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 >

Kai Gui^1,#, Tianyi Yang^1,#, Chengying Xiong¹, Yue Wang¹, Zhiqiang He¹, Wuxian Li^2,3,*, Min Tang^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070143 - 30 December 2025

Abstract Objectives: The mechanism by which specific tumor subsets in colorectal cancer (CRC) use alternative metabolic pathways, particularly those modulated by hypoxia and fructose, to alter the tumor microenvironment (TME) remains unclear. This study aimed to identify these malignant subpopulations and characterize their intercellular signaling networks and spatial organization through an integrative multi-omics approach. Methods: Leveraging bulk datasets, single-cell RNA sequencing, and integrative spatial transcriptomics, we developed a prognostic model based on hypoxia-and fructose metabolism-related genes (HFGs) to delineate tumor cell subpopulations and their intercellular signaling networks. Results: We identified a specific subset of stanniocalcin-2 positive (STC2+)… More > Graphic Abstract

Jing Cai^1,#, Haoyun Zhu^1,#, Weiling Guo¹, Ting Huang¹, Pangzhou Chen^1,2, Wen Zhou¹, Ziyun Guan^1,3,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069902 - 30 December 2025

Abstract Background: Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity. Current preclinical models, however, are inadequate for predicting individual patient responses towards different drugs. This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations. Methods: Tumor and adjacent tissues from female breast cancer patients were collected during surgery. Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models. The obtained patient-derived conditional reprogramming breast cancer (CRBC) cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres… 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

Mohammed Benamara^1,2, Boumediene Touati³, Said Bennaceur⁴, Bendjillali Ridha Ilyas^5,*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.072641 - 27 December 2025

Abstract This study explores the thin-layer convective solar drying of Marrubium vulgare L. leaves under conditions typical of sun-rich semi-arid climates. Drying experiments were conducted at three inlet-air temperatures (40°C, 50°C, 60°C) and two air velocities (1.5 and 2.5 m·s⁻¹) using an indirect solar dryer with auxiliary temperature control. Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient (r), root-mean-square error (RMSE), and Akaike information criterion (AIC). A complementary heat-transfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance, and an… More > Graphic Abstract

Xiaozhe Guo¹, Suyan Long², Ziyu Yue², Yifan Wang², Guanting Yin¹, Yuyang Wang¹, Zhaoyuan Wu^1,*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069820 - 27 December 2025

Abstract The increasing complexity of China’s electricity market creates substantial challenges for settlement automation, data consistency, and operational scalability. Existing provincial settlement systems are fragmented, lack a unified data structure, and depend heavily on manual intervention to process high-frequency and retroactive transactions. To address these limitations, a graph-based unified settlement framework is proposed to enhance automation, flexibility, and adaptability in electricity market settlements. A flexible attribute-graph model is employed to represent heterogeneous multi-market data, enabling standardized integration, rapid querying, and seamless adaptation to evolving business requirements. An extensible operator library is designed to support configurable settlement… More >

Binjiang Hu^1,*, Yihua Zhu², Liang Tu^1,2, Zun Ma³, Xian Meng³, Kewei Xu³

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069777 - 27 December 2025

Abstract This paper proposes an equivalent modeling method for photovoltaic (PV) power stations via a particle swarm optimization (PSO) K-means clustering (KMC) algorithm with passive filter parameter clustering to address the complexities, simulation time cost and convergence problems of detailed PV power station models. First, the amplitude–frequency curves of different filter parameters are analyzed. Based on the results, a grouping parameter set for characterizing the external filter characteristics is established. These parameters are further defined as clustering parameters. A single PV inverter model is then established as a prerequisite foundation. The proposed equivalent method combines the… More >

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 >

Bindi Saurabh Thakkar¹, Pradeep Kumar Karsh^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-22, 2026, DOI:10.32604/cmc.2025.072839 - 09 December 2025

Abstract This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies. Hybrid composites, widely used in aerospace, automotive, and structural applications, often face variability in material properties, geometric configurations, and manufacturing processes, leading to uncertainty in their dynamic response. To address this, three surrogate-based machine learning approaches like radial basis function (RBF), multivariate adaptive regression splines (MARS), and polynomial neural networks (PNN) are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates. The research focuses on predicting the first three natural frequencies… More >

Tahira Khalil¹, Sadeeq Jan^2,*, Rania M. Ghoniem³, Muhammad Imran Khan Khalil¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.072655 - 09 December 2025

Abstract The contemporary era is characterized by rapid technological advancements, particularly in the fields of communication and multimedia. Digital media has significantly influenced the daily lives of individuals of all ages. One of the emerging domains in digital media is the creation of cartoons and animated videos. The accessibility of the internet has led to a surge in the consumption of cartoons among young children, presenting challenges in monitoring and controlling the content they view. The prevalence of cartoon videos containing potentially violent scenes has raised concerns regarding their impact, especially on young and impressionable minds.… More >