Wen-Shou Tan^1,#, Hsuan Kuo^2,#, Chang-Ge Jiang¹, Mei-Han Lu¹, Yi-He Lu¹, Yung-Li Wang¹, Ching-Shuen Wang¹, Thi Thuy Tien Vo³, I-Ta Lee^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070871 - 30 December 2025

Abstract This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma (OSCC), a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis. Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes. Various salivary biomarkers, including microRNAs, cytokines, proteins, metabolites, and exosomes, have been linked to oncogenic signaling pathways involved in tumor progression, immune modulation, and therapeutic resistance. Advances in quantitative polymerase chain reaction, mass spectrometry, and next-generation sequencing have enabled comprehensive biomarker profiling, while point-of-care detection More >

Huihui Shi^1,#, Lei Chen^2,#, Juan Huang^3,#, Xuejing Lin², Lei Huang⁴, Min Tang⁴, Kai Lu^5,*, Wenchao Wang^4,*, Maoling Zhu^1,§,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.068737 - 30 December 2025

Abstract Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study aimed to identify key genes involved in HCC development and elucidate their molecular mechanisms, with a particular focus on mitochondrial function and apoptosis. Methods: Differential expression analyses were performed across three datasets—The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC), GSE36076, and GSE95698—to identify overlapping differentially expressed genes (DEGs). A prognostic risk model was then constructed. Cysteine/serine-rich nuclear protein 1 (CSRNP1) expression levels in HCC cell lines were assessed via western blot (WB) and quantitative reverse transcription polymerase chain reaction (qRT-PCR).… More > Graphic Abstract

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 >

Chang Su, Liangliang Zhao^*, Dongbing Xiang

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-24, 2026, DOI:10.32604/cmc.2025.071319 - 09 December 2025

Abstract To address low learning efficiency and inadequate path safety in spraying robot navigation within complex obstacle-rich environments—with dense, dynamic, unpredictable obstacles challenging conventional methods—this paper proposes a hybrid algorithm integrating Q-learning and improved A*-Artificial Potential Field (A-APF). Centered on the Q-learning framework, the algorithm leverages safety-oriented guidance generated by A-APF and employs a dynamic coordination mechanism that adaptively balances exploration and exploitation. The proposed system comprises four core modules: (1) an environment modeling module that constructs grid-based obstacle maps; (2) an A-APF module that combines heuristic search from A* algorithm with repulsive force strategies from… More >

Baixuan Han¹, Yueping Peng^1,*, Zecong Ye², Hexiang Hao¹, Xuekai Zhang¹, Wei Tang¹, Wenchao Kang¹, Qilong Li¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-31, 2026, DOI:10.32604/cmc.2025.071071 - 09 December 2025

Abstract Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm, a lightweight multi-category abnormal behavior detection algorithm based on improved YOLOv11n is designed. By integrating multi-head grouped self-attention mechanism and Partial-Conv, a two-way feature grouping fusion module (DFPF) was designed, which carried out effective channel segmentation and fusion strategies to reduce redundant calculations and memory access. C3K2 module was improved, and then unstructured pruning and feature distillation technology were used. The algorithm model is lightweight, and the feature extraction ability for airborne visual abnormal behavior… More >

Wei Liu^1,*, Ruiyang Wang¹, Guangwei Liu²

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.070328 - 09 December 2025

Abstract Q-learning is a classical reinforcement learning method with broad applicability. It can respond effectively to environmental changes and provide flexible strategies, making it suitable for solving robot path-planning problems. However, Q-learning faces challenges in search and update efficiency. To address these issues, we propose an improved Q-learning (IQL) algorithm. We use an enhanced Ant Colony Optimization (ACO) algorithm to optimize Q-table initialization. We also introduce the UCH mechanism to refine the reward function and overcome the exploration dilemma. The IQL algorithm is extensively tested in three grid environments of different scales. The results validate the… More >

Jiajun Sun, Shunshun Ji, Chao Zhang^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.068668 - 09 December 2025

Abstract Asparagus stem blight is a devastating crop disease, and the early detection of its pathogenic spores is essential for effective disease control and prevention. However, spore detection is still hindered by complex backgrounds, small target sizes, and high annotation costs, which limit its practical application and widespread adoption. To address these issues, a semi-supervised spore detection framework is proposed for use under complex background conditions. Firstly, a difficulty perception scoring function is designed to quantify the detection difficulty of each image region. For regions with higher difficulty scores, a masking strategy is applied, while the… More >

Longfei Gao^*, Weidong Wang, Dieyun Ke

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.068873 - 10 November 2025

Abstract At present, energy consumption is one of the main bottlenecks in autonomous mobile robot development. To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments, this paper proposes an Attention-Enhanced Dueling Deep Q-Network (AD-Dueling DQN), which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework. A multi-objective reward function, centered on energy efficiency, is designed to comprehensively consider path length, terrain slope, motion smoothness, and obstacle avoidance, enabling optimal low-energy trajectory generation in 3D space from the… More >

Zhenpeng Jiang, Qingquan Liu^*, Ende Wang

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.068780 - 10 November 2025

Abstract Rapidly-exploring Random Tree (RRT) and its variants have become foundational in path-planning research, yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety. To address these challenges, we introduce HS-APF-RRT*, a novel algorithm that fuses layered sampling, an enhanced Artificial Potential Field (APF), and a dynamic neighborhood-expansion mechanism. First, the workspace is hierarchically partitioned into macro, meso, and micro sampling layers, progressively biasing random samples toward safer, lower-energy regions. Second, we augment the traditional APF by More >

Di Wu¹, Chunguang Ren¹, Liangliang Li¹, Chongpei Zheng², Wenwen Su^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 4079-4090, 2025, DOI:10.32604/phyton.2025.072856 - 29 December 2025

Abstract To identify the pathogen responsible for fruit rot disease in Rosa roxburghii Tratt. from Guiding County, Guizhou Province, China, diseased fruit samples were collected. The pathogen was isolated, purified, and identified through morphological, molecular, and pathogenic analyses. Subsequently, its biological characteristics were evaluated. Furthermore, to determine the agent with the strongest toxicity against the identified pathogen, the antifungal activity of six chemical and biological agents was evaluated through indoor toxicity assays. Finally, Neopestalotiopsis clavispora was identified as the pathogen responsible for fruit rot disease in R. roxburghii Tratt. The diameter of the pathogen grown under different carbon and… More >