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https://www.selleckchem.com/products/a2ti-2.html [This corrects the article DOI 10.1371/journal.pone.0240398.].The causative agent of the pandemic identified as SARS-CoV-2 leads to a severe respiratory illness similar to SARS and MERS with fever, cough, and shortness of breath symptoms and severe cases that can often be fatal. In our study, we report our findings based on molecular docking analysis which could be the new effective way for controlling the SARS-CoV-2 virus and additionally, another manipulative possibilities involving the mimicking of immune system as occurred during the bacterial cell recognition system. For this purpose, we performed molecular docking using computational biology techniques on several SARS-CoV-2 proteins that are responsible for its pathogenicity against N-acetyl-D-glucosamine. A similar molecular dynamics analysis has been carried out on both SARS-CoV-2 and anti-Staphylococcus aureus neutralizing antibodies to establish the potential of N-acetyl-D-glucosamine which likely induces the immune response against the virus. The results of molecular dynamic analysis have confirmed that SARS-l SARS-CoV-2 proteins as well as induce an immune response against the virus in the host.In recent years, the rapid development of deep neural networks has made great progress in automatic organ segmentation from abdominal CT scans. However, automatic segmentation for small organs (e.g., the pancreas) is still a challenging task. As an inconspicuous and small organ in the abdomen, the pancreas has a high degree of anatomical variability and is indistinguishable from the surrounding organs and tissues, which usually leads to a very vague boundary. Therefore, the accuracy of pancreatic segmentation is sometimes below satisfaction. In this paper, we propose a 2.5D U-net with an attention mechanism. The proposed network includes 2D convolutional layers and 3D convolutional layers, which means that it requires less computational resources than 3D segmentatio

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