Meerim Park¹, Seungman Park², Ensel Oh³, Jongmun Choi⁴, Mi Mi Kwon¹, Seog-Yun Park⁵, Jun Ah Lee¹, Hyeon Jin Park^1,*

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.079120 - 21 May 2026

Abstract Objectives: Germline variants in cancer predisposition genes have been increasingly recognized in pediatric cancers. However, their spectrum in East Asian children with central nervous system (CNS) tumors remains insufficiently defined. This study investigated the prevalence and clinical significance of pathogenic or likely pathogenic (P/LP) germline mutations in Korean children, adolescents, and young adults (AYAs) with CNS tumors. Methods: We performed targeted next-generation sequencing of 358 cancer-associated genes using peripheral blood DNA from 108 patients. Germline variants were classified according to ACMG/AMP guidelines and curated using ClinVar and relevant literature. Results: Among 108 patients, 17 (15.7%) carried P/LP… More >

Hyungkeun Cha¹, Yong Seok Lee², Gui Young Kwon³, Boran Kim⁴, Yeonsook Moon⁵, Lucia Kim⁶, Hae-Seong Nam^1,*

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.077514 - 21 May 2026

Abstract Objective: Studies on the comprehensive utility of complete blood count-derived inflammatory biomarkers (CBC-IBs) as biomarkers in pembrolizumab-treated advanced non-small-cell lung cancer (NSCLC) are scarce. This study aimed to investigate the clinical relevance of a panel of CBC-IBs as potential predictive biomarkers and assess whether integrating the systemic immune-inflammation index (SII) with programmed death-ligand 1 (PD-L1) expression could overcome the limitations of PD-L1 as a standalone predictive biomarker. Methods: Our real-world preliminary study was conducted on a cohort of patients with advanced NSCLC. Patients who had undergone PD-L1 immunohistochemistry testing at the time of diagnosis, and had… More >

Shadi Zerehpoosh¹, Yasuhito Tanaka², Said A. Al-Busafi^3,4, Gulnara Aghayeva⁵, Samir Rouabhia⁶, Qiuwei Pan⁷, Mohammed Eslam^1,*

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.076937 - 21 May 2026

Abstract Hepatocellular carcinoma (HCC) represents a critical global health challenge, standing as a leading cause of cancer mortality with a significant and projected increasing incidence worldwide. A primary hurdle in HCC management is late diagnosis, often attributable to the absence of early symptoms. Despite considerable advancements in therapeutic strategies over the past decade, including immune checkpoint inhibitors and targeted therapies, mortality rates remain high, underscoring the urgent need for more effective novel approaches. The inherent molecular complexity and heterogeneity of HCC, where only a minority of tumors possess readily targetable drivers, contribute to treatment resistance and More >

Mariana Lopes^1,#, Carlos Vila Nova^2,3,#, Rui Caetano Oliveira^3,4, Fernando Schmitt⁵, Fernando Mendes^1,6,7,8,9,*, Diana Martins^1,6,7,8

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.074215 - 21 May 2026

Abstract Objectives: Triple-negative breast cancer (TNBC) accounts for approximately 15% of all invasive breast cancers and is characterized by aggressive behavior, limited therapeutic options, and poor clinical outcomes. Due to the absence of hormone receptors and HER2 expression, systemic treatment relies predominantly on chemotherapy, which is associated with high rates of early recurrence and mortality. Emerging evidence suggests that alterations in the microbiome can contribute to TNBC progression and influence therapeutic response, particularly affecting the efficacy of chemotherapy and immunotherapy through immune-mediated mechanisms; however, its role in TNBC remains incompletely understood. This systematic review aims to explore… More >

Haoyu Li¹, Jiayi Wang¹, Zhaoyu Wu¹, Shuo Yan¹, Ziqi Zhang¹, Yang Gao^2,3, Genwang Peng^2,3, Zhiwei Cao^2,*

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077736 - 18 May 2026

Abstract Key components of rail transit systems, such as tracks and vehicle bodies, are prone to developing various types and manifestations of defects during long-term operation. These defects not only accelerate component aging and failure but also pose serious threats to train operational safety. Among existing intelligent detection methods, they mostly rely solely on visible light images demonstrate limited robustness in complex scenarios. This limitation stems from their high dependence on ambient lighting conditions, rendering them insufficient to meet practical railway inspection requirements. While mainstream multimodal detection methods incorporate the complementary strengths of heterogeneous data sources,… More >

Hui Zhang^1,*, Yingying Xie¹, Yu Zhang^2,*, Zhan Gao¹, Aijun Li¹, Sheng Shi¹, Xingyue Li¹, Zheming Zhou¹, Haotian Wang¹

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075835 - 18 May 2026

Abstract A composite bridge deck system consisting of an orthotropic steel deck and a normal-temperature-cured reactive powder concrete (RPC) layer is proposed to address the problems of pavement damage and fatigue cracks in steel bridge decks. In this study, a local finite element model of a bridge segment was established using ANSYS to calculate and compare the stress states of four deck systems: normal-temperature-cured RPC composite box girders, high-temperature-cured RPC composite box girders, pure steel box girders, and ordinary concrete composite box girders. Additionally, static load tests were conducted on a scaled local model to validate… More > Graphic Abstract

Zhiye Zhou^1,2, Jianan Chen³, Qiang Zhu^3,*

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.076758 - 13 May 2026

Abstract Background: Human dental pulp stem cells (hDPSCs) are promising for dental tissue regeneration. Dioscin (Dio), a natural compound, has various biological activities, but its effects on hDPSCs are unclear. This study aims to systematically elucidate the effects of Dio on promoting the osteogenic differentiation of hDPSCs and the underlying molecular mechanisms. Methods: Characterized hDPSCs were treated with Dio. Cell viability, proliferation, osteogenic differentiation (alkaline phosphatase (ALP) activity, Alizarin Red S (ARS)), and migration (Transwell) were assessed. Mitophagy (fluorescence, Western blot for PTEN-induced kinase 1 (PINK1), parkin RBR E3 ubiquitin-protein ligase (PRKN), microtubule-associated protein 1 light chain… More > Graphic Abstract

Andrea De Matthaeis¹, Laura Rehak^2,*, Maria Bianchi³, Rossana Putzulu³, Nicola Piccirillo^3,4, Giulio Maccauro¹

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.073783 - 13 May 2026

Abstract For over two decades, mesenchymal stem cells (MSCs) have been recognised as the cornerstone of orthobiologic treatments for musculoskeletal diseases. However, clinical evidence increasingly indicates that MSC engraftment in inflamed tissues is minimal and transient, with effects mainly driven by paracrine and immunomodulatory mechanisms induced by macrophage efferocytosis. This evolving paradigm emphasises the immune system as the central orchestrator of tissue repair. Peripheral blood mononuclear cells (PBMNCs) have emerged as potent effectors of regenerative inflammation, mediating apoptotic cell clearance through efferocytosis, facilitating the transition of macrophages from pro-inflammatory (M1) to reparative (M2) phenotypes, and releasing… More >

Akash Garg^*

Journal on Artificial Intelligence, Vol.8, pp. 273-298, 2026, DOI:10.32604/jai.2026.079401 - 12 May 2026

Abstract As cyber threats continue to evolve in scale and sophistication, the need for intelligent and adaptive security mechanisms has become increasingly urgent. Intrusion Detection Systems (IDS) are critical components in safeguarding computer networks from malicious activities. This review paper presents a comprehensive analysis of recent advancements in deep learning-based IDS, examining various architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and generative adversarial networks (GANs). The study compares traditional intrusion detection techniques with modern deep learning approaches, highlighting their strengths, limitations, and suitability for real-world deployment. Special attention is given to… More >

Soukaina Mjahed¹, Ouail Mjahed^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.081953 - 08 May 2026

Abstract The rapid emergence of sophisticated, dynamic, and rare or previously unseen attack pattern exposes fundamental limitations of conventional intrusion detection systems (IDS) based on static learning architectures. While deep learning (DL) models have demonstrated strong performance by capturing complex spatial and temporal traffic patterns, existing DL-based IDS largely rely on fixed decision structures, restricting adaptability to evolving threats. Furthermore, current hybrid DL-metaheuristic approaches typically use such metaheuristics as offline or auxiliary optimizers, without interacting with the deep model’s internal latent representations. This paper introduces a novel co-evolutionary IDS that establishes a tight, bidirectional coupling between… More >