Retinal status analysis method based on feature extraction and quantitative grading in OCT images

Background: Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. Methods: This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. Results: This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. Conclusions: This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosi

Retinal status analysis method based on feature extraction and quantitative grading in OCT images

The raw database includes 200 retinal OCT images judged as normal by ophthalmologists and 100 images with various abnormalities. The software includes the main steps for retinal status analysis. The software was carried out in Matlab

Protein Interactomic Analysis of SAPKs and ABA-Inducible bZIPs Revealed Key Roles of SAPK10 in Rice Flowering

As core components of ABA signaling pathway, SnRK2s (Sucrose nonfermenting1–Related protein Kinase 2) bind to and phosphorylate AREB/ABF (ABA responsive element binding protein/ABRE-binding factor) transcriptional factors, particularly bZIPs (basic region-leucine zipper), to participate in various biological processes, including flowering. Rice contains 10 SnRK2 members denoted as SAPK1-10 (Stress-Activated Protein Kinase) and dozens of bZIPs. However, which of the SAPKs and bZIPs pair and involve in ABA signaling remains largely unknown. In this study, we carried out a systematical protein-protein interactomic analysis of 10 SAPKs and 9 ABA-inducible bZIPs using yeast-two-hybrid technique, and identified 14 positive interactions. The reliability of Y2H work was verified by in vitro pull-down assay of the key flowering regulator bZIP77 with SAPK9 and SAPK10, respectively. Moreover, SAPK10 could phosphorylate bZIP77 in vitro. Over-expression of SAPK10 resulted in earlier flowering time, at least partially through regulating the FAC-MADS15 pathway. Conclusively, our results provided an overall view of the SAPK-bZIP interactions, and shed novel lights on the mechanisms of ABA-regulated rice flowering

A Comprehensive Proteomic Survey of ABA-Induced Protein Phosphorylation in Rice (Oryza sativa L.)

abscisic acid (ABA) is a key phytohormone regulating plant development and stress response. The signal transduction of ABA largely relies on protein phosphorylation. However; little is known about the phosphorylation events occurring during ABA signaling in rice thus far. By employing a label-free; MS (Mass Spectrometry)-based phosphoproteomic approach; we identified 2271 phosphosites of young rice seedlings and their intensity dynamics in response to ABA; during which 1060 proteins were found to be differentially phosphorylated. Western-blot analysis verified the differential phosphorylation pattern of D1, SMG1 and SAPK9 as indicated by the MS result; suggesting the high reliability of our phosphoproteomic data. The DP (differentially phosphorylated) proteins are extensively involved in ABA as well as other hormone signaling pathways. It is suggested that ABA antagonistically regulates brassinosteroid (BR) signaling via inhibiting BR receptor activity. The result of this study not only expanded our knowledge of rice phosphoproteome, but also shed more light on the pattern of protein phosphorylation in ABA signaling

A Comprehensive Proteomic Survey of ABA-Induced Protein Phosphorylation in Rice (Oryza sativa L.)

abscisic acid (ABA) is a key phytohormone regulating plant development and stress response. The signal transduction of ABA largely relies on protein phosphorylation. However; little is known about the phosphorylation events occurring during ABA signaling in rice thus far. By employing a label-free; MS (Mass Spectrometry)-based phosphoproteomic approach; we identified 2271 phosphosites of young rice seedlings and their intensity dynamics in response to ABA; during which 1060 proteins were found to be differentially phosphorylated. Western-blot analysis verified the differential phosphorylation pattern of D1, SMG1 and SAPK9 as indicated by the MS result; suggesting the high reliability of our phosphoproteomic data. The DP (differentially phosphorylated) proteins are extensively involved in ABA as well as other hormone signaling pathways. It is suggested that ABA antagonistically regulates brassinosteroid (BR) signaling via inhibiting BR receptor activity. The result of this study not only expanded our knowledge of rice phosphoproteome, but also shed more light on the pattern of protein phosphorylation in ABA signaling