Enhancing Retinal Fundus Image Quality Assessment With Swin-Transformer-Based Learning Across Multiple Color-Spaces.

Purpose: The assessment of retinal image (RI) quality holds significant importance in both clinical trials and large datasets, because suboptimal images can potentially conceal early signs of diseases, thereby resulting in inaccurate medical diagnoses. This study aims to develop an automatic method for Retinal Image Quality Assessment (RIQA) that incorporates visual explanations, aiming to comprehensively evaluate the quality of retinal fundus images (RIs). Methods: We developed an automatic RIQA system, named Swin-MCSFNet, utilizing 28,792 RIs from the EyeQ dataset, as well as 2000 images from the EyePACS dataset and an additional 1,000 images from the OIA-ODIR dataset. After preprocessing, including cropping black regions, data augmentation, and normalization, a Swin-MCSFNet classifier based on the Swin-Transformer for multiple color-space fusion was proposed to grade the quality of RIs. The generalizability of Swin-MCSFNet was validated across multiple data centers. Additionally, for enhanced interpretability, a Score-CAM-generated heatmap was applied to provide visual explanations. Results: Experimental results reveal that the proposed Swin-MCSFNet achieves promising performance, yielding a micro-receiver operating characteristic (ROC) of 0.93 and ROC scores of 0.96, 0.81, and 0.96 for the "Good," "Usable," and "Reject" categories, respectively. These scores underscore the accuracy of RIQA based on Swin-MCSF in distinguishing among the three categories. Furthermore, heatmaps generated across different RIQA classification scores and various color spaces suggest that regions in the retinal images from multiple color spaces contribute significantly to the decision-making process of the Swin-MCSFNet classifier. Conclusions: Our study demonstrates that the proposed Swin-MCSFNet outperforms other methods in experiments conducted on multiple datasets, as evidenced by the superior performance metrics and insightful Score-CAM heatmaps. Translational Relevance: This study constructs a new retinal image quality evaluation system, which will contribute to the subsequent research of retinal images.

The association between genetic variations and morphology-based brain networks changes in Alzheimer's disease.

Alzheimer's disease (AD) is a highly heritable disease. The morphological changes of cortical cortex (such as, cortical thickness and surface area) in AD always accompany by the change of the functional connectivity to other brain regions and influence the short- and long-range brain network connections, causing functional deficits of AD. In this study, the first hypothesis is that genetic variations might affect morphology-based brain networks, leading to functional deficits; the second hypothesis is that protein-protein interaction (PPI) between the candidate proteins and known interacting proteins to AD might exist and influence AD. 600 470 variants and structural magnetic resonance imaging scans from 175 AD patients and 214 healthy controls were obtained from the Alzheimer's Disease Neuroimaging Initiative-1 database. A co-sparse reduced-rank regression model was fit to study the relationship between non-synonymous mutations and morphology-based brain networks. After that, PPIs between selected genes and BACE1, an enzyme that was known to be related to AD, are explored by using molecular dynamics (MD) simulation and co-immunoprecipitation (Co-IP) experiments. Eight genes affecting morphology-based brain networks were identified. The results of MD simulation showed that the PPI between TGM4 and BACE1 was the strongest among them and its interaction was verified by Co-IP. Hence, gene variations influence morphology-based brain networks in AD, leading to functional deficits. This finding, validated by MD simulation and Co-IP, suggests that the effect is robust.

Neurodevelopmental toxicity of organophosphate flame retardant triphenyl phosphate (TPhP) on zebrafish (Danio rerio) at different life stages.

As a substitute for polybrominated diphenyl ethers (PBDEs), organophosphate flame retardant triphenyl phosphate (TPhP) is widely used in our daily products and diffusely exists in our living surroundings, but there is a paucity of information concerning its neurodevelopmental toxicity. Herein, we investigated the effects of TPhP exposure on developmental parameters, locomotor behavior, oxidative stress, apoptosis and transcriptional levels in zebrafish at different developmental stages, so as to explore the effects of TPhP exposure on zebrafish neural development and the underlying molecular mechanisms. TPhP concentration gradient exposure reduced the survival rate, hatchability, heart rate, body length and eye distance of zebrafish embryos/larvae, and caused malformations of zebrafish larvae. TPhP also leads to abnormal locomotor behaviors, such as reduced swimming distance and swimming speed, and impaired panic avoidance reflex to high light stimulation. TPhP caused ROS accumulation in 96 hpf larvae and induced Nrf2-antioxidant response in zebrafish. In addition, TPhP further activated mitochondrial signaling pathways, which affected apoptosis in the zebrafish eye region, resulting in visual impairment. Neurodevelopmental (mbpa, syn2a, foxo3a and pax6a), Retinoid acid metabolism (cyp26a1, raraa, rbp5, rdh1, crabp1a and rbp2a) and apoptosis-related genes (bcl2a, baxa and casp9) revealed the molecular mechanism of abnormal behavior and phenotypic symptoms, and also indicated that 96 hpf larvae are more sensitive than 7 dpf larvae. Thus, in the present study, we revealed the neurotoxic effects of TPhP at different early life stages in zebrafish, and zebrafish locomotor behavior impairments induced by TPhP exposure are attributed to co-regulation of visuomotor dysfunction and neuro-related genes. These results suggest that the safety of TPhP in organisms and even in humans needs to be further studied.