Ke Liu^1,2,3,#, Xia Xue^1,2,3,#, Haiming Qin^4,5,#, Jiaying Zhu^6,#, Meng Jin^1,6, Die Dai⁶, Youcai Tang¹, Ihtisham Bukhari¹, Hangfan Liu¹, Chunjing Qiu¹, Feifei Ren¹, Pengyuan Zheng^1,2,3, Yang Mi^1,2,3,*, Weihua Chen^6,7,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.072661 - 19 January 2026

Abstract Background: The gut microbiome has emerged as a critical modulator of cancer immunotherapy response. However, the mechanisms by which gut-associated metabolites influence checkpoint blockade efficacy in prostate cancer (PC) remain not fully explored. The study aimed to explore how gut metabolites regulate death-ligand 1 (PD-L1) blockade via exosomes and boost immune checkpoint inhibitors (ICIs) in PC. Methods: We recruited 70 PC patients to set up into five subgroups. The integrated multi-omics analysis was performed. In parallel, we validated the function of gut microbiome-associated metabolites on PD-L1 production and immunotherapy treatment efficacy in PC cell lines… More >

Shail Rakesh Modi, Terrick Andey^*, George Acquaah-Mensah^*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070793 - 19 January 2026

Abstract Objectives: The current treatment options and therapeutic targets for triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer (BrCA), are limited. This study aimed to identify novel biomarkers and transcriptional regulatory networks (TRN) inherent in TNBC samples. Methods: We analyzed pan-cancer BrCA datasets from The Cancer Genome Atlas (TCGA) to compare triple-positive breast cancer (TPBC) with TNBC. TRN algorithms and virtual inference of protein-enriched regulon (VIPER) were used to identify master regulators and their target genes. Utilizing TNBC cells (MDA-MB-231 and MDA-MB-468), we validated the relationship of nuclear factor erythroid 2-like 3 (NFE2L3) and… More > Graphic Abstract

Rebecca H. Maggs^*, Marcus J. Brookes, Kenneth S. Rankin

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.069781 - 19 January 2026

Abstract Background: Photodynamic therapy (PDT) may eradicate residual malignant cells following sarcoma resection, through reactive oxygen species (ROS) mediated cytotoxicity, thus improve clinical outcomes. This study aims to assess the efficacy of 5-aminolevulinic acid (5-ALA) as a photosensitizer in combination with red light (RL) for PDT of bone sarcoma cells in vitro. Methods: Three bone sarcoma cell lines underwent treatment with 5-ALA and RL or sham-RL (SL). 5-ALA uptake was assessed using flow cytometry. Production of ROS was measured using CellROX Green staining and fluorescence microscopy. Cell viability was assessed using Cell Counting Kit-8 assays. Results: All cell… More >

Bu Zou^1,#, Yi-En Xu^2,#, Hui-Chan He³, Zu-Lu Ye², Da-Lei Zhou², Cai-Yun He^2,*, Chan Huang^4,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.069453 - 19 January 2026

Abstract Objectives: Gastric cancer (GC) remains a major global health concern, and Phosphoinositide-3-Kinase Regulatory Subunit 1 (PIK3R1), a regulatory subunit of the PI3K signaling pathway, may play a critical yet underexplored role in GC progression. This study aimed to investigate the prognostic significance of PIK3R1 in GC and its association with the tumor immune microenvironment. Methods: PIK3R1 expression and its clinical relevance were analyzed using datasets from GC patients who underwent gastrectomy, including cohorts from The Cancer Genome Atlas (TCGA) and the Sun Yat-sen University Cancer Center (SYSUCC). Prognostic models integrating PIK3R1 expression with clinical parameters… More >

Safwan Al-sayed¹, Xi Wang¹, Yijiang Peng^1,*, Esraa Hyarat², Ahmad Ali AlZubi³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.074068 - 12 January 2026

Abstract In modern construction, Lightweight Aggregate Concrete (LWAC) has been recognized as a vital material of concern because of its unique properties, such as reduced density and improved thermal insulation. Despite the extensive knowledge regarding its macroscopic properties, there is a wide knowledge gap in understanding the influence of microscale parameters like aggregate porosity and volume ratio on the mechanical response of LWAC. This study aims to bridge this knowledge gap, spurred by the need to enhance the predictability and applicability of LWAC in various construction environments. With the help of advanced numerical methods, including the… More >

Changjun Zhou¹, Dongfang Chen¹, Chenyang Shi¹, Taiyong Li^2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073662 - 12 January 2026

Abstract With the rapid development of smart manufacturing, intelligent safety monitoring in industrial workshops has become increasingly important. To address the challenges of complex backgrounds, target scale variation, and excessive model parameters in worker violation detection, this study proposes ADCP-YOLO, an enhanced lightweight model based on YOLOv8. Here, “ADCP” represents four key improvements: Alterable Kernel Convolution (AKConv), Dilated-Wise Residual (DWR) module, Channel Reconstruction Global Attention Mechanism (CRGAM), and Powerful-IoU loss. These components collaboratively enhance feature extraction, multi-scale perception, and localization accuracy while effectively reducing model complexity and computational cost. Experimental results show that ADCP-YOLO achieves a More >

Xinli Hao¹, Qingyuan Gong², Yang Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073155 - 12 January 2026

Abstract Topological information is very important for understanding different types of online web services, in particular, for online social networks (OSNs). People leverage such information for various applications, such as social relationship modeling, community detection, user profiling, and user behavior prediction. However, the leak of such information will also pose severe challenges for user privacy preserving due to its usefulness in characterizing users. Large-scale web crawling-based information probing is a representative way for obtaining topological information of online web services. In this paper, we explore how to defend against topological information probing for online web services,… More >

Tao Zhang^1,*, Hailun Wang¹, Tianyue Wang¹, Tian Tian²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072696 - 12 January 2026

Abstract The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation, mechanical wear, and airflow disturbances during prolonged operation. These conditions can lead to a series of issues, including mechanical faults, air path malfunctions, and combustion irregularities. Traditional model-based approaches face inherent limitations due to their inability to handle nonlinear problems, natural factors, measurement uncertainties, fault coupling, and implementation challenges. The development of artificial intelligence algorithms has provided an effective solution to these issues, sparking extensive research into data-driven fault diagnosis methodologies. The review mechanism involved searching IEEE Xplore, ScienceDirect,… More >

Afnan Alhindi^*, Saad Al-Ahmadi, Mohamed Maher Ben Ismail

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072625 - 12 January 2026

Abstract Split Learning (SL) has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency. Specifically, neural networks are divided into client and server sub-networks in order to mitigate the exposure of sensitive data and reduce the overhead on client devices, thereby making SL particularly suitable for resource-constrained devices. Although SL prevents the direct transmission of raw data, it does not alleviate entirely the risk of privacy breaches. In fact, the data intermediately transmitted to the server sub-model may include patterns or information that could reveal sensitive data. Moreover,… More >

Md Minhazul Islam^1,2, Yunfei Yin^1,2,*, Md Tanvir Islam^1,2, Zheng Yuan^1,2, Argho Dey^1,2

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072550 - 12 January 2026

Abstract Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes, where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions. To address these issues, we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder, guided multimodal fusion, and deep supervision. The framework is built upon the synergistic combination of cross-attention, gated fusion, and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation, enabling efficient… More >