987 resultados para Quantitative Interpretation


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Abstract : In the subject of fingerprints, the rise of computers tools made it possible to create powerful automated search algorithms. These algorithms allow, inter alia, to compare a fingermark to a fingerprint database and therefore to establish a link between the mark and a known source. With the growth of the capacities of these systems and of data storage, as well as increasing collaboration between police services on the international level, the size of these databases increases. The current challenge for the field of fingerprint identification consists of the growth of these databases, which makes it possible to find impressions that are very similar but coming from distinct fingers. However and simultaneously, this data and these systems allow a description of the variability between different impressions from a same finger and between impressions from different fingers. This statistical description of the withinand between-finger variabilities computed on the basis of minutiae and their relative positions can then be utilized in a statistical approach to interpretation. The computation of a likelihood ratio, employing simultaneously the comparison between the mark and the print of the case, the within-variability of the suspects' finger and the between-variability of the mark with respect to a database, can then be based on representative data. Thus, these data allow an evaluation which may be more detailed than that obtained by the application of rules established long before the advent of these large databases or by the specialists experience. The goal of the present thesis is to evaluate likelihood ratios, computed based on the scores of an automated fingerprint identification system when the source of the tested and compared marks is known. These ratios must support the hypothesis which it is known to be true. Moreover, they should support this hypothesis more and more strongly with the addition of information in the form of additional minutiae. For the modeling of within- and between-variability, the necessary data were defined, and acquired for one finger of a first donor, and two fingers of a second donor. The database used for between-variability includes approximately 600000 inked prints. The minimal number of observations necessary for a robust estimation was determined for the two distributions used. Factors which influence these distributions were also analyzed: the number of minutiae included in the configuration and the configuration as such for both distributions, as well as the finger number and the general pattern for between-variability, and the orientation of the minutiae for within-variability. In the present study, the only factor for which no influence has been shown is the orientation of minutiae The results show that the likelihood ratios resulting from the use of the scores of an AFIS can be used for evaluation. Relatively low rates of likelihood ratios supporting the hypothesis known to be false have been obtained. The maximum rate of likelihood ratios supporting the hypothesis that the two impressions were left by the same finger when the impressions came from different fingers obtained is of 5.2 %, for a configuration of 6 minutiae. When a 7th then an 8th minutia are added, this rate lowers to 3.2 %, then to 0.8 %. In parallel, for these same configurations, the likelihood ratios obtained are on average of the order of 100,1000, and 10000 for 6,7 and 8 minutiae when the two impressions come from the same finger. These likelihood ratios can therefore be an important aid for decision making. Both positive evolutions linked to the addition of minutiae (a drop in the rates of likelihood ratios which can lead to an erroneous decision and an increase in the value of the likelihood ratio) were observed in a systematic way within the framework of the study. Approximations based on 3 scores for within-variability and on 10 scores for between-variability were found, and showed satisfactory results. Résumé : Dans le domaine des empreintes digitales, l'essor des outils informatisés a permis de créer de puissants algorithmes de recherche automatique. Ces algorithmes permettent, entre autres, de comparer une trace à une banque de données d'empreintes digitales de source connue. Ainsi, le lien entre la trace et l'une de ces sources peut être établi. Avec la croissance des capacités de ces systèmes, des potentiels de stockage de données, ainsi qu'avec une collaboration accrue au niveau international entre les services de police, la taille des banques de données augmente. Le défi actuel pour le domaine de l'identification par empreintes digitales consiste en la croissance de ces banques de données, qui peut permettre de trouver des impressions très similaires mais provenant de doigts distincts. Toutefois et simultanément, ces données et ces systèmes permettent une description des variabilités entre différentes appositions d'un même doigt, et entre les appositions de différents doigts, basées sur des larges quantités de données. Cette description statistique de l'intra- et de l'intervariabilité calculée à partir des minuties et de leurs positions relatives va s'insérer dans une approche d'interprétation probabiliste. Le calcul d'un rapport de vraisemblance, qui fait intervenir simultanément la comparaison entre la trace et l'empreinte du cas, ainsi que l'intravariabilité du doigt du suspect et l'intervariabilité de la trace par rapport à une banque de données, peut alors se baser sur des jeux de données représentatifs. Ainsi, ces données permettent d'aboutir à une évaluation beaucoup plus fine que celle obtenue par l'application de règles établies bien avant l'avènement de ces grandes banques ou par la seule expérience du spécialiste. L'objectif de la présente thèse est d'évaluer des rapports de vraisemblance calcul és à partir des scores d'un système automatique lorsqu'on connaît la source des traces testées et comparées. Ces rapports doivent soutenir l'hypothèse dont il est connu qu'elle est vraie. De plus, ils devraient soutenir de plus en plus fortement cette hypothèse avec l'ajout d'information sous la forme de minuties additionnelles. Pour la modélisation de l'intra- et l'intervariabilité, les données nécessaires ont été définies, et acquises pour un doigt d'un premier donneur, et deux doigts d'un second donneur. La banque de données utilisée pour l'intervariabilité inclut environ 600000 empreintes encrées. Le nombre minimal d'observations nécessaire pour une estimation robuste a été déterminé pour les deux distributions utilisées. Des facteurs qui influencent ces distributions ont, par la suite, été analysés: le nombre de minuties inclus dans la configuration et la configuration en tant que telle pour les deux distributions, ainsi que le numéro du doigt et le dessin général pour l'intervariabilité, et la orientation des minuties pour l'intravariabilité. Parmi tous ces facteurs, l'orientation des minuties est le seul dont une influence n'a pas été démontrée dans la présente étude. Les résultats montrent que les rapports de vraisemblance issus de l'utilisation des scores de l'AFIS peuvent être utilisés à des fins évaluatifs. Des taux de rapports de vraisemblance relativement bas soutiennent l'hypothèse que l'on sait fausse. Le taux maximal de rapports de vraisemblance soutenant l'hypothèse que les deux impressions aient été laissées par le même doigt alors qu'en réalité les impressions viennent de doigts différents obtenu est de 5.2%, pour une configuration de 6 minuties. Lorsqu'une 7ème puis une 8ème minutie sont ajoutées, ce taux baisse d'abord à 3.2%, puis à 0.8%. Parallèlement, pour ces mêmes configurations, les rapports de vraisemblance sont en moyenne de l'ordre de 100, 1000, et 10000 pour 6, 7 et 8 minuties lorsque les deux impressions proviennent du même doigt. Ces rapports de vraisemblance peuvent donc apporter un soutien important à la prise de décision. Les deux évolutions positives liées à l'ajout de minuties (baisse des taux qui peuvent amener à une décision erronée et augmentation de la valeur du rapport de vraisemblance) ont été observées de façon systématique dans le cadre de l'étude. Des approximations basées sur 3 scores pour l'intravariabilité et sur 10 scores pour l'intervariabilité ont été trouvées, et ont montré des résultats satisfaisants.

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OBJECTIVE: Prospective studies have shown that quantitative ultrasound (QUS) techniques predict the risk of fracture of the proximal femur with similar standardised risk ratios to dual-energy x-ray absorptiometry (DXA). Few studies have investigated these devices for the prediction of vertebral fractures. The Basel Osteoporosis Study (BOS) is a population-based prospective study to assess the performance of QUS devices and DXA in predicting incident vertebral fractures. METHODS: 432 women aged 60-80 years were followed-up for 3 years. Incident vertebral fractures were assessed radiologically. Bone measurements using DXA (spine and hip) and QUS measurements (calcaneus and proximal phalanges) were performed. Measurements were assessed for their value in predicting incident vertebral fractures using logistic regression. RESULTS: QUS measurements at the calcaneus and DXA measurements discriminated between women with and without incident vertebral fracture, (20% height reduction). The relative risks (RRs) for vertebral fracture, adjusted for age, were 2.3 for the Stiffness Index (SI) and 2.8 for the Quantitative Ultrasound Index (QUI) at the calcaneus and 2.0 for bone mineral density at the lumbar spine. The predictive value (AUC (95% CI)) of QUS measurements at the calcaneus remained highly significant (0.70 for SI, 0.72 for the QUI, and 0.67 for DXA at the lumbar spine) even after adjustment for other confounding variables. CONCLUSIONS: QUS of the calcaneus and bone mineral density measurements were shown to be significant predictors of incident vertebral fracture. The RRs for QUS measurements at the calcaneus are of similar magnitude as for DXA measurements.

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Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays.

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Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

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Introduction Lesion detection in multiple sclerosis (MS) is an essential part of its clinical diagnosis. In addition, radiological characterisation of MS lesions is an important research field that aims at distinguishing different MS types, monitoring drug response and prognosis. To date, various MR protocols have been proposed to obtain optimal lesion contrast for early and comprehensive diagnosis of the MS disease. In this study, we compare the sensitivity of five different MR contrasts for lesion detection: (i) the DIR sequence (Double Inversion Recovery, [4]), (ii) the Dark-fluid SPACE acquisition schemes, a 3D variant of a 2D FLAIR sequence [1], (iii) the MP2RAGE [2], an MP-RAGE variant that provides homogeneous T1 contrast and quantitative T1-values, and the sequences currently used for clinical MS diagnosis (2D FLAIR, MP-RAGE). Furthermore, we investigate the T1 relaxation times of cortical and sub-cortical regions in the brain hemispheres and the cerebellum at 3T. Methods 10 early-stage female MS patients (age: 31.64.7y; disease duration: 3.81.9y; disability score, EDSS: 1.80.4) and 10 healthy controls (age and gender-matched: 31.25.8y) were included in the study after obtaining informed written consent according to the local ethic protocol. All experiments were performed at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil [5]. The imaging protocol included the following sequences, (all except for axial FLAIR 2D with 1x1x1.2 mm3 voxel and 256x256x160 matrix): DIR (TI1/TI2/TR XX/3652/10000 ms, iPAT=2, TA 12:02 min), MP-RAGE (TI/TR 900/2300 ms, iPAT=3, TA 3:47 min); MP2RAGE (TI1/TI2/TR 700/2500/5000 ms, iPAT=3, TA 8:22 min, cf. [2]); 3D FLAIR SPACE (only for patient 4-6, TI/TR 1800/5000 ms, iPAT=2, TA=5;52 min, cf. [1]); Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix, TI/TR 2500/9000 ms, iPAT=2, TA 4:05 min). Lesions were identified by two experienced neurologist and radiologist, manually contoured and assigned to regional locations (s. table 1). Regional lesion masks (RLM) from each contrast were compared for number and volumes of lesions. In addition, RLM were merged in a single "master" mask, which represented the sum of the lesions of all contrasts. T1 values were derived for each location from this mask for patients 5-10 (3D FLAIR contrast was missing for patient 1-4). Results & Discussion The DIR sequence appears the most sensitive for total lesions count, followed by the MP2RAGE (table 1). The 3D FLAIR SPACE sequence turns out to be more sensitive than the 2D FLAIR, presumably due to reduced partial volume effects. Looking for sub-cortical hemispheric lesions, the DIR contrast appears to be equally sensitive to the MP2RAGE and SPACE, but most sensitive for cerebellar MS plaques. The DIR sequence is also the one that reveals cortical hemispheric lesions best. T1 relaxation times at 3T in the WM and GM of the hemispheres and the cerebellum, as obtained with the MP2RAGE sequence, are shown in table 2. Extending previous studies, we confirm overall longer T1-values in lesion tissue and higher standard deviations compared to the non-lesion tissue and control tissue in healthy controls. We hypothesize a biological (different degree of axonal loss and demyelination) rather than technical origin. Conclusion In this study, we applied 5 MR contrasts including two novel sequences to investigate the contrast of highest sensitivity for early MS diagnosis. In addition, we characterized for the first time the T1 relaxation time in cortical and sub-cortical regions of the hemispheres and the cerebellum. Results are in agreement with previous publications and meaningful biological interpretation of the data.

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OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

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Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

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Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.

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Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

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La douleur neuropathique est définie comme une douleur causée par une lésion du système nerveux somato-sensoriel. Elle se caractérise par des douleurs exagérées, spontanées, ou déclenchées par des stimuli normalement non douloureux (allodynie) ou douloureux (hyperalgésie). Bien qu'elle concerne 7% de la population, ses mécanismes biologiques ne sont pas encore élucidés. L'étude des variations d'expressions géniques dans les tissus-clés des voies sensorielles (notamment le ganglion spinal et la corne dorsale de la moelle épinière) à différents moments après une lésion nerveuse périphérique permettrait de mettre en évidence de nouvelles cibles thérapeutiques. Elles se détectent de manière sensible par reverse transcription quantitative real-time polymerase chain reaction (RT- qPCR). Pour garantir des résultats fiables, des guidelines ont récemment recommandé la validation des gènes de référence utilisés pour la normalisation des données ("Minimum information for publication of quantitative real-time PCR experiments", Bustin et al 2009). Après recherche dans la littérature des gènes de référence fréquemment utilisés dans notre modèle de douleur neuropathique périphérique SNI (spared nerve injury) et dans le tissu nerveux en général, nous avons établi une liste de potentiels bons candidats: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) et L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) et hydroxymethyl-bilane synthase (HMBS). Nous avons évalué la stabilité d'expression de ces gènes dans le ganglion spinal et dans la corne dorsale à différents moments après la lésion nerveuse (SNI) en calculant des coefficients de variation et utilisant l'algorithme geNorm qui compare les niveaux d'expression entre les différents candidats et détermine la paire de gènes restante la plus stable. Il a aussi été possible de classer les gènes selon leur stabilité et d'identifier le nombre de gènes nécessaires pour une normalisation la plus précise. Les gènes les plus cités comme référence dans le modèle SNI ont été GAPDH, HMBS, Actb, HPRT1 et 18S. Seuls HPRT1 and 18S ont été précédemment validés dans des arrays de RT-qPCR. Dans notre étude, tous les gènes testés dans le ganglion spinal et dans la corne dorsale satisfont au critère de stabilité exprimé par une M-value inférieure à 1. Par contre avec un coefficient de variation (CV) supérieur à 50% dans le ganglion spinal, 18S ne peut être retenu. La paire de gènes la plus stable dans le ganglion spinal est HPRT1 et Actb et dans la corne dorsale il s'agit de RPL29 et RPL13a. L'utilisation de 2 gènes de référence stables suffit pour une normalisation fiable. Nous avons donc classé et validé Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 et 18S comme gènes de référence utilisables dans la corne dorsale pour le modèle SNI chez le rat. Dans le ganglion spinal 18S n'a pas rempli nos critères. Nous avons aussi déterminé que la combinaison de deux gènes de référence stables suffit pour une normalisation précise. Les variations d'expression génique de potentiels gènes d'intérêts dans des conditions expérimentales identiques (SNI, tissu et timepoints post SNI) vont pouvoir se mesurer sur la base d'une normalisation fiable. Non seulement il sera possible d'identifier des régulations potentiellement importantes dans la genèse de la douleur neuropathique mais aussi d'observer les différents phénotypes évoluant au cours du temps après lésion nerveuse.

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The advent and application of high-resolution array-based comparative genome hybridization (array CGH) has led to the detection of large numbers of copy number variants (CNVs) in patients with developmental delay and/or multiple congenital anomalies as well as in healthy individuals. The notion that CNVs are also abundantly present in the normal population challenges the interpretation of the clinical significance of detected CNVs in patients. In this review we will illustrate a general clinical workflow based on our own experience that can be used in routine diagnostics for the interpretation of CNVs.

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Barnardos supports children whose well-being is under threat, by working with them, their families and communities and by campaigning for the rights of children. Barnardos was established in Ireland in 1962 and is Ireland’s leading independent Children's charity.  

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Introduction: In the middle of the 90's, the discovery of endogenous ligands for cannabinoid receptors opened a new era in this research field. Amides and esters of arachidonic acid have been identified as these endogenous ligands. Arachidonoylethanolamide (anandamide or AEA) and 2-Arachidonoylglycerol (2-AG) seem to be the most important of these lipid messengers. In addition, virodhamine (VA), noladin ether (2-AGE), and N-arachidonoyl dopamine (NADA) have been shown to bind to CB receptors with varying affinities. During recent years, it has become more evident that the EC system is part of fundamental regulatory mechanisms in many physiological processes such as stress and anxiety responses, depression, anorexia and bulimia, schizophrenia disorders, neuroprotection, Parkinson disease, anti-proliferative effects on cancer cells, drug addiction, and atherosclerosis. Aims: This work presents the problematic of EC analysis and the input of Information Dependant Acquisition based on hybrid triple quadrupole linear ion trap (QqQLIT) system for the profiling of these lipid mediators. Methods: The method was developed on a LC Ultimate 3000 series (Dionex, Sunnyvale, CA, USA) coupled to a QTrap 4000 system (Applied biosystems, Concord, ON, Canada). The ECs were separated on an XTerra C18 MS column (50 × 3.0 mm i.d., 3.5 μm) with a 5 min gradient elution. For confirmatory analysis, an information-dependant acquisition experiment was performed with selected reaction monitoring (SRM) as survey scan and enhanced produced ion (EPI) as dependant scan. Results: The assay was found to be linear in the concentration range of 0.1-5 ng/mL for AEA, 0.3-5 ng/mL for VA, 2-AGE, and NADA and 1-20 ng/mL for 2-AG using 0.5 mL of plasma. Repeatability and intermediate precision were found less than 15% over the tested concentration ranges. Under non-pathophysiological conditions, only AEA and 2-AG were actually detected in plasma with concentration ranges going from 104 to 537 pg/mL and from 2160 to 3990 pg/mL respectively. We have particularly focused our scopes on the evaluation of EC level changes in biological matrices through drug addiction and atherosclerosis processes. We will present preliminary data obtained during pilot study after administration of cannabis on human patients. Conclusion: ECs have been shown to play a key role in regulation of many pathophysiological processes. Medical research in these different fields continues to growth in order to understand and to highlight the predominant role of EC in the CNS and peripheral tissues signalisation. The profiling of these lipids needs to develop rapid, highly sensitive and selective analytical methods.