RUYU YAN^1,#, JUNJIE WANG^1,#, MINXIA LIU², KECHENG ZHOU^1,3,*

BIOCELL, Vol.46, No.10, pp. 2159-2165, 2022, DOI:10.32604/biocell.2022.021107

Abstract Emerging cohorts and basic studies have associated certain genetic modifications in cancer patients, such as gene mutation, amplification, or deletion, with the overall survival prognosis, underscoring patients’ genetic background may directly regulate drug sensitivity/resistance during chemotherapies. Understanding the molecular mechanism underpinning drug sensitivity/resistance and further uncovering the effective drugs have been the major ambition in the cancer drug discovery. The emergence and popularity of CRISPR/Cas9 technology have reformed the entire life science research, providing a precise and simplified genome editing tool with unlimited editing possibilities. Furthermore, it presents a powerful tool in cancer drug discovery, More >

MENGMENG LIU^1,#, YUE PAN^1,2,#, XUFENG TAO¹, WENLI KANG¹, YINGJIE LIU¹, YONGJIE YANG^3,4,*, GARY GUISHAN XIAO^1,*

BIOCELL, Vol.46, No.10, pp. 2257-2265, 2022, DOI:10.32604/biocell.2022.020325

Abstract Pancreatic ductal adenocarcinoma (PDAC) is universally acknowledged as the cancer with the highest mortality rate. Berberine has high medicinal value and has been used as an anti-cancer agent. Hence the purpose of this study was to investigate the anti-cancer effect of berberine in PDAC. Berberine was shown to have a selective anti-cancer effect on PDAC by MTT assay in vitro. Pancreatic cancer stem cells (PCSCs), regulated by epithelial–mesenchymal transition (EMT), could promote the proliferation of PDAC cells. However, berberine suppressed the proliferation and stemness of PCSCs through immunofluorescence staining, stem cell sphere assays and so forth in More >

GIUSEPPE STEFANO NETTI^1,*, FEDERICA SPADACCINO¹, VALERIA CATALANO¹, GIUSEPPE CASTELLANO², GIOVANNI STALLONE³, ELENA RANIERI¹

BIOCELL, Vol.46, No.10, pp. 2235-2239, 2022, DOI:10.32604/biocell.2022.020209

Abstract Pentraxin-3 (PTX3), the prototype of long pentraxins, seems to influence complement system (CS) modulation. PTX3 and CS sustain carcinogenesis, enriching tumor microenvironment (TME) with pro-inflammatory molecules promoting angiogenesis in prostate cancer (PC) and renal cell carcinoma (RCC). Furthermore, cancer cells overexpress complement regulatory proteins, such as CD46, CD55 and CD59, which negatively affect complement pathways for support cancer cells survival. This viewpoint aims to elucidate the ambivalent role of PTX3 and the CS in the context of tumor microenvironment (TME). More >

ISABELLA PANFOLI^1,*, MAURIZIO BRUSCHI², GIOVANNI CANDIANO²

BIOCELL, Vol.46, No.10, pp. 2167-2176, 2022, DOI:10.32604/biocell.2022.020154

Abstract Precision medicine is based on the identification of biomarkers of tumor development and progression. Liquid biopsy is at the forefront of the ability to gather diagnostic and prognostic information on tumors, as it can be noninvasively performed prior or during treatment. Liquid biopsy mostly utilizes circulating tumor cells, or free DNA, but also exosomes. The latter are nanovesicles secreted by most cell types, found in any body fluid that deliver proteins, nucleic acids and lipids to nearby and distant cells with a unique homing ability. Exosomes function in signalling between the tumor microenvironment and the… More >

NADIRE ÖZENVER^1,2, THOMAS EFFERTH^2,*

BIOCELL, Vol.46, No.10, pp. 2151-2157, 2022, DOI:10.32604/biocell.2022.019937

Abstract Carnosic acid (CA) is a natural phenolic diterpene mainly occurring in some species of the Lamiaceae family. Numerous studies described the cytotoxicity of CA towards different types of cancer both in vitro and in vivo. Particularly, the influence of CA in combination with other drugs, vitamins or natural products through affecting various targets has raised interest. Current experimental in vivo data suggested that CA may cooperate with clinically used anticancer drugs promoting their activity against cancer. From this point of view, CA gained importance, because it may alter pharmacodynamic profiles of various agents in the More >

MARCO INVERNIZZI^1,2,*, NICOLA FUSCO^3,4,*

BIOCELL, Vol.46, No.10, pp. 2221-2223, 2022, DOI:10.32604/biocell.2022.021043

Abstract This article has no abstract. More >

HAIYANG CHEN^1,2,#, JINGYAO SU^1,#, DANYANG CHEN^1,#, YUYE DU¹, RUILIN ZHENG¹, QINGLIN DENG², QIANQIAN DU³, BING ZHU^1,*, YINGHUA LI^1,*

BIOCELL, Vol.46, No.10, pp. 2267-2273, 2022, DOI:10.32604/biocell.2022.020218

Abstract At present, Hepatocarcinoma is one of the main causes of tumor related death all over the world. However, there are still many clinical restrictions on the treatment of liver cancer. Recently, L-Selenocystine has been shown to be a novel treatment for tumors, especially human glioma cells. But, the mechanism of L-Selenocystine against hepatocellular carcinoma remains unclear. Therefore, the main objective of this study was to investigate the effects of L-Selenocystine on HepG2 cell proliferation and activation of reactive oxygen species (ROS) mediated signaling pathway. L-Selenocystine can significantly inhibit HepG2 cell proliferation by activating caspase-3 and More >

D. Banumathy^1,*, Osamah Ibrahim Khalaf², Carlos Andrés Tavera Romero³, P. Vishnu Raja⁴, Dilip Kumar Sharma⁵

Computer Systems Science and Engineering, Vol.44, No.1, pp. 595-612, 2023, DOI:10.32604/csse.2023.025611

Abstract The most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient… More >

K. Nagalakshmi^1,*, S. Dr. Suriya²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 501-517, 2023, DOI:10.32604/csse.2023.022687

Abstract Breast cancer is one of the deadly diseases prevailing in women. Earlier detection and diagnosis might prevent the death rate. Effective diagnosis of breast cancer remains a significant challenge, and early diagnosis is essential to avoid the most severe manifestations of the disease. The existing systems have computational complexity and classification accuracy problems over various breast cancer databases. In order to overcome the above-mentioned issues, this work introduces an efficient classification and segmentation process. Hence, there is a requirement for developing a fully automatic methodology for screening the cancer regions. This paper develops a fully… More >

Doaa Sami Khafaga¹, Amel Ali Alhussan^1,*, El-Sayed M. El-kenawy^2,3, Ali E. Takieldeen³, Tarek M. Hassan⁴, Ehab A. Hegazy⁵, Elsayed Abdel Fattah Eid⁶, Abdelhameed Ibrahim⁷, Abdelaziz A. Abdelhamid^8,9

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 749-765, 2022, DOI:10.32604/cmc.2022.029605

Abstract One of the most common kinds of cancer is breast cancer. The early detection of it may help lower its overall rates of mortality. In this paper, we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal images. The proposed approach starts with data preprocessing the input images and segmenting the significant regions of interest. In addition, to properly train the machine learning models, data augmentation is applied to increase the number of segmented regions using various scaling ratios. On the other hand, to extract the relevant features from the… More >