ALEKSANDRA GORNOSTAEVA, LUDMILA BURAVKOVA, MARGARITA LOBANOVA, ELENA ANDREEVA^*

BIOCELL, Vol.48, No.5, pp. 677-692, 2024, DOI:10.32604/biocell.2024.048873

Abstract The structural and associated molecules of the extracellular matrix (ECM) complex is an important component of the local milieu of cells, both for maintaining their functions and homeostasis. It is a dynamic structure that is finely tuned to changes in the microenvironment. One of these factors is hypoxia, which can arise in tissues due to physiological or pathological effects. As a result of the hypoxic effect, the properties of the ECM are significantly modified, stiffness increases, the balance between degradation and synthesis of structural proteins shifts, and the deposition of biologically active mediators’ changes. Hypoxia-inducible factors (HIFs) contribute significantly to… More >

XUAN SHI^1,2, YUFEN WANG¹, CHENYU LI¹, WANGSHU FU³, XINYUE ZHANG³, AIXIA GONG^1,*

BIOCELL, Vol.48, No.5, pp. 835-845, 2024, DOI:10.32604/biocell.2024.048076

Abstract Background: The incidence of colorectal cancer (CRC) has been increasing in recent years. Thus, the discovery of factors that can assist in alleviating CRC is urgently warranted. Methods: To identify a potential factor involved in the development of CRC, we screened the upregulated genes in tumor tissues through four datasets from an online database. The expression of reticulocalbin 1 (RCN1), a Ca-binding protein, was upregulated in the four datasets. Based on loss-of-function experiments, the effect of RCN1 on cell viability was assessed by Cell Counting Kit-8 (CCK-8) assay. The regulatory effect of RCN1 on apoptosis was evaluated through Annexin V-fluorescein… More > Graphic Abstract

JIA SHAO^1,2, CAN ZHANG², YAONAN TANG², AIQIN HE², WEIPEI ZHU^1,*

BIOCELL, Vol.48, No.4, pp. 571-580, 2024, DOI:10.32604/biocell.2024.049092

Abstract Objective: Previous studies indicated that aberrant circular RNA (circRNA) expression affects gene expression regulatory networks, leading to the aberrant activation of tumor pathways and promoting tumor cell growth. However, the expression, clinical significance, and effects on cell propagation, invasion, and dissemination of circRNA_001896 in cervical cancer (CC) tissues remain unclear. Methods: The Gene Expression Omnibus (GEO) datasets (GSE113696 and GSE102686) were used to examine differential circRNA expression in CC and adjacent tissues. The expression of circRNA_001896 was detected in 72 CC patients using fluorescence quantitative PCR. Correlation analysis with clinical pathological features was performed through COX multivariate and univariate analysis.… More >

Teng Wang, Yao Zhang, Jiangguo Liang, Shuai Wang, Shuanggen Liu^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3891-3907, 2024, DOI:10.32604/cmc.2024.048115

Abstract With the widespread data collection and processing, privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals. Support vector machine (SVM) is one of the most elementary learning models of machine learning. Privacy issues surrounding SVM classifier training have attracted increasing attention. In this paper, we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction, called Fed_DPDR-DPML, which greatly improves data utility while providing strong privacy guarantees. Considering in distributed learning scenarios, multiple participants usually hold unbalanced or small amounts of data. Therefore, Fed_DPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted… More >

Xiaohui Cui^1,2,#, Chao Song^1,2,#, Dongmei Li^1,2,*, Xiaolong Qu^1,2, Jiao Long^1,2, Yu Yang^1,2, Hanchao Zhang³

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3603-3618, 2024, DOI:10.32604/cmc.2024.047321

Abstract Named Entity Recognition (NER) stands as a fundamental task within the field of biomedical text mining, aiming to extract specific types of entities such as genes, proteins, and diseases from complex biomedical texts and categorize them into predefined entity types. This process can provide basic support for the automatic construction of knowledge bases. In contrast to general texts, biomedical texts frequently contain numerous nested entities and local dependencies among these entities, presenting significant challenges to prevailing NER models. To address these issues, we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer (RoBGP). Our model… More >

Pengjun Li¹, Qixin Zhao¹, Yingmin Liu¹, Chao Zhong¹, Jinlong Wang^1,*, Zhihan Lyu²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3825-3865, 2024, DOI:10.32604/cmc.2024.046851

Abstract Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order. Amidst the challenges posed by intricate and unpredictable risk factors, knowledge graph technology is effectively driving risk management, leveraging its ability to associate and infer knowledge from diverse sources. This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios. Firstly, employing bibliometric methods, the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge… More >

Yu Zhao, Zhijie Zhou^*, Hongdong Fan, Xiaoxia Han, Jie Wang, Manlin Chen

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 73-91, 2024, DOI:10.32604/iasc.2024.042285

Abstract In industrial production and engineering operations, the health state of complex systems is critical, and predicting it can ensure normal operation. Complex systems have many monitoring indicators, complex coupling structures, non-linear and time-varying characteristics, so it is a challenge to establish a reliable prediction model. The belief rule base (BRB) can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities. Since each indicator of the complex system can reflect the health state to some extent, the BRB is built based on the causal relationship between system indicators and the… More >

Molly Clarke^1,*, Karin Hamann², Nancy Klein², Laura Olivieri³, Yue-Hin Loke²

Congenital Heart Disease, Vol.19, No.1, pp. 5-17, 2024, DOI:10.32604/chd.2024.046328

Abstract Background: Patients with congenital heart disease (CHD) will transition to lifelong adult congenital cardiac care. However, their structural heart disease is challenging to convey via two-dimensional drawings. This study utilized a tele-educational environment, with personalized three-dimensional (3D) modeling and health Details (3D + Details = “4D”), to improve actual and perceived knowledge, both important components of transition readiness in CHD patients. Methods: Participants aged ≥13 years with a history of CHD and cardiac magnetic resonance imaging (MRI) studies were eligible. Cardiac MRI datasets were then used to segment and create 3D heart models (using Mimics, Materialize Inc.). Participants first completed… More >

Abdullah Alsaleh^1,2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 431-449, 2024, DOI:10.32604/csse.2023.043107

Abstract With the increasing number of connected devices in the Internet of Things (IoT) era, the number of intrusions is also increasing. An intrusion detection system (IDS) is a secondary intelligent system for monitoring, detecting and alerting against malicious activity. IDS is important in developing advanced security models. This study reviews the importance of various techniques, tools, and methods used in IoT detection and/or prevention systems. Specifically, it focuses on machine learning (ML) and deep learning (DL) techniques for IDS. This paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of Vehicles. To speed… More >

Xiaohui Yang, Kun Zhang^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1843-1859, 2024, DOI:10.32604/cmc.2023.047660

Abstract Data is regarded as a valuable asset, and sharing data is a prerequisite for fully exploiting the value of data. However, the current medical data sharing scheme lacks a fair incentive mechanism, and the authenticity of data cannot be guaranteed, resulting in low enthusiasm of participants. A fair and trusted medical data trading scheme based on smart contracts is proposed, which aims to encourage participants to be honest and improve their enthusiasm for participation. The scheme uses zero-knowledge range proof for trusted verification, verifies the authenticity of the patient’s data and the specific attributes of the data before the transaction,… More >