TIANZHU LI^1,#, YU ZHANG^2,#, TONG ZHANG^2,#, YANNAN LI², HUI XUE², JINGLONG CAO², WENSHUANG HOU², YINGHUA LUO^3,*, CHENGHAO JIN^2,4,*,

BIOCELL, Vol.47, No.1, pp. 195-204, 2023, DOI:10.32604/biocell.2023.025593 - 26 September 2022

Abstract Schisandrin B (Sch B) is a monomer with anti-cancer and anti-inflammatory effects, which are isolated from the plant Schisandra chinensis (Turcz) Baillon. We investigated the anti-gastric cancer (GC) effects of Sch B and its underlying molecular mechanisms. The Cell Counting Kit-8 assay was used to determine the effects of Sch B on the viability of GC and normal cell lines. Hoechst/propidium iodide staining and flow cytometry were used to assess the apoptosis induction of Sch B. Western blotting was used to evaluate the effects of Sch B on downstream apoptotic proteins. The DCFH-DA fluorescent probe was… More >

TIANXING LIU¹, HONGYAN DIAO^2,*

BIOCELL, Vol.47, No.1, pp. 27-32, 2023, DOI:10.32604/biocell.2022.023568 - 26 September 2022

Abstract Non-coding RNAs are speculated to exert important regulatory functions at the level of gene expression, oncogenesis, and many other pathologies. Hepatitis B virus (HBV) infection is a leading cause of hepatocellular carcinoma (HCC), and some studies have shown that the expression of non-coding RNAs has an assignable effect on the development of HBV-induced HCC. In this context, the functions and molecular mechanisms of the HBVinduced non-coding RNA expression in the development of hepatoma have attracted increasing attention. This review covers the progress in the exploration of the relationship between HBV-induced hepatoma and non-coding RNA expression, More >

BINFEN HOU¹, LI ZHAO¹, T IANHAO ZHAO¹, MINGMING YANG¹, WANWAN ZHU¹, XIAODONG CHEN², XIQUAN KE¹, ZHENZENG MA¹, LIN GU¹, MENG WANG¹, MIN DENG^1,*

BIOCELL, Vol.47, No.1, pp. 175-186, 2023, DOI:10.32604/biocell.2022.021359 - 26 September 2022

Abstract Aim: Gastric cancer (GC) is one of the most common malignant tumors. Chrysophanol has been reported to possess antitumor effects on a variety of cancers; however, its role in GC remains unclear. This study aimed to investigate the effects of chrysophanol on the proliferation, pyroptosis, migration, and invasion of GC cells. Methods: Human GC cell lines MKN 28 and AGS cells were treated with different concentrations of chrysophanol, then cell proliferation, migration, invasion and pyroptosis were determined by CCK-8, colony-forming assay, wound healing assay, Transwell assay, and flow cytometry. Cell migration and invasion were reassessed in… More >

Iftikhar Naseer^1,*, Tehreem Masood¹, Sheeraz Akram¹, Arfan Jaffar¹, Muhammad Rashid², Muhammad Amjad Iqbal³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2039-2054, 2023, DOI:10.32604/cmc.2023.032927 - 22 September 2022

Abstract Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the lung. It is mostly caused by the instinctive growth of cells in the lung. Lung nodule detection has a significant role in detecting and screening lung cancer in Computed tomography (CT) scan images. Early detection plays an important role in the survival rate and treatment of lung cancer patients. Moreover, pulmonary nodule classification techniques based on the convolutional neural network can be used for the accurate and efficient detection of lung cancer. This work proposed an automatic… More >

S. Ayshwarya Lakshmi^1,*, K. Anandavelu²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3403-3413, 2023, DOI:10.32604/iasc.2023.030970 - 17 August 2022

Abstract Skin cancer segmentation is a critical task in a clinical decision support system for skin cancer detection. The suggested enhanced cuckoo search based optimization model will be used to evaluate several metrics in the skin cancer picture segmentation process. Because time and resources are always limited, the proposed enhanced cuckoo search optimization algorithm is one of the most effective strategies for dealing with global optimization difficulties. One of the most significant requirements is to design optimal solutions to optimize their use. There is no particular technique that can answer all optimization issues. The proposed enhanced… More >

S. Priya^1,*, N. K. Karthikeyan¹, D. Palanikkumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2673-2685, 2023, DOI:10.32604/iasc.2023.028599 - 17 August 2022

Abstract In recent years, cervical cancer is one of the most common diseases which occur in any woman regardless of any age. This is the deadliest disease since there were no symptoms shown till it is diagnosed to be the last stage. For women at a certain age, it is better to have a proper screening for cervical cancer. In most underdeveloped nations, it is very difficult to have frequent scanning for cervical cancer. Data Mining and machine learning methodologies help widely in finding the important causes for cervical cancer. The proposed work describes a multi-class More >

Mesfer Al Duhayyim^1,*, Areej A. Malibari², Sami Dhahbi³, Mohamed K. Nour⁴, Isra Al-Turaiki⁵, Marwa Obayya⁶, Abdullah Mohamed⁷

Computer Systems Science and Engineering, Vol.45, No.1, pp. 753-767, 2023, DOI:10.32604/csse.2023.030556 - 16 August 2022

Abstract Recently, computer aided diagnosis (CAD) model becomes an effective tool for decision making in healthcare sector. The advances in computer vision and artificial intelligence (AI) techniques have resulted in the effective design of CAD models, which enables to detection of the existence of diseases using various imaging modalities. Oral cancer (OC) has commonly occurred in head and neck globally. Earlier identification of OC enables to improve survival rate and reduce mortality rate. Therefore, the design of CAD model for OC detection and classification becomes essential. Therefore, this study introduces a novel Computer Aided Diagnosis for… More >

Sindhuja Manickavasagam^1,*, Poonkuzhali Sugumaran²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 939-953, 2023, DOI:10.32604/csse.2023.030491 - 16 August 2022

Abstract The combination of machine learning (ML) approaches in healthcare is a massive advantage designed at curing illness of millions of persons. Several efforts are used by researchers for detecting and providing primary phase insights as to cancer analysis. Lung cancer remained the essential source of disease connected mortality for both men as well as women and their frequency was increasing around the world. Lung disease is the unrestrained progress of irregular cells which begin off in one or both Lungs. The previous detection of cancer is not simpler procedure however if it can be detected,… More >

Mahmoud Ragab^1,2,3,*, Jaber Alyami^4,5

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2309-2322, 2023, DOI:10.32604/csse.2023.026877 - 01 August 2022

Abstract Liver cancer is one of the major diseases with increased mortality in recent years, across the globe. Manual detection of liver cancer is a tedious and laborious task due to which Computer Aided Diagnosis (CAD) models have been developed to detect the presence of liver cancer accurately and classify its stages. Besides, liver cancer segmentation outcome, using medical images, is employed in the assessment of tumor volume, further treatment plans, and response monitoring. Hence, there is a need exists to develop automated tools for liver cancer detection in a precise manner. With this motivation, the… More >

Saleem Mustafa¹, Arfan Jaffar¹, Muhammad Waseem Iqbal^2,*, Asma Abubakar², Abdullah S. Alshahrani³, Ahmed Alghamdi⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2205-2218, 2023, DOI:10.32604/iasc.2023.029549 - 19 July 2022

Abstract Melanoma is of the lethal and rare types of skin cancer. It is curable at an initial stage and the patient can survive easily. It is very difficult to screen all skin lesion patients due to costly treatment. Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders, pigment networks, and the color of melanoma. These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease. The trained clinicians can overcome the issues such as low contrast, lesions varying in size,… More >