Rafl M. Kamil¹, Shaik Nyamathulla^1,*, Syed Mahmood^1,2,3,4,*

Journal of Polymer Materials, Vol.42, No.4, pp. 959-992, 2025, DOI:10.32604/jpm.2025.072005 - 26 December 2025

Abstract With the global diabetes epidemic, diabetic foot ulcers (DFUs) have become a major health burden, affecting approximately 18 million people worldwide each year, and account for about 80% of diabetes-related amputations. Five-year mortality among DFU patients approaches 30%, which is comparable to that of many malignancies. Yet despite standard wound care, only about 30%–40% of chronic DFUs achieve complete healing within 12 weeks. This persistent failure shows that conventional dressings remain passive supports. They do not counteract underlying pathologies such as ischemia, prolonged inflammation, and infection. Recent advances in polymeric nanofiber scaffolds, particularly electrospun matrices,… More > Graphic Abstract

Damodharan Palaniappan¹, Tan Kuan Tak², K. Vijayan³, Balajee Maram⁴, Pravin R Kshirsagar⁵, Naim Ahmad^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4107-4127, 2025, DOI:10.32604/cmes.2025.073387 - 23 December 2025

Abstract A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy (DR) stratification. A curated cohort of 1198 patients (2915 UWF_RI and 17,854 UWF_FA images) with strict registration quality supports training across three angiographic phases (initial, mid, final). The generator is based on a modified pix2pixHD with an added Gradient Variance Loss to better preserve microvasculature, and is evaluated using MAE, PSNR, SSIM, and MS-SSIM on held-out pairs. Quantitatively, the mid phase achieves the lowest MAE (98.76 ± 42.67), while SSIM remains high across phases. Expert review shows substantial agreement (Cohen’s More >

Sophia Strukel¹, Vikrant Rai^1,2,*

BIOCELL, Vol.49, No.10, pp. 1887-1911, 2025, DOI:10.32604/biocell.2025.067207 - 22 October 2025

Abstract Diabetic foot ulcers (DFUs) are a serious complication of diabetes mellitus and are associated with high morbidity, risk of amputation, and increased mortality. Although DFUs typically remain a chronic, non-healing wound, a small portion of DFUs may undergo malignant transformation. The subsequent malignancies are skin cancers such as squamous cell carcinoma (SCC), basal cell carcinoma, or melanoma. Understanding the pathophysiology of DFUs and the molecular and clinical determinants that contribute to their potential malignant transformation if crucial for clinical management. Chronic inflammation, dysregulation of cytokine signaling, faulty immune surveillance, and impaired wound healing all play… More >

Wei Hu¹, Dan Xiong^2,*

BIOCELL, Vol.49, No.9, pp. 1711-1731, 2025, DOI:10.32604/biocell.2025.067670 - 25 September 2025

Abstract Objectives: Podocytes undergo epithelial-mesenchymal transition (EMT) and ferroptosis in response to hyperglycemic stimulation. This is considered an important early event in the development and progression of diabetic nephropathy (DN). Rhein is the main active anthraquinone derivative in several common traditional herbal medicines. This study aimed to investigate the protective effects of Rhein on podocyte ferroptosis and EMT. Methods: The mouse glomerular podocyte cell line MPC5 was stimulated with high glucose (HG), Rhein, and the ferroptosis inhibitor ferrostatin-1 (Fer-1). Mechanistic investigations employed plasmids to overexpress and knockdown Sirtuin-1 (SIRT1), solute carrier family 7 member 11 (SLC7A11),… 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.144, No.2, pp. 2683-2683, 2025, DOI:10.32604/cmes.2025.069871 - 31 August 2025

Abstract This article has no abstract. More >

Fathe Jeribi^1,2, Ayesha Siddiqa^3,*, Hareem Kibriya⁴, Ali Tahir¹, Nadim Rana¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 955-982, 2025, DOI:10.32604/cmc.2025.065853 - 29 August 2025

Abstract Wound classification is a critical task in healthcare, requiring accurate and efficient diagnostic tools to support clinicians. In this paper, we investigated the effectiveness of the YOLO11n model in classifying different types of wound images. This study presents the training and evaluation of a lightweight YOLO11n model for automated wound classification using the AZH dataset, which includes six wound classes: Background (BG), Normal Skin (N), Diabetic (D), Pressure (P), Surgical (S), and Venous (V). The model’s architecture, optimized through experiments with varying batch sizes and epochs, ensures efficient deployment in resource-constrained environments. The model’s architecture… More >

Pooja Bidwai^1,2, Shilpa Gite^1,3, Biswajeet Pradhan^4,*, Abdullah Almari⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2645-2676, 2025, DOI:10.32604/cmc.2025.061018 - 03 July 2025

Abstract Diabetic Retinopathy (DR) is a critical disorder that affects the retina due to the constant rise in diabetics and remains the major cause of blindness across the world. Early detection and timely treatment are essential to mitigate the effects of DR, such as retinal damage and vision impairment. Several conventional approaches have been proposed to detect DR early and accurately, but they are limited by data imbalance, interpretability, overfitting, convergence time, and other issues. To address these drawbacks and improve DR detection accurately, a distributed Explainable Convolutional Neural network-enabled Light Gradient Boosting Machine (DE-ExLNN) is… More >

Saleh Albahli^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1095-1128, 2025, DOI:10.32604/cmes.2025.058821 - 11 April 2025

Abstract Predicting hospital readmission and length of stay (LOS) for diabetic patients is critical for improving healthcare quality, optimizing resource utilization, and reducing costs. This study leverages machine learning algorithms to predict 30-day readmission rates and LOS using a robust dataset comprising over 100,000 patient encounters from 130 hospitals collected over a decade. A comprehensive preprocessing pipeline, including feature selection, data transformation, and class balancing, was implemented to ensure data quality and enhance model performance. Exploratory analysis revealed key patterns, such as the influence of age and the number of diagnoses on readmission rates, guiding the More >

Tariq Mahmood^1,2, Tanzila Saba¹, Faten S. Alamri^3,*, Alishba Tahir⁴, Noor Ayesha⁵

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1173-1193, 2025, DOI:10.32604/cmc.2025.061150 - 26 March 2025

Abstract Innovation in learning algorithms has made retinal vessel segmentation and automatic grading techniques crucial for clinical diagnosis and prevention of diabetic retinopathy. The traditional methods struggle with accuracy and reliability due to multi-scale variations in retinal blood vessels and the complex pathological relationship in fundus images associated with diabetic retinopathy. While the single-modal diabetic retinopathy grading network addresses class imbalance challenges and lesion representation in fundus image data, dual-modal diabetic retinopathy grading methods offer superior performance. However, the scarcity of dual-modal data and the lack of effective feature fusion methods limit their potential due to… More >

Chengzhang Zhu^1,2, Ahmed Alasri¹, Tao Xu³, Yalong Xiao^1,2,*, Abdulrahman Noman¹, Raeed Alsabri¹, Xuanchu Duan⁴, Monir Abdullah⁵

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5153-5167, 2025, DOI:10.32604/cmc.2024.058647 - 06 March 2025

Abstract Globally, diabetic retinopathy (DR) is the primary cause of blindness, affecting millions of people worldwide. This widespread impact underscores the critical need for reliable and precise diagnostic techniques to ensure prompt diagnosis and effective treatment. Deep learning-based automated diagnosis for diabetic retinopathy can facilitate early detection and treatment. However, traditional deep learning models that focus on local views often learn feature representations that are less discriminative at the semantic level. On the other hand, models that focus on global semantic-level information might overlook critical, subtle local pathological features. To address this issue, we propose an… More >