SIYUAN LIU, YUAN ZHAO, YU YU, DOU YE, QIAN WANG, ZHAOYAN WANG, ZUO LUAN^*

BIOCELL, Vol.48, No.7, pp. 1115-1126, 2024, DOI:10.32604/biocell.2024.050493

Abstract Introduction: Transplantation of mesenchymal stromal cells (MSCs) is a promising therapy for type 1 diabetes (T1D). However, whether the infused MSCs affect the endoplasmic reticulum stress or subsequent unfolded protein response in β cells remains unclear. Methods: To investigate this, we induced early-onset T1D in non-obese diabetic mice using streptozotocin. Subsequently, T1D mice were randomly assigned to receive either MSCs or phosphate-buffered saline. We observed the in vivo homing of MSCs and assessed their effectiveness by analyzing blood glucose levels, body weight, histopathology, pancreatic protein expression, and serum levels of cytokines, proinsulin, and C-peptide. Results: Infused MSCs… More > Graphic Abstract

V. Thanikachalam^1,*, 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 >

Zhuoqun Xia¹, Hangyu Hu¹, Wenjing Li^2,3, Qisheng Jiang¹, Lan Pu¹, Yicong Shu¹, Arun Kumar Sangaiah^4,5,*

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 >

Anas Bilal¹, Azhar Imran², Talha Imtiaz Baig^3,4, Xiaowen Liu^1,*, 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 >

Heba M. El-Hoseny^1,*, 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 >

Abdul Qadir Khan¹, Guangmin Sun^1,*, 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 >

WEI LU^1,*, 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 >

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 >

HANY M. ABD EL-LATEEF^1,2,*, SAFA H. QAHL³, EMAN FAYAD⁴, SARAH A. ALTALHI⁴, IBRAHIM JAFRI⁴, EL SHAIMAA SHABANA⁵, MARWA K. DARWISH^6,7, REHAB MAHER⁸, SAAD SHAABAN^1,9, SHADY G. EL-SAWAH^10,*

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

FENGMEI QIAN^1,2, PEIYAO REN², LI ZHAO², DANNA ZHENG², WENFANG HE³, JUAN JIN^3,*

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