Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction method proposed here utilizes… More >

Kai Wang¹, Biao He^2,*, Pijush Samui³, Jian Zhou⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569

Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset, which serves… More >

Yunchang Liu^1,*, Fei Wan¹, Chengwu Liang²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4343-4361, 2024, DOI:10.32604/cmc.2024.047211

Abstract Traffic flow prediction plays a key role in the construction of intelligent transportation system. However, due to its complex spatio-temporal dependence and its uncertainty, the research becomes very challenging. Most of the existing studies are based on graph neural networks that model traffic flow graphs and try to use fixed graph structure to deal with the relationship between nodes. However, due to the time-varying spatial correlation of the traffic network, there is no fixed node relationship, and these methods cannot effectively integrate the temporal and spatial features. This paper proposes a novel temporal-spatial dynamic graph convolutional network (TSADGCN). The dynamic… More >

QIOU GU¹, CHUILIN LAI¹, XIAO GUAN¹, JING ZHU², TIAN ZHAN¹, JIANPING ZHANG^1,*

BIOCELL, Vol.48, No.2, pp. 253-269, 2024, DOI:10.32604/biocell.2023.028336

Abstract Objectives: Colorectal cancer (CRC) is a serious threat to human health worldwide. Oxaliplatin is a platinum analog and is widely used to treat CRC. However, resistance to oxaliplatin restricts its effectiveness and application while its target recognition and mechanism of action also remain unclear. Therefore, we aimed to develop an oxaliplatin-resistant prognostic model to clarify these aspects. Methods: We first obtained oxaliplatin-resistant and parental cell lines, and identified oxaliplatin-resistant genes using RNA sequencing (RNA-seq) and differential gene analysis. We then acquired relevant data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cox regression and Least Absolute… More > Graphic Abstract

Zhou Ji¹, Mengmeng Zhou², Qiang Wang², Jiandong Huang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1557-1582, 2024, DOI:10.32604/cmes.2023.046025

Abstract To improve the prediction accuracy of the International Roughness Index (IRI) of Jointed Plain Concrete Pavements (JPCP) and Continuously Reinforced Concrete Pavements (CRCP), a machine learning approach is developed in this study for the modelling, combining an improved Beetle Antennae Search (MBAS) algorithm and Random Forest (RF) model. The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study. The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well. The results by the comparative analysis showed the prediction accuracy of the IRI of the newly… More > Graphic Abstract

XIANGDONG SUN^1,2,#, HUIJUAN WEN^1,2,#, FAZHAN LI^1,2, IHTISHAM BUKHARI^1,2, FEIFEI REN^1,2, XIA XUE^1,2, PENGYUAN ZHENG^1,2,*, YANG MI^1,2,*

Oncology Research, Vol.32, No.2, pp. 283-296, 2024, DOI:10.32604/or.2023.044618

Abstract Nicotinamide adenine dinucleotide (NAD+) plays an essential role in cellular metabolism, mitochondrial homeostasis, inflammation, and senescence. However, the role of NAD+-regulated genes, including coding and long non-coding genes in cancer development is poorly understood. We constructed a prediction model based on the expression level of NAD+ metabolism-related genes (NMRGs). Furthermore, we validated the expression of NMRGs in gastric cancer (GC) tissues and cell lines; additionally, β-nicotinamide mononucleotide (NMN), a precursor of NAD+, was used to treat the GC cell lines to analyze its effects on the expression level of NMRGs lncRNAs and cellular proliferation, cell cycle, apoptosis, and senescence-associated secretory… More > Graphic Abstract

KUAILU LIN^1,2, QIANYU GU², XIXI LAI^2,3,*

BIOCELL, Vol.47, No.12, pp. 2681-2696, 2023, DOI:10.32604/biocell.2023.043298

Abstract Objectives: Triple-negative breast cancer (TNBC) poses a significant challenge due to the lack of reliable prognostic gene signatures and an understanding of its immune behavior. Methods: We analyzed clinical information and mRNA expression data from 162 TNBC patients in TCGA-BRCA and 320 patients in METABRIC-BRCA. Utilizing weighted gene coexpression network analysis, we pinpointed 34 TNBC immune genes linked to survival. The least absolute shrinkage and selection operator Cox regression method identified key TNBC immune candidates for prognosis prediction. We calculated chemotherapy sensitivity scores using the “pRRophetic” package in R software and assessed immunotherapy response using the Tumor Immune Dysfunction and… More >

Hyangjin Park¹, Haeryun Cho², So Yeon Yoo^3,*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1219-1228, 2023, DOI:10.32604/ijmhp.2023.041490

Abstract This study examined factors related to the psychological well-being of older adults and built and verified a model for predicting psychological well-being. The participants were 350 older adults aged over 60 years who lived in South Korea and were active in the local community. The model proposed in this study was found to be suitable. Depression, self-efficacy, and social support had a direct effect on the psychological well-being of older adults, while depression, activities of daily living (ADLs), and self-efficacy had an indirect effect. Self-efficacy and social support mediated the relationship between depression and psychological well-being, and self-efficacy mediated the… More >

JING GUO¹, CHANGYONG TONG¹, JIANGUANG SHI¹, XINJIAN LI¹, XUEQIN CHEN^2,*

Oncology Research, Vol.32, No.1, pp. 199-212, 2024, DOI:10.32604/or.2023.030969

Abstract Oxidative stress (OS) is intimately associated with tumorigenesis and has been considered a potential therapeutic strategy. However, the OS-associated therapeutic target for esophageal squamous cell carcinoma (ESCC) remains unconfirmed. In our study, gene expression data of ESCC and clinical information from public databases were downloaded. Through LASSO-Cox regression analysis, a risk score (RS) signature map of prognosis was constructed and performed external verification with the GSE53625 cohort. The ESTIMATE, xCell, CIBERSORT, TIMER, and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment (IM). Afterward, functional enrichment analysis clarified the underlying mechanism of the model. Nomogram… More >

ZHAOXU YAO^*, HAIBIN MA, LIN LIU, QIAN ZHAO, LONGCHAO QIN, XUEYAN REN, CHUANJUN WU, KAILI SUN

BIOCELL, Vol.47, No.9, pp. 1965-1975, 2023, DOI:10.32604/biocell.2023.030796

Abstract Objective: Through integrated bioinformatics analysis, the goal of this work was to find new, characterised N7-methylguanosine modification-related long non-coding RNAs (m7G-lncRNAs) that might be used to predict the prognosis of laryngeal squamous cell carcinoma (LSCC). Methods: The clinical data and LSCC gene expression data for the current investigation were initially retrieved from the TCGA database & sanitised. Then, using co-expression analysis of m7G-associated mRNAs & lncRNAs & differential expression analysis (DEA) among LSCC & normal sample categories, we discovered lncRNAs that were connected to m7G. The prognosis prediction model was built for the training category using univariate & multivariate COX… More >