5 resultados para nuclear magnetic resonanc spectroscopy

em Universidade do Minho


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PhD Thesis in Sciences Specialization in Chemistry

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Three PEGylated derivatives of 1,4,7,10-tetraazacyclododecane-1-((6-amino)hexanoic)-4,7,10-triacetic acid) (DOTA-AHA) with different molecular weights were prepared and characterized. Their Gd(III) chelates were studied in aqueous solution using variable-temperature 1H nuclear magnetic relaxation dispersion (NMRD) and 17ONMR spectroscopy in view of the determination of their relaxivity and the parameters that govern it. The relaxivity varied from 5.1 to 6.5 mM-1.s-1 (37 ºC and 60 MHz) with the increasing molecular weight of the PEG chain, being slightly higher than that of the parent chelate Gd(DOTA-AHA), due to a small contribution of a slow global rotation of the complexes. A variable temperature 1H NMR study of several Ln(III) chelates of DOTA-A(PEG750)HA allowed the determination of the isomeric M/m ratio (M = square antiprismatic isomer and m = twisted square antiprismatic isomer, the latter presenting a much faster water exchange) which for the Gd(III) chelate was estimated in circa 1:0.2, very close to that of [Gd(DOTA)]-. This explains why the PEGylated Gd(III) chelate has a water rate exchange similar to that of [Gd(DOTA)]-. The predominance of the M isomer is a consequence of the bulky PEG moiety which does not favor the stabilization of the m isomer in sterically crowded systems at the substituent site, contrary to what happens with less packed asymmetrical DOTA-type chelates with substitution in one of the four acetate C(α) atoms.

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Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

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Objectives: The therapeutic effects of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation in patients with major depression have shown promising results; however, there is a lack of mechanistic studies using biological markers (BMs) as an outcome. Therefore, our aim was to review noninvasive brain stimulation trials in depression using BMs. Methods: The following databases were used for our systematic review: MEDLINE, Web of Science, Cochrane, and SCIELO. We examined articles published before November 2012 that used TMS and transcranial direct current stimulation as an intervention for depression and had BM as an outcome measure. The search was limited to human studies written in English. Results: Of 1234 potential articles, 52 articles were included. Only studies using TMS were found. Biological markers included immune and endocrine serum markers, neuroimaging techniques, and electrophysiological outcomes. In 12 articles (21.4%), end point BM measurements were not significantly associated with clinical outcomes. All studies reached significant results in the main clinical rating scales. Biological marker outcomes were used as predictors of response, to understand mechanisms of TMS, and as a surrogate of safety. Conclusions: Functional magnetic resonance imaging, single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, cortical excitability, and brain-derived neurotrophic factor consistently showed positive results. Brain-derived neurotrophic factor was the best predictor of patients’ likeliness to respond. These initial results are promising; however, all studies investigating BMs are small, used heterogeneous samples, and did not take into account confounders such as age, sex, or family history. Based on our findings, we recommend further studies to validate BMs in noninvasive brain stimulation trials in MDD.

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The current study describes the in vitro phosphorylation of a human hair keratin, using protein kinase for the first time. Phosphorylation of keratin was demonstrated by 31P NMR (Nuclear Magnetic Resonance) and Diffuse Reflectance Infrared Fourier Transform (DRIFT) techniques. Phosphorylation induced a 2.5 fold increase of adsorption capacity in the first 10 minutes for cationic moiety like Methylene Blue (MB). Thorough description of MB adsorption process was performed by several isothermal models. Reconstructed fluorescent microscopy images depict distinct amounts of dye bound to the differently treated hair. The results of this work suggest that the enzymatic phosphorylation of keratins might have significant implications in hair shampooing and conditioning, where short application times of cationic components are of prime importance.