Objective To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis(AV).Methods In this study,the vaginal secretion samples of 3 769 patients receiving treatment at the Department of Obstetrics and Gynecology,West China Second Hospital,Sichuan University between January 2020 and December 2021 were selected.Using the results of manual microscopy as the control,we developed the linear kernel SVM algorithm,an artificial intelligence(AI)automated analysis software,with Python Scikit-learn script.The AI automated analysis software could identify leucocytes with toxic appearance and parabasal epitheliocytes(PBC).The bacterial grading parameters were reset using standard strains of lactobacillus and AV common isolates.The receiver operating characteristic(ROC)curve analysis was used to determine the cut-off value of AV evaluation results for different scoring items were obtained by using the results of manual microscopy as the control.Then,the parameters of automatic AV identification were determined and the automatic AV analysis scoring method was initially established.Results A total of 3 769 vaginal secretion samples were collected.The AI automated analysis system incorporated five parameters and each parameter incorporated three severity scoring levels.We selected 1.5 μm as the cut-off value for the diameter between Lactobacillus and common AV bacterial isolates.The automated identification parameter of Lactobacillus was the ratio of bacteria≥1.5 μm to those＜1.5 μm.The cut-off scores were 2.5 and 0.5,In the parameter of white blood cells(WBC),the cut-off value of the absolute number of WBC was 103 μL-1 and the cut-off value of WBC-to-epithelial cell ratio was 10.The automated identification parameter of toxic WBC was the ratio of toxic WBC toWBC and the cut-off values were 1%and 15%.The parameter of background flora was bacteria＜1.5 μm and the cut-off values were 5×103 μL-1 and 3×104 μL-1.The parameter of the parabasal epitheliocytes was the ratio of PBC to epithelial cells and the cut-off values were 1%and 10%.The agreement rate between the results of automated microscopy and those of manual microscopy was 92.5%.Out of 200 samples,automated microscopy and manual microscopy produced consistent scores for 185 samples,while the results for 15 samples were inconsistent.Conclusion We developed an AI recognition software for AV and established an automated vaginal secretion microscopy scoring system for AV.There was good overall concordance between automated microscopy and manual microscopy.The AI identification software for AV can complete clinical lab examination with rather high objectivity,sensitivity,and efficiency,markedly reducing the workload of manual microscopy.

Objective To establish the cell model of ethanol-induced liver injury and explore the protective effects of tea poly-phenols (TP)on ethanol-induced liver injury .Methods Cell morphology were observed by microscope ,and then alanine aminotrans-ferase (ALT) ,nmda transaminase (AST) ,gamma GGTP ,GGT and ROS changes were detected .Results Alcohol maked L02 hepa-tocyte fatty degeneration .Compared with ethanol group ,steatosis in TP + ethanol group was lighter ,its ALT ,AST ,GGT content and intracellular ROS reduced .Conclusion TP can decrease cell fatty change degree in vitro experiments ,improue the enzymology indexes ,reduce the generation of reactive oxygen species to avoid liver damage .

This study was aimed to detect the effect of genipin and Vitamin E (VitE) on non-alcoholic fatty liver disease. L02 cells were divided into five groups:control group, palmic acid treated group, VitE treated group, genipin treated group, and a combination group. All treatments were terminated at the end of 72 hours. Pathological changes of L02 cells were observed. Mitochondrial membrane potential changes were detected by flow cytometry. MDA, SOD, ALT, AST, GGT, TG in culture medium and expression of UCP2 mRNA and protein in L02 cells were detected. We also studied the effects of genipin and VitE on UCP2 and other related factors such as NF-kappaB and TNF-alpha on the L02 cell model of non-alcoholic fatty liver disease. In combination group, the degree of adipose degeneration of L02 cells mitigated significantly; mitochondrial membrane potential and the level of SOD activity increased; the level of MDA, ALT, AST, GGT, TG and the expression of UCP2, NF-kappaB,TNF-alpha in L02 cells decreased. The use of genipin in combination with VitE can increase mitochondrial membrane potential and markedly relieve the adipose degeneration of liver cells.
Cell Line ; Drug Synergism ; Fatty Liver ; metabolism ; Humans ; Ion Channels ; genetics ; metabolism ; Iridoid Glycosides ; pharmacology ; Iridoids ; Liver ; cytology ; Membrane Potential, Mitochondrial ; Mitochondrial Proteins ; genetics ; metabolism ; NF-kappa B ; genetics ; metabolism ; Non-alcoholic Fatty Liver Disease ; Protective Agents ; pharmacology ; RNA, Messenger ; genetics ; metabolism ; Tumor Necrosis Factor-alpha ; genetics ; metabolism ; Uncoupling Protein 2 ; Vitamin E ; pharmacology

Pathology is the bridge of medicine between basic course and clinic course.The building and development of the subject is inseparable from the surgical pathology.Teachers should enrich and enhance professional knowledge,pay attention to the concepts and key points,and handle properly the relationship of the general pathology and the systematic pathology.Multimedia tools for teaching pathology are suitable but still need improvement.