Proteins on microbial identification: past achievements, present state-of-the-art, and future challenges

The use of chemical analysis of microbial components, including proteins, became an important achievement in the 80’s of the last century to the microbial identification. This led a more objective microbial identification scheme, called chemotaxonomy, and the analytical tools used in the field are mainly 1D/2D gel electrophoresis, spectrophotometry, high-performance liquid chromatography, gas chromatography, and combined gas chromatography-mass spectrometry. The Edman degradation reaction was also applied to peptides sequence giving important insights to the microbial identification. The rapid development of these techniques, in association with knowledge generated by DNA sequencing and phylogeny based on rRNA gene and housekeeping genes sequences, boosted the microbial identification to an unparalleled scale. The recent results of mass spectrometry (MS), like Matrix-Assisted Laser Desorption/Ionisation Time-of-Flight (MALDI-TOF), for rapid and reliable microbial identification showed considerable promise. In addition, the technique is rapid, reliable and inexpensive in terms of labour and consumables when compared with other biological techniques. At present, MALDI-TOF MS adds an additional step for polyphasic identification which is essential when there is a paucity of characters or high DNA homologies for delimiting very close related species. The full impact of this approach is now being appreciated when more diverse species are studied in detail and successfully identified. However, even with the best polyphasic system, identification of some taxa remains time-consuming and determining what represents a species remains subjective. The possibilities opened with new and even more robust mass spectrometers combined with sound and reliable databases allow not only the microbial identification based on the proteome fingerprinting but also include de novo specific proteins sequencing as additional step. These approaches are pushing the boundaries in the microbial identification field.

The effects of solvent composition on the affinity of a peptide towards hair keratin: experimental and molecular dynamics data

The study of the interaction between hair filaments and formulations or peptides is of utmost importance in fields like cosmetic research. Keratin intermediate filaments structure is not fully described, limiting the molecular dynamics (MD) studies in this field although its high potential to improve the area. We developed a computational model of a truncated protofibril, simulated its behavior in alcoholic based formulations and with one peptide. The simulations showed a strong interaction between the benzyl alcohol molecules of the formulations and the model, leading to the disorganization of the keratin chains, which regress with the removal of the alcohol molecules. This behavior can explain the increase of peptide uptake in hair shafts evidenced in fluorescence microscopy pictures. The model developed is valid to computationally reproduce the interaction between hair and alcoholic formulations and provide a robust base for new MD studies about hair properties. It is shown that the MD simulations can improve hair cosmetic research, improving the uptake of a compound of interest.

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.

GIS application in water resources master planning

Due to water scarcity, it is important to organize and regulate water resources utilization to satisfy the conflicting water demands and needs. This paper aims to describe a comprehensive methodology for managing the water sector of a defined urbanized region, using the robust capabilities of a Geographic Information System (GIS). The proposed methodology is based on finding alternatives to cover the gap between recent supplies and future demands. Nablus which is a main governorate located in the north of West Bank, Palestine, was selected as case study because this area is classified as arid to semi-arid area. In fact, GIS integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographic information. The resulted plan of Nablus represents an example of the proposed methodology implementation and a valid framework for the elaboration of a water master plan.

Inkjet printing technology for flexible pressure sensors

Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.

Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniae

Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniae

Development of a methodology to incorporate risk and uncertainty in electricity power planning

Dissertação de mestrado em Engenharia Industrial

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

Assistive locomotion strategies for active lower limb devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Segmentação do tecido tumoral cerebral em imagens de ressonância magnética

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Interação multimodal de dispositivos robóticos em ambiente simulado

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Light responsive multilayer surfaces with controlled spatial extinction capability

Multilayer systems obtained using the Layer-by-Layer (LbL) technology have been proposed for a variety of biomedical applications in tissue engineering and regenerative medicine. LbL assembly is a simple and highly versatile method to modify surfaces and fabricate robust and highly-ordered nanostructured coatings over almost any type of substrates and with a wide range of substances. The incorporation of polyoxometalate (POM) inorganic salts as constituents of the layers presents a possibility of promoting light-stimuli responses in LbL substrates. We propose the design of a biocompatible photo-responsive multilayer system based on a Preyssler-type POM ([NaP5W30O110]14â ) and a natural origin polymer, chitosan, using the LbL methodology. The photo-reduction properties of the POM allow the spatially controlled disruption of the assembled layers due to the weakening of the electrostatic interactions between the layers. This system has found applicability in detaching devices, such as the cell sheet technology, which may solve the drawbacks actually found in other cell treatment proposals.

Adipogenic cell sheets to recreate in vitro adipose tissue microenvironments

Cell sheet (CS) engineering, taking advantage of cellular self-matrix organized as in native tissue, has been largely explored, including by us, for different purposes [1â 3]. Herein we propose for the ï¬ rst time, the use of human adipose stem cells (hASCs)-derived CS to create adipose tissue analogues with different levels of maturation. hASCs were cultured on UpCellTM thermo-responsive dishes for 1, 3 and 5 days under basal conditions previously established by us [3]. The inï¬ uence of pre-differentiation time and respective cell number, over CS stability and differentiation was assessed. Mechanically robust CS were only obtained with 5 days pre-differentiation period. Adipogenesis was followed along the culture assessing the variation of expression of mesenchymal (CD73, CD105 but not CD90) and adipogenic (PPARg, FABP4 and LPL) markers by ï¬ ow cytometry, immunocytochemistry and RT-PCR. Increased ratio of differentiated cells was achieved for longer pre-differentiation periods, while maturation degree was modulated by the maintenance medium. Independently of the overall CS differentiation/maturation level, 3D constructs were fabricated by stacking and further culturing 3 CS. Thus, by varying the culture conditions, different 3D adipose tissue-like microenvironments were recreated, enabling future development of new tissue engineering strategies, as well as further study of adipose tissue role in the regeneration of different tissues.

Desenvolvimento de um protótipo didático de uma máquina de corte de pedra por fio diamantado

Dissertação de mestrado integrado em Engenharia Mecânica

Urbanismo participativo e resiliência das comunidades: especificação de uma aplicação

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação