CT attenuation values of blood and myocardium: rationale for accurate coronary artery calcifications detection with multi-detector CT.

OBJECTIVES: To determine inter-session and intra/inter-individual variations of the attenuations of aortic blood/myocardium with MDCT in the context of calcium scoring. To evaluate whether these variations are dependent on patients' characteristics. METHODS: Fifty-four volunteers were evaluated with calcium scoring non-enhanced CT. We measured attenuations (inter-individual variation) and standard deviations (SD, intra-individual variation) of the blood in the ascending aorta and of the myocardium of left ventricle. Every volunteer was examined twice to study the inter-session variation. The fat pad thickness at the sternum and noise (SD of air) were measured too. These values were correlated with the measured aortic/ventricular attenuations and their SDs (Pearson). Historically fixed thresholds (90 and 130 HU) were tested against different models based on attenuations of blood/ventricle. RESULTS: The mean attenuation was 46 HU (range, 17-84 HU) with mean SD 23 HU for the blood, and 39 HU (10-82 HU) with mean SD 18 HU for the myocardium. The attenuation/SD of the blood were significantly higher than those of the myocardium (p < 0.01). The inter-session variation was not significant. There was a poor correlation between SD of aortic blood/ventricle with fat thickness/noise. Based on existing models, 90 HU threshold offers a confidence interval of approximately 95% and 130 HU more than 99%. CONCLUSIONS: Historical thresholds offer high confidence intervals for exclusion of aortic blood/myocardium and by the way for detecting calcifications. Nevertheless, considering the large variations of blood/myocardium CT values and the influence of patient's characteristics, a better approach might be an adaptive threshold.

Genome-wide analysis of adaptive molecular evolution in the carnivorous plant Utricularia gibba

The genome of the bladderwort Utricularia gibba provides an unparalleled opportunity to uncover the adaptive landscape of an aquatic carnivorous plant with unique phenotypic features such as absence of roots, development of water-filled suction bladders, and a highly ramified branching pattern. Despite its tiny size, the U. gibba genome accommodates approximately as many genes as other plant genomes. To examine the relationship between the compactness of its genome and gene turnover, we compared the U. gibba genome with that of four other eudicot species, defining a total of 17,324 gene families (orthogroups). These families were further classified as either 1) lineage-specific expanded/contracted or 2) stable in size. The U. gibba-expanded families are generically related to three main phenotypic features: 1) trap physiology, 2) key plant morphogenetic/developmental pathways, and 3) response to environmental stimuli, including adaptations to life in aquatic environments. Further scans for signatures of protein functional specialization permitted identification of seven candidate genes with amino acid changes putatively fixed by positive Darwinian selection in the U. gibba lineage. The Arabidopsis orthologs of these genes (AXR, UMAMIT41, IGS, TAR2, SOL1, DEG9, and DEG10) are involved in diverse plant biological functions potentially relevant for U. gibba phenotypic diversification, including 1) auxin metabolism and signal transduction, 2) flowering induction and floral meristem transition, 3) root development, and 4) peptidases. Taken together, our results suggest numerous candidate genes and gene families as interesting targets for further experimental confirmation of their functional and adaptive roles in the U. gibba's unique lifestyle and highly specialized body plan.

Neural mechanisms underlying adaptive actions after slips

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory thetabeta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

RT-PCR-ELISA for detection of Apple stem grooving virus in apple trees

A method to detect Apple stem grooving virus (ASGV) based on reverse transcription polymerase chain reaction (RT-PCR) was developed using primers ASGV4F-ASGV4R targeting the viral replicase gene, followed by a sandwich hybridisation, in microtiter plates, for colorimetric detection of the PCR products. The RT-PCR was performed with the Titan™ RT-PCR system, using AMV and diluted crude extracts of apple (Malus domestica) leaf or bark for the first strand synthesis and a mixture of Taq and PWO DNA polymerase for the PCR step. The RT-PCR products is hybridised with both a biotin-labelled capture probe linked to a streptavidin-coated microtiter plate and a digoxigenin (DIG)-labelled detection probe. The complex was detected with an anti-DIG conjugate labelled with alkaline phosphatase. When purified ASGV was added to extracts of plant tissue, as little as 400 fg of the virus was detected with this method. The assay with ASGV4F-ASGV4R primers specifically detected the virus in ASGV-infected apple trees from different origins, whereas no signal was observed with amplification products obtained with primers targeting the coat protein region of the ASGV genome or with primers specific for Apple chlorotic leaf spot virus (ACLSV) and Apple stem pitting virus (ASPV). The technique combines the power of PCR to increase the number of copies of the targeted gene, the specificity of DNA hybridization, and the ease of colorimetric detection and sample handling in microplates.

Vibration analysis for Bearing outer race condition diagnostics

This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.

Detection of Horizontal Two-Phase Flow Patterns Through a Neural Network Model

One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.

Switchable Lanthanide Luminescence for Detection of Biomolecules

Binary probes are oligonucleotide probe pairs that hybridize adjacently to a complementary target nucleic acid. In order to detect this hybridization, the two probes can be modified with, for example, fluorescent molecules, chemically reactive groups or nucleic acid enzymes. The benefit of this kind of binary probe based approach is that the hybridization elicits a detectable signal which is distinguishable from background noise even though unbound probes are not removed by washing before measurement. In addition, the requirement of two simultaneous binding events increases specificity. Similarly to binary oligonucleotide probes, also certain enzymes and fluorescent proteins can be divided into two parts and used in separation-free assays. Split enzyme and fluorescent protein reporters have practical applications among others as tools to investigate protein-protein interactions within living cells. In this study, a novel label technology, switchable lanthanide luminescence, was introduced and used successfully in model assays for nucleic acid and protein detection. This label technology is based on a luminescent lanthanide chelate divided into two inherently non-luminescent moieties, an ion carrier chelate and a light harvesting antenna ligand. These form a highly luminescent complex when brought into close proximity; i.e., the label moieties switch from a dark state to a luminescent state. This kind of mixed lanthanide complex has the same beneficial photophysical properties as the more typical lanthanide chelates and cryptates - sharp emission peaks, long emission lifetime enabling time-resolved measurement, and large Stokes’ shift, which minimize the background signal. Furthermore, the switchable lanthanide luminescence technique enables a homogeneous assay set-up. Here, switchable lanthanide luminescence label technology was first applied to sensitive, homogeneous, single-target nucleic acid and protein assays with picomolar detection limits and high signal to background ratios. Thereafter, a homogeneous four-plex nucleic acid array-based assay was developed. Finally, the label technology was shown to be effective in discrimination of single nucleotide mismatched targets from fully matched targets and the luminescent complex formation was analyzed more thoroughly. In conclusion, this study demonstrates that the switchable lanthanide luminescencebased label technology can be used in various homogeneous bioanalytical assays.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Clinical assessment of the effect of digital filtering on the detection of ventricular late potentials

Ventricular late potentials are low-amplitude signals originating from damaged myocardium and detected on the body surface by ECG filtering and averaging. Digital filters present in commercial equipment may interfere with the ability of arrhythmia stratification. We compared 40-Hz BiSpec (BI) and classical 40- to 250-Hz band-pass Butterworth bidirectional (BD) filters in terms of impact on time domain variables and diagnostic properties. In a transverse retrospective age-adjusted case-control study, 221 subjects with sinus rhythm without bundle branch block were divided into three groups after signal-averaged ECG acquisition: GI (N = 40), clinically normal controls, GII (N = 158), subjects with coronary heart disease without sustained monomorphic ventricular tachycardia (SMVT), and GIII (N = 23), subjects with heart disease and documented SMVT. Conventional variables analyzed from vector magnitude data after averaging to 0.3 µV final noise were obtained by application of each filter to the averaged signal, and evaluated in pairs by numerical comparison and by diagnostic agreement assessment, using conventional and optimized thresholds of normality. Significant differences were found between BI and BD variables in all groups, with diagnostic results showing significant disagreement between both filters [kappa value of 0.61 (P<0.05) for GII and 0.31 for GIII (P = NS)]. Sensitivity for SMVT was lower with BI than with BD (65.2 vs 91.3%, respectively, P<0.05). Filters provided significantly different numerical and diagnostic results and the BI filter showed only limited clinical application to risk stratification of ventricular arrhythmia.

Detection of patients with functional dyspepsia using wavelet transform applied to their electrogastrogram

The aim of the present study was to develop a classifier able to discriminate between healthy controls and dyspeptic patients by analysis of their electrogastrograms. Fifty-six electrogastrograms were analyzed, corresponding to 42 dyspeptic patients and 14 healthy controls. The original signals were subsampled, filtered and divided into the pre-, post-, and prandial stages. A time-frequency transformation based on wavelets was used to extract the signal characteristics, and a special selection procedure based on correlation was used to reduce their number. The analysis was carried out by evaluating different neural network structures to classify the wavelet coefficients into two groups (healthy subjects and dyspeptic patients). The optimization process of the classifier led to a linear model. A dimension reduction that resulted in only 25% of uncorrelated electrogastrogram characteristics gave 24 inputs for the classifier. The prandial stage gave the most significant results. Under these conditions, the classifier achieved 78.6% sensitivity, 92.9% specificity, and an error of 17.9 ± 6% (with a 95% confidence level). These data show that it is possible to establish significant differences between patients and normal controls when time-frequency characteristics are extracted from an electrogastrogram, with an adequate component reduction, outperforming the results obtained with classical Fourier analysis. These findings can contribute to increasing our understanding of the pathophysiological mechanisms involved in functional dyspepsia and perhaps to improving the pharmacological treatment of functional dyspeptic patients.

Evaluation of 99mTc-HYNIC-βAla-Bombesin(7-14) as an agent for pancreas tumor detection in mice

Pancreatic adenocarcinoma is important in oncology because of its high mortality rate. Deaths may be avoided if an early diagnosis could be achieved. Several types of tumors overexpress gastrin-releasing peptide receptors (GRPr), including pancreatic cancer cells. Thus, a radiolabeled peptide derivative of gastrin-releasing peptide (GRP) may be useful as a specific imaging probe. The purpose of the present study was to evaluate the feasibility of using99mTc-HYNIC-βAla-Bombesin(7-14)as an imaging probe for Capan-1 pancreatic adenocarcinoma. Xenographic pancreatic tumor was developed in nude mice and characterized by histopathological analysis. Biodistribution studies and scintigraphic images were carried out in tumor-bearing nude mice. The two methods showed higher uptake by pancreatic tumor when compared to muscle (used as control), and the tumor-to-muscle ratio indicated that99mTc-HYNIC-βAla-Bombesin(7-14)uptake was four-fold higher in tumor cells than in other tissues. Scintigraphic images also showed a clear signal at the tumor site. The present data indicate that99mTc-HYNIC-βAla-Bombesin(7-14)may be useful for the detection of pancreatic adenocarcinoma.

Detection of Epilepsy with a Commercial EEG Headband

Epilepsy is a chronic brain disorder, characterized by reoccurring seizures. Automatic sei-zure detector, incorporated into a mobile closed-loop system, can improve the quality of life for the people with epilepsy. Commercial EEG headbands, such as Emotiv Epoc, have a potential to be used as the data acquisition devices for such a system. In order to estimate that potential, epileptic EEG signals from the commercial devices were emulated in this work based on the EEG data from a clinical dataset. The emulated characteristics include the referencing scheme, the set of electrodes used, the sampling rate, the sample resolution and the noise level. Performance of the existing algorithm for detection of epileptic seizures, developed in the context of clinical data, has been evaluated on the emulated commercial data. The results show, that after the transformation of the data towards the characteristics of Emotiv Epoc, the detection capabilities of the algorithm are mostly preserved. The ranges of acceptable changes in the signal parameters are also estimated.

Imagerie à haut contraste et caractérisation d'exoplanètes par la spectroscopie intégrale de champ

Cette thèse porte sur l’amélioration des techniques d’imagerie à haut-contraste permettant la détection directe de compagnons à de faibles séparations de leur étoile hôte. Plus précisément, elle s’inscrit dans le développement du Gemini Planet Imager (GPI) qui est un instrument de deuxième génération pour les télescopes Gemini. Cette caméra utilisera un spectromètre à champ intégral (SCI) pour caractériser les compagnons détectés et pour réduire le bruit de tavelure limitant leur détection et corrigera la turbulence atmosphérique à un niveau encore jamais atteint en utilisant deux miroirs déformables dans son système d’optique adaptative (OA) : le woofer et le tweeter. Le woofer corrigera les aberrations de basses fréquences spatiales et de grandes amplitudes alors que le tweeter compensera les aberrations de plus hautes fréquences ayant une plus faible amplitude. Dans un premier temps, les performances pouvant être atteintes à l’aide des SCIs présentement en fonction sur les télescopes de 8-10 m sont investiguées en observant le compagnon de l’étoile GQ Lup à l’aide du SCI NIFS et du système OA ALTAIR installés sur le télescope Gemini Nord. La technique de l’imagerie différentielle angulaire (IDA) est utilisée pour atténuer le bruit de tavelure d’un facteur 2 à 6. Les spectres obtenus en bandes JHK ont été utilisés pour contraindre la masse du compagnon par comparaison avec les prédictions des modèles atmosphériques et évolutifs à 8−60 MJup, où MJup représente la masse de Jupiter. Ainsi, il est déterminé qu’il s’agit plus probablement d’une naine brune que d’une planète. Comme les SCIs présentement en fonction sont des caméras polyvalentes pouvant être utilisées pour plusieurs domaines de l’astrophysique, leur conception n’a pas été optimisée pour l’imagerie à haut-contraste. Ainsi, la deuxième étape de cette thèse a consisté à concevoir et tester en laboratoire un prototype de SCI optimisé pour cette tâche. Quatre algorithmes de suppression du bruit de tavelure ont été testés sur les données obtenues : la simple différence, la double différence, la déconvolution spectrale ainsi qu’un nouvel algorithme développé au sein de cette thèse baptisé l’algorithme des spectres jumeaux. Nous trouvons que l’algorithme des spectres jumeaux est le plus performant pour les deux types de compagnons testés : les compagnons méthaniques et non-méthaniques. Le rapport signal-sur-bruit de la détection a été amélioré d’un facteur allant jusqu’à 14 pour un compagnon méthanique et d’un facteur 2 pour un compagnon non-méthanique. Dernièrement, nous nous intéressons à certains problèmes liés à la séparation de la commande entre deux miroirs déformables dans le système OA de GPI. Nous présentons tout d’abord une méthode utilisant des calculs analytiques et des simulations Monte Carlo pour déterminer les paramètres clés du woofer tels que son diamètre, son nombre d’éléments actifs et leur course qui ont ensuite eu des répercussions sur le design général de l’instrument. Ensuite, le système étudié utilisant un reconstructeur de Fourier, nous proposons de séparer la commande entre les deux miroirs dans l’espace de Fourier et de limiter les modes transférés au woofer à ceux qu’il peut précisément reproduire. Dans le contexte de GPI, ceci permet de remplacer deux matrices de 1600×69 éléments nécessaires pour une séparation “classique” de la commande par une seule de 45×69 composantes et ainsi d’utiliser un processeur prêt à être utilisé plutôt qu’une architecture informatique plus complexe.

Detection of methotrexate using surface plasmon resonance biosensors for chemotherapy monitoring

Le méthotrexate (MTX), un agent anti-cancéreux fréquemment utilisé en chimiothérapie, requiert généralement un suivi thérapeutique de la médication (Therapeutic Drug Monitoring, TDM) pour surveiller son niveau sanguin chez le patient afin de maximiser son efficacité tout en limitant ses effets secondaires. Malgré la fenêtre thérapeutique étroite entre l’efficacité et la toxicité, le MTX reste, à ce jour, un des agents anti-cancéreux les plus utilisés au monde. Les techniques analytiques existantes pour le TDM du MTX sont coûteuses, requièrent temps et efforts, sans nécessairement fournir promptement les résultats dans le délai requis. Afin d’accélérer le processus de dosage du MTX en TDM, une stratégie a été proposée basée sur un essai compétitif caractérisé principalement par le couplage plasmonique d’une surface métallique et de nanoparticules d’or. Plus précisément, l’essai quantitatif exploite la réaction de compétition entre le MTX et une nanoparticule d’or fonctionnalisée avec l’acide folique (FA-AuNP) ayant une affinité pour un récepteur moléculaire, la réductase humaine de dihydrofolate (hDHFR), une enzyme associée aux maladies prolifératives. Le MTX libre mixé avec les FA-AuNP, entre en compétition pour les sites de liaison de hDHFR immobilisés sur une surface active en SPR ou libres en solution. Par la suite, les FA-AuNP liées au hDHFR fournissent une amplification du signal qui est inversement proportionnelle à la concentration de MTX. La résonance des plasmons de surface (SPR) est généralement utilisée comme une technique spectroscopique pour l’interrogation des interactions biomoléculaires. Les instruments SPR commerciaux sont généralement retrouvés dans les grands laboratoires d’analyse. Ils sont également encombrants, coûteux et manquent de sélectivité dans les analyses en matrice complexe. De plus, ceux-ci n’ont pas encore démontré de l’adaptabilité en milieu clinique. Par ailleurs, les analyses SPR des petites molécules comme les médicaments n’ont pas été explorés de manière intensive dû au défi posé par le manque de la sensibilité de la technique pour cette classe de molécules. Les développements récents en science des matériaux et chimie de surfaces exploitant l’intégration des nanoparticules d’or pour l’amplification de la réponse SPR et la chimie de surface peptidique ont démontré le potentiel de franchir les limites posées par le manque de sensibilité et l’adsorption non-spécifique pour les analyses directes dans les milieux biologiques. Ces nouveaux concepts de la technologie SPR seront incorporés à un système SPR miniaturisé et compact pour exécuter des analyses rapides, fiables et sensibles pour le suivi du niveau du MTX dans le sérum de patients durant les traitements de chimiothérapie. L’objectif de cette thèse est d’explorer différentes stratégies pour améliorer l’analyse des médicaments dans les milieux complexes par les biocapteurs SPR et de mettre en perspective le potentiel des biocapteurs SPR comme un outil utile pour le TDM dans le laboratoire clinique ou au chevet du patient. Pour atteindre ces objectifs, un essai compétitif colorimétrique basé sur la résonance des plasmons de surface localisée (LSPR) pour le MTX fut établi avec des nanoparticules d’or marquées avec du FA. Ensuite, cet essai compétitif colorimétrique en solution fut adapté à une plateforme SPR. Pour les deux essais développés, la sensibilité, sélectivité, limite de détection, l’optimisation de la gamme dynamique et l’analyse du MTX dans les milieux complexes ont été inspectés. De plus, le prototype de la plateforme SPR miniaturisée fut validé par sa performance équivalente aux systèmes SPR existants ainsi que son utilité pour analyser les échantillons cliniques des patients sous chimiothérapie du MTX. Les concentrations de MTX obtenues par le prototype furent comparées avec des techniques standards, soit un essai immunologique basé sur la polarisation en fluorescence (FPIA) et la chromatographie liquide couplée avec de la spectrométrie de masse en tandem (LC-MS/MS) pour valider l’utilité du prototype comme un outil clinique pour les tests rapides de quantification du MTX. En dernier lieu, le déploiement du prototype à un laboratoire de biochimie dans un hôpital démontre l’énorme potentiel des biocapteurs SPR pour utilisation en milieux clinique.