Marwa M. Eid^1,2,*, Amel Ali Alhussan³, Ebrahim A. Mattar⁴, Nima Khodadadi^5,*, El-Sayed M. El-Kenawy^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073555 - 29 January 2026

Abstract Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs, improving material utilization, and ensuring structural safety in modern construction. Traditional empirical methods often fail to capture the non-linear relationships among concrete constituents, especially with the growing use of supplementary cementitious materials and recycled aggregates. This study presents an integrated machine learning framework for concrete strength prediction, combining advanced regression models—namely CatBoost—with metaheuristic optimization algorithms, with a particular focus on the Somersaulting Spider Optimizer (SSO). A comprehensive dataset encompassing diverse mix proportions and material types was used to evaluate baseline machine learning models,… More >

Min Hee Kim¹, Boyoon Huh¹, Joo-Won Park^1,*, Woo-Jae Park^2,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.071523 - 19 January 2026

Abstract Breast cancer is one of the most prevalent malignancies among women and comprises a heterogeneous spectrum of molecular subtypes with distinct biological behaviors. Among various regulatory molecules, sphingolipids play pivotal roles in dynamically modulating fundamental cellular processes such as proliferation, apoptosis, and metastasis through metabolic interconversions, including phosphorylation, glycosylation, and the generation of sphingosine-1-phosphate. This review aims to elucidate the mechanisms through which sphingolipid metabolism orchestrates cancer cell fate and drives breast cancer progression. Particular emphasis is placed on the balance between proapoptotic ceramides and pro-survival metabolites, such as sphingosine-1-phosphate, which collectively influence tumor growth More >

Harpreet Kaur^1,*, Dhrubalochan Rana², Sowvik Bag², Paramjeet Singh³

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.071209 - 19 January 2026

Abstract The prolonged and intricate history of oncological treatments has transitioned significantly since the introduction of chemotherapy. Substantial therapeutic benefits in cancer therapy have been achieved by the integration of conventional treatments with molecular biosciences and omics technologies. Human epidermal growth factor receptor, hormone receptors, and angiogenesis factors are among the established therapies in tumor reduction and managing side effects. Novel targeted therapies like KRAS G12C, Claudin-18 isoform 2 (CLDN18.2), Trophoblast cell-surface antigen 2 (TROP2), and epigenetic regulators emphasize their promise in advancing precision medicine. However, in many cases, the resistance mechanisms associated with these interventions… More > Graphic Abstract

José Arturo Ramírez-Fernández¹, Henevith G. Méndez-Figueroa¹, Sebastián Ossandón^2,*, Ricardo Galván-Martínez³, Miguel Ángel Hernández-Pérez³, Ricardo Orozco-Cruz³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072707 - 12 January 2026

Abstract In this study, artificial neural networks (ANNs) were implemented to determine design parameters for an impressed current cathodic protection (ICCP) prototype. An ASTM A36 steel plate was tested in 3.5% NaCl solution, seawater, and NS4 using electrochemical impedance spectroscopy (EIS) to monitor the evolution of the substrate surface, which affects the current required to reach the protection potential (Eprot). Experimental data were collected as training datasets and analyzed using statistical methods, including box plots and correlation matrices. Subsequently, ANNs were applied to predict the current demand at different exposure times, enabling the estimation of electrochemical More >

Sarah M. Alhammad¹, Diaa Salama AbdElminaam^2,3,*, Asmaa Rizk Ibrahim⁴, Ahmed Taha²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.069263 - 12 January 2026

Abstract Accurate parameter extraction of photovoltaic (PV) models plays a critical role in enabling precise performance prediction, optimal system sizing, and effective operational control under diverse environmental conditions. While a wide range of metaheuristic optimisation techniques have been applied to this problem, many existing methods are hindered by slow convergence rates, susceptibility to premature stagnation, and reduced accuracy when applied to complex multi-diode PV configurations. These limitations can lead to suboptimal modelling, reducing the efficiency of PV system design and operation. In this work, we propose an enhanced hybrid optimisation approach, the modified Spider Wasp Optimization… More >

Keiko Yanagihara^1,*, Masato Yoshida², Kensaku Awaji², Tamami Yamakawa¹, Sena Kato¹, Miki Tamura¹, Koji Nagata³

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.073891 - 30 December 2025

Abstract Background: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have transformed the management of hormone receptor–positive/HER2–negative (HR+/HER2–) advanced breast cancer, yet evidence for elderly or poor-performance patients remains limited. This study examined real-world outcomes of palbociclib plus endocrine therapy in Asian patients, with additional subgroup analyses by age and performance status. Methods: We retrospectively analyzed 46 consecutive Asian patients with recurrent or de novo HR+/HER2− breast cancer treated with first-line palbociclib plus ET between April 2021 and March 2025. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), disease control rate (DCR), and safety.… 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

Ashok Kumar Sah^1,*, Ranjay Kumar Choudhary^1,2, Velilyaeva Alie Sabrievna³, Karomatov Inomdzhon Dzhuraevich⁴, Anass M. Abbas⁵, Manar G. Shalabi⁵, Nadeem Ahmad Siddique⁶, Raji Rubayyi Alshammari⁷, Navjyot Trivedi⁸, Rabab H. Elshaikh¹

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.068238 - 30 December 2025

Abstract Male breast cancer (MBC) is rare, representing 0.5%–1% of all breast cancers, but its incidence is increasing due to improved diagnostics and awareness. MBC typically presents in older men, is human epidermal growth factor receptor 2 (HER2)-negative and estrogen receptor (ER)-positive, and lacks routine screening, leading to delayed diagnosis and advanced disease. Major risk factors include hormonal imbalance, radiation exposure, obesity, alcohol use, and Breast Cancer Gene 1 and 2 (BRCA1/2) mutations. Clinically, it may resemble gynecomastia but usually appears as a unilateral, painless mass or nipple discharge. Advances in imaging and liquid biopsy have 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 >

Yuri A. Piven¹, Danila V. Sorokin², Nastassia A. Varabyeva¹, Alexandra L. Mikhaylova², Fedor B. Bogdanov², Elena V. Shafranovskaya¹, Raman M. Puzanau³, Fedor A. Lakhvich¹, Alexander M. Scherbakov^2,4,*

Oncology Research, Vol.33, No.12, pp. 4049-4072, 2025, DOI:10.32604/or.2025.067832 - 27 November 2025

Abstract Background: The most aggressive forms of breast cancer are characterized by independence from steroid hormones but a strong dependence on growth factors. In such cancer cells, oncogenic receptors, including human epidermal growth factor receptor 2 (HER2), are activated, and their targeted inhibition represents an attractive therapeutic strategy. The study aimed to develop small-molecule potential dual heat shock protein 90 (HSP90)-HER2 inhibitors and evaluate them as anticancer agents in HER2-positive cells. Methods: The research project involved obtaining a series of compounds with potential dual inhibitory activity against HSP90 and HER2 by targeted organic synthesis, which was… More > Graphic Abstract