Kyung-Wan Baek^1,2,#, Jinkyung Cho^3,#, Ji Hyun Kim⁴, Ji-Seok Kim^1,2,*

BIOCELL, Vol.49, No.8, pp. 1339-1362, 2025, DOI:10.32604/biocell.2025.064916 - 29 August 2025

Abstract Chronic kidney disease (CKD) affects a significant fraction of the global population and is closely associated with elevated cardiovascular risk and poor clinical outcomes. Its pathophysiology entails complex molecular and cellular disturbances, including reduced nitric oxide bioavailability, persistent low-grade inflammation, oxidative stress, endothelial dysfunction, altered mineral metabolism, genetic predispositions, and uremic toxin accumulation. As current pharmacological treatments provide only partial risk reduction, complementary approaches are imperative. Exercise training, both aerobic and resistance, has emerged as a potent non-pharmacological intervention targeting these underlying molecular pathways. Regular exercise can enhance nitric oxide signaling, improve antioxidant defenses, attenuate… More >

Geemitha Ratnayake^*, Yaqoub Jafar, Bruno Leslie, Luis Henrique Braga^*

Canadian Journal of Urology, Vol.32, No.3, pp. 209-212, 2025, DOI:10.32604/cju.2025.064122 - 27 June 2025

Abstract Background: Bladder augmentation is often necessary to address poorly compliant and low-capacity bladders which can result from Posterior Urethral Valve. Traditional techniques are limited by complications from using bowel tissue, thus in the setting of a megaureter, ureterocystoplasty is favorable. Methods: We present a case of Teapot ureterocystoplasty, which improves vascular protection of the ureter by leaving the distal 3 cm of the ureter tubularized. Cystograms demonstrated bladder capacity improvement from 50 mL to 180 mL post-operatively. Additionally, creatinine stabilized after a peak of 250 µmol/L. Result and Conclusion: This patient is doing well at 4.5-year More >

JU-YEON LEE¹, DAEUN MOON², JINU KIM^2,3,*

BIOCELL, Vol.49, No.1, pp. 79-92, 2025, DOI:10.32604/biocell.2024.058340 - 24 January 2025

Abstract The epidermal growth factor receptor (EGFR) is a transmembrane glycoprotein that plays a crucial role in signal transduction and cellular responses. This review explores the function of EGFR in kidney physiology and its implications for various kidney diseases. EGFR signaling is essential for kidney function and repair mechanisms, and its dysregulation significantly impacts both acute and chronic kidney conditions. The review discusses the normal distribution of EGFR in kidney tubular segments, the mechanism of its activation and inhibition, and the therapeutic potential of EGFR-targeting antagonists and ligands. Additionally, it explores the pathophysiological characteristics observed More >

Nazik Alturki¹, Abdulaziz Altamimi², Muhammad Umer^3,*, Oumaima Saidani¹, Amal Alshardan¹, Shtwai Alsubai⁴, Marwan Omar⁵, Imran Ashraf^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3513-3534, 2024, DOI:10.32604/cmes.2023.045868 - 11 March 2024

Abstract Chronic kidney disease (CKD) is a major health concern today, requiring early and accurate diagnosis. Machine learning has emerged as a powerful tool for disease detection, and medical professionals are increasingly using ML classifier algorithms to identify CKD early. This study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California, UC Irvine Machine Learning repository. The research introduces TrioNet, an ensemble model combining extreme gradient boosting, random forest, and extra tree classifier, which excels in providing highly accurate predictions for CKD. Furthermore, K nearest neighbor (KNN) More >

GIULIA CHIABOTTO^1,*, STEFANIA BRUNO^2,*

BIOCELL, Vol.47, No.7, pp. 1499-1508, 2023, DOI:10.32604/biocell.2023.028121 - 21 June 2023

Abstract Renal fibrosis and inflammation are common pathological features of chronic kidney disease (CKD). Since currently available treatments can only delay the progression of CKD, the outcome of patients with CKD is still poor. One therapeutic option for the prevention of CKD-related complications could be the use of mesenchymal stromal cells (MSCs), which have shown beneficial effects in tissue fibrosis and regeneration after damage. However, safety issues, such as cellular rejection and carcinogenicity, limit their clinical application. Among the bioactive factors secreted by MSCs, extracellular vesicles (EVs) have shown the same beneficial effect of MSCs, without More > Graphic Abstract

Sultan Mesfer Aldossary^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3387-3404, 2023, DOI:10.32604/iasc.2023.035249 - 15 March 2023

Abstract With the emergence of cloud technologies, the services of healthcare systems have grown. Simultaneously, machine learning systems have become important tools for developing matured and decision-making computer applications. Both cloud computing and machine learning technologies have contributed significantly to the success of healthcare services. However, in some areas, these technologies are needed to provide and decide the next course of action for patients suffering from diabetic kidney disease (DKD) while ensuring privacy preservation of the medical data. To address the cloud data privacy problem, we proposed a DKD prediction module in a framework using cloud… More >

S. Prakash^1,*, P. Vishnu Raja², A. Baseera³, D. Mansoor Hussain⁴, V. R. Balaji⁵, K. Venkatachalam⁶

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1273-1287, 2022, DOI:10.32604/csse.2022.021784 - 08 February 2022

Abstract Urban living in large modern cities exerts considerable adverse effects on health and thus increases the risk of contracting several chronic kidney diseases (CKD). The prediction of CKDs has become a major task in urbanized countries. The primary objective of this work is to introduce and develop predictive analytics for predicting CKDs. However, prediction of huge samples is becoming increasingly difficult. Meanwhile, MapReduce provides a feasible framework for programming predictive algorithms with map and reduce functions. The relatively simple programming interface helps solve problems in the scalability and efficiency of predictive learning algorithms. In the… More >

R. H. Aswathy^1,*, P. Suresh¹, Mohamed Yacin Sikkandar², S. Abdel-Khalek³, Hesham Alhumyani⁴, Rashid A. Saeed⁴, Romany F. Mansour⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2097-2111, 2022, DOI:10.32604/cmc.2022.019790 - 27 September 2021

Abstract In recent times, Internet of Things (IoT) and Cloud Computing (CC) paradigms are commonly employed in different healthcare applications. IoT gadgets generate huge volumes of patient data in healthcare domain, which can be examined on cloud over the available storage and computation resources in mobile gadgets. Chronic Kidney Disease (CKD) is one of the deadliest diseases that has high mortality rate across the globe. The current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm (FPA)-based Deep Neural Network (DNN) model abbreviated as FPA-DNN. The steps involved in the… More >

Vinothini Arumugam^*, S. Baghavathi Priya

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 947-959, 2022, DOI:10.32604/iasc.2022.018654 - 22 September 2021

Abstract Nowadays, Chronic Kidney Disease (CKD) is one of the vigorous public health diseases. Hence, early detection of the disease may reduce the severity of its consequences. Besides, medical databases of any disease diagnosis may be collected from the blood test, urine test, and patient history. Nevertheless, medical information retrieved from various sources is diverse. Therefore, it is unadaptable to evaluate numerical and nominal features using the same feature selection algorithm, which may lead to fallacious analysis. Applying machine learning techniques over the medical database is a common way to help feature identification for CKD prediction.… More >

Danielle Kirelik^1,2, Mark Fisher², Michael DiMaria², Danielle E. Soranno³, Katja M. Gist²

Congenital Heart Disease, Vol.14, No.5, pp. 760-764, 2019, DOI:10.1111/chd.12776

Abstract Background: There are several limitations when using creatinine to estimate glomerular filtration rate, especially in children with chronic medical conditions who are at high risk of kidney dysfunction. Cystatin C has been the recent focus of research as a replacement biomarker for creatinine. Our objective was to compare the 2 biomarkers in pediatric single‐ventricle heart disease patients who have undergone the Fontan operation. We hypothesized that there would be poor correlation and agreement between the 2 estimates of renal function.
Methods: This was a single center retrospective chart review of 20 patients who had previously undergone Fontan… More >