Shizhou Yu^1,2, Jie Zhang¹, Linggai Cao¹, Jie Liu¹, Peng Lu³, Jiemeng Tao³, Xueliang Ren¹, Zhixiao Yang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.2, 2026, DOI:10.32604/phyton.2026.073509 - 28 February 2026

Abstract Tobacco (Nicotiana tabacum, 2n = 48) is a key non-food economic crop, yet its stress response and gene regulatory mechanisms remain poorly understood. By analyzing 603 transcriptome datasets, this study identified 1405 tissue-specific genes, revealing tissue-specific synthesis of terpenoids and other ecologically important secondary metabolites in sepals and other tissues. Comparative stress-response analysis highlighted distinct gene expression patterns in leaves and roots under biotic and abiotic stresses. Additionally, 28,396 expression quantitative trait loci (eQTLs) were mapped in leaves, offering valuable genetic regulatory markers. These findings provide crucial insights into tobacco’s gene expression characteristics and their functional More >

Yu-Xuan Zhou¹, Kai-Qing Zhou^1,*, Wei-Lin Chen¹, Zhou-Hua Liao¹, Di-Wen Kang^1,2

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.075099 - 10 February 2026

Abstract The Pigeon-Inspired Optimization (PIO) algorithm constitutes a metaheuristic method derived from the homing behaviour of pigeons. Initially formulated for three-dimensional path planning in unmanned aerial vehicles (UAVs), the algorithm has attracted considerable academic and industrial interest owing to its effective balance between exploration and exploitation, coupled with advantages in real-time performance and robustness. Nevertheless, as applications have diversified, limitations in convergence precision and a tendency toward premature convergence have become increasingly evident, highlighting a need for improvement. This review systematically outlines the developmental trajectory of the PIO algorithm, with a particular focus on its core… More >

Longcang Wang, Yongbing Gao^*, Xinguang Wang, Xin Liu

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072889 - 10 February 2026

Abstract Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods, this paper proposes the IPKE-MoE framework, which consists of three parts, namely, a sensitive word variant extraction framework, a sensitive word variant knowledge enhancement layer and a mixture-of-experts (MoE) classification layer. First, sensitive word variants are precisely extracted through dynamic iterative prompt templates and the context-aware capabilities of Large Language Models (LLMs). Next, the extracted variants are used to construct a knowledge enhancement layer for sensitive word variants based on RoCBert models. Specifically, after locating variants via n-gram… More >

Weichen Wang¹, Shaofeng Wang¹, Wenjing Liu^1,*, Luncai Zhou², Erqing Zhang¹, Ting Gao³, Grigory Petrishin⁴

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071278 - 08 January 2026

Abstract In dry-coupled ultrasonic thickness measurement, thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy. Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise. This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference. By decomposing A-scan signals into Intrinsic Mode Functions (IMFs), the framework employs energy contribution thresholds (>85%) and kurtosis indices (>3) to autonomously select IMFs containing valid specimen echoes. Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing. More >

Miguel Meñaca-Puentes^1,*, Juan-Camilo Arias-Ospina¹, Narmer F. Galeano², Reinel Tabares-Soto^1,3, Carlos Alberto Ruiz Villa¹

Congenital Heart Disease, Vol.20, No.6, pp. 743-767, 2025, DOI:10.32604/chd.2025.070423 - 10 February 2026

Abstract Atherosclerotic cardiovascular disease remains the leading cause of global mortality, with low-density lipoprotein cholesterol established as a primary causal risk factor. Despite widespread implementation of statin therapy, substantial interindividual variability in treatment response persists, necessitating precision medicine approaches to optimize therapeutic outcomes. This comprehensive narrative review synthesizes current understanding of pharmacogenomic determinants influencing lipid-lowering therapy efficacy, examines mechanisms underlying residual cardiovascular risk, and evaluates emerging therapeutic modalities targeting previously unexploited pathways in lipid metabolism. Genetic variants in key genes including 3-hydroxy-3-methylglutaryl-CoA reductase, apolipoprotein E, low-density lipoprotein receptor, and proprotein convertase subtilisin/kexin type 9 demonstrate significant… More >

Shahin Imran^1,2, Maki Katsuhara^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3653-3665, 2025, DOI:10.32604/phyton.2025.073959 - 01 December 2025

Abstract Barley (Hordeum vulgare L.) employs the Na⁺ transporter HvHKT1;1, which is an N⁺-selective transporter. This study characterized the full-length HvHKT1;1 (HvHKT1;1-FL) and three mRNA variants (HvHKT1;1-V1, -V2, and -V3), which encode polypeptides of 64.7, 54.0, 40.5, and 32.9 kDa, respectively. Tissue-specific expression profiling revealed that HvHKT1;1-FL is the most abundant transcript across leaf, sheath, and root tissues under normal conditions, with the highest expression in leaves. Under 150 mM NaCl stress, HvHKT1;1-FL and its variants showed a dynamic, time-dependent expression pattern, with peak leaf expression at 2 h, sheath expression at 12 h, and root expression at 2 h, suggesting their… More >

Noor Ayesha¹, Muhammad Mujahid², Abeer Rashad Mirdad², Faten S. Alamri^3,*, Amjad R. Khan²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1883-1899, 2025, DOI:10.32604/cmc.2025.063560 - 09 June 2025

Abstract Large language models (LLMs) and natural language processing (NLP) have significant promise to improve efficiency and refine healthcare decision-making and clinical results. Numerous domains, including healthcare, are rapidly adopting LLMs for the classification of biomedical textual data in medical research. The LLM can derive insights from intricate, extensive, unstructured training data. Variants need to be accurately identified and classified to advance genetic research, provide individualized treatment, and assist physicians in making better choices. However, the sophisticated and perplexing language of medical reports is often beyond the capabilities of the devices we now utilize. Such an… More >

Hongqun Xiang¹, Jian Zhuang^2,3, Luoning Bao^4,5, Yan Shi^2,3,*

Congenital Heart Disease, Vol.20, No.2, pp. 245-263, 2025, DOI:10.32604/chd.2025.064366 - 30 April 2025

Abstract Congenital heart disease (CHD) is the most common birth defect, with 34% of cases attributed to genetic variants. NOTCH1, a multi-domain transmembrane protein, regulates heart development by controlling the differentiation and migration of myocardial mesoderm cells, and different variants are present in different types of CHD. In this review, we aim to provide a detailed description of NOTCH1 structural domains and their functions, highlighting NOTCH1 variants in CHD and the molecular mechanisms through which they contribute to CHD occurrence. NOTCH1 has two main domains, the NOTCH extracellular domain (NECD) and the NOTCH intracellular domain… More >

Mohammed A. El-Shorbagy¹, Anas Bouaouda^2,*, Laith Abualigah^3,4, Fatma A. Hashim^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2339-2404, 2025, DOI:10.32604/cmes.2025.061028 - 03 March 2025

Abstract With the rapid advancements in technology and science, optimization theory and algorithms have become increasingly important. A wide range of real-world problems is classified as optimization challenges, and meta-heuristic algorithms have shown remarkable effectiveness in solving these challenges across diverse domains, such as machine learning, process control, and engineering design, showcasing their capability to address complex optimization problems. The Stochastic Fractal Search (SFS) algorithm is one of the most popular meta-heuristic optimization methods inspired by the fractal growth patterns of natural materials. Since its introduction by Hamid Salimi in 2015, SFS has garnered significant attention… More >

Saeed Dinarvand^*, Amirmohammad Abbasi, Sogol Gharsi

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 37-60, 2025, DOI:10.32604/fdmp.2024.057545 - 24 January 2025

Abstract The present review explores the promising role of nanofluids and related hybrid variants in enhancing the efficiency of flat tube car radiators. As vehicles become more advanced and demand better thermal performance, traditional coolants are starting to fall short. Nanofluids, which involve tiny nanoparticles dispersed into standard cooling liquids, offer a new solution by significantly improving heat transfer capabilities. The article categorizes the different types of nanofluids (ranging from those based on metals and metal oxides to carbon materials and hybrid combinations) and examines their effects on the improvement of radiator performance. General consensus More >