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  • Open Access

    ARTICLE

    A Deep Learning Based Sentiment Analytic Model for the Prediction of Traffic Accidents

    Nadeem Malik1,*, Saud Altaf1, Muhammad Usman Tariq2, Ashir Ahmed3, Muhammad Babar4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1599-1615, 2023, DOI:10.32604/cmc.2023.040455

    Abstract The severity of traffic accidents is a serious global concern, particularly in developing nations. Knowing the main causes and contributing circumstances may reduce the severity of traffic accidents. There exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter, blogs and Facebook. Although such approaches are popular, there exists an issue of data management and low prediction accuracy. This article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory (XLNet-Bi-LSTM) to predict traffic collisions based on data collected from… More >

  • Open Access

    ARTICLE

    Diagnostic and classification value of immune-related lncRNAs in dilated cardiomyopathy

    CONGCHEN BAI1, QIHANG KONG2, HAO TANG2, SHUWEN ZHANG2, JUNTENG ZHOU3,*, XIAOJING LIU2,4,*

    BIOCELL, Vol.47, No.11, pp. 2517-2533, 2023, DOI:10.32604/biocell.2023.043864

    Abstract Background: Various physiological mechanisms are linked to dilated cardiomyopathy (DCM) development, including oxidative stress, immune irregularities, inflammation, fibrosis, and genetic changes. However, precise molecular drivers of DCM, especially regarding abnormal immune responses, remain unclear. This study investigates immune-related long non-coding RNAs (lncRNAs) in DCM’s diagnostic and therapeutic potential. Methods: GSE141910, GSE135055, and GSE165303 datasets were acquired from the GEO database. LASSO, SVM-RFE, and random forest algorithms identified DCM-associated immune-related lncRNAs. Diagnostic capabilities were assessed by Nomogram and receiver operating characteristic (ROC) curves. Multivariate linear regression explored lncRNA correlations with ejection fraction. Single-sample gene set enrichment analysis (ssGSEA) gauged immune cell… More > Graphic Abstract

    Diagnostic and classification value of immune-related lncRNAs in dilated cardiomyopathy

  • Open Access

    ARTICLE

    FGD5 as a novel prognostic biomarker and its association with immune infiltrates in lung adenocarcinoma

    ZHONGXIANG TANG1,2, LILI WANG1,2, GUOJUN WU1,2, LING QIN1,2,*, YURONG TAN1,2,*

    BIOCELL, Vol.47, No.11, pp. 2503-2516, 2023, DOI:10.32604/biocell.2023.031565

    Abstract Background: Non-small cell lung cancer (NSCLC) has a poor prognosis with a low 5-year survival rate. Lung adenocarcinoma (LUAD) accounts for 50%. Facio-genital dysplasia-5 (FGD5), a member of a subfamily of Rho GTP-GDP exchange factors, may be a good molecular biomarker for diagnosis and prognosis. Objective: To explore the clinical application of FGD5, the study was designed to investigate the prognosis value of FGD5 expression and its correlation with immune infiltrates in LUAD patients. Methods: Through the Wilcoxon signed-rank test and logistic regression, the correlation between clinical characteristics and FGD5 expression was analyzed. Kaplan–Meier plotter analysis, Cox regression, and a… More > Graphic Abstract

    FGD5 as a novel prognostic biomarker and its association with immune infiltrates in lung adenocarcinoma

  • Open Access

    REVIEW

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

    PRIYADHARSHINI THANJAVUR SRIRAMAMOORTHI1,2, GAYATHRI GOPAL1,2, SHIBI MURALIDAR1,2, SAI RAMANAN ESWARAN1,2, DANUSH NARAYAN PANNEERSELVAM1,2, BHUVANESWARAN MEIYANATHAN1,2, SRICHANDRASEKAR THUTHIKKADU INDHUPRAKASH1,2, SENTHIL VISAGA AMBI1,2,*

    BIOCELL, Vol.47, No.11, pp. 2335-2350, 2023, DOI:10.32604/biocell.2023.029379

    Abstract The novel coronavirus pneumonia (COVID-19) is spreading worldwide and threatening people greatly. The routes by which SARS-CoV-2 causes lung injury have grown to be a major concern in the scientific community since patients with new Coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV-2) have a high likelihood of developing acute respiratory distress syndrome (ARDS) in severe cases. The mortality rate of COVID-19 has increased over the period due to rapid spread, and it becomes crucial to understand the disease epidemiology, pathogenic mechanisms, and suitable treatment strategies. ARDS is a respiratory disorder and is one of the clinical manifestations observed in patients… More > Graphic Abstract

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

  • Open Access

    ARTICLE

    TonEBP expression is essential in the IL-1β–induced migration and invasion of human A549 lung cancer cells

    HEE JU SONG, TAEHEE KIM, HAN NA CHOI, SOO JIN KIM, SANG DO LEE*

    Oncology Research, Vol.32, No.1, pp. 151-161, 2024, DOI:10.32604/or.2023.030690

    Abstract Lung cancer has the highest mortality rate among all cancers, in part because it readily metastasizes. The tumor microenvironment, comprising blood vessels, fibroblasts, immune cells, and macrophages [including tumor-associated macrophages (TAMs)], is closely related to cancer cell growth, migration, and invasion. TAMs secrete several cytokines, including interleukin (IL)-1β, which participate in cancer migration and invasion. p21-activated kinase 1 (PAK1), an important signaling molecule, induces cell migration and invasion in several carcinomas. Tonicity-responsive enhancer-binding protein (TonEBP) is also known to participate in cancer cell growth, migration, and invasion. However, the mechanisms by which it increases lung cancer migration remain unclear. Therefore,… More > Graphic Abstract

    TonEBP expression is essential in the IL-1β–induced migration and invasion of human A549 lung cancer cells

  • Open Access

    ARTICLE

    An Efficient Character-Level Adversarial Attack Inspired by Textual Variations in Online Social Media Platforms

    Jebran Khan1, Kashif Ahmad2, Kyung-Ah Sohn1,3,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2869-2894, 2023, DOI:10.32604/csse.2023.040159

    Abstract In recent years, the growing popularity of social media platforms has led to several interesting natural language processing (NLP) applications. However, these social media-based NLP applications are subject to different types of adversarial attacks due to the vulnerabilities of machine learning (ML) and NLP techniques. This work presents a new low-level adversarial attack recipe inspired by textual variations in online social media communication. These variations are generated to convey the message using out-of-vocabulary words based on visual and phonetic similarities of characters and words in the shortest possible form. The intuition of the proposed scheme is to generate adversarial examples… More >

  • Open Access

    ARTICLE

    Fast and Accurate Detection of Masked Faces Using CNNs and LBPs

    Sarah M. Alhammad1, Doaa Sami Khafaga1,*, Aya Y. Hamed2, Osama El-Koumy3, Ehab R. Mohamed3, Khalid M. Hosny3

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2939-2952, 2023, DOI:10.32604/csse.2023.041011

    Abstract Face mask detection has several applications, including real-time surveillance, biometrics, etc. Identifying face masks is also helpful for crowd control and ensuring people wear them publicly. With monitoring personnel, it is impossible to ensure that people wear face masks; automated systems are a much superior option for face mask detection and monitoring. This paper introduces a simple and efficient approach for masked face detection. The architecture of the proposed approach is very straightforward; it combines deep learning and local binary patterns to extract features and classify them as masked or unmasked. The proposed system requires hardware with minimal power consumption… More >

  • Open Access

    ARTICLE

    Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

    Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

  • Open Access

    REVIEW

    The bacterial small RNAs: The new biomarkers of oral microbiota-associated cancers and diseases

    MENGYING MAO1,2,3,#, TING DONG1,2,3,#, YANJING LIANG3,4, KEYONG YUAN1,2,3, QIAOQIAO JIN1,2,3, PENGFEI ZHANG1,2,3, ZHENGWEI HUANG1,2,3,*

    BIOCELL, Vol.47, No.10, pp. 2187-2193, 2023, DOI:10.32604/biocell.2023.042357

    Abstract The oral microbiota is a vital part of the human microbiota that functions in various physiological processes and is highly relevant to cancers and other diseases. With the alterations of host immune competence, the homeostatic balance existing between the oral microbiota and host may be disturbed and result in the development of diseases. Numerous observations have suggested that small RNAs are key regulators of bacterial pathogenesis and bacteria-host interactions. Further, bacterial small RNAs are considered to be promising biomarkers for the development of novel, and efficacious therapies for oral dysbiosis. Mechanistic insights into how oral pathogens communicate with other bacteria… More > Graphic Abstract

    The bacterial small RNAs: The new biomarkers of oral microbiota-associated cancers and diseases

  • Open Access

    REVIEW

    Cancer-associated fibroblasts of colorectal cancer: Translational prospects in liquid biopsy and targeted therapy

    ELYN AMIELA SALLEH1, YEONG YEH LEE2, ANDEE DZULKARNAEN ZAKARIA3, NUR ASYILLA CHE JALIL4, MARAHAINI MUSA1,*

    BIOCELL, Vol.47, No.10, pp. 2233-2244, 2023, DOI:10.32604/biocell.2023.030541

    Abstract Colorectal cancer (CRC) is a major global health concern. Accumulation of cancer-associated fibroblasts (CAFs) in CRC is associated with poor prognosis and disease recurrence. CAFs are the main cellular component of the tumor microenvironment. CAF-tumor cell interplay, which is facilitated by various secretomes, drives colorectal carcinogenesis. The complexity of CAF populations contributes to the heterogeneity of CRC and influences patient survival and treatment response. Due to their significant roles in colorectal carcinogenesis, different clinical applications utilizing or targeting CAFs have been suggested. Circulating CAFs (cCAFs) which can be detected in blood samples, have been proposed to help in determining patient… More > Graphic Abstract

    Cancer-associated fibroblasts of colorectal cancer: Translational prospects in liquid biopsy and targeted therapy

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