Lv Ling^1,#, Minying Lu^2,#, Ling Ye³, Yuanhang Chen², Sheng Lin², Jun Yang², Yu Rong^2,*, Guixiong Wu^4,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069889 - 30 December 2025

Abstract Background: A significant proportion of patients still cannot benefit from existing targeted therapies and immunotherapies, making the search for new treatment strategies extremely urgent. In this study, we combined integrate public data analysis with experimental validation to identify novel prognostic biomarkers and therapeutic targets for lung adenocarcinoma (LUAD). Methods: We analyzed RNA and protein databases to assess the expression levels of cytochrome C oxidase 5B (COX5B) in LUAD. Several computational algorithms were employed to investigate the relationship between COX5B and immune infiltration in LUAD. To further elucidate the role of COX5B in LUAD, we utilized… More > Graphic Abstract

Kun Deng^1,2,3, Jianliang Huang^1,2,3, Danyang Li^2,3, Wei Gao^2,3, Minghua Wu^2,3,4,*, Mingsheng Lei^1,5,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069442 - 30 December 2025

Abstract Background: Glioblastoma (GBM) prognosis has seen little improvement over the past two decades. While immunotherapy has revolutionized cancer treatment, its impact on GBM remains limited. To characterize the evolving research landscape and identify future directions in GBM immunotherapy, we conducted a comprehensive bibliometric review. Methods: All literature related to immunotherapy in GBM from 1999 to 2024 was collected from the Web of Science Core Collection. CtieSpace and VOSviewer were used to conduct bibliometric analysis and visualize the data. Results: Bibliometric analysis identified 5038 publications authored by 23,335 researchers from 4699 institutions across 96 countries/regions, published in… More >

Xu Guo¹, Yanan Yu², Xiaolin Ma³, Yuanjie Cai^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069274 - 30 December 2025

Abstract Background: Long non-coding RNAs (lncRNAs) act as epigenetic regulators for tumor hallmarks. This investigation sought to probe the carcinogenic trait of PAN3-AS1 across pan-cancer comprehensively. Methods: We studied the diagnostic and prognostic features and the immune landscape of PAN3-AS1 across pan-cancer by bioinformatics approaches. The hierarchical regulatory networks governing PAN3-AS1 expression in colon cancer were explored via chromatin immunoprecipitation, luciferase activity assays, and RNA immunoprecipitation, etc. We screened drugs sensitive to WAP four-disulfide core domain 13 (WFDC13) by virtual screening and molecular docking. Results: Single-cell transcriptomics demonstrated that a variety of immune populations abnormally expressed PAN3-AS1… More >

Xiaopan Zou^1,2, Meiyang Sun³, Xin Jiang¹, Jingze Yu², Xiaomeng Li^4,*, Bingyu Nie^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.066662 - 30 December 2025

Abstract Objective: Triple-negative breast cancer (TNBC) is highly aggressive and lacks an effective targeted therapy. This study aimed to elucidate the functions and possible mechanisms of action of zinc finger miz-type containing 2 (ZMIZ2) and minichromosome maintenance complex component 3 (MCM3) in TNBC progression. Methods: The relationship between ZMIZ2 expression and clinical characteristics of TNBC was investigated. In vitro and in vivo experiments were performed to investigate the role of ZMIZ2 dysregulation in TNBC cell malignant behaviors. The regulatory relationship between ZMIZ2 and MCM3 was also explored. Transcriptome sequencing was performed to elucidate possible mechanisms underlying the ZMIZ2/MCM3… More >

Marija Macenić, Tomislav Kurevija^*, Tin Herbst

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.067067 - 27 December 2025

Abstract The increased interest in geothermal energy is evident, along with the exploitation of traditional hydrothermal systems, in the growing research and projects developing around the reuse of already-drilled oil, gas, and exploration wells. The Republic of Croatia has around 4000 wells, however, due to a long period since most of these wells were drilled and completed, there is uncertainty about how many are available for retrofitting as deep-borehole heat exchangers. Nevertheless, as hydrocarbon production decreases, it is expected that the number of wells available for the revitalization and exploitation of geothermal energy will increase. The… 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 >

Zilin Zhang¹, Yan Liu^1,*, Jia Liu², Senbao Hou³, Yuping Zhang¹, Chenyuan Wang¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-14, 2026, DOI:10.32604/cmc.2025.072286 - 09 December 2025

Abstract With the growing demand for more comprehensive and nuanced sentiment understanding, Multimodal Sentiment Analysis (MSA) has gained significant traction in recent years and continues to attract widespread attention in the academic community. Despite notable advances, existing approaches still face critical challenges in both information modeling and modality fusion. On one hand, many current methods rely heavily on encoders to extract global features from each modality, which limits their ability to capture latent fine-grained emotional cues within modalities. On the other hand, prevailing fusion strategies often lack mechanisms to model semantic discrepancies across modalities and to… More >

Guangyu Huo, Chang Su, Xiaoyu Zhang^*, Xiaohui Cui, Lizhong Zhang

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.072147 - 09 December 2025

Abstract Long-term traffic flow prediction is a crucial component of intelligent transportation systems within intelligent networks, requiring predictive models that balance accuracy with low-latency and lightweight computation to optimize traffic management and enhance urban mobility and sustainability. However, traditional predictive models struggle to capture long-term temporal dependencies and are computationally intensive, limiting their practicality in real-time. Moreover, many approaches overlook the periodic characteristics inherent in traffic data, further impacting performance. To address these challenges, we introduce ST-MambaGCN, a State-Space-Based Spatio-Temporal Graph Convolution Network. Unlike conventional models, ST-MambaGCN replaces the temporal attention layer with Mamba, a state-space More >

Shih-Lin Lin^*, Cheng-Wei Li

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071915 - 09 December 2025

Abstract This study focuses on developing a deep learning model capable of recognizing vehicle brands and models, integrated with a law enforcement intelligence platform to overcome the limitations of existing license plate recognition techniques—particularly in handling counterfeit, obscured, or absent plates. The research first entailed collecting, annotating, and classifying images of various vehicle models, leveraging image processing and feature extraction methodologies to train the model on Microsoft Custom Vision. Experimental results indicate that, for most brands and models, the system achieves stable and relatively high performance in Precision, Recall, and Average Precision (AP). Furthermore, simulated tests… More >

Jia Yan Lim^1,2, Siti Madiha Muhammad Amir³, Roslan Yahya³, Marta Peña Fernández², Tze Chuen Yap^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070707 - 09 December 2025

Abstract Additive Manufacturing, also known as 3D printing, has transformed conventional manufacturing by building objects layer by layer, with material extrusion or fused deposition modeling standing out as particularly popular. However, due to its manufacturing process and thermal nature, internal voids and pores are formed within the thermoplastic materials being fabricated, potentially leading to a decrease in mechanical properties. This paper discussed the effect of printing parameters on the porosity and the mechanical properties of the 3D printed polylactic acid (PLA) through micro-computed tomography (microCT), computational image analysis, and Charpy impact testing. The results for both… More >