RESUMO
Resumen: Antecedentes: los conservantes de origen sintético, como nitratos y nitritos, empleados en la industria alimentaria para la conservación de matrices cárnicas, han reportado efectos desfavorables a largo plazo en la salud de los consumidores recurrentes. Objetivo: conocer las características fisicoquímicas y antimicrobianas del propóleo como potencial bioconservante en matrices cárnicas de alto consumo. Materiales y métodos: se desarrolló una revisión bibliográfica de literatura acorde a la pregunta problema planteada por el grupo de investigación, y se llevó a cabo una búsqueda en las bases de datos Scopus, NCBI, SciELO, ScienceDirect y Google Scholar de artículos de revisión, artículos científicos, libros y trabajos de grado. Resultados: el propóleo es un compuesto natural con una variedad amplia de elementos útiles para la conservación de matrices cárnicas, por sus propiedades antimicrobianas y antioxidantes. Conclusiones: el propóleo presenta propiedades antimicrobianas y antioxidantes útiles en el campo de la industria alimentaria, por lo que se considera una de las alternativas más viables para la conservación de productos cárnicos y la disminución del uso de conservantes sintéticos en producción cárnica. No obstante, es fundamental el desarrollo de más investigaciones que permitan evaluar el comportamiento de los compuestos activos del propóleo en las diversas matrices cárnicas
Abstract: Background: Preservatives of synthetic origin, such as nitrates and nitrites, used in the food industry for the preservation of meat matrices, have reported long-term unfavorable effects on the health of recurrent consumers. Objective: To know the physicochemical and antimicrobial characteristics of propolis as a potential biopreservative in high consumption meat matrices. Materials and Methods: A bibliographic review of literature was developed according to the problem question posed by the research group, carrying out a search in the Scopus, NCBI, SciELO, ScienceDirect and Google Scholar databases of review articles, scientific articles, books and works degree. Results: Propolis is a natural compound with a wide variety of useful elements for the conservation of meat matrices, due to its antimicrobial and antioxidant properties. Conclusions: Propolis has useful antimicrobial and antioxidant properties in the field of the food industry, being considered one of the most viable alternatives for the preservation of meat products and the reduction of the use of synthetic preservatives in meat production. However, it is essential to develop more research to evaluate the behavior of the active compounds of propolis in the various meat matrices
Assuntos
AntioxidantesRESUMO
BACKGROUND: We investigated the potential of proteomic fingerprinting with mass spectrometric serum profiling, coupled with pattern recognition methods, to identify biomarkers that could improve diagnosis of tuberculosis. METHODS: We obtained serum proteomic profiles from patients with active tuberculosis and controls by surface-enhanced laser desorption ionisation time of flight mass spectrometry. A supervised machine-learning approach based on the support vector machine (SVM) was used to obtain a classifier that distinguished between the groups in two independent test sets. We used k-fold cross validation and random sampling of the SVM classifier to assess the classifier further. Relevant mass peaks were selected by correlational analysis and assessed with SVM. We tested the diagnostic potential of candidate biomarkers, identified by peptide mass fingerprinting, by conventional immunoassays and SVM classifiers trained on these data. FINDINGS: Our SVM classifier discriminated the proteomic profile of patients with active tuberculosis from that of controls with overlapping clinical features. Diagnostic accuracy was 94% (sensitivity 93.5%, specificity 94.9%) for patients with tuberculosis and was unaffected by HIV status. A classifier trained on the 20 most informative peaks achieved diagnostic accuracy of 90%. From these peaks, two peptides (serum amyloid A protein and transthyretin) were identified and quantitated by immunoassay. Because these peptides reflect inflammatory states, we also quantitated neopterin and C reactive protein. Application of an SVM classifier using combinations of these values gave diagnostic accuracies of up to 84% for tuberculosis. Validation on a second, prospectively collected testing set gave similar accuracies using the whole proteomic signature and the 20 selected peaks. Using combinations of the four biomarkers, we achieved diagnostic accuracies of up to 78%. INTERPRETATION: The potential biomarkers for tuberculosis that we identified through proteomic fingerprinting and pattern recognition have a plausible biological connection with the disease and could be used to develop new diagnostic tests.
