5 resultados para Salivary IgA
em Universidade do Minho
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The authors acknowledge to Sofia Neves from ICVS for her help in the antibodies selection.
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Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.
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This study focuses on the prospective mediation role of family coping between burden and cortisol levels in informal caregivers of addicts as well as on the feasible use of two different ways to analyse the salivary cortisol levels. Participants were 120 Portuguese informal caregivers of addicts. The cortisol samples were collected at awakening, 45 minutes later and after a 30 minute presentation of images taken from the International Affective Picture System. Family coping and caregiver burden were measured using the Portuguese versions of the Caregiver Reaction Assessment, and the Family Crisis Oriented Personal Evaluation Scale. Cortisol samples were collected in salivettes and the results were computed in order to determine the Area Under the Curve scores (AUCg, AUCi). Results found family coping to be negatively correlated with burden and AUCg levels (i.e. overall intensity) and positively correlated with either AUCg and AUCi (i.e. change over time). The mediation model revealed that family coping was a partial mediator in the relationship between the burden and AUCg levels. Therefore, Family Coping appears to be an essential variable in understanding the stress response and should be considered in further studies and interventions. In addition, the use of two different formulas for calculating cortisol levels provided important new information concerning the relationship between cortisol, burden and family coping. It seems that burden has a more profound effect on the overall intensity of the neuroendocrine response to caregiver stress and not so much on the sensitivity of the system.
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Objectives: This research work intends to clarify the role of artificial saliva, in particularly the role of mucin, a salivary protein, on the surface properties and adhesion ability of Candida spp. oral clinical isolates to abiotic surfaces. Methods: Four oral clinical isolates of Candida spp. were used: two Candida albicans strains (AC; AM) and two Candida parapsilosis strains (AD; AM2). The strains were isolated from patients using oral prosthesis. The microorganisms were cultured in the absence or presence of mucin and artificial saliva, and their adhesion to an abiotic surface (coated with mucin and artificial saliva) was evaluated. Results: The presence of mucin per se onto the abiotic surface decreased the adhesion of all strains, although the combination of mucin with artificial saliva had reduced this effect. No direct correlation between adhesion and the surface free energies of adhesion of the microorganisms was found. Significance: Candida spp. were human commensal microorganisms that became pathogenic when the host immune defenses were compromised. Medical devices were colonized by Candida spp. particularly, oral prostheses, which might lead to the degradation of the prostheses and systemic infections. The salivary secretions that constantly cover the oral cavity influenced Candida spp. adhesion process. Therefore, it was important to understand the interactions between Candida spp., salivary proteins and the characteristic of oral prosthesis when developing materials for oral prostheses.
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Dissertação de mestrado em Genética Molecular