Objective To compare the effect of aerobic and resistance exercise on brown adipose tissues in rats.Methods Sprague-Dawley rats were randomly assigned to a control(C)group,an aerobic exercise (T) group and a resistance exercise(L)group.The rats of group T performed treadmill exercise 5 days per week for 8 weeks,while those of group L climbed vertical ladders with progressively increased weights once in 3 days for 8 weeks.All rats were weighed before and after the intervention.Then the bilateral interscapular brown adipose tissue was isolated and weighed at 48h after the last exercise.The hematoxylin-eosin staining was used to observe the morphology of adipocytes,and the quantitative real-time PCR and Western blotting were employed to detect the mRNA and protein expression of browning genes [PR-domain-containing 16 (PRDM 16),PPAR gamma coactivator-1α (PGC-1 α) and uncoupling protein 1(UCP1)] respectively.Results After the intervention,the increment of weight of group T and group L were only 52％ and 70％ of group C(P＜0.01 and P＜0.05).The weight of BAT in both group T and L was lower than group C,but without significance(P＞0.05).The average size of lipid droplets in group T decreased significantly(P＜0.01) and slightly in group L(P＞0.05) compared with group C.The PRDM16,PGC-1α and UCP1 mRNA expression of group T was 1.78(P＜0.01),2.2(P＜ 0.01) and 1.3(P＞0.05) times of group C,while that of group L was 1.30(P＞0.05),1.25(P＞0.05) and 1.21(P＞0.05) times of group C.The PRDM16,PGC-1α and UCP1 protein level in group T was 1.46-fold(P＜0.05),1.56-fold(P＞0.05)and 1.20-fold(P＞0.05),while that of group L was 1.08-fold(P＞0.05),0.94-fold(P＞0.05) and 1.20-fold(P＞0.05) of group C.Conclusion Eight weeks of aerobic exercise can significantly make the lipid droplets of adipocyte smaller,increase the differentiation and metabolic activity of BAT,and weakly stimulate BAT thermogenesis.However,8 weeks of resistance exercise has no significant effect on BAT.

Objective To discuss the value of clinical radiomic nomogram(CRN)and deep convolutional neural network(DCNN)in distinguishing atypical pulmonary hamartoma(APH)from atypical lung adenocarcinoma(ALA).Methods A total of 307 patients were retrospectively recruited from two institutions.Patients in institu-tion 1 were randomly divided into the training(n=184:APH=97,ALA=87)and internal validation sets(n=79:APH=41,ALA=38)in a ratio of 7∶3,and patients in institution 2 were assigned as the external validation set(n=44:APH=23,ALA=21).A CRN model and a DCNN model were established,respectively,and the performances of two models were compared by delong test and receiver operating characteristic(ROC)curves.A human-machine competition was conducted to evaluate the value of AI in the Lung-RADS classification.Results The areas under the curve(AUCs)of DCNN model were higher than those of CRN model in the training,internal and external validation sets(0.983 vs 0.968,0.973 vs 0.953,and 0.942 vs 0.932,respectively),however,the differences were not statistically significant(p=0.23,0.31 and 0.34,respectively).With a radiologist-AI com-petition experiment,AI tended to downgrade more Lung-RADS categories in APH and affirm more Lung-RADS cat-egories in ALA than radiologists.Conclusion Both DCNN and CRN have higher value in distinguishing APH from ALA,with the former performing better.AI is superior to radiologists in evaluating the Lung-RADS classification of pulmonary nodules.