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  • Open Access

    CORRECTION

    Correction: Diabetic Retinopathy Diagnosis Using Interval Neutrosophic Segmentation with Deep Learning Model

    V. Thanikachalam1,*, M. G. Kavitha2, V. Sivamurugan1

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 857-858, 2024, DOI:10.32604/csse.2024.052484

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

    Zhuoqun Xia1, Hangyu Hu1, Wenjing Li2,3, Qisheng Jiang1, Lan Pu1, Yicong Shu1, Arun Kumar Sangaiah4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 409-430, 2024, DOI:10.32604/cmes.2024.030052

    Abstract Early screening of diabetes retinopathy (DR) plays an important role in preventing irreversible blindness. Existing research has failed to fully explore effective DR lesion information in fundus maps. Besides, traditional attention schemes have not considered the impact of lesion type differences on grading, resulting in unreasonable extraction of important lesion features. Therefore, this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator (MPAG) and a lesion localization module (LLM). Firstly, MPAG is used to predict patches of different sizes and generate a weighted attention map based on the prediction score and… More >

  • Open Access

    ARTICLE

    DeepSVDNet: A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

    Anas Bilal1, Azhar Imran2, Talha Imtiaz Baig3,4, Xiaowen Liu1,*, Haixia Long1, Abdulkareem Alzahrani5, Muhammad Shafiq6

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 511-528, 2024, DOI:10.32604/csse.2023.039672

    Abstract Artificial Intelligence (AI) is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy (VTDR), which is a leading cause of visual impairment and blindness worldwide. However, previous automated VTDR detection methods have mainly relied on manual feature extraction and classification, leading to errors. This paper proposes a novel VTDR detection and classification model that combines different models through majority voting. Our proposed methodology involves preprocessing, data augmentation, feature extraction, and classification stages. We use a hybrid convolutional neural network-singular value decomposition (CNN-SVD) model for feature extraction and selection and an improved SVM-RBF with a Decision Tree More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Approach for Efficient Diabetic Retinopathy Classification Combining VGG16-CNN

    Heba M. El-Hoseny1,*, Heba F. Elsepae2, Wael A. Mohamed2, Ayman S. Selmy2

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1855-1872, 2023, DOI:10.32604/cmc.2023.042107

    Abstract Diabetic retinopathy is a critical eye condition that, if not treated, can lead to vision loss. Traditional methods of diagnosing and treating the disease are time-consuming and expensive. However, machine learning and deep transfer learning (DTL) techniques have shown promise in medical applications, including detecting, classifying, and segmenting diabetic retinopathy. These advanced techniques offer higher accuracy and performance. Computer-Aided Diagnosis (CAD) is crucial in speeding up classification and providing accurate disease diagnoses. Overall, these technological advancements hold great potential for improving the management of diabetic retinopathy. The study’s objective was to differentiate between different classes… More >

  • Open Access

    ARTICLE

    Optimizing Fully Convolutional Encoder-Decoder Network for Segmentation of Diabetic Eye Disease

    Abdul Qadir Khan1, Guangmin Sun1,*, Yu Li1, Anas Bilal2, Malik Abdul Manan1

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2481-2504, 2023, DOI:10.32604/cmc.2023.043239

    Abstract In the emerging field of image segmentation, Fully Convolutional Networks (FCNs) have recently become prominent. However, their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters, which can often be a cumbersome manual task. The main aim of this study is to propose a more efficient, less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images. To this end, our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network (FCEDN). The optimization is handled by a novel Genetic Grey Wolf Optimization (G-GWO) algorithm. This algorithm employs the Genetic Algorithm (GA) to… More >

  • Open Access

    ARTICLE

    Exosomal miR-30a-5p targets NLRP3 to suppress podocyte pyroptosis in diabetic nephropathy

    WEI LU1,*, KAN GUO2, DIANMEI XI1, ZHAOXIA XIA1

    BIOCELL, Vol.47, No.9, pp. 1995-2008, 2023, DOI:10.32604/biocell.2023.024591

    Abstract Background: Mesenchymal stem cell (MSC)-derived exosomes are closely related to pyroptosis in diabetic nephropathy (DN). This study aimed to explore the protective effect of exosomal miR-30a-5p on podocyte pyroptosis in DN. Methods: Streptozotocin was used to establish the mouse model of DN. Human bone marrow MSC-derived exosomes were extracted and identified via transmission electron microscopy, nanoparticle tracking analysis, and western blotting. MiR-30a-5p mimics and non-control (NC) mimics were transfected into MSCs and podocytes, and exosomes were isolated from the MSCs. High glucose (HG)-induced podocyte model was established to determine the effect of exosomal miR-30a-5p on pyroptosis… More >

  • Open Access

    ARTICLE

    PLDMLT: Multi-Task Learning of Diabetic Retinopathy Using the Pixel-Level Labeled Fundus Images

    Hengyang Liu, Chuncheng Huang*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1745-1761, 2023, DOI:10.32604/cmc.2023.040710

    Abstract In the field of medical images, pixel-level labels are time-consuming and expensive to acquire, while image-level labels are relatively easier to obtain. Therefore, it makes sense to learn more information (knowledge) from a small number of hard-to-get pixel-level annotated images to apply to different tasks to maximize their usefulness and save time and training costs. In this paper, using Pixel-Level Labeled Images for Multi-Task Learning (PLDMLT), we focus on grading the severity of fundus images for Diabetic Retinopathy (DR). This is because, for the segmentation task, there is a finely labeled mask, while the severity… More >

  • Open Access

    ARTICLE

    The potency of N, N'-diphenyl-1,4-phenylenediamine and adipose-derived stem cell co-administration in alleviating hepatorenal dysfunction complications associated with type 1 diabetes mellitus in rats

    HANY M. ABD EL-LATEEF1,2,*, SAFA H. QAHL3, EMAN FAYAD4, SARAH A. ALTALHI4, IBRAHIM JAFRI4, EL SHAIMAA SHABANA5, MARWA K. DARWISH6,7, REHAB MAHER8, SAAD SHAABAN1,9, SHADY G. EL-SAWAH10,*

    BIOCELL, Vol.47, No.8, pp. 1885-1895, 2023, DOI:10.32604/biocell.2023.030680

    Abstract Background: The increasing occurrence of diabetes mellitus (DM) noted worldwide has considerably elicited concern in the recent past. DM is associated with elevated vascular complications, morbidity, mortality, and poor quality of life. In this context, mesenchymal stem cells (MSCs) have shown significant therapeutic potentialities in managing and curing type 1 DM owing to their self-renewable, immunosuppressive, and differentiation capacities. We investigated the potential action of N, N′-diphenyl-1,4-phenylenediamine (DPPD), a well-known synthetic antioxidant to enhance the therapeutic ability of the adipose-derived stem cells (AD-MSCs) in alleviating kidney and liver complications in diabetic rats. Methods: Over the… More > Graphic Abstract

    The potency of <i>N</i>, <i>N'</i>-diphenyl-1,4-phenylenediamine and adipose-derived stem cell co-administration in alleviating hepatorenal dysfunction complications associated with type 1 diabetes mellitus in rats

  • Open Access

    ARTICLE

    Study of molecular mechanisms underlying the medicinal plant Tripterygium wilfordii-derived compound celastrol in treating diabetic nephropathy based on network pharmacology and molecular docking

    FENGMEI QIAN1,2, PEIYAO REN2, LI ZHAO2, DANNA ZHENG2, WENFANG HE3, JUAN JIN3,*

    BIOCELL, Vol.47, No.8, pp. 1853-1867, 2023, DOI:10.32604/biocell.2023.029353

    Abstract Background: Diabetic nephropathy (DN) is a serious complication of diabetes with rising prevalence worldwide. We aimed to explore the anti-DN mechanisms of the compound celastrol derived from the medicinal plant Tripterygium wilfordii. Methods: Celastrol-related targets were obtained from Herbal Ingredients’ Targets (HIT) and GeneCards databases. DN-related targets were retrieved from GeneCards, DisGeNET, and Therapeutic Targets Database (TTD). A Protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using ClusterProfiler. The cytoHubba plugin… More > Graphic Abstract

    Study of molecular mechanisms underlying the medicinal plant <i>Tripterygium wilfordii</i>-derived compound celastrol in treating diabetic nephropathy based on network pharmacology and molecular docking

  • Open Access

    VIEWPOINT

    Effect of non-enzymatic glycation on collagen nanoscale mechanisms in diabetic and age-related bone fragility

    JAMES L. ROSENBERG1, WILLIAM WOOLLEY1, IHSAN ELNUNU1, JULIA KAMML2, DAVID S. KAMMER2, CLAIRE ACEVEDO1,3,*

    BIOCELL, Vol.47, No.7, pp. 1651-1659, 2023, DOI:10.32604/biocell.2023.028014

    Abstract Age and diabetes have long been known to induce an oxidative reaction between glucose and collagen, leading to the accumulation of advanced glycation end-products (AGEs) cross-links in collagenous tissues. More recently, AGEs content has been related to loss of bone quality, independent of bone mass, and increased fracture risk with aging and diabetes. Loss of bone quality is mostly attributed to changes in material properties, structural organization, or cellular remodeling. Though all these factors play a role in bone fragility disease, some common recurring patterns can be found between diabetic and age-related bone fragility. The More >

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