Boundary-Repairing Dual-Path Network for Retinal Layer Segmentation in OCT Image with Pigment Epithelial Detachment.

Automatic retinal layer segmentation in optical coherence tomography (OCT) images is crucial for the diagnosis of ocular diseases. Currently, automatic retinal layer segmentation works well with normal OCT images. However, pigment epithelial detachment (PED) dramatically alters the retinal structure, causing blurred boundaries and partial disappearance of the Bruch's Membrane (BM), thus posing challenges to the segmentation.

Genetically predicted retinal vascular occlusion in relation to cardiovascular diseases: A bidirectional two-sample Mendelian randomization analysis.

Introduction: Increasing evidence implicates retinal vascular occlusions as a susceptibility factor for cardiovascular diseases (CVDs), whereas inconsistent results on the relationship were reported in previous observational studies. This research using a bidirectional two-sample Mendelian randomization (MR) analysis aimed to investigate the potential association between genetically determined central/branch retinal artery and retinal vein occlusions (CRAO/BRAO/RVO) and the risk of CVD.

Methods: Summary statistics of retinal vascular occlusions from the largest available genome-wide association study of European descent were used to investigate their relationship with CVDs, and vice versa.

Causal inference between serum bilirubin levels and juvenile idiopathic arthritis-associated uveitis: A bidirectional Mendelian randomization study.

Background: Several observational studies have suggested an association between low serum bilirubin levels and Behçet's disease uveitis. However, the causal inference between bilirubin level and juvenile idiopathic arthritis-associated uveitis (JIAU) remains ambiguous. We investigated the potential causal relationship between serum bilirubin levels and JIAU using a bidirectional two-sample Mendelian randomization (MR) framework.

Semi-supervised contrast learning-based segmentation of choroidal vessel in optical coherence tomography images.

Choroidal vessels account for 85% of all blood vessels in the eye, and the accurate segmentation of choroidal vessels from optical coherence tomography (OCT) images provides important support for the quantitative analysis of choroid-related diseases and the development of treatment plans. Although deep learning-based methods have great potential for segmentation, these methods rely on large amounts of well-labeled data, and the data collection process is both time-consuming and laborious.In this paper, we propose a novel asymmetric semi-supervised segmentation framework called SSCR, based on a student-teacher model, to segment choroidal vessels in OCT images.

TSSK-Net: Weakly supervised biomarker localization and segmentation with image-level annotation in retinal OCT images.

The localization and segmentation of biomarkers in OCT images are critical steps in retina-related disease diagnosis. Although fully supervised deep learning models can segment pathological regions, their performance relies on labor-intensive pixel-level annotations. Compared with dense pixel-level annotation, image-level annotation can reduce the burden of manual annotation.

Contrastive uncertainty based biomarkers detection in retinal optical coherence tomography images.

Retinal biomarker in optical coherence tomography (OCT) images plays a key guiding role in the follow-up diagnosis and clinical treatment of eye diseases. Although there have been many deep learning methods to automatically process retinal biomarker, the detection of retinal biomarkers is still a great challenge due to the similar characteristics to normal tissue, large changes in size and shape and fuzzy boundary of different types of biomarkers. To overcome these challenges, a novel contrastive uncertainty network (CUNet) is proposed for retinal biomarkers detection in OCT images.

Causal analysis of serum polyunsaturated fatty acids with juvenile idiopathic arthritis and ocular comorbidity.

Background & Objective: To investigate the causal effects of plasma Polyunsaturated fatty acids (PUFAs) on the risk of juvenile idiopathic arthritis (JIA) and ocular comorbidity through Mendelian randomization (MR) analysis.

Methods: Genetic variants (formerly single nucleotide polymorphisms, SNPs) that are strongly associated with PUFAs levels (P < 5×10) were selected as instrumental variables. Summary-level MR was performed with outcome estimates for JIA (n = 31,142) and JIA associated iridocyclitis (n = 94,197).

Causal association of juvenile idiopathic arthritis-associated uveitis with depression and anxiety: a bidirectional Mendelian randomization study.

Purpose: The objective of this article was to examine the potential effect of juvenile idiopathic arthritis-associated uveitis (JIAU) on the risk of major depressive and anxiety disorders through Mendelian randomization (MR) study.

Methods: Genetic instrumental variables from the largest available genome-wide association study for JIAU, major depressive disorder, and anxiety disorder were applied. A set of complementary MR approaches including inverse-variance weighted (IVW) were carried out to verify the estimate association and assess horizontal pleiotropy.

Pathological Changes and Expression of JAK-STAT Signaling Pathway Hallmark Proteins in Rat Retinas at Different Time Points After Retinal Ischemia Reperfusion Injury.

Retinal ischemia reperfusion injury (RIRI) is a conventional pathological process in various retinal vascular diseases. Many studies select only one specific time point to apply drugs and then assess the therapeutic effect of drugs; however, the baselines are not the same at different time points, which may cause variation in the judgement. Therefore, further investigation is needed.

Meta-Analysis of the Genetic Association between PTPN22 and CTLA-4 Variants and Risk of Uveitis.

Background: Though the risk of protein tyrosine phosphatase nonreceptor 22 (PTPN22) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) genetic variants with uveitis have been developed, the combined results still remain uncertain and controversial.

Objectives: The aim of this study was to perform a meta-analysis to estimate the precise association of PTPN22 (rs2488457 and rs2476601) and CTLA-4 (rs231775, rs5742909, rs4553808, and rs3087243) polymorphisms with uveitis susceptibility.

Method: Five electronic databases (PubMed, Embase, Web of Science, China Biomedical Database, and China National Knowledge Infrastructure) were systematically searched for relevant literature up to July 20, 2021.

Exploration of retinoblastoma pathogenesis with bioinformatics.

Background: Differentially expressed genes (DEGs) from retinoblastoma (RB) tissues play key roles in the progression of RB. However, the role of DEGs in different subtypes and stages of RB has not yet been systematically analyzed.

Methods: In this study, the DEGs for tumor and adjacent from 3 RB data sets GSE24673, GSE97508, and GSE110811 were analyzed with regard to the different subtypes and stages of the disease.

miR-130a-3p Enhances the Chemosensitivity of Y79 Retinoblastoma Cells to Vincristine by Targeting PAX6 Expression.

Purpose: Chemoresistance remains the primary obstacle threatening the prognosis of retinoblastoma (RB). microRNAs (miRNAs) are acknowledged as critical regulators of drug resistance. This study explored the molecular mechanism of miR-130a-3p affecting the chemosensitivity of RB to vincristine (VCR).