WEIXUE WANG^#, TONGTONG WANG^#, YAN ZHANG, TING DENG, HAIYANG ZHANG^*, YI BA^*

Oncology Research, Vol.32, No.3, pp. 489-502, 2024, DOI:10.32604/or.2023.046676

Abstract Different from necrosis, apoptosis, autophagy and other forms of cell death, ferroptosis is a mechanism that catalyzes lipid peroxidation of polyunsaturated fatty acids under the action of iron divalent or lipoxygenase, leading to cell death. Apatinib is currently used in the third-line standard treatment of advanced gastric cancer, targeting the anti-angiogenesis pathway. However, Apatinib-mediated ferroptosis in vascular endothelial cells has not been reported yet. Tumor-secreted exosomes can be taken up into target cells to regulate tumor development, but the mechanism related to vascular endothelial cell ferroptosis has not yet been discovered. Here, we show that exosomes secreted by gastric cancer… More >

DAOLUN YU¹, DEYONG SHE², KAI GE¹, LEI YANG¹, RUINA ZHAN¹, SHAN LU^3,*, YAFEI CAI^4,*

BIOCELL, Vol.48, No.1, pp. 139-147, 2024, DOI:10.32604/biocell.2023.045884

Abstract Background: SMAD family proteins (SMADs) are crucial transcription factors downstream of transforming growth factor beta (TGF-ß)/SMAD signaling pathways that have been reported to play a pivotal role in mammalian reproduction. However, the role of SMAD family member 8 (SMAD8, also known as SMAD9), a member of the SMAD family, in mammalian reproduction remains unclear. Methods: We employed RNA interference techniques to knock down Smad8 expression in mouse granulosa cells (GCs) to investigate the effects of Smad8 on GC growth and steroidogenesis. Results: Our findings revealed a significant decrease in the proliferative capacity and a substantial increase in the apoptosis rate… More >

Zahid Farooq Khan¹, Muhammad Ramzan^1,*, Mudassar Raza¹, Muhammad Attique Khan^2,3, Khalid Iqbal⁴, Taerang Kim⁵, Jae-Hyuk Cha⁵

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1207-1225, 2024, DOI:10.32604/cmc.2023.045491

Abstract Accurate detection and classification of artifacts within the gastrointestinal (GI) tract frames remain a significant challenge in medical image processing. Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases. Key to this is the development of robust algorithms for image classification and detection, crucial in designing sophisticated systems for diagnosis and treatment. This study makes a small contribution to endoscopic image classification. The proposed approach involves multiple operations, including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception. Additionally, feature optimization utilizes the binary dragonfly algorithm… More >

Lu Chen^1,#, Huaqiang Chen^2,#, Zhikai Pan⁷, Sheng Xu², Guangsheng Lai², Shuwen Chen^2,5,6, Shuihua Wang^3,8, Xiaodong Gu^2,6,*, Yudong Zhang^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 361-382, 2024, DOI:10.32604/cmes.2023.031229

Abstract Aim: This study aims to establish an artificial intelligence model, ThyroidNet, to diagnose thyroid nodules using deep learning techniques accurately. Methods: A novel method, ThyroidNet, is introduced and evaluated based on deep learning for the localization and classification of thyroid nodules. First, we propose the multitask TransUnet, which combines the TransUnet encoder and decoder with multitask learning. Second, we propose the DualLoss function, tailored to the thyroid nodule localization and classification tasks. It balances the learning of the localization and classification tasks to help improve the model’s generalization ability. Third, we introduce strategies for augmenting the data. Finally, we submit… More >

Abdul Haseeb¹, Muhammad Attique Khan^2,*, Majed Alhaisoni³, Ghadah Aldehim⁴, Leila Jamel⁴, Usman Tariq⁵, Taerang Kim⁶, Jae-Hyuk Cha⁶

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3895-3920, 2023, DOI:10.32604/cmc.2023.045244

Abstract Diagnosing gastrointestinal cancer by classical means is a hazardous procedure. Years have witnessed several computerized solutions for stomach disease detection and classification. However, the existing techniques faced challenges, such as irrelevant feature extraction, high similarity among different disease symptoms, and the least-important features from a single source. This paper designed a new deep learning-based architecture based on the fusion of two models, Residual blocks and Auto Encoder. First, the Hyper-Kvasir dataset was employed to evaluate the proposed work. The research selected a pre-trained convolutional neural network (CNN) model and improved it with several residual blocks. This process aims to improve… 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

Mamona Arshad¹, Ahmad Karim¹, Salman Naseer², Shafiq Ahmad³, Mejdal Alqahtani³, Akber Abid Gardezi⁴, Muhammad Shafiq^5,*, Jin-Ghoo Choi⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2123-2135, 2023, DOI:10.32604/cmc.2022.028680

Abstract The exponential growth in the development of smartphones and handheld devices is permeated due to everyday activities i.e., games applications, entertainment, online banking, social network sites, etc., and also allow the end users to perform a variety of activities. Because of activities, mobile devices attract cybercriminals to initiate an attack over a diverse range of malicious activities such as theft of unauthorized information, phishing, spamming, Distributed Denial of Services (DDoS), and malware dissemination. Botnet applications are a type of harmful attack that can be used to launch malicious activities and has become a significant threat in the research area. A… More >

Nida Aslam^1,*, Irfan Ullah Khan², Salma Abdulrahman Bader², Aisha Alansari³, Lama Abdullah Alaqeel², Razan Mohammed Khormy², Zahra Abdultawab AlKubaish², Tariq Hussain^4,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3167-3188, 2023, DOI:10.32604/cmc.2023.039721

Abstract One of the most widely used smartphone operating systems, Android, is vulnerable to cutting-edge malware that employs sophisticated logic. Such malware attacks could lead to the execution of unauthorized acts on the victims’ devices, stealing personal information and causing hardware damage. In previous studies, machine learning (ML) has shown its efficacy in detecting malware events and classifying their types. However, attackers are continuously developing more sophisticated methods to bypass detection. Therefore, up-to-date datasets must be utilized to implement proactive models for detecting malware events in Android mobile devices. Therefore, this study employed ML algorithms to classify Android applications into malware… More >

YAN ZHENG^1,2, SIHUI MA^3,4,*, KATSUHIKO SUZUKI⁴, HISANORI KATO³, HUIJUAN JIA^3,*

BIOCELL, Vol.47, No.8, pp. 1897-1906, 2023, DOI:10.32604/biocell.2023.027632

Abstract Mental disorders such as depression and anxiety inflict significant burdens on individuals and society. Commonly prescribed treatments often involve cognitive therapy and medications. However, for patients resistant to these conventional methods, alternative therapies like the Ketogenic Diet (KD) offer a promising avenue. KD and its key metabolite, β-hydroxybutyrate (BHB), have been hypothesized to alleviate mental disorders through anti-inflammatory actions, a crucial pathway in the pathophysiology of depression. This mini-review examines 15 clinical trials exploring the influence of KD and BHB on inflammation and their potential roles in managing mental disorders. Both human and animal studies were scrutinized to elucidate possible… More >

Madallah Alruwaili^1,*, Muhammad Hameed Siddiqi¹, Kamran Farid², Mohammad Azad¹, Saad Alanazi¹, Asfandyar Khan², Abdullah Khan²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2293-2311, 2023, DOI:10.32604/csse.2023.040312

Abstract Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate, ECG, nasal/oral airflow, temperature, light sensor, and fall detection sensor. Different researchers have done different work in the field of health monitoring with sensor networks. Different researchers used built-in apps, such as some used a small number of parameters, while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate, and outdated tools for study development. While no efficient, cheap, and updated work is proposed in the field of sensor-based health monitoring systems. Therefore, this study developed… More >