Benyu Wang^*, Ke Chen, Bingjian Wang^#,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070137 - 08 January 2026

Abstract To examine stress redistribution phenomena in bridges subjected to varying operational conditions, this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge. An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns. XGBoost (eXtreme Gradient Boosting), a gradient-boosting machine learning (ML) algorithm, was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution. Unlike traditional numerical models that rely on extensive assumptions and idealizations, XGBoost effectively captures nonlinear and time-varying relationships between stress… More >

Se Ha Jang^1,2,#, Hyung Seok Kim^3,#, Jung Woo Eun^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.072240 - 30 December 2025

Abstract Hepatocellular carcinoma (HCC) remains one of the most prevalent and lethal malignancies worldwide. Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of gene expression and cancer progression, yet the functional diversity of RP11-derived lncRNAs—originally mapped to bacterial artificial chromosome (BAC) clones from the Roswell Park Cancer Institute—has only recently begun to be appreciated. This mini-review aims to systematically synthesize current findings on RP11-derived lncRNAs in HCC, outlining their genomic origins, molecular mechanisms, and biological significance. We highlight their roles in metabolic reprogramming, microRNA network modulation, and tumor progression, as well as their diagnostic and More >

Sarra B. Shakartalla^1,2,3, Iman M. Talaat^1,2,4,*, Nival Ali¹, Shahenaz S. Salih^1,5, Zainab M. Al Shareef^1,2, Noura Alkhayyal⁶, Riyad Bendardaf^2,7,*, Sameh S. M. Soliman^1,8,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070808 - 30 December 2025

Abstract Objectives: Breast cancer (BC) is the leading cause of cancer-related mortality in women, largely due to metastasis. This study aims to explore the role of purine nucleoside phosphorylase (PNP), a key enzyme in purine metabolism, in the aggressiveness and metastatic behavior of BC. Methods: A comprehensive analysis was performed using in silico transcriptomic data (n = 2509 patients), immunohistochemical profiling of BC tissues (n = 103), and validation through western blotting in multiple BC cell lines. Gene expression and survival analyses were conducted using Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and… More >

Rabindranath Bera^1,#, Yotaro Ochi^2,3, Ying-Jung Huang¹, Ming-Chung Kuo^1,4, Kenichi Yoshida⁵, Seishi Ogawa², Lee-Yung Shih^1,4,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070259 - 30 December 2025

Abstract Background: Breakpoint Cluster Region-Abelson (BCR::ABL1) fusion protein is essential in the pathogenesis of chronic myeloid leukemia (CML); however, the chronic-to-blast phase transformation remains elusive. We identified novel kinesin light chain 2 (KLC2) mutations in CML-myeloid blast phase patients. We aimed to examine the functional role of KLC2 mutations in leukemogenesis. Methods: To evaluate the biological role of KLC2 mutants (MT) in CML cells, we expressed KLC2-MT in different human CML cell lines harboring BCR::ABL1 and performed immunoblot, immunofluorescence, cell proliferation, differentiation, and apoptosis; Tyrosine kinase inhibitor (TKI)-drug activities; and clonogenic assays for in vitro functional analyses. We co-expressed KLC2-MT… More >

Yimin Liu^1,#, Bin Liu^2,3,4,#, Huabin Gao¹, Jinlong Wang⁵, Jingya Duan¹, Xiaolan Huang¹, Yuexi Liu¹, Ying Huang¹, Wenjing Liao¹, Ruonan Li^1,*, Hua Linghu^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069007 - 30 December 2025

Abstract Objectives: High-grade serous ovarian cancer (HGSOC), the most common subtype of epithelial ovarian cancer (EOC), exhibits a mesenchymal phenotype characterized by fibrotic stroma and poor prognosis. Human epididymis protein 4 (HE4), a key diagnostic biomarker for ovarian cancer, is involved in fibrotic processes in several non-malignant diseases. Given the clinical significance of stromal fibrosis in HGSOC and the potential link between HE4 and fibrosis, this study aimed to investigate the role of HE4 in the formation of stromal fibrosis in HGSOC. Methods: A total of 126 patients with gynecological conditions were included and divided into… More > Graphic Abstract

Chenxi Xiu^1,2,*, Xihua Chu², Ao Mei¹, Liangfei Gong¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-39, 2026, DOI:10.32604/cmc.2025.073193 - 09 December 2025

Abstract Granular materials exhibit complex macroscopic mechanical behaviors closely related to their micro-scale microstructural features. Traditional macroscopic phenomenological elasto-plastic models, however, usually have complex formulations and lack explicit relations to these microstructural features. To avoid these limitations, this study proposes a micromechanics-based softening hyperelastic model for granular materials, integrating softening hyperelasticity with microstructural insights to capture strain softening, critical state, and strain localization behaviors. The model has two key advantages: (1) a clear conceptualization, straightforward formulation, and ease of numerical implementation (via Abaqus UMAT subroutine in this study); (2) explicit incorporation of micro-scale features (e.g., contact… More >

Chia-Hui Liu^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-18, 2026, DOI:10.32604/cmc.2025.072887 - 09 December 2025

Abstract The Industrial Internet of Things (IIoT) has emerged as a cornerstone of Industry 4.0, enabling large-scale automation and data-driven decision-making across factories, supply chains, and critical infrastructures. However, the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping, data tampering, and device impersonation. While digital signatures are indispensable for ensuring authenticity and non-repudiation, conventional schemes such as RSA and ECC are vulnerable to quantum algorithms, jeopardizing long-term trust in IIoT deployments. This study proposes a lightweight, stateless, hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT. The… More >

Mingming Huang¹, Yunfan Ye^1,*, Zhiping Cai²

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.072399 - 09 December 2025

Abstract As a fundamental component in computer vision, edges can be categorized into four types based on discontinuities in reflectance, illumination, surface normal, or depth. While deep CNNs have significantly advanced generic edge detection, real-time multi-class semantic edge detection under resource constraints remains challenging. To address this, we propose a lightweight framework based on PiDiNet that enables fine-grained semantic edge detection. Our model simultaneously predicts background and four edge categories from full-resolution inputs, balancing accuracy and efficiency. Key contributions include: a multi-channel output structure expanding binary edge prediction to five classes, supported by a deep supervision More >

Zhonghao Wang^1,2, Xin Liu^1,2,*, Changhua Yue³, Haiwen Yuan⁴

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.071813 - 09 December 2025

Abstract To address critical challenges in nighttime ship detection—high small-target missed detection (over 20%), insufficient lightweighting, and limited generalization due to scarce, low-quality datasets—this study proposes a systematic solution. First, a high-quality Night-Ships dataset is constructed via CycleGAN-based day-night transfer, combined with a dual-threshold cleaning strategy (Laplacian variance sharpness filtering and brightness-color deviation screening). Second, a Cross-stage Lightweight Fusion-You Only Look Once version 8 (CLF-YOLOv8) is proposed with key improvements: the Neck network is reconstructed by replacing Cross Stage Partial (CSP) structure with the Cross Stage Partial Multi-Scale Convolutional Block (CSP-MSCB) and integrating Bidirectional Feature Pyramid More >

Shaobo Kang, Mingzhi Yang^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.071488 - 09 December 2025

Abstract Fabric defect detection plays a vital role in ensuring textile quality. However, traditional manual inspection methods are often inefficient and inaccurate. To overcome these limitations, we propose FD-YOLO, an enhanced lightweight detection model based on the YOLOv11n framework. The proposed model introduces the Bi-level Routing Attention (BRAttention) mechanism to enhance defect feature extraction, enabling more detailed feature representation. It proposes Deep Progressive Cross-Scale Fusion Neck (DPCSFNeck) to better capture small-scale defects and incorporates a Multi-Scale Dilated Residual (MSDR) module to strengthen multi-scale feature representation. Furthermore, a Shared Detail-Enhanced Lightweight Head (SDELHead) is employed to reduce More >