Giovanna Rizzo

Effects of Particulate Matter on Genomic DNA Methylation Content and iNOS Promoter Methylation

Background Altered patterns of gene expression mediate the effects of particulate matter (PM) on human health, but mechanisms through which PM modifies gene expression are largely undetermined. Objectives We aimed at identifying short- and long-term effects of PM exposure on DNA methylation, a major genomic mechanism of gene expression control, in workers in an electric furnace steel plant with well-characterized exposure to PM with aerodynamic diameters < 10 μm (PM10). Methods We measured global genomic DNA methylation content estimated in Alu and long interspersed nuclear element-1 (LINE-1) repeated elements, and promoter DNA methylation of iNOS (inducible nitric oxide synthase), a gene suppressed by DNA methylation and induced by PM exposure in blood leukocytes. Quantitative DNA methylation analysis was performed through bisulfite PCR pyrosequencing on blood DNA obtained from 63 workers on the first day of a work week (baseline, after 2 days off work) and after 3 days of work (postexposure). Individual PM10 exposure was between 73.4 and 1,220 μg/m3. Results Global methylation content estimated in Alu and LINE-1 repeated elements did not show changes in postexposure measures compared with baseline. PM10 exposure levels were negatively associated with methylation in both Alu [β = −0.19 %5-methylcytosine (%5mC); p = 0.04] and LINE-1 [β = −0.34 %5mC; p = 0.04], likely reflecting long-term PM10 effects. iNOS promoter DNA methylation was significantly lower in postexposure blood samples compared with baseline (difference = −0.61 %5mC; p = 0.02). Conclusions We observed changes in global and gene specific methylation that should be further characterized in future investigations on the effects of PM.

A modified damped Richardson-Lucy algorithm to reduce isotropic background effects in spherical deconvolution

Spherical deconvolution methods have been applied to diffusion MRI to improve diffusion tensor tractography results in brain regions with multiple fibre crossing. Recent developments, such as the introduction of non-negative constraints on the solution, allow a more accurate estimation of fibre orientations by reducing instability effects due to noise robustness. Standard convolution methods do not, however, adequately model the effects of partial volume from isotropic tissue, such as gray matter, or cerebrospinal fluid, which may degrade spherical deconvolution results. Here we use a newly developed spherical deconvolution algorithm based on an adaptive regularization (damped version of the Richardson-Lucy algorithm) to reduce isotropic partial volume effects. Results from both simulated and in vivo datasets show that, compared to a standard non-negative constrained algorithm, the damped Richardson-Lucy algorithm reduces spurious fibre orientations and preserves angular resolution of the main fibre orientations. These findings suggest that, in some brain regions, non-negative constraints alone may not be sufficient to reduce spurious fibre orientations. Considering both the speed of processing and the scan time required, this new method has the potential for better characterizing white matter anatomy and the integrity of pathological tissue.

A Model-Based Deconvolution Approach to Solve Fiber Crossing in Diffusion-Weighted MR Imaging

A deconvolution approach is presented to solve fiber crossing in diffusion magnetic resonance imaging. In order to provide a direct physical interpretation of the signal generation process, we started from the classical multicompartment model and rewrote this in terms of a convolution process, identifying a significant scalar parameter alpha to characterize the physical system response. Deconvolution is performed by a modified version of the Richardson-Lucy algorithm. Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution. The in vivo data confirms the efficacy of this method to resolve fiber crossing in real complex brain structures. These results suggest the usefulness of our approach in fiber tracking or connectivity studies

In Vivo Quantification of Helical Blood Flow in Human Aorta by Time-Resolved Three-Dimensional Cine Phase Contrast Magnetic Resonance Imaging

The mechanics of blood flow in arteries plays a key role in the health of individuals. In this framework, the role played by the presence of helical flow in the human aorta is still not clear in its relation to physiology and pathology. We report here a method for quantifying helical flow in vivo employing time-resolved cine phase contrast magnetic resonance imaging to obtain the complete spatio-temporal description of the three-dimensional pulsatile blood flow patterns in aorta. The method is applied to data of one healthy volunteer. Particle traces were calculated from velocity data: to them we applied a Lagrangian-based method for helical flow quantification, the Helical Flow Index, which has been developed and evaluated in silico in order to reveal global organization of blood flow. Our results: (i) put in evidence that the systolic hemodynamics in aorta is characterized by an evolving helical flow (we quantified a 24% difference in terms of the content of helicity in the streaming blood, between mid and early systole); (ii) indicate that in the first part of the systole helicity is ascrivable mainly to the asymmetry of blood flow in the left ventricle, joined with the laterality of the aorta. In conclusion, this study shows that the quantification of helical blood flow in vivo is feasible, and it might allow detection of anomalies in the expected physiological development of helical flow in aorta and accordingly, could be used in a diagnostic/prognostic index for clinical practice.

Mechanistic insight into the physiological relevance of helical blood flow in the human aorta: an in vivo study

The hemodynamics within the aorta of five healthy humans were investigated to gain insight into the complex helical flow patterns that arise from the existence of asymmetries in the aortic region. The adopted approach is aimed at (1) overcoming the relative paucity of quantitative data regarding helical blood flow dynamics in the human aorta and (2) identifying common characteristics in physiological aortic flow topology, in terms of its helical content. Four-dimensional phase-contrast magnetic resonance imaging (4D PC MRI) was combined with algorithms for the calculation of advanced fluid dynamics in this study. These algorithms allowed us to obtain a 4D representation of intra-aortic flow fields and to quantify the aortic helical flow. For our purposes, helicity was used as a measure of the alignment of the velocity and the vorticity. There were two key findings of our study: (1) intra-individual analysis revealed a statistically significant difference in the helical content at different phases of systole and (2) group analysis suggested that aortic helical blood flow dynamics is an emerging behavior that is common to normal individuals. Our results also suggest that helical flow might be caused by natural optimization of fluid transport processes in the cardiovascular system, aimed at obtaining efficient perfusion. The approach here applied to assess in vivo helical blood flow could be the starting point to elucidate the role played by helicity in the generation and decay of rotating flows in the thoracic aorta.

In Vivo Serotonin 5HT2A Receptor Binding and Personality Traits in Healthy Subjects: A Positron Emission Tomography Study

Using positron emission tomography (PET) and [11C]raclopride, an association between striatal D2 dopamine receptors and emotional detachment has been recently reported. Several laboratory findings indicate a link between the serotoninergic system and harm avoidance. In this study we investigated, in a group of healthy volunteers, the relationship between the in vivo binding of 3-(2′-[18F]fluoroethyl)spiperone ([18F]FESP) to cortical 5HT2 and striatal D2 receptors and three personality dimensions, i.e., “novelty seeking,” “reward dependence,” and “harm avoidance.” Eleven healthy volunteers were evaluated by means of the Tridimensional personality Questionnaire (C. R. 11, Arch. Gen. Psychiatry 44: 573–588.) and underwent a PET scan with [18F]FESP. Harm avoidance showed a significant inverse correlation with [18F]FESP binding in the cerebral cortex, particularly in the frontal cortex (R2 = −0.709, P = 0.0145) and left parietal cortex (R = −0.629, P = 0.038) but not in the basal ganglia (r = −0.176, P = 0.651). Similar results were obtained using SPM at a P threshold of 0.05. No significant correlation was observed with novelty seeking or reward dependence. In the cerebral cortex, high values of [18F]FESP binding values are associated with a high tendency to avoid danger, indicating involvement of the serotoninergic system and, in particular, 5HT2A receptors, in this trait of personality. The results of this as well as of previous studies on personality dimensions indicate the existence of a relationship between behavioral and neurobiological factors. In addition these results support the concept that the variability of PET data may be explained by neurochemical differences related to the prevalence of specific personality traits.

Inflow boundary conditions for image-based computational hemodynamics: Impact of idealized versus measured velocity profiles in the human aorta

Here we analyse the influence of assumptions made on boundary conditions (BCs) extracted from phase-contrast magnetic resonance imaging (PC-MRI) in vivo measured flow data, applied on hemodynamic models of human aorta. This study aims at investigating if the imposition of BCs based on defective information, even when measured and specific-to-the-subject, might lead to misleading numerical representations of the aortic hemodynamics. In detail, we focus on the influence of assumptions regarding velocity profiles at the inlet section of the ascending aorta, incorporating phase flow data within the computational model. The obtained results are compared in terms of disturbed shear and helical bulk flow structures, when the same measured flow rate is prescribed as inlet BC in terms of 3D or 1D (axial) measured or idealized velocity profiles. Our findings clearly indicate that: (1) the imposition of PC-MRI measured axial velocity profiles as inflow BC may capture disturbed shear with sufficient accuracy, without the need to prescribe (and measure) realistic fully 3D velocity profiles; (2) attention should be put in setting idealized or PC-MRI measured axial velocity profiles at the inlet boundaries of aortic computational models when bulk flow features are investigated, because helical flow structures are markedly affected by the BC prescribed at the inflow. We conclude that the plausibility of the assumption of idealized velocity profiles as inlet BCs in personalized computational models can lead to misleading representations of the aortic hemodynamics both in terms of disturbed shear and bulk flow structures.

Basal ganglia and language: phonology modulates dopaminergic release

Basal ganglia have been implicated in syntactic and phonological processes, but direct evidence has been scarce. Here, we used [11C]raclopride and positron emission tomography to measure modulations of the dopaminergic system induced by phonological or syntactic processing. Two significant effects were found. First, the level of accuracy in phonological processing significantly correlated with tracer binding potential in the left caudate nucleus. Second, the speed in phonological processing significantly correlated with tracer binding potential in the left putamen. Thus, a more accurate and fast phonological processing was associated with a reduced dopamine requirement in the left striatum. These findings show that the striatal dopaminergic system plays an essential role in grammatical processes that form the core of human language.

Errors Introduced by Tissue Heterogeneity in Estimation of Local Cerebral Glucose Utilization with Current Kinetic Models of the [18F]Fluorodeoxyglucose Method

The effects of tissue heterogeneity on the estimation of regional cerebral glucose utilization (rCMRglc) in normal humans with [18F]2-fluoro-2-deoxy-d-glucose ([18F]FDG) and positron emission tomography (PET) were compared with respect to the various kinetic models of the [18F]FDG method. The kinetic models were conventional homogeneous tissue models of the [18F]FDG method, with (4K Model) and without (3K Model) a rate constant to account for an apparent loss of [18F]2-fluoro-2-deoxy-d-glucose-6-phosphate ([18F]FDG-6-P), and a tissue heterogeneity model (TH Model). When either of the kinetic models designed for homogeneous tissues was applied to heterogeneous tissues, estimates of the rate constant for efflux of [18F]FDG from the tissue (k*2) and of the rate constant for phosphorylation of [18F]FDG (k*3) decreased as the duration of the experimental period was increased. When the 4K Model was used, estimates of the rate constant for the apparent dephosphorylation of [18F]FDG-6-P (k*4) were significantly greater than zero and fell with increasing duration of the experimental period. Although the TH Model included no term to describe an apparent dephosphorylation of [18F]FDG-6-P, the fit of the TH Model to the time course of total tissue radioactivity was at least as good as and often better than the fit of the 4K Model in the 120-min period following the pulse of [18F]FDG. Hence, the high estimates of k*4 found in PET studies of ≤120 min can be explained as the consequence of measuring radioactivity in a heterogeneous tissue and applying a model designed for a homogeneous tissue; there remains no evidence of significant dephosphorylation of [18F]FDG-6-P in this time period. Furthermore, use of the 4K Model led to an overestimation of rCMRglc; whole-brain glucose utilization calculated with the 4K Model was >20% higher than values usually obtained in normal humans by the model-independent Kety–Schmidt technique. rCMRglc was accurately estimated by the TH Model and, in experimental periods sufficiently long to minimize the effects of tissue heterogeneity, also by the original 3K Model of the deoxyglucose method.

On the use of in vivo measured flow rates as boundary conditions for image-based hemodynamic models of the human aorta: implications for indicators of abnormal flow

The purpose of this study is to investigate how the imposition of personalized, non-invasively measured blood flow rates as boundary conditions (BCs) influences image-based computational hemodynamic studies in the human aorta. We extracted from 4D phase-contrast MRI acquisitions of a healthy human (1) the geometry of the thoracic aorta with supra-aortic arteries and (2) flow rate waveforms at all boundaries. Flow simulations were carried out, and the implications that the imposition of different BC schemes based on the measured flow rates have on wall shear stress (WSS)-based indicators of abnormal flow were analyzed. Our results show that both the flow rate repartition among the multiple outlets of the aorta and the distribution and magnitude of the WSS-based indicators are strongly influenced by the adopted BC strategy. Keeping as reference hemodynamic model the one where the applied BC scheme allowed to obtain a satisfactory agreement between the computed and the measured flow rate waveforms, differences in WSS-based indicators up to 49% were observed when the other BC strategies were applied. In conclusion, we demonstrate that in subject-specific computational hemodynamics models of the human aorta the imposition of BC settings based on non-invasively measured flow rate waveforms influences indicators of abnormal flow to a large extent. Hence, a BCs set-up assuring realistic, subject-specific instantaneous flow rate distribution must be applied when BCs such as flow rates are prescribed.