LU ZHANG^*, JINGUO CHU^*, YUSHAN YU

Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988

Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups… 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

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) imputer is utilized to deal… More >

ELYN AMIELA SALLEH¹, YEONG YEH LEE², ANDEE DZULKARNAEN ZAKARIA³, NUR ASYILLA CHE JALIL⁴, MARAHAINI MUSA^1,*

BIOCELL, Vol.47, No.10, pp. 2233-2244, 2023, DOI:10.32604/biocell.2023.030541

Abstract Colorectal cancer (CRC) is a major global health concern. Accumulation of cancer-associated fibroblasts (CAFs) in CRC is associated with poor prognosis and disease recurrence. CAFs are the main cellular component of the tumor microenvironment. CAF-tumor cell interplay, which is facilitated by various secretomes, drives colorectal carcinogenesis. The complexity of CAF populations contributes to the heterogeneity of CRC and influences patient survival and treatment response. Due to their significant roles in colorectal carcinogenesis, different clinical applications utilizing or targeting CAFs have been suggested. Circulating CAFs (cCAFs) which can be detected in blood samples, have been proposed to help in determining patient… More > Graphic Abstract

QIAO ZHOU^1,2,3, JIAN LIU^2,4, LING XIN⁴, YANYAN FANG^2,4, LEI WAN^2,4, DAN HUANG^2,4, JINCHEN GUO¹, JIANTING WEN^2,4

BIOCELL, Vol.47, No.4, pp. 761-772, 2023, DOI:10.32604/biocell.2023.026698

Abstract The pathophysiology of osteoarthritis (OA) is multifactorial, with the primary risk factors being obesity, age, environmental variables, and genetic predisposition. The available evidence suggests that genetic diversity does not adequately account for all clinical characteristics and heterogeneity of OA. Genetics has emerged as a nascent and crucial area of research in OA. The epigenetic module presents a potential link between genetic and environmental risk factors and the susceptibility and pathogenesis of OA. As a critical epigenetic alteration, DNA methylation has been shown to have an important role in the etiology of OA and is a viable biomarker for predicting disease… More >

ISABELLA PANFOLI^1,*, MAURIZIO BRUSCHI², GIOVANNI CANDIANO²

BIOCELL, Vol.46, No.10, pp. 2167-2176, 2022, DOI:10.32604/biocell.2022.020154

Abstract Precision medicine is based on the identification of biomarkers of tumor development and progression. Liquid biopsy is at the forefront of the ability to gather diagnostic and prognostic information on tumors, as it can be noninvasively performed prior or during treatment. Liquid biopsy mostly utilizes circulating tumor cells, or free DNA, but also exosomes. The latter are nanovesicles secreted by most cell types, found in any body fluid that deliver proteins, nucleic acids and lipids to nearby and distant cells with a unique homing ability. Exosomes function in signalling between the tumor microenvironment and the rest of the body, promoting… More >

MARCO INVERNIZZI^1,2,*, NICOLA FUSCO^3,4,*

BIOCELL, Vol.46, No.10, pp. 2221-2223, 2022, DOI:10.32604/biocell.2022.021043

Abstract This article has no abstract. More >

Shuxuan Xie, Zengchen Yu, Zhihan Lv^*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 489-522, 2021, DOI:10.32604/cmes.2021.016728

Abstract In recent years, the development of artificial intelligence (AI) and the gradual beginning of AI’s research in the medical field have allowed people to see the excellent prospects of the integration of AI and healthcare. Among them, the hot deep learning field has shown greater potential in applications such as disease prediction and drug response prediction. From the initial logistic regression model to the machine learning model, and then to the deep learning model today, the accuracy of medical disease prediction has been continuously improved, and the performance in all aspects has also been significantly improved. This article introduces some… More >

Deukhun Kim¹, Heejin Kim², Jin Kwak^{3, *}

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1527-1553, 2020, DOI:10.32604/cmc.2020.010535

Abstract Numerous industries, especially the medical industry, are likely to exhibit significant developments in the future. Ever since the announcement of the precision medicine initiative by the United States in 2015, interest in the field has considerably increased. The techniques of precision medicine are employed to provide optimal treatment and medical services to patients, in addition to the prevention and management of diseases via the collection and analysis of big data related to their individual genetic characteristics, occupation, living environment, and dietary habits. As this involves the accumulation and utilization of sensitive information, such as patient history, DNA, and personal details,… More >

Andrew D. Spearman

Congenital Heart Disease, Vol.12, No.6, pp. 828-833, 2017, DOI:10.1111/chd.12543

Abstract A genetic basis of congenital heart disease (CHD) has been known for decades. In addition to the sequence of the genome, the contribution of epigenetics to pediatric cardiology is increasingly recognized. Multiple epigenetic mechanisms, including DNA methylation, histone modification, and RNA-based regulation, are known mediators of cardiovascular disease, including both development and progression of CHD and its sequelae. Basic understanding of the concepts of epigenetics will be essential to all pediatric cardiologists in order to understand mechanisms of pathophysiology, pharmacotherapeutic concepts, and to understand the role of epigenetics in precision medicine. More >