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.

Implementação da Marcação CE para estruturas metálicas: estudo de caso na serralharia da Carpincasais

Dissertação de mestrado em Engenharia Industrial

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.

Redefining the MED13L syndrome

Congenital cardiac and neurodevelopmental deficits have been recently linked to the mediator complex subunit 13-like protein MED13L, a subunit of the CDK8-associated mediator complex that functions in transcriptional regulation through DNA-binding transcription factors and RNA polymerase II. Heterozygous MED13L variants cause transposition of the great arteries and intellectual disability (ID). Here, we report eight patients with predominantly novel MED13L variants who lack such complex congenital heart malformations. Rather, they depict a syndromic form of ID characterized by facial dysmorphism, ID, speech impairment, motor developmental delay with muscular hypotonia and behavioral difficulties. We thereby define a novel syndrome and significantly broaden the clinical spectrum associated with MED13L variants. A prominent feature of the MED13L neurocognitive presentation is profound language impairment, often in combination with articulatory deficits.

Inactivation of PNKP by mutant ATXN3 triggers apoptosis by activating the DNA damage-response pathway in SCA3.

Spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph disease (MJD), is an untreatable autosomal dominant neurodegenerative disease, and the most common such inherited ataxia worldwide. The mutation in SCA3 is the expansion of a polymorphic CAG tri-nucleotide repeat sequence in the C-terminal coding region of the ATXN3 gene at chromosomal locus 14q32.1. The mutant ATXN3 protein encoding expanded glutamine (polyQ) sequences interacts with multiple proteins in vivo, and is deposited as aggregates in the SCA3 brain. A large body of literature suggests that the loss of function of the native ATNX3-interacting proteins that are deposited in the polyQ aggregates contributes to cellular toxicity, systemic neurodegeneration and the pathogenic mechanism in SCA3. Nonetheless, a significant understanding of the disease etiology of SCA3, the molecular mechanism by which the polyQ expansions in the mutant ATXN3 induce neurodegeneration in SCA3 has remained elusive. In the present study, we show that the essential DNA strand break repair enzyme PNKP (polynucleotide kinase 3'-phosphatase) interacts with, and is inactivated by, the mutant ATXN3, resulting in inefficient DNA repair, persistent accumulation of DNA damage/strand breaks, and subsequent chronic activation of the DNA damage-response ataxia telangiectasia-mutated (ATM) signaling pathway in SCA3. We report that persistent accumulation of DNA damage/strand breaks and chronic activation of the serine/threonine kinase ATM and the downstream p53 and protein kinase C-d pro-apoptotic pathways trigger neuronal dysfunction and eventually neuronal death in SCA3. Either PNKP overexpression or pharmacological inhibition of ATM dramatically blocked mutant ATXN3-mediated cell death. Discovery of the mechanism by which mutant ATXN3 induces DNA damage and amplifies the pro-death signaling pathways provides a molecular basis for neurodegeneration due to PNKP inactivation in SCA3, and for the first time offers a possible approach to treatment.

Searching for therapeutic strategies in a mouse modelo of Machado-Joseph disease: targeting proteostases

Tese de Doutoramento em Ciências da Saúde

The role of the mammalian DNA end-processing enzyme polynucleotide kinase 3'-phosphatase in spinocerebellar ataxia Type 3 pathogenesis

DNA strand-breaks (SBs) with non-ligatable ends are generated by ionizing radiation, oxidative stress, various chemotherapeutic agents, and also as base excision repair (BER) intermediates. Several neurological diseases have already been identified as being due to a deficiency in DNA end-processing activities. Two common dirty ends, 3'-P and 5'-OH, are processed by mammalian polynucleotide kinase 3'-phosphatase (PNKP), a bifunctional enzyme with 3'-phosphatase and 5'-kinase activities. We have made the unexpected observation that PNKP stably associates with Ataxin-3 (ATXN3), a polyglutamine repeat-containing protein mutated in spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph Disease (MJD). This disease is one of the most common dominantly inherited ataxias worldwide; the defect in SCA3 is due to CAG repeat expansion (from the normal 14-41 to 55-82 repeats) in the ATXN3 coding region. However, how the expanded form gains its toxic function is still not clearly understood. Here we report that purified wild-type (WT) ATXN3 stimulates, and by contrast the mutant form specifically inhibits, PNKP's 3' phosphatase activity in vitro. ATXN3-deficient cells also show decreased PNKP activity. Furthermore, transgenic mice conditionally expressing the pathological form of human ATXN3 also showed decreased 3'-phosphatase activity of PNKP, mostly in the deep cerebellar nuclei, one of the most affected regions in MJD patients' brain. Finally, long amplicon quantitative PCR analysis of human MJD patients' brain samples showed a significant accumulation of DNA strand breaks. Our results thus indicate that the accumulation of DNA strand breaks due to functional deficiency of PNKP is etiologically linked to the pathogenesis of SCA3/MJD.

Pre-clinical trials for Machado-Joseph Disease: Hypothesis-based and hypothesis-free therapeutic approaches

Tese de Doutoramento em Ciências da Saúde