This article is available online at http://www.jlr.org ties ( 1-7 ), highlighting the need for effi cient means of characterizing lipid composition in vivo ( 1-7 ). Parameters such as mean unsaturation, mean polyunsaturation, and mean chain length can provide useful information about diet, fat distribution, and metabolism ( 9-14 ). The abovementioned parameters of lipid deposits can be obtained in vitro using high resolution proton magnetic resonance spectroscopy (HR-NMR) (15)(16)(17)(18)(19)(20). The disadvantages associated with in vitro techniques are well known: invasiveness and time-consuming extraction protocols ( 21 ). The main advantage is high resolution, which allows discrimination between olefi nic proton peaks and glycerol methilenic peaks.To the best of our knowledge, ours was one of the fi rst groups to suggest that in vivo magnetic resonance spectroscopy (MRS) can provide information about fat composition in living animals ( 22 ). In that paper, chemical shift imaging was used to obtain parametric maps of PUFA distribution in adipose tissue of living rats. Recently, other groups have proposed in vivo single-voxel localized spectroscopy for the characterization of lipid tissue in animals ( 23 ) and humans ( 24 ) at 7 T. Single-voxel techniques take advantage of the possibility to select a relatively small volume of interest (of the order of 1-2 mm 3 in animals) that allows to obtain good voxel-based shimming and consequently, well-resolved resonances ( 23 ).However, with optimized single-voxel techniques in vivo spectra are also affected by relatively high line-width with partially overlapping peaks. Reliable extraction of lipid parameters from in vivo spectra requires suitable methods for spectral analysis and processing ( 23, 24 ). Lipid parameters are calculated from the relationships between the Abstract In vivo single-voxel magnetic resonance spectroscopy (MRS) at 4.7T and ex vivo high-resolution proton magnetic resonance spectroscopy (HR-NMR) at 500 MHz were used to study the composition of adipose tissues in Zucker obese and Zucker lean rats. Lipid composition was characterized by unsaturation and polyunsaturation indexes and mean chain lengths. In vitro experiments were conducted in known mixtures of triglycerides and oils in order to validate the method. To avoid inaccuracies due to partial peak overlapping in MRS, peak quantifi cation was performed after fi tting of spectral peaks by using the QUEST algorithm. The intensity of different spectral lines was also corrected for T2 relaxation. Albeit with different sensitivity and accuracy, both techniques revealed that white adipose tissue is characterized by lower unsaturation and polyunsaturation indexes in obese rats compared with controls. HR-NMR revealed similar differences in brown adipose tissue. The present fi ndings confi rm the hypothesis that obese and lean Zucker rats have different adipose tissue composition.
Proton magnetic resonance spectroscopy (MRS) is a sensitive method for investigating the biochemical compounds in a tissue. The interpretation of the data relies on the quantification algorithms applied to MR spectra. Each of these algorithms has certain underlying assumptions and may allow one to incorporate prior knowledge, which could influence the quality of the fit. The most commonly considered types of prior knowledge include the line-shape model (Lorentzian, Gaussian, Voigt), knowledge of the resonating frequencies, modeling of the baseline, constraints on the damping factors and phase, etc. In this article, we study whether the statistical outcome of a biological investigation can be influenced by the quantification method used. We chose to study lipid signals because of their emerging role in the investigation of metabolic disorders. Lipid spectra, in particular, are characterized by peaks that are in most cases not Lorentzian, because measurements are often performed in difficult body locations, e.g. in visceral fats close to peristaltic movements in humans or very small areas close to different tissues in animals. This leads to spectra with several peak distortions. Linear combination of Model spectra (LCModel), Advanced Method for Accurate Robust and Efficient Spectral fitting (AMARES), quantitation based on QUantum ESTimation (QUEST), Automated Quantification of Short Echo-time MRS (AQSES)-Lineshape and Integration were applied to simulated spectra, and area under the curve (AUC) values, which are proportional to the quantity of the resonating molecules in the tissue, were compared with true values. A comparison between techniques was also carried out on lipid signals from obese and lean Zucker rats, for which the polyunsaturation value expressed in white adipose tissue should be statistically different, as confirmed by high-resolution NMR measurements (considered the gold standard) on the same animals. LCModel, AQSES-Lineshape, QUEST and Integration gave the best results in at least one of the considered groups of simulated or in vivo lipid signals. These outcomes highlight the fact that quantification methods can influence the final result and its statistical significance.
Isoxazoline-containing peptidomimetics, designed to be effective α(v)β(3) and α(5)β(1) integrin ligands, were synthesized through an original procedure involving N,O-bis(trimethylsilyl)hydroxyamine conjugate addition to alkylidene acetoacetates, followed by intramolecular hemiketalization. To mimic the RGD recognition sequence, basic and acidic terminal appendages were introduced, and the final products were tested in cell adhesion inhibition assays. All the synthesized compounds proved to be excellent ligands for both integrin receptors, and a strong influence on intracellular signaling and phosphorylation pathways was demonstrated by evaluation of fibronectin-induced phosphorylation of ERK. The molecular basis of the observed inhibitory activity was suggested on the results of docking experiments.
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