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Glycosylation is the most complex post-modification effect of proteins. It participates in many biological processes in the human body and is closely related to many disease states. Among them, N-linked glycosylation is the most contained glycosylation data. However, the current N-linked glycosylation prediction tool does not take into account the serious imbalance between positive and negative data. In this study, we used protein sequence and amino acid characteristics to construct an N-linked glycosylation prediction model called N-GlycoGo. Based on sequence, structure, and function, 11 heterogeneous features were encoded. Further, XGBoost was selected for modeling. Finally, independent testing of human and mouse prediction models showed that N-GlycoGo is superior to other tools with Matthews correlation coefficient (MCC) values of 0.397 and 0.719, respectively, which is higher than other glycosylation site prediction tools. We have developed a fast and accurate prediction tool, N-GlycoGo, for N-linked glycosylation. N-GlycoGo is available at http://ncblab.nchu.edu.tw/n-glycogo/.

Optical coherence tomography angiography (OCTA) is a popular medical imaging technology that can quickly establish a three-dimensional model of the fundus without dye injection. However the number of images in a model is quite large, so finding the lesions through image processing technology can greatly reduce the time required for the judgment of the condition. This paper proposes a method for finding choroidal neovascularization (CNV) in OCTA images. Among the several characteristics of CNV, the larger turning angle of blood vessels is a relatively clear feature, so we will use this property to find out whether there is CNV in an OCTA image. We will transform the color space to CIELAB space, and extract the L-channel prior to preceding to the next step. We will then use some image segmentation methods to find the clearer vessel region. Finally, we will detect the CNV through certain morphology methods. The experimental result shows that our proposed method can effectively find the CNV in the OCTA image, meaning that we can make automated judgments through this method in the future and reduce the time necessary for human judgment.

To investigate the effect and complications of Combined Endoscope assisted Procedures (CEaP): endoscopic cyclophotocoagulation and pars plana ablation (ECP-plus), along with endoscopic panretinal photocoagulation (PRP).

No abstract