Dongchi Cai^1,2,#, Jialin Ji^3,#, Chunhui Yang^1,*, Hong Cai^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.071152 - 30 December 2025

Abstract Metabolic reprogramming involving branched-chain amino acids (BCAAs)—leucine, isoleucine, and valine—is increasingly recognized as pivotal in cancer progression, metastasis, and immune modulation. This review comprehensively explores how cancer cells rewire BCAA metabolism to enhance proliferation, survival, and therapy resistance. Tumors manipulate BCAA uptake and catabolism via high expression of transporters like L-type amino acid transporter 1 (LAT1) and enzymes including branched chain amino acid transaminase 1(BCAT1), branched chain amino acid transaminase 2 (BCAT2), branched-chain alpha-keto acid dehydrogenase (BCKDH), and branched chain alpha-keto acid dehydrogenase kinase (BCKDK). These alterations sustain energy production, biosynthesis, redox homeostasis, and oncogenic… More >

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 >

Lei Wang^1,2, Menghan Wei², Ziwei Huangfu³, Shunjie Zhu², Xuejian Ge^1,*, Zhengquan Li⁴

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-32, 2026, DOI:10.32604/cmc.2025.071295 - 09 December 2025

Abstract Iterative Learning Control (ILC) provides an effective framework for optimizing repetitive tasks, making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transportation systems (ITS). This paper presents a systematic review of ILC’s developmental progress, current methodologies, and practical implementations across these two critical domains. The review first analyzes the key technical challenges encountered when integrating ILC into precision manufacturing workflows. Through case studies, it evaluates demonstrated improvements in positioning accuracy, surface finish quality, and production throughput. Furthermore, the study examines ILC’s applications in ITS, with particular focus on vehicular motion control More >

Wen-Tsai Sung¹, Indra Griha Tofik Isa^2,3, Sung-Jung Hsiao^4,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-31, 2026, DOI:10.32604/cmc.2025.070922 - 09 December 2025

Abstract Mango is a plant with high economic value in the agricultural industry; thus, it is necessary to maximize the productivity performance of the mango plant, which can be done by implementing artificial intelligence. In this study, a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential, so that it becomes an early detection warning system that has an impact on increasing agricultural productivity. The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules, namely the C2S module. The C2S module consists of three sub-modules such as the… More >

Ali S. Alzaharani, Abid Iqbal^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-27, 2026, DOI:10.32604/cmc.2025.070410 - 10 November 2025

Abstract In this study, an automated multimodal system for detecting, classifying, and dating fruit was developed using a two-stage YOLOv11 pipeline. In the first stage, the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them. These bounding boxes are subsequently passed to a YOLOv11 classification model, which analyzes cropped images and assigns class labels. An additional counting module automatically tallies the detected fruits, offering a near-instantaneous estimation of quantity. The experimental results suggest high precision and recall for detection, high classification accuracy (across 15 classes), and near-perfect counting in More >

Asal Jameel Khudhair^#, Amenah Dahim Abbood^#,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.068553 - 10 November 2025

Abstract Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities. Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can. Therefore, we utilized two objective functions… More >

Ravita Chahar, Ashutosh Kumar Dubey^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-65, 2026, DOI:10.32604/cmc.2025.066990 - 10 November 2025

Abstract Objective: The increasing global prevalence of mental health disorders highlights the urgent need for the development of innovative diagnostic methods. Conditions such as anxiety, depression, stress, bipolar disorder (BD), and autism spectrum disorder (ASD) frequently arise from the complex interplay of demographic, biological, and socioeconomic factors, resulting in aggravated symptoms. This review investigates machine intelligence approaches for the early detection and prediction of mental health conditions. Methods: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework was employed to conduct a systematic review and analysis covering the period 2018 to 2025. The potential… More >

Jun He¹, Jianli Luo¹, Yanling Wang^1,*, Dai Zhou^1,*, Shuanglin Xiang^2,*

Congenital Heart Disease, Vol.20, No.5, pp. 613-623, 2025, DOI:10.32604/chd.2025.071773 - 30 November 2025

Abstract Pediatric congenital heart disease (CHD) pharmacotherapy faces three fundamental barriers: developmental pharmacokinetic complexity, anatomic-genetic heterogeneity, and evidence chain gaps. Traditional agents exhibit critical limitations: digoxin’s narrow therapeutic index (0.5–0.9 ng/mL) is exacerbated by ABCB1 mutations (toxicity risk increases 4.1-fold), furosemide efficacy declines by 35% in neonates due to NKCC2 immaturity, and β-blocker responses vary by CYP2D6 polymorphisms (poor metabolizers require 50–75% dose reduction). Novel strategies demonstrate transformative potential—CRISPR editing achieves 81% reversal of BMPR2-associated pulmonary vascular remodeling, metabolically matured cardiac organoids replicate adult myocardial energy metabolism for drug screening, and SGLT2 inhibitors activate triple mechanisms (calcium overload More >

Boxuan Han^1,2,#, Shaokun Liu^3,#, Ridhima Das³, Shiqian Liu⁴, Yang Zhang^1,2,*

Oncology Research, Vol.33, No.12, pp. 3633-3656, 2025, DOI:10.32604/or.2025.071296 - 27 November 2025

Abstract Organoid technology, characterized by high fidelity in mimicking the in vivo microenvironment, preservation of tumor heterogeneity, and capacity for high-throughput operations, has emerged as a critical tool in head and neck cancer research. To address clinical challenges in head and neck cancer management—including marked tumor heterogeneity, therapeutic resistance, and significant prognostic variability—this review focuses on four key translational applications of organoid technology: In mechanistic studies, organoid models provide a reliable platform for investigating tumorigenesis, progression, and drug resistance mechanisms. In personalized therapy, organoid-based drug sensitivity testing enables data-driven clinical decision-making. For biomarker discovery, organoids facilitate the More >

Mukesh Kumar Verma^1,2,*, Manohar Yadav¹

Revue Internationale de Géomatique, Vol.34, pp. 855-879, 2025, DOI:10.32604/rig.2025.069914 - 17 November 2025

Abstract Precision Agriculture (PA) is revolutionizing modern farming by leveraging remote sensing (RS) technologies for continuous, non-destructive crop monitoring. This review comprehensively explores RS systems categorized by platform—terrestrial, airborne, and space-borne—and evaluates the role of multi-sensor fusion in addressing the spatial and temporal complexity of agricultural environments. Emphasis is placed on data from LiDAR, GNSS, cameras, and radar, alongside derived metrics such as plant height, projected leaf area, and biomass. The study also highlights the significance of data processing methods, particularly machine learning (ML) and deep learning (DL), in extracting actionable insights from large datasets. By More >