Diabetic Retinopathy Lesion Segmentation Method Based on Multi-Scale Attention and Lesion Perception

The early diagnosis of diabetic retinopathy (DR) can effectively prevent irreversible vision loss and assist ophthalmologists in providing timely and accurate treatment plans. However, the existing methods based on deep learning have a weak perception ability of different scale information in retinal fundus images, and the segmentation capability of subtle lesions is also insufficient. This paper aims to address these issues and proposes MLNet for DR lesion segmentation, which mainly consists of the Multi-Scale Attention Block (MSAB) and the Lesion Perception Block (LPB). The MSAB is designed to capture multi-scale lesion features in fundus images, while the LPB perceives subtle lesions in depth. In addition, a novel loss function with tailored lesion weight is designed to reduce the influence of imbalanced datasets on the algorithm. The performance comparison between MLNet and other state-of-the-art methods is carried out in the DDR dataset and DIARETDB1 dataset, and MLNet achieves the best results of 51.81% mAUPR, 49.85% mDice, and 37.19% mIoU in the DDR dataset, and 67.16% mAUPR and 61.82% mDice in the DIARETDB1 dataset. The generalization experiment of MLNet in the IDRiD dataset achieves 59.54% mAUPR, which is the best among other methods. The results show that MLNet has outstanding DR lesion segmentation ability

Miocene Diversification and High-Altitude Adaptation of Parnassius Butterflies (Lepidoptera: Papilionidae) in Qinghai–Tibet Plateau Revealed by Large-Scale Transcriptomic Data

The early evolutionary pattern and molecular adaptation mechanism of alpine Parnassius butterflies to high altitudes in Qinghai–Tibet Plateau are poorly understood up to now, due to difficulties in sampling, limited sequence data, and time calibration issues. Here, we present large-scale transcriptomic datasets of eight representative Parnassius species to reveal the phylogenetic timescale and potential genetic basis for high-altitude adaptation with multiple analytic strategies using 476 orthologous genes. Our phylogenetic results strongly supported that the subgenus Parnassius formed a well-resolved basal clade, and the subgenera Tadumia and Kailasius were closely related in the phylogenetic trees. In addition, molecular dating analyses showed that the Parnassius began to diverge at about 13.0 to 14.3 million years ago (middle Miocene), correlated with their hostplant’s spatiotemporal distributions, as well as geological and palaeoenvironmental changes of the Qinghai–Tibet Plateau. Moreover, the accelerated evolutionary rate, candidate positively selected genes and their potentially functional changes were detected, probably contributed to the high-altitude adaptation of Parnassius species. Overall, our study provided some new insights into the spatiotemporally evolutionary pattern and high altitude adaptation of Parnassius butterflies from the extrinsic and intrinsic view, which will help to address evolution, biodiversity, and conservation questions concerning Parnassius and other butterfly species