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1.  Crosstalk between Helicobacter pylori and Gastric Epithelial Cells Is Impaired by Docosahexaenoic Acid 
PLoS ONE  2013;8(4):e60657.
H. pylori colonizes half of the world's population leading to gastritis, ulcers and gastric cancer. H. pylori strains resistant to antibiotics are increasing which raises the need for alternative therapeutic approaches. Docosahexaenoic acid (DHA) has been shown to decrease H. pylori growth and its associated-inflammation through mechanisms poorly characterized. We aimed to explore DHA action on H. pylori-mediated inflammation and adhesion to gastric epithelial cells (AGS) and also to identify bacterial structures affected by DHA. H. pylori growth and metabolism was assessed in liquid cultures. Bacterial adhesion to AGS cells was visualized by transmission electron microscopy and quantified by an Enzyme Linked Immunosorbent Assay. Inflammatory proteins were assessed by immunoblotting in infected AGS cells, previously treated with DHA. Bacterial total and outer membrane protein composition was analyzed by 2-dimensional gel electrophoresis. Concentrations of 100 µM of DHA decreased H. pylori growth, whereas concentrations higher than 250 µM irreversibly inhibited bacteria survival. DHA reduced ATP production and adhesion to AGS cells. AGS cells infected with DHA pre-treated H. pylori showed a 3-fold reduction in Interleukin-8 (IL-8) production and a decrease of COX2 and iNOS. 2D electrophoresis analysis revealed that DHA changed the expression of H. pylori outer membrane proteins associated with stress response and metabolism and modified bacterial lipopolysaccharide phenotype. As conclusions our results show that DHA anti-H. pylori effects are associated with changes of bacteria morphology and metabolism, and with alteration of outer membrane proteins composition, that ultimately reduce the adhesion of bacteria and the burden of H. pylori-related inflammation.
PMCID: PMC3618039  PMID: 23577140
2.  Quantitative multi-parameter mapping of R1, PD*, MT, and R2* at 3T: a multi-center validation 
Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD*), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2* = 1/T2*). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2* (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.
PMCID: PMC3677134  PMID: 23772204
multi-center; T1; PD; MT; T2*; 3T; MPM; qMRI
3.  White matter pathology in Parkinson's disease: The effect of imaging protocol differences and relevance to executive function 
Neuroimage  2012;62(3-2):1675-1684.
Diffusion magnetic resonance imaging is increasingly used as a non-invasive method to investigate white matter structure in neurological and neuropsychiatric disease. However, many options are available for the acquisition sequence and analysis method. Here we used Parkinson's disease as a model neurodegenerative disorder to compare imaging protocols and analysis options. We investigated fractional anisotropy and mean diffusivity of white matter in patients and age-matched controls, comparing two datasets acquired with different imaging protocols. One protocol prioritised the number of b value acquisitions, whilst the other prioritised the number of gradient directions. The dataset with more gradient directions was more sensitive to reductions in fractional anisotropy in Parkinson's disease, whilst the dataset with more b values was more sensitive to increases in mean diffusivity. Moreover, the areas of reduced fractional anisotropy were highly similar to areas of increased mean diffusivity in PD patients. Next, we compared two widely used analysis methods: tract-based spatial statistics identified reduced fractional anisotropy and increased mean diffusivity in Parkinson's disease in many of the major white matter tracts in the frontal and parietal lobes. Voxel-based analyses were less sensitive, with similar patterns of white matter pathology observed only at liberal statistical thresholds. We also used tract-based spatial statistics to identify correlations between a test of executive function (phonemic fluency), fractional anisotropy and mean diffusivity in prefrontal white matter in both Parkinson's disease patients and controls. These findings suggest that in Parkinson's disease there is widespread pathology of cerebral white matter, and furthermore, pathological white matter in the frontal lobe may be associated with executive dysfunction. Diffusion imaging protocols that prioritised the number of directions versus the number of b values were differentially sensitive to alternative markers of white matter pathology, such as fractional anisotropy and mean diffusivity.
► DTI shows abnormal frontal white matter in Parkinson's disease. ► FA and MD in the frontal lobe correlate with executive function in PD. ► The number of directions and b values affects sensitivity to FA/MD changes in PD. ► TBSS is more sensitive than VBM to white matter change in Parkinson's disease.
PMCID: PMC3413883  PMID: 22713671
DTI, diffusion tensor imaging; FA, fractional anisotropy; FWE, family-wise error; H&Y, Hoehn and Yahr; MD, mean diffusivity; MMSE, mini-mental state examination; MR, magnetic resonance; PD, Parkinson's disease; TBSS, tract-based spatial statistics; TFCE, threshold-free cluster enhancement; UPDRS, Unified Parkinson's Disease Rating Scale; DTI; TBSS; VBM; Parkinson's disease; Executive function
4.  Docosahexaenoic Acid Inhibits Helicobacter pylori Growth In Vitro and Mice Gastric Mucosa Colonization 
PLoS ONE  2012;7(4):e35072.
H. pylori drug-resistant strains and non-compliance to therapy are the major causes of H. pylori eradication failure. For some bacterial species it has been demonstrated that fatty acids have a growth inhibitory effect. Our main aim was to assess the ability of docosahexaenoic acid (DHA) to inhibit H. pylori growth both in vitro and in a mouse model. The effectiveness of standard therapy (ST) in combination with DHA on H. pylori eradication and recurrence prevention success was also investigated. The effects of DHA on H. pylori growth were analyzed in an in vitro dose-response study and n in vivo model. We analized the ability of H. pylori to colonize mice gastric mucosa following DHA, ST or a combination of both treatments. Our data demonstrate that DHA decreases H. pylori growth in vitro in a dose-dependent manner. Furthermore, DHA inhibits H. pylori gastric colonization in vivo as well as decreases mouse gastric mucosa inflammation. Addition of DHA to ST was also associated with lower H. pylori infection recurrence in the mouse model. In conclusion, DHA is an inhibitor of H. pylori growth and its ability to colonize mouse stomach. DHA treatment is also associated with a lower recurrence of H. pylori infection in combination with ST. These observations pave the way to consider DHA as an adjunct agent in H. pylori eradication treatment.
PMCID: PMC3328494  PMID: 22529974
5.  QuickBundles, a Method for Tractography Simplification 
Diffusion MR data sets produce large numbers of streamlines which are hard to visualize, interact with, and interpret in a clinically acceptable time scale, despite numerous proposed approaches. As a solution we present a simple, compact, tailor-made clustering algorithm, QuickBundles (QB), that overcomes the complexity of these large data sets and provides informative clusters in seconds. Each QB cluster can be represented by a single centroid streamline; collectively these centroid streamlines can be taken as an effective representation of the tractography. We provide a number of tests to show how the QB reduction has good consistency and robustness. We show how the QB reduction can help in the search for similarities across several subjects.
PMCID: PMC3518823  PMID: 23248578
tractography; diffusion MRI; fiber clustering; white matter segmentation; dimensionality reduction; clustering algorithms; DTI
6.  Vascular contributions to pattern analysis: Comparing gradient and spin echo fMRI at 3T 
Neuroimage  2011;56(2-10):643-650.
Multivariate pattern analysis is often assumed to rely on signals that directly reflect differences in the distribution of particular neural populations. The source of the signal used in these analyses remains unclear however, and an alternative model suggests that signal from larger draining veins may play a significant role. The current study was designed to investigate the vascular contribution to pattern analyses at 3T by comparing the results obtained from gradient and spin echo data. Classification analyses were carried out comparing line orientations in V1, tone frequencies in A1, and responses from different fingers in M1. In all cases, classification accuracy in the spin echo data was not significantly different from chance. In contrast, classification accuracies in the gradient echo data were significantly above chance, and significantly higher than the accuracies observed for the spin echo data. These results suggest that at the field strength and spatial resolution used for the majority of fMRI studies, a considerable proportion of the signal used by pattern analysis originates in the vasculature.
PMCID: PMC3084461  PMID: 20350605
fMRI; Multivariate pattern analysis; Classification; Decoding; Spin echo

Results 1-6 (6)