Lv Ling^1,#, Minying Lu^2,#, Ling Ye³, Yuanhang Chen², Sheng Lin², Jun Yang², Yu Rong^2,*, Guixiong Wu^4,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069889 - 30 December 2025

Abstract Background: A significant proportion of patients still cannot benefit from existing targeted therapies and immunotherapies, making the search for new treatment strategies extremely urgent. In this study, we combined integrate public data analysis with experimental validation to identify novel prognostic biomarkers and therapeutic targets for lung adenocarcinoma (LUAD). Methods: We analyzed RNA and protein databases to assess the expression levels of cytochrome C oxidase 5B (COX5B) in LUAD. Several computational algorithms were employed to investigate the relationship between COX5B and immune infiltration in LUAD. To further elucidate the role of COX5B in LUAD, we utilized… More > Graphic Abstract

Xu Guo¹, Yanan Yu², Xiaolin Ma³, Yuanjie Cai^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069274 - 30 December 2025

Abstract Background: Long non-coding RNAs (lncRNAs) act as epigenetic regulators for tumor hallmarks. This investigation sought to probe the carcinogenic trait of PAN3-AS1 across pan-cancer comprehensively. Methods: We studied the diagnostic and prognostic features and the immune landscape of PAN3-AS1 across pan-cancer by bioinformatics approaches. The hierarchical regulatory networks governing PAN3-AS1 expression in colon cancer were explored via chromatin immunoprecipitation, luciferase activity assays, and RNA immunoprecipitation, etc. We screened drugs sensitive to WAP four-disulfide core domain 13 (WFDC13) by virtual screening and molecular docking. Results: Single-cell transcriptomics demonstrated that a variety of immune populations abnormally expressed PAN3-AS1… More >

Illia Khurtin^*, Mukesh Prasad

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-15, 2026, DOI:10.32604/cmc.2025.067481 - 09 December 2025

Abstract The field of artificial intelligence has advanced significantly in recent years, but achieving a human-like or Artificial General Intelligence (AGI) remains a theoretical challenge. One hypothesis suggests that a key issue is the formalisation of extracting meaning from information. Meaning emerges through a three-stage interpretative process, where the spectrum of possible interpretations is collapsed into a singular outcome by a particular context. However, this approach currently lacks practical grounding. In this research, we developed a model based on contexts, which applies interpretation principles to the visual information to address this gap. The field of computer… More >

Muhammad Adil¹, Nadeem Javaid^1,*, Imran Ahmed², Abrar Ahmed³, Nabil Alrajeh^4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071215 - 10 November 2025

Abstract Heart disease remains a leading cause of mortality worldwide, emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention. However, existing Deep Learning (DL) approaches often face several limitations, including inefficient feature extraction, class imbalance, suboptimal classification performance, and limited interpretability, which collectively hinder their deployment in clinical settings. To address these challenges, we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture. The preprocessing stage involves label encoding and feature scaling. To address the issue of… More >

Mubashir Ali^1,2, Jingzhen Li¹, Zedong Nie^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4153-4177, 2025, DOI:10.32604/cmes.2025.073048 - 23 December 2025

Abstract Diabetes imposes a substantial burden on global healthcare systems. Worldwide, nearly half of individuals with diabetes remain undiagnosed, while conventional diagnostic techniques are often invasive, painful, and expensive. In this study, we propose a noninvasive approach for diabetes detection using photoplethysmography (PPG), which is widely integrated into modern wearable devices. First, we derived velocity plethysmography (VPG) and acceleration plethysmography (APG) signals from PPG to construct multi-channel waveform representations. Second, we introduced a novel multiset spatiotemporal feature fusion framework that integrates hand-crafted temporal, statistical, and nonlinear features with recursive feature elimination and deep feature extraction using… More >

Yang Lei^1,*, Bo Jiang¹, Yucai Zhao², Gaofeng Fu³, Falin Qi¹, Tian Tian¹, Qiankuan Feng¹, Qiming Qu¹

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1657-1679, 2025, DOI:10.32604/sdhm.2025.069415 - 17 November 2025

Abstract Detecting internal defects, particularly voids behind linings, is critical for ensuring the structural integrity of aging high-speed rail (HSR) tunnel networks. While ground-penetrating radar (GPR) is widely employed, systematic quantification of performance boundaries for air-coupled (A-CGPR) and ground-coupled (G-CGPR) systems within the complex electromagnetic environment of multilayer reinforced HSR tunnels remains limited. This study establishes physics-based quantitative performance limits for A-CGPR and G-CGPR through rigorously validated GPRMax finite-difference time-domain (FDTD) simulations and comprehensive field validation over a 300 m operational HSR tunnel section. Key performance metrics were quantified as functions of: (a) detection distance (A-CGPR:… More >

Si-Yu Gao¹, Siu-Man Ng^2,*

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1471-1482, 2025, DOI:10.32604/ijmhp.2025.068702 - 31 October 2025

Abstract Background: Existing Chinese stigma scales focus on the perceptions of people with mental illness (PMI) without assessing the general public’s attitudes toward integrating PMI into the community. Developing a valid and reliable Chinese instrument measuring the attitude domain will be helpful to future research in this area. The current study aimed to validate a shortened Chinese version of the Community Attitudes towards the Mentally Ill Scale (C-CAMI-SF). Methods: Four hundred participants who are (1) Chinese; (2) aged 18 years and above; and (3) able to complete the Chinese questionnaire in a self-reported manner participated in… More >

Ibrahim Yahaya Garta, William Eric Manongga, Su-Wen Huang, Rung-Ching Chen^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4457-4471, 2025, DOI:10.32604/cmc.2025.067149 - 23 October 2025

Abstract Unlike the detection of marked on-street parking spaces, detecting unmarked spaces poses significant challenges due to the absence of clear physical demarcation and uneven gaps caused by irregular parking. In urban cities with heavy traffic flow, these challenges can result in traffic disruptions, rear-end collisions, sideswipes, and congestion as drivers struggle to make decisions. We propose a real-time detection system for on-street parking spaces using YOLO models and recommend the most suitable space based on KD-tree search. Lightweight versions of YOLOv5, YOLOv7-tiny, and YOLOv8 with different architectures are trained. Among the models, YOLOv5s with SPPF… More >

Ruiqi Li^1,2, Hongda Chen^1,2,*, Haixiao Hu^1,2,3, Yu Zhang², Shuxin Li^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011327

Abstract Composite hydrogen cylinders are recognized as the most efficient solution for storage and transportation of high-pressure gaseous hydrogen. The plastic-lined and fully carbon fiber-wound Type IV composite cylinders are one of the most attractive advanced hydrogen storage technologies. The design of carbon fiber reinforcements on the dome section of the cylinder is one of the critical challenges in the development of Type IV composite hydrogen cylinders. Conventional design approaches ignored the variable angle of fiber-wound layers and the influence of fiber angle and thickness variations in the dome section on design and often result in… More >

Saif Allah Allouani¹, Amine Zenjari², Abla Berrada¹, Mohammed Ben Amar¹, Amal Zaki^2,*

Journal of Psychology in Africa, Vol.35, No.5, pp. 619-625, 2025, DOI:10.32604/jpa.2025.070238 - 24 October 2025

Abstract This study adapted and validated the Three-Dimensional Wisdom Scale (3D-WS; Ardelt, 2003) for a Moroccan adult sample. The 3D-WS conceptualizes wisdom through cognitive, reflective, and affective dimensions. A total of 404 Moroccan adults (56.9% women; M = 31.8 years, SD = 9.4) completed an online survey. Exploratory factor analysis (principal-axis extraction with Promax rotation) reduced the scale to 15 culturally adapted items across three factors, accounting for 44.3% of the total variance. Confirmatory factor analysis demonstrated satisfactory fit: χ²/df = 1.46, GFI = 0.94, CFI = 0.91, RMSEA = 0.049. Bifactor modeling indicated a strong More >