Biomedical subjects

Marie-Claude Asselin

Publications and source records attributed to Marie-Claude Asselin.

4 recordsLinked to original sources

PubMed2004

NARC-1/PCSK9 and its natural mutants: zymogen cleavage and effects on the low density lipoprotein (LDL) receptor and LDL cholesterol.

The discovery of autosomal dominant hypercholesterolemic patients with mutations in the PCSK9 gene, encoding the proprotein convertase NARC-1, resulting in the missense mutations suggested a role in low density lipoprotein (LDL) metabolism. We show that the endoplasmic reticulum-localized proNARC-1 to NARC-1 zymogen conversion is Ca2+-independent and that within the zymogen autocatalytic processing site SSVFAQ [downward arrow]SIP Val at P4 and Pro at P3' are critical. The S127R and D374Y mutations result in approximately 50-60% and > or =98% decrease in zymogen processing, respectively. In contrast, the double [D374Y + N157K], F216L, and R218S natural mutants resulted in normal zymogen processing. The cell surface LDL receptor (LDLR) levels are reduced by 35% in lymphoblasts of S127R patients. The LDLR levels are also reduced in stable HepG2 cells overexpressing NARC-1 or its natural mutant S127R, and this reduction is abrogated in the presence of 5 mm ammonium chloride, suggesting that overexpression of NARC-1 increases the turnover rate of the LDLR. Adenoviral expression of wild type human NARC-1 in mice resulted in a maximal approximately 9-fold increase in circulating LDL cholesterol, while in LDLR-/- mice a delayed approximately 2-fold increase in LDL cholesterol was observed. In conclusion, NARC-1 seems to affect both the level of LDLR and that of circulating apoB-containing lipoproteins in an LDLR-dependent and -independent fashion.

Adenoviridae↗

PubMed2004

Parametrically defined cerebral blood vessels as non-invasive blood input functions for brain PET studies.

A non-invasive alternative to arterial blood sampling for the generation of a blood input function for brain positron emission tomography (PET) studies is presented. The method aims to extract the dimensions of the blood vessel directly from PET images and to simultaneously correct the radioactivity concentration for partial volume and spillover. This involves simulation of the tomographic imaging process to generate images of different blood vessel and background geometries and selecting the one that best fits, in a least-squares sense, the acquired PET image. A phantom experiment was conducted to validate the method which was then applied to eight subjects injected with 6-[18F]fluoro-L-DOPA and one subject injected with [11C]CO-labelled red blood cells. In the phantom study, the diameter of syringes filled with an 11C solution and inserted into a water-filled cylinder were estimated with an accuracy of half a pixel (1 mm). The radioactivity concentration was recovered to 100 +/- 4% in the 8.7 mm diameter syringe, the one that most closely approximated the superior sagittal sinus. In the human studies, the method systematically overestimated the calibre of the superior sagittal sinus by 2-3 mm compared to measurements made in magnetic resonance venograms on the same subjects. Sources of discrepancies related to the anatomy of the blood vessel were found not to be fundamental limitations to the applicability of the method to human subjects. This method has the potential to provide accurate quantification of blood radioactivity concentration from PET images without the need for blood samples, corrections for delay and dispersion, co-registered anatomical images, or manually defined regions of interest.

Adult↗

PubMed2002

In vivo metabolism and partitioning of 6-[18F]fluoro-L-meta-tyrosine in whole blood: a unified compartment model.

Physiological quantification of dynamic PET data requires the determination of an input function, preferably from plasma. A compartmental model relating a parent radiotracer, its radiolabelled metabolites and their exchange between plasma and erythrocytes is presented. This model allows for the time course of radioactivity measured in whole blood to be transformed into the time course of the radiotracer in plasma. The utility of this approach is illustrated with blood data collected on 30 human subjects injected with 6-[18F]fluoro-L-meta-tyrosine (FmT), a pre-synaptic dopaminergic radiotracer. A three-compartment four-parameter model is shown to yield significantly better fits to the blood data than related lower and higher order models. This model is found to be robust to measurement noise, and yet sensitive to metabolic changes induced by pretreatment with carbidopa. For FmT, the between-subject variations are shown to be small enough to warrant the use of a population-based correction; tissue time-activity curves were simulated to verify that this correction does not significantly affect the precision and accuracy of the derived rate constants. The unified blood model can be adapted for radiotracers other than FmT as long as the blood partition ratio of the parent radiotracer differs from that of its metabolites and/or the rate at which they equilibrate between plasma and erythrocytes is different.

Adult↗

PubMed2002

Positron emission tomography partial volume correction: estimation and algorithms.

Partial volume effects in positron emission tomography (PET) lead to quantitative under- and over-estimations of the regional concentrations of radioactivity in reconstructed images and corresponding errors in derived functional or parametric images. The limited resolution of PET leads to "tissue-fraction" effects, reflecting underlying tissue heterogeneity, and "spillover" effects between regions. Addressing the former problem in general requires supplementary data, for example, coregistered high-resolution magnetic resonance images, whereas the latter effect can be corrected for with PET data alone if the point-spread function of the tomograph has been characterized. Analysis of otherwise homogeneous region-of-interest data ideally requires a combination of tissue classification and correction for the point-spread function. The formulation of appropriate algorithms for partial volume correction (PVC) is dependent on both the distribution of the signal and the distribution of the underlying noise. A mathematical framework has therefore been developed to accommodate both of these factors and to facilitate the development of new PVC algorithms based on the description of the problem. Several methodologies and algorithms have been proposed and implemented in the literature in order to address these problems. These methods do not, however, explicitly consider the noise model while differing in their underlying assumptions. The general theory for estimation of regional concentrations, associated error estimation, and inhomogeneity tests are presented in a weighted least squares framework. The analysis has been validated using both simulated and real PET data sets. The relations between the current algorithms and those published previously are formulated and compared. The incorporation of tensors into the formulation of the problem has led to the construction of computationally rapid algorithms taking into account both tissue-fraction and spillover effects. The suitability of their application to dynamic and static images is discussed.

Algorithms↗