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Chinese Journal of Digestive Endoscopy ; (12): 789-794, 2021.
Artigo em Chinês | WPRIM | ID: wpr-912174

RESUMO

Objective:To develop a deep convolutional neural network (CNN) to automatically detect gastric lesions in endoscopic images.Methods:A CNN-based diagnostic system was constructed based on ResNet-34 residual network structure and DeepLabv3 structure, and trained by using 17 217 routine gastroscopy images.These images were from 1 121 gastric lesions of five types acquired in Peking University People′s Hospital between 2012 and 2018, namely peptic ulcer (PU), early gastric cancer (EGC) and high-grade intraepithelial neoplasia (HGIN), advanced gastric cancer (AGC), gastric submucosal tumors (SMTs), and normal gastric mucosa without lesions. The trained CNN was evaluated through a test dataset that contained 1 091 routine gastroscopy images of 237 gastric lesions. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the CNN were calculated.Results:The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the CNN-assisted diagnosis of EGC and HGIN were 78.6% (33/42), 84.4% (27/32), 60.0% (6/10), 87.1% (27/31), and 54.5% (6/11), respectively. The accuracy, sensitivity, and specificity of CNN-assisted diagnosis of PU were 90.4% (47/52), 92.7% (38/41), and 81.8% (9/11), respectively, the outcomes of AGC were 88.1% (52/59), 91.8% (45/49), and 70.0% (7/10), respectively, and those of gastric SMTs were 86.0% (43/50), 89.7% (35/39), and 72.7% (8/11), respectively. The CNN′s recognition time for all images of the test set was 42 seconds.Conclusion:The constructed CNN system, as a rapid and accurate auxiliary diagnostic instrument, can detect not only EGC and HGIN but also other gastric lesions.

2.
Acta Pharmaceutica Sinica B ; (6): 512-528, 2020.
Artigo em Inglês | WPRIM | ID: wpr-792992

RESUMO

A series of 2-(((5-akly/aryl-1-pyrazol-3-yl)methyl)thio)-5-alkyl-6-(cyclohexylmethyl)-pyrimidin-4(3)-ones were synthesized and their anti-HIV-1 activities were evaluated. Most of these compounds were highly active against wild-type (WT) HIV-1 strain (IIIB) with EC values in the range of 0.0038-0.4759 μmol/L. Among those compounds, had an EC value of 3.8 nmol/L and SI (selectivity index) of up to 25,468 indicating excellent activity against WT HIV-1. anti-HIV-1 activity and resistance profile studies suggested that compounds and displayed potential anti-HIV-1 activity against laboratory adapted strains and primary isolated strains including different subtypes and tropism strains (ECs range from 4.3 to 63.6 nmol/L and 18.9-219.3 nmol/L, respectively). On the other hand, it was observed that those two compounds were less effective with EC values of 2.77 and 4.87 μmol/L for HIV-1A (K103N + Y181C). The activity against reverse transcriptase (RT) was also evaluated for those compounds. Both and obtained sub-micromolar IC values showing their potential in RT inhibition. The pharmacokinetics examination in rats indicated that compound has acceptable pharmacokinetic properties and bioavailability. Preliminary structure-activity relationships and molecular modeling studies were also discussed.

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