatitis(PEP)is one of the most common complications after endoscopic retrograde cholangiopancreatography(ERCP).Numerous PEP prediction models have been established based on different statistical methods at home and abroad.The PEP prediction model,as a tool for evaluating and screening high-risk populations,can provide a basis for medical staff to find high-risk PEP patients early and take effective preventive measures.In recent years,new PEP prediction models have appeared one after another,but there is still a lack of recognized reliable prediction models in clinic.This article reviews the research status of PEP risk prediction models,aim to provide a direction for establishing a more reliable,accurate,and practical PEP risk prediction model in the later period.
3.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.
4.Determining Disease Activity and Glucocorticoid Response in Thyroid-Associated Ophthalmopathy:Preliminary Study Using Dynamic Contrast-Enhanced MRI
Hao HU ; Xiong-Ying PU ; Jiang ZHOU ; Wen-Hao JIANG ; Qian WU ; Jin-Ling LU ; Fei-Yun WU ; Huan-Huan CHEN ; Xiao-Quan XU
Korean Journal of Radiology 2024;25(12):1070-1082
Objective:
To assess the role of dynamic contrast-enhanced (DCE)-MRI of the extraocular muscles (EOMs) for determining the activity of thyroid-associated ophthalmopathy (TAO) and treatment response to glucocorticoids (GCs).
Materials and Methods:
We prospectively enrolled 65 patients with TAO (41 active, 82 eyes; 24 inactive, 48 eyes). Twenty-two active patients completed the GC treatment and follow-up assessment, including 15 patients (30 eyes) and 7 patients (14 eyes), defined as responsive and unresponsive, respectively. Model-free (time to peak [TTP], area under the curve [AUC], and Slope max) and model-based (Ktrans , Kep, and Ve) parameters of EOMs in embedded simplified histogram analyses were calculated and compared between groups. Multivariable logistic regression analysis was used to identify the independent predictors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance.
Results:
Active patients exhibited significantly higher TTP at the 10th percentile (-10th), TTP-mean, and TTP at the 90th percentile (-90th); AUC-10th, AUC-mean, AUC-90th, and AUC-max; Ktrans -10th and Ktrans -mean; and Ve-10th, Ve-mean, Ve-90th, and Ve-max than inactive patients (P < 0.05). Responsive patients exhibited significantly lower TTP-min; higher Ktrans -mean and Ktrans -max; and higher Kep-10th, Kep-mean, and Kep-max than unresponsive patients (P < 0.05). TTP-mean and Ve-mean were independent variables for determining disease activity (P = 0.017 and 0.022, respectively). A combination of the two parameters could determine active TAO with moderate performance (AUROC = 0.687). TTP-min and Ktrans -mean were independent predictors of the response to GCs (P = 0.023 and 0.004, respectively), uniting which could determine the response to GCs with decent performance (AUROC = 0.821).
Conclusion
DCE-MRI-derived model-free and model-based parameters of EOMs can assist in the evaluation of TAO. In particular, TTP-mean and Ve-mean could be useful for determining the activity of TAO, whereas TTP-min and K trans -mean could be promising biomarkers for determining the response to GCs.
5.Determining Disease Activity and Glucocorticoid Response in Thyroid-Associated Ophthalmopathy:Preliminary Study Using Dynamic Contrast-Enhanced MRI
Hao HU ; Xiong-Ying PU ; Jiang ZHOU ; Wen-Hao JIANG ; Qian WU ; Jin-Ling LU ; Fei-Yun WU ; Huan-Huan CHEN ; Xiao-Quan XU
Korean Journal of Radiology 2024;25(12):1070-1082
Objective:
To assess the role of dynamic contrast-enhanced (DCE)-MRI of the extraocular muscles (EOMs) for determining the activity of thyroid-associated ophthalmopathy (TAO) and treatment response to glucocorticoids (GCs).
Materials and Methods:
We prospectively enrolled 65 patients with TAO (41 active, 82 eyes; 24 inactive, 48 eyes). Twenty-two active patients completed the GC treatment and follow-up assessment, including 15 patients (30 eyes) and 7 patients (14 eyes), defined as responsive and unresponsive, respectively. Model-free (time to peak [TTP], area under the curve [AUC], and Slope max) and model-based (Ktrans , Kep, and Ve) parameters of EOMs in embedded simplified histogram analyses were calculated and compared between groups. Multivariable logistic regression analysis was used to identify the independent predictors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance.
Results:
Active patients exhibited significantly higher TTP at the 10th percentile (-10th), TTP-mean, and TTP at the 90th percentile (-90th); AUC-10th, AUC-mean, AUC-90th, and AUC-max; Ktrans -10th and Ktrans -mean; and Ve-10th, Ve-mean, Ve-90th, and Ve-max than inactive patients (P < 0.05). Responsive patients exhibited significantly lower TTP-min; higher Ktrans -mean and Ktrans -max; and higher Kep-10th, Kep-mean, and Kep-max than unresponsive patients (P < 0.05). TTP-mean and Ve-mean were independent variables for determining disease activity (P = 0.017 and 0.022, respectively). A combination of the two parameters could determine active TAO with moderate performance (AUROC = 0.687). TTP-min and Ktrans -mean were independent predictors of the response to GCs (P = 0.023 and 0.004, respectively), uniting which could determine the response to GCs with decent performance (AUROC = 0.821).
Conclusion
DCE-MRI-derived model-free and model-based parameters of EOMs can assist in the evaluation of TAO. In particular, TTP-mean and Ve-mean could be useful for determining the activity of TAO, whereas TTP-min and K trans -mean could be promising biomarkers for determining the response to GCs.
6.Determining Disease Activity and Glucocorticoid Response in Thyroid-Associated Ophthalmopathy:Preliminary Study Using Dynamic Contrast-Enhanced MRI
Hao HU ; Xiong-Ying PU ; Jiang ZHOU ; Wen-Hao JIANG ; Qian WU ; Jin-Ling LU ; Fei-Yun WU ; Huan-Huan CHEN ; Xiao-Quan XU
Korean Journal of Radiology 2024;25(12):1070-1082
Objective:
To assess the role of dynamic contrast-enhanced (DCE)-MRI of the extraocular muscles (EOMs) for determining the activity of thyroid-associated ophthalmopathy (TAO) and treatment response to glucocorticoids (GCs).
Materials and Methods:
We prospectively enrolled 65 patients with TAO (41 active, 82 eyes; 24 inactive, 48 eyes). Twenty-two active patients completed the GC treatment and follow-up assessment, including 15 patients (30 eyes) and 7 patients (14 eyes), defined as responsive and unresponsive, respectively. Model-free (time to peak [TTP], area under the curve [AUC], and Slope max) and model-based (Ktrans , Kep, and Ve) parameters of EOMs in embedded simplified histogram analyses were calculated and compared between groups. Multivariable logistic regression analysis was used to identify the independent predictors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance.
Results:
Active patients exhibited significantly higher TTP at the 10th percentile (-10th), TTP-mean, and TTP at the 90th percentile (-90th); AUC-10th, AUC-mean, AUC-90th, and AUC-max; Ktrans -10th and Ktrans -mean; and Ve-10th, Ve-mean, Ve-90th, and Ve-max than inactive patients (P < 0.05). Responsive patients exhibited significantly lower TTP-min; higher Ktrans -mean and Ktrans -max; and higher Kep-10th, Kep-mean, and Kep-max than unresponsive patients (P < 0.05). TTP-mean and Ve-mean were independent variables for determining disease activity (P = 0.017 and 0.022, respectively). A combination of the two parameters could determine active TAO with moderate performance (AUROC = 0.687). TTP-min and Ktrans -mean were independent predictors of the response to GCs (P = 0.023 and 0.004, respectively), uniting which could determine the response to GCs with decent performance (AUROC = 0.821).
Conclusion
DCE-MRI-derived model-free and model-based parameters of EOMs can assist in the evaluation of TAO. In particular, TTP-mean and Ve-mean could be useful for determining the activity of TAO, whereas TTP-min and K trans -mean could be promising biomarkers for determining the response to GCs.
7.Determining Disease Activity and Glucocorticoid Response in Thyroid-Associated Ophthalmopathy:Preliminary Study Using Dynamic Contrast-Enhanced MRI
Hao HU ; Xiong-Ying PU ; Jiang ZHOU ; Wen-Hao JIANG ; Qian WU ; Jin-Ling LU ; Fei-Yun WU ; Huan-Huan CHEN ; Xiao-Quan XU
Korean Journal of Radiology 2024;25(12):1070-1082
Objective:
To assess the role of dynamic contrast-enhanced (DCE)-MRI of the extraocular muscles (EOMs) for determining the activity of thyroid-associated ophthalmopathy (TAO) and treatment response to glucocorticoids (GCs).
Materials and Methods:
We prospectively enrolled 65 patients with TAO (41 active, 82 eyes; 24 inactive, 48 eyes). Twenty-two active patients completed the GC treatment and follow-up assessment, including 15 patients (30 eyes) and 7 patients (14 eyes), defined as responsive and unresponsive, respectively. Model-free (time to peak [TTP], area under the curve [AUC], and Slope max) and model-based (Ktrans , Kep, and Ve) parameters of EOMs in embedded simplified histogram analyses were calculated and compared between groups. Multivariable logistic regression analysis was used to identify the independent predictors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance.
Results:
Active patients exhibited significantly higher TTP at the 10th percentile (-10th), TTP-mean, and TTP at the 90th percentile (-90th); AUC-10th, AUC-mean, AUC-90th, and AUC-max; Ktrans -10th and Ktrans -mean; and Ve-10th, Ve-mean, Ve-90th, and Ve-max than inactive patients (P < 0.05). Responsive patients exhibited significantly lower TTP-min; higher Ktrans -mean and Ktrans -max; and higher Kep-10th, Kep-mean, and Kep-max than unresponsive patients (P < 0.05). TTP-mean and Ve-mean were independent variables for determining disease activity (P = 0.017 and 0.022, respectively). A combination of the two parameters could determine active TAO with moderate performance (AUROC = 0.687). TTP-min and Ktrans -mean were independent predictors of the response to GCs (P = 0.023 and 0.004, respectively), uniting which could determine the response to GCs with decent performance (AUROC = 0.821).
Conclusion
DCE-MRI-derived model-free and model-based parameters of EOMs can assist in the evaluation of TAO. In particular, TTP-mean and Ve-mean could be useful for determining the activity of TAO, whereas TTP-min and K trans -mean could be promising biomarkers for determining the response to GCs.
8.Determining Disease Activity and Glucocorticoid Response in Thyroid-Associated Ophthalmopathy:Preliminary Study Using Dynamic Contrast-Enhanced MRI
Hao HU ; Xiong-Ying PU ; Jiang ZHOU ; Wen-Hao JIANG ; Qian WU ; Jin-Ling LU ; Fei-Yun WU ; Huan-Huan CHEN ; Xiao-Quan XU
Korean Journal of Radiology 2024;25(12):1070-1082
Objective:
To assess the role of dynamic contrast-enhanced (DCE)-MRI of the extraocular muscles (EOMs) for determining the activity of thyroid-associated ophthalmopathy (TAO) and treatment response to glucocorticoids (GCs).
Materials and Methods:
We prospectively enrolled 65 patients with TAO (41 active, 82 eyes; 24 inactive, 48 eyes). Twenty-two active patients completed the GC treatment and follow-up assessment, including 15 patients (30 eyes) and 7 patients (14 eyes), defined as responsive and unresponsive, respectively. Model-free (time to peak [TTP], area under the curve [AUC], and Slope max) and model-based (Ktrans , Kep, and Ve) parameters of EOMs in embedded simplified histogram analyses were calculated and compared between groups. Multivariable logistic regression analysis was used to identify the independent predictors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance.
Results:
Active patients exhibited significantly higher TTP at the 10th percentile (-10th), TTP-mean, and TTP at the 90th percentile (-90th); AUC-10th, AUC-mean, AUC-90th, and AUC-max; Ktrans -10th and Ktrans -mean; and Ve-10th, Ve-mean, Ve-90th, and Ve-max than inactive patients (P < 0.05). Responsive patients exhibited significantly lower TTP-min; higher Ktrans -mean and Ktrans -max; and higher Kep-10th, Kep-mean, and Kep-max than unresponsive patients (P < 0.05). TTP-mean and Ve-mean were independent variables for determining disease activity (P = 0.017 and 0.022, respectively). A combination of the two parameters could determine active TAO with moderate performance (AUROC = 0.687). TTP-min and Ktrans -mean were independent predictors of the response to GCs (P = 0.023 and 0.004, respectively), uniting which could determine the response to GCs with decent performance (AUROC = 0.821).
Conclusion
DCE-MRI-derived model-free and model-based parameters of EOMs can assist in the evaluation of TAO. In particular, TTP-mean and Ve-mean could be useful for determining the activity of TAO, whereas TTP-min and K trans -mean could be promising biomarkers for determining the response to GCs.
9.Study on the mechanism of heterogeneous nuclear ribonucleoprotein L promoting the proliferation of hepatocellular carcinoma cells
Jiaxin CHEN ; Song HU ; Fubin LIU ; Zhenwei MA ; Kang YANG ; Shengquan ZOU ; Fei XIONG ; Bing WANG
Chinese Journal of Hepatobiliary Surgery 2023;29(9):694-699
Objective:To investigate the effect of HNRNPL protein on the proliferative ability of primary hepatocellular carcinoma cells and its potential mechanism.Methods:Online public database and real-time quantitative PCR were used to analyze the difference of HNRNPL expression between cancer and adjacent tissues. The effects of HNRNPL on HCC cell MHCC97H and HepG2 proliferation and MAPK pathway were investigated by Western blot, cell counting assay, colony formation assay and nude mouse transplantation tumor experiments.Results:The level of HNRNPL mRNA was validated to be higher in HCC tissue (2.76±0.37) than in normal tissue (1.00±0.14) with statistical difference ( t=3.93, P=0.002). Colony formation assay showed that the colony numbers of two MHCC97H knockdown groups (33.3±7.7) and (43.3±2.2) were lower than their control group (84.3±6.2), and two HepG2 knockdown groups (59.0±15.5) and (41.7±4.8) were lower than their control group (200.3±6.2) with statistical difference (both P<0.01). HNRNPL knockdown decreased the proliferation ability and activation level of MAPK pathway in HCC cells. Overexpression of oncogene c-RAF partially alleviated the anti-proliferation effect of HNRNPL knockdown and rescued the tumorigenic capacity. Conclusion:HNRNPL can promote hepatocellular carcinoma cell proliferation by activating MAPK signaling pathway.
10.Progress in research and development of soft tissue three-dimensional bioprinting and its supporting equipment.
Yan Ke HU ; Shu Ying CHEN ; Fei ZHOU ; Ya Hui XIONG ; Lei CHEN ; Shao Hai QI
Chinese Journal of Burns 2022;38(11):1090-1095
As a cutting-edge technology of tissue engineering, three-dimensional bioprinting can accurately fabricate biomimetic tissue, which has made great progress in the field of hard tissue printing such as bones and teeth. Meanwhile, the research on soft tissue bioprinting is also developing rapidly. This article mainly discussed the development progress in various bioprinting technologies and supporting equipment including printing software, printing hardware, supporting consumables, and bioreactors for soft tissue three-dimensional bioprinting, and made a prospect for the future research and development direction of soft tissue three-dimensional bioprinting.
Bioprinting/methods*
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Biocompatible Materials
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Printing, Three-Dimensional
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Tissue Engineering
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Research

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