HONGYUAN LIANG^1,#, YANQIU LI^2,#, YONGGANG QU³, LINGYUN ZHANG^4,*

Oncology Research, Vol.32, No.2, pp. 393-407, 2024, DOI:10.32604/or.2023.031134

Abstract Advanced LUAD shows limited response to treatment including immune therapy. With the development of sequencing omics, it is urgent to combine high-throughput multi-omics data to identify new immune checkpoint therapeutic response markers. Using GSE72094 (n = 386) and GSE31210 (n = 226) gene expression profile data in the GEO database, we identified genes associated with lung adenocarcinoma (LUAD) death using tools such as “edgeR” and “maftools” and visualized the characteristics of these genes using the “circlize” R package. We constructed a prognostic model based on death-related genes and optimized the model using LASSO-Cox regression methods. By calculating the cell death… More >

JUAN SHEN^1,#, WEIYU ZHANG^2,3,#, QINQIN JIN^2,3,#, FUYU GONG^4,#, HEPING ZHANG⁵, HONGLIANG XU⁵, JIEJIE LI^2,3, HUI YAO^2,3, XIYA JIANG^2,3, YINTING YANG^2,3, LIN HONG^2,3, JIE MEI^2,3, YANG SONG^6,*, SHUGUANG ZHOU^2,3,7,*

Oncology Research, Vol.32, No.2, pp. 339-351, 2024, DOI:10.32604/or.2023.030887

Abstract Background: Invasive breast carcinoma (BRCA) is associated with poor prognosis and high risk of mortality. Therefore, it is critical to identify novel biomarkers for the prognostic assessment of BRCA. Methods: The expression data of polo-like kinase 1 (PLK1) in BRCA and the corresponding clinical information were extracted from TCGA and GEO databases. PLK1 expression was validated in diverse breast cancer cell lines by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. Single sample gene set enrichment analysis (ssGSEA) was performed to evaluate immune infiltration in the BRCA microenvironment, and the random forest (RF) and support vector machine (SVM) algorithms… More >

Muhammad Mumtaz Ali, Faiqa Maqsood, Shiqi Liu, Weiyan Hou, Liying Zhang, Zhenfei Wang^*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2699-2714, 2023, DOI:10.32604/cmc.2023.045310

Abstract Breast cancer, particularly Invasive Ductal Carcinoma (IDC), is a primary global health concern predominantly affecting women. Early and precise diagnosis is crucial for effective treatment planning. Several AI-based techniques for IDC-level classification have been proposed in recent years. Processing speed, memory size, and accuracy can still be improved for better performance. Our study presents ECAM, an Enhanced Channel-Wise Attention Mechanism, using deep learning to analyze histopathological images of Breast Invasive Ductal Carcinoma (BIDC). The main objectives of our study are to enhance computational efficiency using a Separable CNN architecture, improve data representation through hierarchical feature aggregation, and increase accuracy and… More >

Ming Wan¹, Minglei Hao¹, Jiawei Li¹, Jiangyuan Yao^2,*, Yan Song³

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3573-3592, 2023, DOI:10.32604/cmc.2023.044857

Abstract The process control-oriented threat, which can exploit OT (Operational Technology) vulnerabilities to forcibly insert abnormal control commands or status information, has become one of the most devastating cyber attacks in industrial automation control. To effectively detect this threat, this paper proposes one functional pattern-related anomaly detection approach, which skillfully collaborates the BinSeg (Binary Segmentation) algorithm with FSM (Finite State Machine) to identify anomalies between measuring data and control data. By detecting the change points of measuring data, the BinSeg algorithm is introduced to generate some initial sequence segments, which can be further classified and merged into different functional patterns due… More >

Manjur Kolhar^*, Sultan Mesfer Aldossary

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2857-2879, 2023, DOI:10.32604/cmc.2023.042726

Abstract In many commercial and public sectors, the Internet of Things (IoT) is deeply embedded. Cyber security threats aimed at compromising the security, reliability, or accessibility of data are a serious concern for the IoT. Due to the collection of data from several IoT devices, the IoT presents unique challenges for detecting anomalous behavior. It is the responsibility of an Intrusion Detection System (IDS) to ensure the security of a network by reporting any suspicious activity. By identifying failed and successful attacks, IDS provides a more comprehensive security capability. A reliable and efficient anomaly detection system is essential for IoT-driven decision-making.… More >

Muhammad Suleman¹, Faizan Ullah¹, Ghadah Aldehim^2,*, Dilawar Shah¹, Mohammad Abrar^1,3, Asma Irshad⁴, Sarra Ayouni²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3533-3549, 2023, DOI:10.32604/cmc.2023.042365

Abstract The early detection of skin cancer, particularly melanoma, presents a substantial risk to human health. This study aims to examine the necessity of implementing efficient early detection systems through the utilization of deep learning techniques. Nevertheless, the existing methods exhibit certain constraints in terms of accessibility, diagnostic precision, data availability, and scalability. To address these obstacles, we put out a lightweight model known as Smart MobiNet, which is derived from MobileNet and incorporates additional distinctive attributes. The model utilizes a multi-scale feature extraction methodology by using various convolutional layers. The ISIC 2019 dataset, sourced from the International Skin Imaging Collaboration,… More >

SHIDA HOU^1,#, TIANJUN LAN^2,#, YAOCHENG YANG^3,#, PEISHENG LIANG¹, XIN LIU^4,5, JUNJIE WANG⁶, ZHIFENG CHEN⁷, RONGSHENG ZENG^1,*, ZIJING HUANG^8,*

BIOCELL, Vol.47, No.12, pp. 2641-2660, 2023, DOI:10.32604/biocell.2023.043291

Abstract Background: 5-Methylcytosine (m5C) methylation contributes to the development and progression of various malignant tumors. This study aimed to explore the potential role of m5C methylation regulators (m5CMRs) in head and neck squamous cell carcinoma (HNSCC). Methods: The transcription data of HNSCC samples were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Subsequently, the m5C patterns in HNSCC were evaluated based on 14 m5CMRs. Then, the m5Cscore was developed to quantify m5C patterns by using principal component analysis (PCA) algorithms. Two single-cell RNA sequencing datasets and various methods were employed to assess the prognostic value… More >

JIE DUAN, AIDONG GU^*, WEI CHEN, CHANGHAO CHEN, FANGNAN SONG, FAXI CHEN, FANGFANG JIANG, HUIWEN XING

BIOCELL, Vol.47, No.12, pp. 2609-2615, 2023, DOI:10.32604/biocell.2023.042472

Abstract Objective: This study aims to analyze the clinical significance and mechanism of nuclear factor erythroid 2-related factor 2 (NRF2) and glutathione peroxidase 4 (GPX4) in primary hepatic carcinoma (PHC). Methods: The expression of NRF2 and GPX4 in peripheral blood of patients with PHC was determined to analyze the diagnostic value of the two combined for PHC. The prognostic significance of NRF2 and GPX4 was evaluated by 3-year follow-up. Human liver epithelial cells THLE-2 and human hepatocellular carcinoma cells HepG2 were purchased, and the expression of NRF2 and GPX4 in the cells was determined. NRF2 and GPX4 aberrant expression vectors were… More > Graphic Abstract

Keunhan Park^a,∗, Zhuomin Zhang^b

Frontiers in Heat and Mass Transfer, Vol.4, No.1, pp. 1-26, 2013, DOI:10.5098/hmt.v4.1.3001

Abstract This article reviews the recent advances in near-field radiative energy transfer, particularly in its fundamentals and applications. When the geometrical features of radiating objects or their separating distances fall into the sub-wavelength range, near-field phenomena such as photon tunneling and surface polaritons begin to play a key role in energy transfer. The resulting heat transfer rate can greatly exceed the blackbody radiation limit by several orders magnitude. This astonishing feature cannot be conveyed by the conventional theory of thermal radiation, generating strong demands in fundamental research that can address thermal radiation in the near field. Important breakthroughs of near-field thermal… More >

Wei Zhang¹, Ping He^2,*, Ting Li², Fan Yang¹, Ying Liu³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1893-1910, 2023, DOI:10.32604/cmc.2023.044253

Abstract Some reconstruction-based anomaly detection models in multivariate time series have brought impressive performance advancements but suffer from weak generalization ability and a lack of anomaly identification. These limitations can result in the misjudgment of models, leading to a degradation in overall detection performance. This paper proposes a novel transformer-like anomaly detection model adopting a contrastive learning module and a memory block (CLME) to overcome the above limitations. The contrastive learning module tailored for time series data can learn the contextual relationships to generate temporal fine-grained representations. The memory block can record normal patterns of these representations through the utilization of… More >