Hang Zhang^1,#, Meng-Yuan Chu^1,#, Guohui Lv¹, You-Jie Li¹, Xuhang Liu², Fei Jiao^1,*, Yun-Fei Yan^1,*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.068322 - 23 January 2026

Abstract Objectives: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality, with limited understanding of lncRNA-driven mechanisms in tumor progression. This study aimed to identify differentially expressed lncRNAs in NSCLC tissues and elucidate the functional role of the significantly upregulated RP3-340N1.2 in promoting malignancy. Methods: RNA sequencing was used to screen dysregulated lncRNAs. RP3-340N1.2 was functionally characterized via gain/loss-of-function assays in NSCLC cells, assessing proliferation, migration, and macrophage polarization. Mechanisms of interleukin 6 (IL-6) regulation were explored using cytokine profiling, Actinomycin D assays, and RNA Immunoprecipitation (RIP) assays to study RP3-340N1.2 interactions with… More >

Kwabena Owusu-Mensah^*, Edward Danso Ansong , Kofi Sarpong Adu-Manu, Winfred Yaokumah

Journal of Cyber Security, Vol.8, pp. 33-92, 2026, DOI:10.32604/jcs.2026.074265 - 20 January 2026

Abstract The rapid growth of digital payment systems and remote financial services has led to a significant increase in Card-Not-Present (CNP) fraud, which is now the primary source of card-related losses worldwide. Traditional rule-based fraud detection methods are becoming insufficient due to several challenges, including data imbalance, concept drift, privacy concerns, and limited interpretability. In response to these issues, a systematic review of twenty-four CNP fraud detection frameworks developed between 2014 and 2025 was conducted. This review aimed to identify the technologies, strategies, and design considerations necessary for adaptive solutions that align with evolving regulatory standards.… More >

Fatemeh Ahmadi Abkenari^*, Melika Zandi, Shanmugapriya Gopalakrishnan

Journal of Cyber Security, Vol.8, pp. 93-109, 2026, DOI:10.32604/jcs.2026.074197 - 20 January 2026

Abstract Nowadays, cyberattacks are considered a significant threat not only to the reputation of organizations through the theft of customers’ data or reducing operational throughput, but also to their data ownership and the safety and security of their operations. In recent decades, machine learning techniques have been widely employed in cybersecurity research to detect various types of cyberattacks. In the domain of cybersecurity data, and especially in Trojan detection datasets, it is common for datasets to record multiple statistical measures for a single concept. We referred to them as SWMF features in this paper, which include… More >

Xinyang Li^1,2,3,#, Luyuan Ma^1,2,3,#, Chuan Shen^1,2,3, Ruolan Gu^1,2,3, Shilong Dong^1,2,3, Mingjie Liu^1,2,3, Ying Xiao^1,2,3, Wenpeng Liu^1,2,3, Yuexia Liu^1,2,3, Caiyan Zhao^1,2,3,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.073179 - 19 January 2026

Abstract Background: Hepatocellular carcinoma (HCC) is an aggressive and lethal malignancy. Metabolic reprogramming dynamically remodels the tumor microenvironment (TME) and drives HCC progression. This study investigated the mechanism through which metabolic reprogramming remodels the TME in HCC. Methods: HCC patient transcriptome data were subjected to bioinformatics analysis to identify differentially expressed genes and immune infiltration status. Immunohistochemical analysis was performed to determine the correlation between succinate dehydrogenase complex subunit A (SDHA) expression and M2 macrophage infiltration. SDHA-knockdown or SDHA-overexpressing HCC cells were used for in vitro experiments, including co-culturing, flow cytometry, and enzyme-linked immunosorbent assay. Western blotting… More >

Marco Siringo^1,2,#,*, Michela De Meo^1,#, Alain Jonathan Gelibter³, Chiara Nicolazzo^4,5,§, Paola Gazzaniga^5,§

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.069832 - 19 January 2026

Abstract Objectives: Although immune checkpoint inhibitors (ICIs) and targeted therapies have reshaped treatment non-small cell lung cancer (NSCLC) paradigms, prognosis remains poor for many patients due to delayed diagnosis and resistance mechanisms. Liquid biopsy offers a minimally invasive approach to monitoring tumor evolution. Among circulating biomarkers, circulating tumor cells (CTCs) and cancer-associated macrophage-like cells (CAM-Ls) may provide complementary prognostic insights. The study aimed to evaluate the prognostic role of CTC and CAM-Ls dynamic in metastatic NSCLC patients. Methods: We retrospectively analyzed 77 patients with metastatic NSCLC who underwent CTC and CAM-L evaluation via the CellSearch® system… More >

Jeongeun Ryu¹, Riyeong Kim², Soomin Lee¹, Sumin Kim¹, Hyunwoo Choi^1,2, Seongmin Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.074871 - 12 January 2026

Abstract As containerized environments become increasingly prevalent in cloud-native infrastructures, the need for effective monitoring and detection of malicious behaviors has become critical. Malicious containers pose significant risks by exploiting shared host resources, enabling privilege escalation, or launching large-scale attacks such as cryptomining and botnet activities. Therefore, developing accurate and efficient detection mechanisms is essential for ensuring the security and stability of containerized systems. To this end, we propose a hybrid detection framework that leverages the extended Berkeley Packet Filter (eBPF) to monitor container activities directly within the Linux kernel. The framework simultaneously collects flow-based network… More >

Faisal Mahmud¹, Fahim Mahmud², Rashedur M. Rahman^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073519 - 12 January 2026

Abstract Federated Learning (FL) has become a leading decentralized solution that enables multiple clients to train a model in a collaborative environment without directly sharing raw data, making it suitable for privacy-sensitive applications such as healthcare, finance, and smart systems. As the field continues to evolve, the research field has become more complex and scattered, covering different system designs, training methods, and privacy techniques. This survey is organized around the three core challenges: how the data is distributed, how models are synchronized, and how to defend against attacks. It provides a structured and up-to-date review of… 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 >

Anis Zarrad¹, Thomas Armstrong², Jaber Jemai^3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072768 - 12 January 2026

Abstract Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability. While prioritization selects the most relevant test cases for optimal coverage, ranking further refines their execution order to detect critical faults earlier. This study investigates machine learning techniques to enhance both prioritization and ranking, contributing to more effective and efficient testing processes. We first employ advanced feature engineering alongside ensemble models, including Gradient Boosted, Support Vector Machines, Random Forests, and Naive Bayes classifiers to optimize test case prioritization, achieving an accuracy score of 0.98847… 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 >