RESULTS: A total of 21 distinct metabolic differences between HAE patients and healthy individuals were identified, and they are associated with perturbations in amino acid metabolism, energy metabolism, glyoxylate and dicarboxylate metabolism. Furthermore, the present results showed that the Fischer ratio, which is the molar ratio of branched-chain amino acids to aromatic amino acids, was significantly lower (P
OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
METHODS: In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image.
RESULTS: The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072.
CONCLUSION: our MV-SIR model can accurately perform 3D segmentation of lung nodules with the same segmentation accuracy as the U-net model.
AIM OF THE STUDY: This study aimed to investigate the effect and mechanism of β-glucan prepared from L. rhinocerotis using an enzymatic method on epithelial restitution during intestinal mucosal damage.
MATERIALS AND METHODS: Based on FT-IR, MALDI-TOF-MS, HPSEC-MALLS-RID, and AFM, the structure of polysaccharides from L. rhinocerotis was analysed. In addition, polysaccharides were used to test for wound healing activity in IEC-6 cells by measuring cell migration, proliferation, and expression of cell division control protein 42, Rac-1, RhoA, and Par-3.
RESULTS: β-glucan was extracted using enzyme-assisted extraction, and a yield of approximately 8.5 ± 0.8% was obtained from the dried biomass. The β-glucan extracted by enzyme-assisted extraction (EAE) of polysaccharides was composed entirely of D-glucose with a total carbohydrate content of 95.5 ± 3.2%. The results of HPLC, FTIR, and MALDI-TOF-MS analyses revealed EAEP to be confirmed as β-glucan. The molecular weight of prepared β-glucan was found to be 5.315 × 104 g/mol by HPSEC-MALLS-RID. Furthermore, mucosal wound healing studies showed that the treatment of IEC-6 with a β-glucan concentration of 200 μg/mL promoted cell migration and proliferation, and it enhanced the protein expression of cell division control protein 42, Rac-1, RhoA, and Par-3.
CONCLUSIONS: The present study reveals that the prepared β-glucan accelerates intestinal epithelial cell proliferation and migration via activation of Rho-dependent pathway. Hence, β-glucan can be employed as a prospective therapeutic agent for the treatment of diseases associated with gastrointestinal mucosal damage, such as peptic ulcers and inflammatory bowel disease.
RESULTS: CTNNB1 gene of HEK 293T cells was knocked out by CRISPR-Cas9. This was confirmed by sequencing and western blotting. Methylthiazolyl-tetrazolium bromide assays indicated that deletion of β-catenin significantly weakened adhesion ability and inhibited proliferation rate (P