Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection.

To conduct better research in hepatocellular carcinoma resection, this paper used 3D machine learning and logistic regression algorithm to study the preoperative assistance of patients undergoing hepatectomy. In this study, the logistic regression model was analyzed to find the influencing factors for the survival and recurrence of patients. The clinical data of 50 HCC patients who underwent extensive hepatectomy (≥4 segments of the liver) admitted to our hospital from June 2020 to December 2020 were selected to calculate the liver volume, simulated surgical resection volume, residual liver volume, surgical margin, etc. The results showed that the simulated liver volume of 50 patients was 845.2 + 285.5 mL, and the actual liver volume of 50 patients was 826.3 ± 268.1 mL, and there was no significant difference between the two groups (t = 0.425; P > 0.05). Compared with the logistic regression model, the machine learning method has a better prediction effect, but the logistic regression model has better interpretability. The analysis of the relationship between the liver tumour and hepatic vessels in practical problems has specific clinical application value for accurately evaluating the volume of liver resection and surgical margin.

Agrobacterium-mediated transformation of the ascomycete mushroom Morchella importuna using polyubiquitin and glyceraldehyde-3-phosphate dehydrogenase promoter-based binary vectors.

Morchella importuna is a worldwide distributed edible mushroom with high ecological and economic values, but the molecular and genetic research about this mushroom has been hindered due to lack of an efficient transformation method. Here, we report for the first time the successful transformation of M. importuna by using a hypervirulent Agrobacterium tumefaciens strain bearing the constructed binary plasmid p1391-U-GUS. The selectable markers used were the genes for hygromycin resistance under the control of the polyubquitin promoter from M. importuna. The reporter genes were those for enhanced green fluorescent protein (EGFP) and the ß-Glucuronidase (GUS) under the control of glyceraldehyde-3-phosphate dehydrogenase promoter and polyubquitin promoter respectively. The presence of the reporter gene EGFP in the transformants was confirmed by the fluorescence and confocal microscope and molecular analysis and that of the reporter gene GUS was verified by enzyme activity and molecular analysis. The analysis results of both reporter genes indicated that Agrobacterium-mediated transformation was successfully performed in M. importuna.