ANDI ZHAO^1,2,#, YUE WANG^3,#, ZIJIN WANG^1,2, QING SHAO^1,2, QI GONG^1,2, HUI ZHU^1,2, SHIYA SHEN^1,2, HU LIU^1,2,*, XUEJUAN CHEN^1,2,*

Oncology Research, Vol.32, No.5, pp. 983-998, 2024, DOI:10.32604/or.2024.045972

Abstract Numerous studies have characterized the critical role of circular RNAs (circRNAs) as regulatory factors in the progression of multiple cancers. However, the biological functions of circRNAs and their underlying molecular mechanisms in the progression of uveal melanoma (UM) remain enigmatic. In this study, we identified a novel circRNA, circ_0053943, through re-analysis of UM microarray data and quantitative RT-PCR. Circ_0053943 was found to be upregulated in UM and to promote the proliferation and metastatic ability of UM cells in both in vitro and in vivo settings. Mechanistically, circ_0053943 was observed to bind to the KH1 and KH2 domains of insulin-like growth… More > Graphic Abstract

JIAN TANG¹, CHENQIANG ZHU¹, YUN CHEN¹, YUNLONG WU¹, MING HE¹, YI ZHOU², MINGHUA XIE^2,*

BIOCELL, Vol.48, No.4, pp. 639-651, 2024, DOI:10.32604/biocell.2024.047562

Abstract Background: The specific impact of sphingolipid metabolism on developing hepatocellular Carcinoma (HCC) remains unclear. This study aims to explore the relationship between sphingolipid metabolism and HCC prognosis, immune response, and drug sensitivity. Methods: Data were obtained from The Cancer Genome Atlas (TCGA)-Hepatocellular Carcinoma (LIHC) and Gene Expression Omnibus (GEO, GSE14520 datasets). 47 sphingolipid metabolism genes were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. After classifying HCC samples using the Non-negative Matrix Factorization (NMF) clustering method, differentially expressed genes were screened. Then, 8 risk genes were obtained by univariate analysis, survival random forest reduction and lasso analysis.… More > Graphic Abstract

Verônica Távilla Ferreira Silva, Adriane Maria Ferreira Milagres^*

Journal of Renewable Materials, Vol.12, No.3, pp. 539-551, 2024, DOI:10.32604/jrm.2023.045726

Abstract This study was conducted to evaluate the effectiveness of enzymes in purifying and reducing the degree of polymerization of cellulose for the production of dissolving pulp. Our goal was to determine the contributions of xylanase (X) and endoglucanase (EG) in the treatment of pulp, specifically by quantifying the formation of soluble and insoluble reducing sugars using the dinitrosalycilic acid (DNS) test. Predominantly, the release of soluble reducing sugars (RSSol) was enhanced after xylanase treatment, while endoglucanase (EG) treatment led to changes in insoluble reducing sugars (RSIns). The maximum synergism was observed for RSIns when a high ratio of endoglucanase to… More > Graphic Abstract

Feng Sheng^1,*, Chen Kong², Chao Li³

International Journal of Mental Health Promotion, Vol.26, No.3, pp. 221-228, 2024, DOI:10.32604/ijmhp.2024.030209

Abstract Objective: This study was conducted to explore the relationships among sedentary behavior (SB), electronic product addiction (EPA), and depression (D) in adolescents during the COVID-19 epidemic. Methods: A total of 604 adolescents (including 309 girls and 295 boys aged 12–18) were selected from Qufu City, Shandong Province, China for three rounds of investigation. The model was constructed using AMOS 23.0 software, and cross-lagged analysis was conducted. Results: SB at T1 can significantly positively predict SB and EPA at T2 (p < 0.05). EPA at T1 can significantly positively predict SB and D at T2 (p < 0.05). Physical activity level… More >

Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3417-3434, 2024, DOI:10.32604/cmes.2024.046944

Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part description of its membership level.… More >

Saima Rashid^1,2,*, Fahd Jarad^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2289-2327, 2024, DOI:10.32604/cmes.2023.028773

Abstract Because of the features involved with their varied kernels, differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues. In this paper, we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels. In this approach, the overall population was separated into five cohorts. Furthermore, the descriptive behavior of the system was investigated, including prerequisites for the positivity of solutions, invariant domain of the solution, presence and stability of equilibrium points, and sensitivity analysis. We included a stochastic element in every cohort and… More >

Dandan Wang, Xiaohong Li, Yanwen Zhang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 355-369, 2024, DOI:10.32604/phyton.2024.047183

Abstract Taxus cuspidata is a rare plant with important medicinal and ornamental value. Aiming at the obvious differences between wild and cultivated populations of T. cuspidata from Northeast China, a total of 61 samples, that is, 33 wild yews and 28 cultivated yews were used to analyze the differences and correlations of the kinship, genetic diversity, and genetic structure between them by specific length amplified fragment sequencing (SLAF-seq). Finally, 470725 polymorphic SLAF tags and 58622 valid SNP markers were obtained. Phylogenetic analysis showed that 61 samples were classified into 2 clusters: wild populations and cultivated populations, and some wild yews were… More >

Laith Abualigah^{1,2,3,4,5,6,*}, Serdar Ekinci⁷, Davut Izci^7,8, Raed Abu Zitar⁹

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 169-183, 2023, DOI:10.32604/iasc.2023.040291

Abstract Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and… More >

Yujie Duan¹, Jianguo Liang^1,*, Jianglin Liu¹, Haifeng Gao¹, Yinhui Li², Jinzhu Zhang¹, Xinyu Wen³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1239-1261, 2024, DOI:10.32604/cmes.2023.044400

Abstract In the fiber winding process, strong disturbance, uncertainty, strong coupling, and fiber friction complicate the winding constant tension control. In order to effectively reduce the influence of these problems on the tension output, this paper proposed a tension fluctuation rejection strategy based on feedforward compensation. In addition to the bias harmonic curve of the unknown state, the tension fluctuation also contains the influence of bounded noise. A tension fluctuation observer (TFO) is designed to cancel the uncertain periodic signal, in which the frequency generator is used to estimate the critical parameter information. Then, the fluctuation signal is reconstructed by a… More >

Samina Amin¹, Muhammad Ali Zeb¹, Hani Alshahrani^2,*, Mohammed Hamdi², Mohammad Alsulami², Asadullah Shaikh³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1167-1202, 2024, DOI:10.32604/cmes.2023.043921

Abstract Social media (SM) based surveillance systems, combined with machine learning (ML) and deep learning (DL) techniques, have shown potential for early detection of epidemic outbreaks. This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance. Since, every year, a large amount of data related to epidemic outbreaks, particularly Twitter data is generated by SM. This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM, along with the ML and DL techniques that have been configured for the… More >