MING YANG^1,#, LIANGZHAO CHU^1,#, SHUKAI LIN², HAN PENG¹, NIYA LONG¹, KAYA XU¹, HUA YANG¹, FENG HAN^1,*, JIAN LIU^1,*

Oncology Research, Vol.33, No.5, pp. 1189-1198, 2025, DOI:10.32604/or.2024.055102 - 18 April 2025

Abstract Background: Glioblastoma (GBM) is one of the most malignant types of central nervous system tumors. Oxygen deprivation in the tumor microenvironment is thought to be an important factor in promoting GBM progression. However, the mechanisms of hypoxia-promoted tumor progression remain elusive. Methods: Alternative splicing of diacylglycerol kinase gamma (DGKG)-Δ exon13 was amplified and verified by PCR-Sanger sequencing. The functions of DGKG and DGKG-Δ exon13 were analyzed by Cell counting kit-8 (CCK-8), Transwell, Matrigel-transwell experiments, and in vivo orthotropic GBM animal models. Transcriptome analyses were done to find out the regulated genes. Results: In this study, we found… More > Graphic Abstract

Sony Peng¹, Sophort Siet¹, Ilkhomjon Sadriddinov¹, Dae-Young Kim^2,*, Kyuwon Park^3,*, Doo-Soon Park²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2041-2057, 2025, DOI:10.32604/cmc.2025.061166 - 16 April 2025

Abstract Recommendation systems (RSs) are crucial in personalizing user experiences in digital environments by suggesting relevant content or items. Collaborative filtering (CF) is a widely used personalization technique that leverages user-item interactions to generate recommendations. However, it struggles with challenges like the cold-start problem, scalability issues, and data sparsity. To address these limitations, we develop a Graph Convolutional Networks (GCNs) model that captures the complex network of interactions between users and items, identifying subtle patterns that traditional methods may overlook. We integrate this GCNs model into a federated learning (FL) framework, enabling the model to learn… More >

Yi Li¹, Wenying Zheng², Yu-Sheng Su^3,4,5,*, Meiqin Tang⁶

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2719-2734, 2025, DOI:10.32604/cmc.2025.059949 - 16 April 2025

Abstract AI applications have become ubiquitous, bringing significant convenience to various industries. In e-commerce, AI can enhance product recommendations for individuals and provide businesses with more accurate predictions for market strategy development. However, if the data used for AI applications is damaged or lost, it will inevitably affect the effectiveness of these AI applications. Therefore, it is essential to verify the integrity of e-commerce data. Although existing Provable Data Possession (PDP) protocols can verify the integrity of cloud data, they are not suitable for e-commerce scenarios due to the limited computational capabilities of edge servers, which More >

Zijian Liu¹, Yong Shi², Chuanqi Li¹, Xiliang Zhang^3,*, Jian Zhou¹, Manoj Khandelwal^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 153-183, 2025, DOI:10.32604/cmes.2025.062426 - 11 April 2025

Abstract Given the growing concern over global warming and the critical role of carbon dioxide (CO₂) in this phenomenon, the study of CO₂-induced alterations in coal strength has garnered significant attention due to its implications for carbon sequestration. A large number of experiments have proved that CO₂ interaction time (T), saturation pressure (P) and other parameters have significant effects on coal strength. However, accurate evaluation of CO₂-induced alterations in coal strength is still a difficult problem, so it is particularly important to establish accurate and efficient prediction models. This study explored the application of advanced machine learning (ML)… More >

Rui Zhang¹, Le Ren¹, Zhihang Liu¹, Xinyue Gu¹, Shanshan Du¹, Xiao Chen¹, Bingran Xi¹, Bingnan Zhao^1,2, Chao Si^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 709-721, 2025, DOI:10.32604/phyton.2025.062281 - 31 March 2025

Abstract Plant invasion poses a serious environmental challenge to freshwater ecosystems. Heavy metal pollution and nutrient enrichment, particularly nitrogen (N) and phosphorus (P), are two additional critical environmental issues known to influence the growth of invasive plants. Notably, the N/P ratio in the environments is often inconstant; however, whether these variations can cause differential responses in invasive plants remains underexplored, despite its crucial importance for understanding plant invasiveness. In this study, we examined the effects of different N/P ratios (4:1, 16:1, 32:1, 64:1) on the growth of a widespread invasive plant Alternanthera philoxeroides in cadmium (Cd) polluted… More >

Xiaojian Chen^1,2,#, Zhujiang Dai^1,#, Qiang Wang³, Wei Chen¹, Yun Liu^1,*, Zhongchuan Wang^1,*

BIOCELL, Vol.49, No.3, pp. 503-518, 2025, DOI:10.32604/biocell.2025.059286 - 31 March 2025

Abstract Background: Nudix Hydrolase 21 (NUDT21) is crucial for the regulation of alternative polyadenylation, with its reduced expression frequently resulting in a shortened mRNA 3^′ untranslated region (UTR), thereby enhancing the protein levels of downstream genes. Although NUDT21 is widely recognized for its tumor-suppressive function in various cancers, its involvement in colorectal cancer (CRC) remains poorly understood. Methods: The expression of NUDT21 in CRC and adjacent normal tissues was analyzed through qPCR, Western blot, and immunohistochemistry (IHC). Additionally, we investigated the correlation between NUDT21 expression and patient prognosis. With Cell Counting Kit-8 assay and Transwell assay, we… More >

Haitao Wang^1,2, Yuanzhao Guo^1,2, Xiaotong Han^1,2, Yuan Tian^1,2,*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 137-155, 2025, DOI:10.32604/cmc.2025.060534 - 26 March 2025

Abstract Relation extraction plays a crucial role in numerous downstream tasks. Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue. To tackle the problem of low information density in dialogues, methods based on trigger enhancement have been proposed, yielding positive results. However, trigger enhancement faces challenges, which cause suboptimal model performance. First, the proportion of annotated triggers is low in DialogRE. Second, feature representations of triggers and arguments often contain conflicting information. In this paper, we propose a novel Multi-Feature Filtering and Fusion trigger enhancement approach to overcome these limitations. We first… More >

Can Hu¹, Shanqing Zhang^2,*, Kewei Tao², Gaoming Yang¹, Li Li²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4913-4930, 2025, DOI:10.32604/cmc.2025.059770 - 06 March 2025

Abstract The surge of large-scale models in recent years has led to breakthroughs in numerous fields, but it has also introduced higher computational costs and more complex network architectures. These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization. To address this issue, various network compression techniques have been developed, such as network pruning. A typical pruning algorithm follows a three-step pipeline involving training, pruning, and retraining. Existing methods often directly set the pruned filters to zero during retraining, significantly reducing the parameter space. However, this… More >

Qi Mu^*, Yuanjie Guo, Xiangfu Ge, Xinyue Wang, Zhanli Li

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4669-4690, 2025, DOI:10.32604/cmc.2025.058495 - 06 March 2025

Abstract In low-light image enhancement, prevailing Retinex-based methods often struggle with precise illumination estimation and brightness modulation. This can result in issues such as halo artifacts, blurred edges, and diminished details in bright regions, particularly under non-uniform illumination conditions. We propose an innovative approach that refines low-light images by leveraging an in-depth awareness of local content within the image. By introducing multi-scale effective guided filtering, our method surpasses the limitations of traditional isotropic filters, such as Gaussian filters, in handling non-uniform illumination. It dynamically adjusts regularization parameters in response to local image characteristics and significantly integrates… More >

Haishui Han¹, Jian Tan¹, Junshi Li¹, Changhong Zhao², Ruoyu Liu¹, Qun Zhang^3,4, Zemin Ji^3,4, Hao Kang^5,6,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.2, pp. 293-308, 2025, DOI:10.32604/fdmp.2025.058989 - 06 March 2025

Abstract To address the water sensitivity of conglomerate reservoirs, a series of core sensitivity tests were conducted to evaluate the effects of varying ionic content. These findings serve as a foundation for improving reservoir fluid dynamics and optimizing the concentration of anti-swelling agents in water flooding operations. The experiments revealed a marked disparity in response between cores with differing permeabilities. In Core No. 5, characterized by low permeability, a 0.5% anti-swelling agent achieved only a modest 7.47% reduction in water sensitivity. Conversely, in the higher-permeability Core No. 8, a 5% anti-swelling agent significantly reduced the… More >