Sensitive gene expression profiling of human T cell subsets reveals parallel post-thymic differentiation for CD4+ and CD8+ lineages.

The differentiation of CD4(+) or CD8(+) T cells following priming of naive cells is central in the establishment of the immune response against pathogens or tumors. However, our understanding of this complex process and the significance of the multiple subsets of differentiation remains controversial. Gene expression profiling has opened new directions of investigation in immunobiology. Nonetheless, the need for substantial amount of biological material often limits its application range. In this study, we have developed procedures to perform microarray analysis on amplified cDNA from low numbers of cells, including primary T lymphocytes, and applied this technology to the study of CD4 and CD8 lineage differentiation. Gene expression profiling was performed on samples of 1000 cells from 10 different subpopulations, defining the major stages of post-thymic CD4(+) or CD8(+) T cell differentiation. Surprisingly, our data revealed that while CD4(+) and CD8(+) T cell gene expression programs diverge at early stages of differentiation, they become increasingly similar as cells reach a late differentiation stage. This suggests that functional heterogeneity between Ag experienced CD4(+) and CD8(+) T cells is more likely to be located early during post-thymic differentiation, and that late stages of differentiation may represent a common end in the development of T-lymphocytes.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Le dispositif mythico-rituel comme opérateur efficace (techniques magico-religieuses d'arrêt, figuration et résolution des états critiques : analyse de cas)

(Résumé de l'ouvrage) Dans cet ouvrage réunissant théologiens et philosophes, le corps contemporain est pensé par rapport à ce qui l'excède, ce qui le met en scène, ce qui le reprend, ce qui le transforme aujourd'hui. Dans une première partie, l'ouvrage propose des éclairages sur le corps à partir de ce qui met en question sa vision strictement rationnelle. Puis, trois auteurs évoquent les différentes manières dont la Bible, la philosophie et la littérature contemporaine mettent en scène les corps. Dans une troisième partie, sont abordées des questions plus spécifiquement reliées à la tradition catholique, au christianisme primitif et à la pratique de l'ascèse. Enfin, quatre contributions explorent le défi posé par la déréalisation du corps dans nos sociétés d'aujourd'hui, avec, pour clore l'ensemble, une réflexion sur le dualisme qui traverse le questionnement sur le corps.

Decision making techniques with similarity measures and OWA operators

We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

A highly sensitive in vitro infection assay to explore early stages of mouse mammary tumor virus infection.

Mouse mammary tumor virus (MMTV) infection of adult mice induces a strong response to superantigen (Sag) in their draining lymph nodes, which results from the presentation of Sag by MMTV-infected B cells to Sag-reactive T cells. To date, infection with physiologically relevant doses of MMTV can be detected in vivo only after several days of Sag-mediated T-cell-dependent amplification of infected B cells. Furthermore, no efficient in vitro system of detecting MMTV infection is available. Such a model would allow the dissection of the early phase of infection, the assessment of the contributions of different cell types, and the screening of large panels of molecules for their potential roles in infection and Sag response. For these reasons, we have established an in vitro model for detecting infection which is as sensitive and reproducible as the in vivo model. We found that the viral envelope (Env) protein is crucial for target cell infection but not for presentation of Sag. Furthermore, we show that infection of purified B cells with MMTV induces entry of Sag-responsive T cells into the cell cycle, while other professional antigen-presenting cells, such as dendritic cells, are much less efficient in inducing a response.

Detailed analysis and follow-up studies of a high-throughput screening for indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a key regulator of immune responses and therefore an important therapeutic target for the treatment of diseases that involve pathological immune escape, such as cancer. Here, we describe a robust and sensitive high-throughput screen (HTS) for IDO1 inhibitors using the Prestwick Chemical Library of 1200 FDA-approved drugs and the Maybridge HitFinder Collection of 14,000 small molecules. Of the 60 hits selected for follow-up studies, 14 displayed IC50 values below 20 μM under the secondary assay conditions, and 4 showed an activity in cellular tests. In view of the high attrition rate we used both experimental and computational techniques to identify and to characterize compounds inhibiting IDO1 through unspecific inhibition mechanisms such as chemical reactivity, redox cycling, or aggregation. One specific IDO1 inhibitor scaffold, the imidazole antifungal agents, was chosen for rational structure-based lead optimization, which led to more soluble and smaller compounds with micromolar activity.

Late side-effects after curative intent radiotherapy: Identification of hypersensitive patients for personalized strategy.

Radiation therapy undeniably enhances local control and thus improves overall survival in cancer patients. However, some long-term cancer survivors (less than 10%) develop severe late radio-induced toxicities altering their quality of life. Therefore, there is a need to identify patients who are sensitive to those toxicities and who could benefit from adapted care. In this review, we address all available techniques aiming to detect patients' hyper-radiosensitivity and present the scientific rationales these techniques are based on.

Techniques for CT and MR, post-processing, radiation.

Brain perfusion can be assessed by CT and MR. For CT, two major techniquesare used. First, Xenon CT is an equilibrium technique based on a freely diffusibletracer. First pass of iodinated contrast injected intravenously is a second method,more widely available. Both methods are proven to be robust and quantitative,thanks to the linear relationship between contrast concentration and x-ray attenuation.For the CT methods, concern regarding x-ray doses delivered to the patientsneed to be addressed. MR is also able to assess brain perfusion using the firstpass of gadolinium based contrast agent injected intravenously. This method hasto be considered as a semi-quantitative because of the non linear relationshipbetween contrast concentration and MR signal changes. Arterial spin labelingis another MR method assessing brain perfusion without injection of contrast. Insuch case, the blood flow in the carotids is magnetically labelled by an externalradiofrequency pulse and observed during its first pass through the brain. Eachof this various CT and MR techniques have advantages and limits that will be illustratedand summarised.Learning Objectives:1. To understand and compare the different techniques for brain perfusionimaging.2. To learn about the methods of acquisition and post-processing of brainperfusion by first pass of contrast agent for CT and MR.3. To learn about non contrast MR methods (arterial spin labelling).

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.

Assessment of Nondestructive Testing Technologies for Quality Control/Quality Assurance of Asphalt Mixtures, TR-653, 2015

Asphalt pavements suffer various failures due to insufficient quality within their design lives. The American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) has been proposed to improve pavement quality through quantitative performance prediction. Evaluation of the actual performance (quality) of pavements requires in situ nondestructive testing (NDT) techniques that can accurately measure the most critical, objective, and sensitive properties of pavement systems. The purpose of this study is to assess existing as well as promising new NDT technologies for quality control/quality assurance (QC/QA) of asphalt mixtures. Specifically, this study examined field measurements of density via the PaveTracker electromagnetic gage, shear-wave velocity via surface-wave testing methods, and dynamic stiffness via the Humboldt GeoGauge for five representative paving projects covering a range of mixes and traffic loads. The in situ tests were compared against laboratory measurements of core density and dynamic modulus. The in situ PaveTracker density had a low correlation with laboratory density and was not sensitive to variations in temperature or asphalt mix type. The in situ shear-wave velocity measured by surface-wave methods was most sensitive to variations in temperature and asphalt mix type. The in situ density and in situ shear-wave velocity were combined to calculate an in situ dynamic modulus, which is a performance-based quality measurement. The in situ GeoGauge stiffness measured on hot asphalt mixtures several hours after paving had a high correlation with the in situ dynamic modulus and the laboratory density, whereas the stiffness measurement of asphalt mixtures cooled with dry ice or at ambient temperature one or more days after paving had a very low correlation with the other measurements. To transform the in situ moduli from surface-wave testing into quantitative quality measurements, a QC/QA procedure was developed to first correct the in situ moduli measured at different field temperatures to the moduli at a common reference temperature based on master curves from laboratory dynamic modulus tests. The corrected in situ moduli can then be compared against the design moduli for an assessment of the actual pavement performance. A preliminary study of microelectromechanical systems- (MEMS)-based sensors for QC/QA and health monitoring of asphalt pavements was also performed.

Practical considerations for improving the productivity of mass spectrometry-based proteomics.

Mass spectrometry (MS) is currently the most sensitive and selective analytical technique for routine peptide and protein structure analysis. Top-down proteomics is based on tandem mass spectrometry (MS/ MS) of intact proteins, where multiply charged precursor ions are fragmented in the gas phase, typically by electron transfer or electron capture dissociation, to yield sequence-specific fragment ions. This approach is primarily used for the study of protein isoforms, including localization of post-translational modifications and identification of splice variants. Bottom-up proteomics is utilized for routine high-throughput protein identification and quantitation from complex biological samples. The proteins are first enzymatically digested into small (usually less than ca. 3 kDa) peptides, these are identified by MS or MS/MS, usually employing collisional activation techniques. To overcome the limitations of these approaches while combining their benefits, middle-down proteomics has recently emerged. Here, the proteins are digested into long (3-15 kDa) peptides via restricted proteolysis followed by the MS/MS analysis of the obtained digest. With advancements of high-resolution MS and allied techniques, routine implementation of the middle-down approach has been made possible. Herein, we present the liquid chromatography (LC)-MS/MS-based experimental design of our middle-down proteomic workflow coupled with post-LC supercharging.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.

Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond.

The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.