Kamaljeet¹, Abhishek Vijukumar¹, Hardik Kumar^2,*, Shilpa Debnath², Sourabh Kosey¹

European Cytokine Network, Vol.37, No.1, pp. 13-24, 2026, DOI:10.32604/ecn.2026.078458 - 13 April 2026

Abstract Cytokine storm syndromes have become a much-invoked concept to describe severe immunopathology in infectious, inflammatory, and iatrogenic diseases, but the concept is poorly defined and often mechanistically imprecise. High levels of systemic cytokines have often been viewed as indicators of immune dysfunction, and based on this notion, therapeutic interventions focused on general cytokine inhibition are proposed. Nevertheless, a growing number of clinical and experimental data dispute the notion that hypercytokinemia is necessarily pathological. The present paper reconsiders cytokine storm syndromes in the light of an evolutionary, systems-immunology model, and suggests that most cytokine amplification conditions… More >

Natália Alvarenga Borges¹, Larissa Manhães¹, Ludmilla Dias de Santana e Santana¹, Jessyca Sousa de Brito², Larissa Fonseca³, Ludmila F. M. F. Cardozo⁴, Denise Mafra^2,3,4,*,#,*

European Cytokine Network, Vol.37, No.1, pp. 1-11, 2026, DOI:10.32604/ecn.2026.0ECN78096 - 13 April 2026

Abstract The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that exhibits antagonistic pleiotropy, mediating both protective and detrimental cellular effects depending on the ligand and context. AhR can be activated by a variety of endogenous and exogenous stimuli, including environmental pollutants, UVB radiation, heme, arachidonic acid metabolites, gut microbiota–derived compounds, and xenobiotics. Upon activation, AhR translocates to the nucleus, where it dimerizes with the aryl hydrocarbon receptor nuclear translocator (ARNT) and binds to xenobiotic response elements, inducing the expression of genes involved in xenobiotic metabolism, oxidative stress responses, and inflammatory signaling. In addition to… More >

Jiawen Chen^1,#, Zelin Liu^1,#, Keke Huang¹, Jinlan Li¹, Yajie Zhang¹, Dandan Chen¹, Yanjie Ruan², Ying Pan¹, Furun An¹, Yang Wan^1,*, Jiyu Wang^1,3,*, Qianshan Tao^1,*

European Cytokine Network, Vol.37, No.1, pp. 25-39, 2026, DOI:10.32604/ecn.2026.077875 - 13 April 2026

Abstract Objectives: B-cell lymphoma exhibits significant clinical heterogeneity, necessitating improved biomarkers for risk stratification. C-C chemokine receptor 7 (CCR7) and trimethylation of histone H3 lysine 9 (H3K9me3) are implicated in cellular senescence and tumor invasion. While the clinical significance of their co-expression in lymphomagenesis remains unclear. This study aims to define the expression profiles of CCR7 and H3K9me3 in B-cell lymphoma, explore their correlation with aggressive clinical indicators, and evaluate their combined prognostic value. Methods: The expression of CCR7 and H3K9me3 in tumor tissues from B-cell lymphoma patients was analyzed by immunohistochemical (IHC) double-staining. The mechanistic… More >

Di Xiao^*, Wenting Jiang, Min Li

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079808 - 09 April 2026

Abstract The rapid advancement of the Internet of Things (IoT) has transformed edge devices from simple data collectors into intelligent units capable of local processing and collaborative learning. However, the vast amounts of sensitive data generated by these devices face severe constraints from “data silos” and risks of privacy breaches. Federated learning (FL), as a distributed collaborative paradigm that avoids sharing raw data, holds great promise in the IoT domain. Nevertheless, it remains vulnerable to gradient leakage threats. While traditional differential privacy (DP) techniques mitigate privacy risks, they often come at the cost of significantly reduced… More >

Kuen-Suan Chen^1,2,3, Tsai-Sung Lin⁴, Ruey-Chyn Tsaur^4,*, Minh T. N. Nguyen⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079476 - 09 April 2026

Abstract As artificial intelligence, the Internet of Things, edge computing, and blockchain are increasingly integrated into long-term care (LTC) services, policymakers face complex and often non-compensatory trade-offs among affordability, workforce sustainability, service reliability, and data governance. Conventional compensatory evaluation models tend to mask critical structural weaknesses and limiting their usefulness for Smart LTC policy assessment. This study proposes and applies a Fuzzy Trade-Off-Aware Scoring with Conflicts (Fuzzy TASC) framework to evaluate Smart LTC system performance. Four digital-integration configurations—conventional cloud-based LTC, AI+IoT, AI+Edge, and AI+Blockchain—were compared across 12 OECD countries. A Monte Carlo perturbation procedure was incorporated… More >

Mohammed Shamar Yadkar¹, Sefer Kurnaz¹, Saadaldeen Rashid Ahmed^2,3,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079408 - 09 April 2026

Abstract This advanced research describes CycleGAN-RRW, a new reversible watermarking system for secure image ownership authentication. It uses Cycle-Consistent Generative Adversarial Networks with adaptive feature encoding. In areas such as law, forensics, and telemedicine, digital images usually contain private info that may be changed or used without authorization. Existing watermarking methods may decrease image quality, may not be reversible, or need outside keys. To address these problems, our model embeds metadata into intermediate feature maps with Adaptive Instance Normalization (AdaIN), based on adversarial and perceptual loss. The dual-generator design permits two-way translation between original and watermarked… More >

Yan-Hao Huang^*, Chung-Ming Kao

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079381 - 09 April 2026

Abstract Photovoltaic (PV) equivalent-circuit models are widely used for performance evaluation and diagnostics, but their usefulness relies on both accurate calibration and interpretable understanding of how parameters shape current–voltage (I–V) behavior. For nonlinear and strongly coupled PV models, conventional global sensitivity analysis can be computationally demanding and offer limited insight into effect direction and operating-point dependence. This study presents an method-oriented framework that integrates nature-inspired optimization with surrogate-based explainable global sensitivity analysis under a specified operating condition. The Starfish Optimization Algorithm (SFOA) is first used for parameter identification by searching for the optimal parameter set that… More >

Semih Nart¹, Emre Güler², Melek Güler², Gökay Uğur^3,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079045 - 09 April 2026

Abstract Fluoride materials are renowned for their exceptional optical transparency, ionic conductivity, and chemical stability, making them indispensable in a wide range of technological applications. Despite the previous extensive research on simple metal fluorides, the complex metal fluoride family—particularly compounds with AB₂F₈ stoichiometry—remains largely unexplored. In this work, we present the first comprehensive density functional theory (DFT) investigation of the rare and formerly unreported MgAu₂F₈ complex metal fluoride, systematically revealing its electronic, optical, and thermoelectric properties under varying hydrostatic pressures. Our results reveal that MgAu₂F₈ undergoes a remarkable transformation from a wide-bandgap semiconductor at ambient conditions to a More >

Simona-Vasilica Oprea, Adela Bâra^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078985 - 09 April 2026

Abstract Quantization has emerged as an important technique for enabling efficient deployment of large language models (LLMs) by reducing their memory and computational requirements. This research conducts an evaluation of INT8 quantization on several state-of-the-art LLMs, GPT-2, LLaMA-2-7B-Chat and Qwen1.5-1.8B-Chat, across two hardware configurations: NVIDIA RTX4070 Laptop GPU and RTX4080 Laptop GPU and two tasks: text and code generation. By comparing quantized INT8 models with their FP16 counterparts and a human-written reference, we quantify the trade-offs between performance and efficiency using standard natural language generation metrics (BLEU, ROUGE-1, ROUGE-L) and semantic analysis via GPT-4o and Gemini… More >

Osamah Mohammed Alyasiri^1,2, Yu-N Cheah^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078927 - 09 April 2026

Abstract Term weighting scheme and feature selection are two fundamental components in text classification (TC) systems, particularly in high-dimensional, multi-class, and imbalanced settings. Term weighting schemes aim to improve document representation by emphasizing discriminative terms across classes, while feature selection (FS) seeks to reduce dimensionality, eliminate irrelevant and redundant features, and enhance classification efficiency and effectiveness. However, most existing studies focus on FS independently of the term-weighting strategy used during document representation, thereby limiting the potential benefits of their interaction. This study addresses this gap by pursuing two main objectives. First, it employs an enhanced supervised… More >