Induction of type I interferons by the transcription factors IRF3 and IRF7 is essential in the initiation of antiviral innate immunity. Activation of IRF3/7 requires C-terminal phosphorylation by the upstream kinases TBK1/IKKi, where IRF3/7 phosphorylation promotes dimerization, and subsequent nuclear translocation to the IFN-beta promoter. Recent studies have described the ubiquitin-editing enzyme A20 as a negative regulator of IRF3 signaling by associating with TBK1/IKKi, however the regulatory mechanism of A20 inhibition remains unclear. Here we describe the adaptor protein, TAX1BP1, as a key regulator of A20 function in terminating signaling to IRF3. Murine embryonic fibroblasts (MEFs) deficient in TAX1BP1 displayed increased amounts of IFN-beta production upon viral challenge compared to WT MEFs. TAX1BP1 inhibited virus-mediated activation of IRF3 at the level of TBK1/IKKi. TAX1BP1 and A20 blocked antiviral signaling by disrupting K63-linked polyubiquitination of TBK1/IKKi independently of the A20 deubiquitination (DUB) domain. Furthermore, TAX1BP1 was required for A20 effector function as A20 was defective for the targeting and inactivation of TBK1 and IKKi in Tax1bp1–/– MEFs. Additionally, we found the E3 ubiquitin ligase TRAF3 to play a critical role in promoting TBK1/IKKi ubiquitination. Collectively, our results demonstrate TBK1/IKKi to be novel substrates for A20 and further identifies a novel mechanism whereby A20 and TAX1BP1 restrict antiviral signaling by disrupting a TRAF3/TBK1/IKKi signaling complex. Several viruses utilize a number of strategies to evade the host innate immune response by inhibiting the production of type I interferons. The Human T-cell leukemia virus type 1 (HTLV-1) has been shown to block interferon signaling, however the mechanism of inhibition is poorly understood. We show here that the HTLV-1 encoded protein, Tax plays a critical role in blunting the activation of type I interferons. Tax expression rendered MEFs hyper-permissive in supporting virus replication. Correspondingly, Tax blocked the production of IFN-beta. Interestingly, Tax did not require NEMO interaction to inhibit antiviral signaling to IRF3/7. Instead, Tax targeted RIP1 and further blocked IRF7 K63-linked polyubiquitination. Altogether, we show that Tax inhibits IFN activation by disrupting the ubiquitin dependent activation of IRF7 mediated by RIP1.

Les techniques d'imagerie par résonance magnétique de Diffusion (IRMd) et de Perfusion (IRMp) permettent la détection de divers aspects importants et complémentaires en imagerie cérébrale. Le travail effectué dans cette thèse présente des contributions théoriques et méthodologiques sur les modalités d'IRM basées sur des images pondérées en diffusion, et sur des images de perfusion par injection de produit de contraste. Pour chacune des deux modalités, les contributions de la thèse sont liées au développement de nouvelles méthodes pour améliorer la qualité, le traitement et l'exploitation des signaux acquis. En IRM de diffusion, la nature complexe du signal est étudiée avec un accent sur l'information de phase. Le signal complexe est ensuite exploité pour corriger le biais induit par le bruit d'acquisition des images, améliorant ainsi l'estimation de certaines métriques structurelles. En IRM de perfusion, le traitement du signal est revisité afin de tenir compte du biais dû à la dispersion du bolus. On montre comment ce phénomène, qui peut empêcher la correcte estimation des métriques de perfusion, peut aussi donner des informations importantes sur l'état pathologique du tissu cérébral. Les contributions apportées dans cette thèse sont présentées dans un cadre théorique et méthodologique validé sur de nombreuses données synthétiques et réelles. / Diffusion and Perfusion Magnetic Resonance Imaging (dMRI & pMRI) represent two modalities that allow sensing important and different but complementary aspects of brain imaging. This thesis presents a theoretical and methodological investigation on the MRI modalities based on diffusion-weighted (DW) and dynamic susceptibility contrast (DSC) images. For both modalities, the contributions of the thesis are related to the development of new methods to improve and better exploit the quality of the obtained signals. With respect to contributions in diffusion MRI, the nature of the complex DW signal is investigated to explore a new potential contrast related to tissue microstructure. In addition, the complex signal is exploited to correct a bias induced by acquisition noise of DW images, thus improving the estimation of structural scalar metrics. With respect to contributions in perfusion MRI, the DSC signal processing is revisited in order to account for the bias due to bolus dispersion. This phenomenon prevents the correct estimation of perfusion metrics but, at the same time, can give important insights about the pathological condition of the brain tissue. The contributions of the thesis are presented within a theoretical and methodological framework, validated on both synthetical and real images.

Based on different sampling theorem, for example classic Shannon’s sampling theorem and Papoulis’ generalized sampling theorem, signals are processed by the sampling devices without loss of information. As an interface between radio receiver front-ends and digital signal processing blocks, sampling devices play a dominant role in digital radio communications. Under the concept of Software Defined Radio (SDR), radio systems are going through the second evolution that mixes analog, digital and software technologies in modern radio designs. One design goal of SDR is to put the A/D converter as close as possible to the antenna. BandPass Sampling (BPS) enables one to have an interface between the RF or the higher IF signal and the A/D converter, and it might be a solution to SDR. However, three sources of performance degradation present in BPS systems, harmful signal spectral overlapping, noise aliasing and sampling timing jitter, hinder the conventional BPS theory from practical circuit implementations. In this thesis work, Generalized Quadrature BandPass Sampling (GQBPS) is first invented and comprehensively studied with focus on the noise aliasing problem. GQBPS consists of both BPS and FIR filtering that can use either real or complex coefficients. By well-designed FIR filtering, GQBPS can also perform frequency down-conversion in addition to noise aliasing reduction. GQBPS is a nonuniform sampling method in most cases. With respect to real circuit implementations, uniform sampling is easier to be realized compared to nonuniform sampling. GQBPS has been also extended to Generalized Uniform BandPass Sampling (GUBPS). GUBPS shares the same property of noise aliasing suppression as GQBPS besides that the samples are uniformly spaced. Due to the moving average operation of FIR filtering, the effect of sampling jitter is also reduced to a certain degree in GQBPS and GUBPS. By choosing a suitable sampling rate, harmful signal spectral overlapping can be avoided. Due to the property of quadrature sampling, the “self image” problem caused by I/Q mismatches is eliminated. Comprehensive theoretical analyses and program simulations on GQBPS and GUBPS have been done based on a general mathematic model. Circuit architecture to implementing GUBPS in Switched-Capacitor circuit technique has been proposed and analyzed. To improve the selectivity at the sampling output, FIR filtering is extended by adding a 1st order complex IIR filter in the implementation. GQBPS and GUBPS operate in voltage-mode. Besides voltage sampling, BPS can also be realized by charge sampling in current-mode. Most other research groups in this area are focusing on bandpass charge sampling. However, the theoretical analysis shows that our GQBPS and GUBPS in voltage mode are more efficient to suppress noise aliasing as compared to bandpass charge sampling with embedded filtering. The aliasing bands of sampled-data spectrum are always weighted by continuous-frequency factors for bandpass charge sampling with embedded filtering while discrete-frequency factors for GQBPS and GUBPS. The transmission zeros of intrinsic filtering will eliminate the corresponding whole aliasing bands of both signal and noise in GQBPS and GUBPS, while it will only cause notches at a limited set of frequencies in bandpass charge sampling. In addition, charge sampling performs an intrinsic continuous-time sinc function that always includes lowpass filtering. This is a drawback for a bandpass input signal. / QC 20100921