UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

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.

Influence of climate on clinical diagnostic dry eye tests: pilot study

Purpose. To analyze dry eye disease (DED) tests and their consistency in similar nonsymptomatic population samples living in two geographic locations with different climates (Continental vs. Atlantic). Methods. This is a pilot study including 14 nonsymptomatic residents from Valladolid (Continental climate, Spain) and 14 sex-matched and similarly aged residents from Braga (Atlantic climate, Portugal); they were assessed during the same season (spring) of two consecutive years. Phenol red thread test, conjunctival hyperemia, fluorescein tear breakup time, corneal and conjunctival staining, and Schirmer test were evaluated on three different consecutive visits. Reliability was assessed using the intraclass correlation coefficient and weighted kappa (J) coefficient for quantitative and ordinal variables, respectively. Results. Fourteen subjects were recruited in each city with a mean (TSD) age of 63.0 (T1.7) and 59.1 (T0.9) years (p = 0.08) in Valladolid and Braga, respectively. Intraclass correlation coefficient and J values of the tests performed were below 0.69 and 0.61, respectively, for both samples, thus showing moderate to poor reliability. Subsequently, comparisons were made between the results corresponding to the middle and higher outdoor relative humidity (RH) visit in each location as there were no differences in mean temperature (p Q 0.75) despite RH values significantly differing (p e 0.005). Significant (p e 0.05) differences were observed between Valladolid and Braga samples on tear breakup time (middle RH visit, 2.76 T 0.60 vs. 5.26 T 0.64 seconds; higher RH visit, 2.61 T 0.32 vs. 5.78 T 0.88 seconds) and corneal (middle RH, 0.64 T 0.17 vs. 0.14 T 0.10; higher RH, 0.60 T 0.22 vs. 0.0 T 0.0) and conjunctival staining (middle RH, 0.61 T 0.17 vs. 0.14 T 0.08; higher RH, 0.57 T 0.15 vs. 0.18 T 0.09). Conclusions. This pilot study provides initial evidence to support that DED test outcomes assessing the ocular surface integrity and tear stability are climate dependent. Future large-sample studies should support these outcomes also in DED patients. This knowledge is fundamental for multicenter clinical trials. Lack of consistency in diagnostic clinical tests for DED was also corroborated. (Optom Vis Sci 2015;92:e284Ye289)

End-of-day dryness, corneal sensitivity and blink rate in contact lens wearers

Purpose: To study the relationship among the variables intensity ofthe end-of-day (EOD) dryness, corneal sensitivity and blink rate in soft contact lens (CL) wearers. Methods: Thirty-eight soft CL wearers (25 women and 13 men; mean age 27.1 ± 7.2 years) were enrolled. EOD dryness was assessed using a scale of 0–5 (0, none to 5, very intense). Mechanical and thermal (heat and cold) sensitivity were measured using a Belmonte’s gas esthesiometer. The blink rate was recorded using a video camera while subjects were wearing a hydrogel CL and watching a film for 90 min in a controlled environmental chamber. Results: A significant inverse correlation was found between EOD dryness and mechanical sensitivity (r: −0.39; p = 0.02); however, there were no significant correlations between EOD dryness and thermal sensitivity. A significant (r: 0.56; p < 0.001) correlation also was observed between EOD dryness and blink rate, but no correlations were found between blink rate and mechanical or thermal sensitivity. Conclusions: CL wearers with higher corneal sensitivity to mechanical stimulation reported more EOD dryness with habitual CL wear. Moreover, subjects reporting more EOD dryness had an increased blink rates during wear of a standard CL type. The increased blink rate could act to improve the ocular surface environment and relieve symptoms

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Layer-by-layer technique to developing functional nanolaminate films with antifungal activity

The layer-by-layer (LbL) deposition method was used to build up alternating layers (five) of different polyelectrolyte solutions (alginate, zein-carvacrol nanocapsules, chitosan and chitosan-carvacrol emulsions) on an aminolysed/charged polyethylene terephthalate (A/C PET) film. These nanolaminated films were characterised by contact angle measurements and through the determination of water vapour (WVTR) and oxygen (O2TR) transmission rates. The effect of active nanolaminated films against the Alternaria sp. and Rhizopus stolonifer was also evaluated. This procedure allowed developing optically transparent nanolaminated films with tuneable water vapour and gas properties and antifungal activity. The water and oxygen transmission rate values for the multilayer films were lower than those previously reported for the neat alginate or chitosan films. The presence of carvacrol and zein nanocapsules significantly decreased the water transmission rate (up to 40 %) of the nanolaminated films. However, the O2TR behaved differently and was only improved (up to 45 %) when carvacrol was encapsulated, i.e. nanolaminated films prepared by alternating alginate with nanocapsules of zein-carvacrol layers showed better oxygen barrier properties than those prepared as an emulsion of chitosan and carvacrol. These films containing zein-carvacrol nanocapsules also showed the highest antifungal activity (30 %), which did not significantly differ from those obtained with the highest amount of carvacrol, probably due to the controlled release of the active agent (carvacrol) from the zein-carvacrol nanocapsules. Thus, this work shows that nanolaminated films prepared with alternating layers of alginate and zein-carvacrol nanocapsules can be considered to improve the shelf-life of foodstuffs.

Miguel d'Alte: cartografia (acidentada) da vida e obra de um "pintor maldito"

Dissertação de mestrado em Comunicação Arte e Cultura