Vivian Lee Lay Shan, Gan Keng Hoon^*, Tan Tien Ping, Rosni Abdullah

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4801-4818, 2023, DOI:10.32604/cmc.2023.033752

Abstract Sentiment classification is a useful tool to classify reviews about sentiments and attitudes towards a product or service. Existing studies heavily rely on sentiment classification methods that require fully annotated inputs. However, there is limited labelled text available, making the acquirement process of the fully annotated input costly and labour-intensive. Lately, semi-supervised methods emerge as they require only partially labelled input but perform comparably to supervised methods. Nevertheless, some works reported that the performance of the semi-supervised model degraded after adding unlabelled instances into training. Literature also shows that not all unlabelled instances are equally useful; thus identifying the informative… More >

Sunil Kumar Suryawanshi¹, Usha Chouhan², Jyoti Kant Choudhari^2,*

Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 191-208, 2022, DOI:10.32604/mcb.2022.023911

Abstract Cancer is the second biggest cause of death globally, and the use of therapeutic peptides to specifically target and destroy cancer cells has gotten much interest. Cancer peptides or vaccinations are utilized to treat cancer nowadays, apart from chemotherapy, which has significant discomfort, side effects and costly. It is time demanding to identify and predict potential anticancer peptides using computational biology approaches. Thus, 3-D molecular modeling is being used to find possible ACP candidates. In this research, Curcuma longa has predicted peptide sequences were docked on breast cancer receptors and used a molecular docking technique to assess the anticipated peptides’… More >

Oliver Tusevski^1,*, Marija Todorovska¹, Jasmina Petreska Stanoeva², Marina Stefova², Sonja Gadzovska Simic¹

Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 921-941, 2023, DOI:10.32604/phyton.2023.024995

Abstract Three Hypericum perforatum hairy root lines (HR B, HR F and HR H) along with non-transformed roots were analyzed for phenolic compounds composition and in vitro enzyme inhibitory properties. In silico molecular modeling was performed to predict the interactions of the most representative phenolic compounds in HR clones with enzymes related to depression, neurodegeneration and diabetes. Chromatographic analyses revealed that HR clones represent an efficient source of quinic acid and hydroxybenzoic acids, epicatechin and procyanidin derivatives, quercetin and kaempferol glycosides, as well numerous xanthones. In vitro antidepressant activity of HR extracts through monoamine oxidase A (MAO-A) inhibition was attributed to… More >

Igor Mokryk^1,2,*, Vitaly Demyanchuk^1,2, Volodymyr Vashkeba², Ilya Nechay¹, Borys Todurov^1,2

Congenital Heart Disease, Vol.17, No.6, pp. 641-646, 2022, DOI:10.32604/chd.2022.025096

Abstract Congenital heart disease (CHD) is one of the risk factors for developing infective endocarditis (IE). Right-sided IE occurs in 5%–10% of endocarditis cases, and pulmonary valve (PV) is involved in less than 2% of such patients. Literature data are few, and optimal treatment methods, indications for surgery, and types of operative techniques are still under debate. We present an adult patient with a rare combination of the ventricular septal defect (VSD) and PV IE who underwent surgical treatment. Neocuspidization with autologous pericardium was utilized for the reconstruction of his PV. We discuss details of this novel surgical technique. More > Graphic Abstract

S. Saranya^*, G. Usha

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 339-352, 2023, DOI:10.32604/iasc.2023.031987

Abstract Laterally with the birth of the Internet, the fast growth of mobile strategies has democratised content production owing to the widespread usage of social media, resulting in a detonation of short informal writings. Twitter is microblogging short text and social networking services, with posted millions of quick messages. Twitter analysis addresses the topic of interpreting users’ tweets in terms of ideas, interests, and views in a range of settings and fields. This type of study can be useful for a variation of academics and applications that need knowing people’s perspectives on a given topic or event. Although sentiment examination of… More >

Rong Zeng^1,#, Lin Liu^1,2,#, Jingshan Zhao^1,2,3,#, Wenmei Zhang³, Guohong Zhang¹, Yunfeng Li^1,2,*

Oncologie, Vol.24, No.3, pp. 483-498, 2022, DOI:10.32604/oncologie.2022.025148

Abstract Background: Breast cancer (BC) is the most frequent type of gynecology tumors with high morbidity and mortality. Ampelopsin, the main active compound of Ampelopsis grossedentata, exerts an anti-tumor effect on a variety of cancers. However, the anti-cancer role of ampelopsin in BC remains unclear. The aim of this study is to explore the mechanism of ampelopsin against breast cancer. Materials and Methods: The target genes of ampelopsin in the treatment of breast cancer were determined and analyzed by network pharmacology and molecular docking. Cytoscape software was used to identify the core target genes and construct a protein–protein interaction (PPI) network.… More >

RAHAT ALI¹, AFTAB ALAM², SATYENDRA K. RAJPUT³, RAZI AHMAD^4,*

BIOCELL, Vol.46, No.12, pp. 2681-2694, 2022, DOI:10.32604/biocell.2022.021224

Abstract Parkinson’s disease (PD) is an age-related neurodegenerative ailment that affects dopamine-producing neurons in a specific area of the brain called the substantia nigra of the ventral midbrain. It is clinically characterized by movement disorder and marked with unusual synaptic protein alpha-synuclein accumulation in the brain. To date, only a few Food and Drug Administration (FDA) approved drugs are available on the market for the treatment of PD. Nonetheless, these drugs show parasympathomimetic related adverse events and remarkably higher toxicity; hence, it is important to find more efficacious molecules to treat PD. In our study, We chosen 22 natural compounds as… More >

HASSAN M. OTIFI¹, MISHARI ALSHYARBA², MAJED AL FAYI^3,4, AYED A. DERA^3,4, PRASANNA RAJAGOPALAN^3,4,*

Oncology Research, Vol.29, No.3, pp. 217-227, 2021, DOI:10.32604/or.2022.03570

Abstract Targeted therapies are gaining global attention to tackle Renal Cancer (RC). This study aims to screen FPMXY- 14 (novel arylidene analogue) for Akt inhibition by computational and in vitro methods. FPMXY-14 was subjected to proton NMR analysis and Mass spectrum analysis. Vero, HEK-293, Caki-1, and A498 cell lines were used. Akt enzyme inhibition was studied with the fluorescent-based kit assay. Modeller 9.19, Schrodinger 2018-1, LigPrep module, and Glide docking were used in computational analysis. The nuclear status was assessed by PI/Hoechst- 333258 staining, cell cycle, and apoptosis assays were performed using flow cytometry. Scratch wound and migrations assays were performed.… More >

N. Penchalaiah¹, Abeer S. Al-Humaimeedy², Mashael Maashi³, J. Chinna Babu^4,*, Osamah Ibrahim Khalaf⁵, Theyazn H. H. Aldhyani⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639

Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a… More >

R. Sarasu^1,*, K. K. Thyagharajan², N. R. Shanker³

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1799-1813, 2023, DOI:10.32604/iasc.2023.027429

Abstract Researchers and scientists need rapid access to text documents such as research papers, source code and dissertations. Many research documents are available on the Internet and need more time to retrieve exact documents based on keywords. An efficient classification algorithm for retrieving documents based on keyword words is required. The traditional algorithm performs less because it never considers words’ polysemy and the relationship between bag-of-words in keywords. To solve the above problem, Semantic Featured Convolution Neural Networks (SF-CNN) is proposed to obtain the key relationships among the searching keywords and build a structure for matching the words for retrieving correct… More >