1.Observation on effect of Livin on VSV-induced apoptosis of A549 cells
Xiaolong ZHANG ; Tao ZHANG ; Huanyi LIU ; Zhenguo ZHAO
Cancer Research and Clinic 2013;(1):5-7
Objective To investigate the effect of Livin expression on VSV-induced apoptsis of A549 cells.Methods The expression of Livin of A549 cells was inhibited by RNA interference.VSV-induced apoptosis of A549 cells was observed by Tunel assay.Protein Level of livin was detected by Western blot.Caspase-3 activity was detected by the fluorescence-based quantitative method.Results Livin downregulation VSV-induced apoptosis of A549 cells.Inhibited the expression of Livin of A549 cells had increased Caspase-3 activity.Conclusion The effect of Livin on VSV-induced apoptotic of A549 cells could be increased by RNA interference.
2.Observations on therapeutic effects of diltiazem on coronary myocardiai ischemia
Jian QIU ; Tingshu NI ; Wanjun YANG ; Huanyi LIU ;
Journal of Third Military Medical University 1988;0(06):-
The therapeutic effects of diltiazem in the dosage of 135~240 mg/d on 26 cas-s with coronary myocardial ischemia were observed.It was found that diltiazem could markedly slow down tho heart rate and decrease the blood pressure of the patient when he was at rest and 2,4 and 6 minutes after he underwent exercise test.It could also increase exercise tolerance,delay an exercise-induced anginal attack,improve the ischemic depression of ST segment,and PEP/LVET.Eventually it could pievent the patient from anginal attacks.The therapeutic effects of diltiazem would be more apparent in those cases of myocardial ischemia accompanied with hypertension.
3.An experimental study of magnetic anchor technique-assisted endoscopic submucosal dissection for early esophageal cancer
Min PAN ; Wen ZHANG ; Huanyi LIU ; Shujuan HE ; Shuqin XU ; Peinan LIU ; Aihua SHI ; Feng MA ; Yi LYU ; Xiaopeng YAN
Chinese Journal of Digestive Endoscopy 2021;38(8):650-653
Objective:To investigate the feasibility of magnetic anchor technique for endoscopic submucosal dissection (ESD) in the treatment of early esophageal cancer.Methods:A self-designed magnetic anchoring device (including an anchor magnet and a target magnet) was used to perform ESD on the hypothesized esophageal lesion mucosa of six isolated esophagus of Beagle dogs. The feasibility and convenience of the operation was evaluated.Results:ESD of 6 isolated esophagus of dogs was successfully completed. Through adjusting the position of anchor magnet, the pulling direction and force of the target magnet on the mucosa could be flexibly controlled, the mucosal peeling surface was fully exposed, and tissue tension was provided to ensure the smooth removal of the diseased mucosa. The entire operation was smooth, and the target magnet was conveniently retained. No target magnet slippage or mucosal laceration occurred during the operation.Conclusion:The magnetic anchor technique is safe and feasible for the ESD, effectively pulling the diseased mucosa in treatment of early esophageal cancer, which can greatly improve the endoscopic operation experience.
4.Application and prospect of machine learning in orthopaedic trauma.
Chuwei TIAN ; Xiangxu CHEN ; Huanyi ZHU ; Shengbo QIN ; Liu SHI ; Yunfeng RUI
Chinese Journal of Reparative and Reconstructive Surgery 2023;37(12):1562-1568
OBJECTIVE:
To review the current applications of machine learning in orthopaedic trauma and anticipate its future role in clinical practice.
METHODS:
A comprehensive literature review was conducted to assess the status of machine learning algorithms in orthopaedic trauma research, both nationally and internationally.
RESULTS:
The rapid advancement of computer data processing and the growing convergence of medicine and industry have led to the widespread utilization of artificial intelligence in healthcare. Currently, machine learning plays a significant role in orthopaedic trauma, demonstrating high performance and accuracy in various areas including fracture image recognition, diagnosis stratification, clinical decision-making, evaluation, perioperative considerations, and prognostic risk prediction. Nevertheless, challenges persist in the development and clinical implementation of machine learning. These include limited database samples, model interpretation difficulties, and universality and individualisation variations.
CONCLUSION
The expansion of clinical sample sizes and enhancements in algorithm performance hold significant promise for the extensive application of machine learning in supporting orthopaedic trauma diagnosis, guiding decision-making, devising individualized medical strategies, and optimizing the allocation of clinical resources.
Artificial Intelligence
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Orthopedics
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Machine Learning
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Algorithms