ABSTRACT
Cutinase can degrade aliphatic and aromatic polyesters, as well as polyethylene terephthalate. Lack of commercially available cutinase calls for development of cost-effective production of efficient cutinase. In this study, eight cutinase genes were cloned from Sclerotinia sclerotiorum. The most active gene SsCut-52 was obtained by PCR combined with RT-PCR, expressed in Escherichia coli BL21 and purified by Ni-NTA affinity chromatography to study its characteristics and pathogenicity. Sscut-52 had a total length of 768 bp and 17 signal peptides at the N terminals. Phylogenetic analysis showed that its amino acid sequence had the highest homology with Botrytis keratinase cutinase and was closely related to Rutstroemia cutinase. Sscut-52 was highly expressed during the process of infecting plants by Sclerotinia sclerotiorum. Moreover, the expression level of Sscut-52 was higher than those of other cutinase genes in the process of sclerotia formation from mycelium. The heterologously expressed cutinase existed in the form of inclusion body. The renatured SsCut-52 was active at pH 4.0-10.0, and mostly active at pH 6.0, with a specific activity of 3.45 U/mg achieved. The optimum temperature of SsCut-52 was 20-30 ℃, and less than 60% of the activity could be retained at temperatures higher than 50 ℃. Plant leaf infection showed that SsCut-52 may promote the infection of Banlangen leaves by Sclerotinia sclerotiorum.
Subject(s)
Ascomycota/genetics , Carboxylic Ester Hydrolases , Cloning, Molecular , PhylogenyABSTRACT
Objective To establish a neural network model based on enhanced CT for distinguishing ISUP grade of clear cell renal cell carcinoma (ccRCC). Methods We collected 131 cases of ccRCC, with 92 cases of low ISUP grade and 39 cases of high ISUP grade. Patients were divided into training set and validation set according to 5:5 stratified sampling. The enhanced CT images of each ccRCC patient were evaluated by the radiologist. Recursive feature elimination (RFE) was used to reduce the dimension of patients' general features and enhanced CT features, which was used for neural network modeling and validation. Results Patients' general features and enhanced CT features were verified by RFE method and then reduced to 14 features. The top 5 features were growth pattern, necrosis, enlargement of lymph nodes, tumor size and capsule. The AUC of the neural network model based on these 5 features in training set was 0.8844 (95%CI: 0.8062-0.9626), sensitivity was 89.47% and specificity was 82.61%; and those in validation set were 0.7924 (95%CI: 0.6567-0.9280), 75.00% and 86.96%, respectively. Conclusion The neural network model of ccRCC ISUP grade based on enhanced CT has relatively high diagnostic efficiency.
ABSTRACT
Recent studies have discovered a selective autophagy-lipophagy, which can selectively identify and degrade lipids and plays an important role in regulating cellular lipid metabolism and maintaining intracellular lipid homeostasis. The process of lipophagy can be directly or indirectly regulated by genes, enzymes, transcriptional regulators and other factors. This review examines the role of lipophagy in reducing liver lipid content, regulating pancreatic lipid metabolism, and regulating adipose tissue differentiation, and summarizes the findings of the molecules (Rab GTPase, enzymes, ion channels, transcription factors, small molecular substances) involved in the regulation of lipophagy, which points to new directions for the treatment of diseases caused by lipid accumulation.
Subject(s)
Adipose Tissue , Autophagy , Homeostasis , Lipid Metabolism , LiverABSTRACT
<p><b>OBJECTIVE</b>To evaluate the relationship between dietary habits and the risk of gestational diabetes mellitus (GDM) in Cantonese women.</p><p><b>METHDS</b>This a cross-sectional study included 571 pregnant women who underwent a 75-g oral glucose challenge test at the 24th to 28th gestational week. Food frequency questionnaire (FFQ) was used by three dieticians to evaluate all the subjects' dietary habits.</p><p><b>RESULTS</b>13% of the investigated subjects were identified to have GDM (GDM⁺). No significant differences were found between the GDM⁺ and GDM⁻ groups in the intake of energy, macronutrients, fibers, or cholesterol. The amount of low- and middle-GI fruits consumed daily in the two groups was not statistically different, but the GDM⁺ subjects reported a significantly greater amount of high-GI fruit intake as well as energy-dense foods than the GDM⁻ subjects (P<0.05). Multiple logistic regression analysis revealed that increased consumption of energy-dense snack foods and high glycemic-index fruits were strongly associated with the risk of GDM.</p><p><b>CONCLUSION</b>Local dietary composition (high-GI fruit and energy-dense foods) is closely related to the risk of GDM in Cantonese women, for whom intensive health education of dietary behavior is needed to control GDM.</p>