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doi:10.13040/ijpsr.0975-8232.11(7).3121-34

Cited by 5 publications

(3 citation statements)

References 34 publications

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“…Cancer is a chronic disease that is mostly brought on by the body’s cells multiplying uncontrollably, spreading to other body regions, and causing tumours that may or may not be cancerous [ 38 ]. Cancer is the leading cause of death worldwide.…”

Section: Biological Activitiesmentioning

confidence: 99%

Therapeutic Potential of Pectin and Its Derivatives in Chronic Diseases

Dambuza,

Rungqu,

Oyedeji

et al. 2024

Molecules

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Non-communicable diseases (NCDs) are described as a collection of chronic diseases that do not typically develop from an acute infection, have long-term health effects, and frequently require ongoing care and therapy. These diseases include heart disease, stroke, cancer, chronic lung disease, neurological diseases, osteoporosis, mental health disorders, etc. Known synthetic drugs for the treatment or prevention of NCDs become increasingly dangerous over time and pose high risks due to side effects such as hallucination, heart attack, liver failure, etc. As a result, scientists have had to look for other alternatives that are natural products and that are known to be less detrimental and contain useful bioactive compounds. The increasing understanding of the biological and pharmacological significance of carbohydrates has helped to raise awareness of their importance in living systems and medicine, given they play numerous biological roles. For example, pectin has been identified as a class of secondary metabolites found in medicinal plants that may play a significant role in the treatment and management of a variety of NCDs. Pectin is mainly made of homogalacturonan, which is a linear polymer composed primarily of D-galacturonic acid units (at least 65%) linked in a chain by α-(1,4)-glycosidic linkages. There are also modified pectins or derivatives that improve pectin’s bioavailability. Pectin is found in the cell walls of higher plants (pteridophytes, angiosperms, and gymnosperms), particularly in the middle lamella of the plant material. Citrus pectin is used in various industries. This article compiles information that has been available for years about the therapeutic importance of pectin in chronic diseases, different modes of pectin extraction, the chemistry of pectin, and the potency of pectin and its derivatives.

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Section: Biological Activitiesmentioning

confidence: 99%

Therapeutic Potential of Pectin and Its Derivatives in Chronic Diseases

Dambuza,

Rungqu,

Oyedeji

et al. 2024

Molecules

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“…The standard treatment option for cancer therapy includes immunotherapy, chemotherapy, radiotherapy, surgical removal, and/or targeted therapy, depending on the tumor's stage [118]. CYT plays a pivotal role in patient stratification and its levels have a significant value to choose the suitable treatment for each patient.…”

Section: Role Of Cyt In Patient Stratification and Treatment Selectionmentioning

confidence: 99%

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Agioti,

Zaravinos

2024

IJMS

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Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

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“…It can be defined as a group of more than one disease due to abnormal cell growth or changes in genes, and it can occur anywhere in the body [5]. Many factors cause cancer including [6]: -(1) tobacco consumption, (2) poor diet, (3) lack of physical activity, (4) alcohol, (5) radiation, (6) infection, (7) genetic factors, (8) smoking and (9) age [6]. There are many different types of human cancer, but in this paper, we used some types that included Breast Invasive Carcinoma (BR), Bladder urothelial carcinoma (BL), Colon and rectum (CO), Glioblastoma multiform (GB), Head and neck squamous cell (HN), Kidney renal clear-cell (KI), Parkinson's disease (PD), Prostate adenocarcinoma (PRAD) and Lung adenocarcinoma (LUAD).…”

Section: Introductionmentioning

confidence: 99%

Effective hybrid feature selection using different bootstrap enhances cancers classification performance

2022

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Background Machine learning can be used to predict the different onset of human cancers. Highly dimensional data have enormous, complicated problems. One of these is an excessive number of genes plus over-fitting, fitting time, and classification accuracy. Recursive Feature Elimination (RFE) is a wrapper method for selecting the best subset of features that cause the best accuracy. Despite the high performance of RFE, time computation and over-fitting are two disadvantages of this algorithm. Random forest for selection (RFS) proves its effectiveness in selecting the effective features and improving the over-fitting problem. Method This paper proposed a method, namely, positions first bootstrap step (PFBS) random forest selection recursive feature elimination (RFS-RFE) and its abbreviation is PFBS- RFS-RFE to enhance cancer classification performance. It used a bootstrap with many positions included in the outer first bootstrap step (OFBS), inner first bootstrap step (IFBS), and outer/ inner first bootstrap step (O/IFBS). In the first position, OFBS is applied as a resampling method (bootstrap) with replacement before selection step. The RFS is applied with bootstrap = false i.e., the whole datasets are used to build each tree. The importance features are hybrid with RFE to select the most relevant subset of features. In the second position, IFBS is applied as a resampling method (bootstrap) with replacement during applied RFS. The importance features are hybrid with RFE. In the third position, O/IFBS is applied as a hybrid of first and second positions. RFE used logistic regression (LR) as an estimator. The proposed methods are incorporated with four classifiers to solve the feature selection problems and modify the performance of RFE, in which five datasets with different size are used to assess the performance of the PFBS-RFS-RFE. Results The results showed that the O/IFBS-RFS-RFE achieved the best performance compared with previous work and enhanced the accuracy, variance and ROC area for RNA gene and dermatology erythemato-squamous diseases datasets to become 99.994%, 0.0000004, 1.000 and 100.000%, 0.0 and 1.000, respectively. Conclusion High dimensional datasets and RFE algorithm face many troubles in cancers classification performance. PFBS-RFS-RFE is proposed to fix these troubles with different positions. The importance features which extracted from RFS are used with RFE to obtain the effective features.

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Untitled

Cited by 5 publications

References 34 publications

Therapeutic Potential of Pectin and Its Derivatives in Chronic Diseases

Therapeutic Potential of Pectin and Its Derivatives in Chronic Diseases

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Effective hybrid feature selection using different bootstrap enhances cancers classification performance

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