Intestinal cytochromes P450 regulating the intestinal microbiota and its probiotic profile

Bezirtzoglou, Eugenia

doi:10.3402/mehd.v23i0.18370

Cited by 47 publications

(50 citation statements)

References 55 publications

(82 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some of the colon-cancer genes identified also include steroid hormone biosynthesis, as the bacterial cells in the gut produce steroid hormones that can have implications for colon cancer [ 45 ]. Some colon cancer genes also identified include metabolism of xenobiotics; biotransformation of xenobiotics occurs in the human colon and rectum, and it is known to be associated with colorectal cancer [ 46 – 48 ]. Pentose and glucuronate interconversions were also identified using colon-tissue genes.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers

et al. 2017

View full text Add to dashboard Cite

Machine learning techniques for cancer prediction and biomarker discovery can hasten cancer detection and significantly improve prognosis. Recent “OMICS” studies which include a variety of cancer and normal tissue samples along with machine learning approaches have the potential to further accelerate such discovery. To demonstrate this potential, 2,175 gene expression samples from nine tissue types were obtained to identify gene sets whose expression is characteristic of each cancer class. Using random forests classification and ten-fold cross-validation, we developed nine single-tissue classifiers, two multi-tissue cancer-versus-normal classifiers, and one multi-tissue normal classifier. Given a sample of a specified tissue type, the single-tissue models classified samples as cancer or normal with a testing accuracy between 85.29% and 100%. Given a sample of non-specific tissue type, the multi-tissue bi-class model classified the sample as cancer versus normal with a testing accuracy of 97.89%. Given a sample of non-specific tissue type, the multi-tissue multi-class model classified the sample as cancer versus normal and as a specific tissue type with a testing accuracy of 97.43%. Given a normal sample of any of the nine tissue types, the multi-tissue normal model classified the sample as a particular tissue type with a testing accuracy of 97.35%. The machine learning classifiers developed in this study identify potential cancer biomarkers with sensitivity and specificity that exceed those of existing biomarkers and pointed to pathways that are critical to tissue-specific tumor development. This study demonstrates the feasibility of predicting the tissue origin of carcinoma in the context of multiple cancer classes.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Even though more than 50 CYPs have been identified, CYP3A subfamily represents the major component of a phase I metabolism. CYP3A is responsible for metabolizing nearly half of the marketed xenobiotics, environmental carcinogens, and other endogenous compounds like steroids [51]. Analyzing the intestinal epithelial permeability is an important criterion to determine the rate and extent of drug absorption.…”

Section: Drug-likeness and Molecular Properties Of Active Compoundsmentioning

confidence: 99%

Ethyl 4-(4-methylphenyl)-4-pentenoate from Vetiveria zizanioides Inhibits Dengue NS2B–NS3 Protease and Prevents Viral Assembly: A Computational Molecular Dynamics and Docking Study

Lavanya

Ramaiah

Anbarasu

2016

Cell Biochem Biophys

View full text Add to dashboard Cite

Around 50 % of the world's population is at the risk of dengue, a viral infection. Presently, there are not many drugs and prophylactic measures available to control dengue viral infection, and hence, there is an urgent need to develop effective antidengue compound from natural sources. In the current study, we explored the antiviral properties of the medicinal plant Vetiveria zizanioides against dengue virus. Initially, the antiviral properties of active compounds were examined using docking analysis along with reference ligand. The enzyme-ligand complex which showed higher binding affinity than the reference ligand was employed for subsequent analysis. The stability of the top scoring enzyme-ligand complex was further validated using molecular simulation studies. On the whole, the study reveals that the compound Ethyl 4-(4-methylphenyl)-4-pentenoate has an effective antiviral property, which can serve as a potential lead molecule in drug discovery process.

show abstract

“…Functional foods, such as probiotics, prebiotics, and symbiotics, could modify the activity of the gastrointestinal tract (3).…”

Section: Origin and Chemical Naturementioning

confidence: 99%

Functions of the Human Intestinal Microbiota in Relation to Functional Foods

Stavropoulou¹,

Tsigalou²,

Bezirtzoglou³

2018

Erciyes Med J

View full text Add to dashboard Cite

Interest in functional foods has increased due to their relationship to diet and health. A healthy nutrition preserves the intestinal ecosystem and enhances health. Probiotic Lactobacillus appears to be highly sensitive to diet, environmental factors, stress, and antibiotics. Functional foods are known to play an important role in the stability of a human intestinal ecosystem. Moreover, dissemination of antibiotic resistances into consumed dairy and meat products could select some bacterial species. However, awareness of the relationship between food and health must be constant through permanent surveillance systems. The European Union guidelines should be imposed for the safe use of functional foods as foods or either as biotherapeutic agents. Functional foods are foods that surpass classic nutritional habits and have usually beneficial action for their host. They are classified into three main classes: probiotics, prebiotics, and symbiotics. The use of genetically modified probiotics could provide further chances for the industrial and pharmaceutical exploitation of probiotic microorganisms. In contrast, prebiotics are not microorganisms but non-digestible components. They stimulate the growth and/or the activity of several bacteria in a beneficial way. Their action contributes to a healthy and balanced intestinal microbiota. Systematic administration of prebiotics decreases blood lipid counts, as well as blood pressure, but increases the synthesis and absorption of foods and maybe has an anticarcinogenic action. They are also used extensively in the food industry. Last but not the least is the class of symbiotics, which combines a mixture of probiotics and prebiotics with both effects.

show abstract

Intestinal cytochromes P450 regulating the intestinal microbiota and its probiotic profile

Cited by 47 publications

References 55 publications

Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers

Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers

Ethyl 4-(4-methylphenyl)-4-pentenoate from Vetiveria zizanioides Inhibits Dengue NS2B–NS3 Protease and Prevents Viral Assembly: A Computational Molecular Dynamics and Docking Study

Functions of the Human Intestinal Microbiota in Relation to Functional Foods

Contact Info

Product

Resources

About