Intestinal microbiota alterations by dietary exposure to chemicals from food cooking and processing. Application of data science for risk prediction
| Autor: | José Emilio Labra-Gayo, Sonia González, Silvia Arboleya, Nuria Salazar, Irene Díaz, Miguel Gueimonde, Herminio García-González, Clara G. de los Reyes-Gavilán, Sergio Ruiz-Saavedra |
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| Přispěvatelé: | Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), European Commission, Principado de Asturias, Fundación para la Investigación y la Innovación Biosanitaria del Principado de Asturias |
| Rok vydání: | 2021 |
| Předmět: |
Intestinal microbiota
Biophysics Review Article Disease Biology medicine.disease_cause Dietary carcinogens Biochemistry 03 medical and health sciences 0302 clinical medicine Toxic chemicals Structural Biology Environmental health Machine learning Genetics medicine Carcinogen 030304 developmental biology Subclinical infection 0303 health sciences business.industry Dietary exposure Cooking methods Colorectal cancer Computer Science Applications Diet 030220 oncology & carcinogenesis Food processing business TP248.13-248.65 Genotoxicity Semantic web Biotechnology |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname Scopus Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 1081-1091 (2021) RUO. Repositorio Institucional de la Universidad de Oviedo |
| Popis: | Diet is one of the main sources of exposure to toxic chemicals with carcinogenic potential, some of which are generated during food processing, depending on the type of food (primarily meat, fish, bread and potatoes), cooking methods and temperature. Although demonstrated in animal models at high doses, an unequivocal link between dietary exposure to these compounds with disease has not been proven in humans. A major difficulty in assessing the actual intake of these toxic compounds is the lack of standardised and harmonised protocols for collecting and analysing dietary information. The intestinal microbiota (IM) has a great influence on health and is altered in some diseases such as colorectal cancer (CRC). Diet influences the composition and activity of the IM, and the net exposure to genotoxicity of potential dietary carcinogens in the gut depends on the interaction among these compounds, IM and diet. This review analyses critically the difficulties and challenges in the study of interactions among these three actors on the onset of CRC. Machine Learning (ML) of data obtained in subclinical and precancerous stages would help to establish risk thresholds for the intake of toxic compounds generated during food processing as related to diet and IM profiles, whereas Semantic Web could improve data accessibility and usability from different studies, as well as helping to elucidate novel interactions among those chemicals, IM and diet. This work is receiving support from the project RTI2018-098288-B-I00 (MCIU/AEI/FEDER, UE) and is based on concepts developed partly funded by projects TIN2017-88877-R (AEI/FEDER, UE), TIN2017-87600-P (AEI/FEDER. UE) and IDI/2018/000176 (Asturian Government GRUPIN projects). SRS is the beneficiary of a training contract financed by project RTI2018-098288-B-I00. SA is granted by a Juan de la Cierva postdoctoral contract from the Spanish Ministry of Science and Innovation (Ref. IJCI-2017-32156) and NS is the recipient of a postdoctoral contract awarded by the Fundación para la Investigación y la Innovación Biosanitaria del Principado de Asturias (FINBA). |
| Databáze: | OpenAIRE |
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