An exploratory study on facial emotion recognition capacity in beginning Alzheimer's disease.

Objective: It was the aim of this study to investigate facial emotion recognition (FER) in the elderly with cognitive impairment. Method: Twelve patients with Alzheimer's disease (AD) and 12 healthy control subjects were asked to name dynamic or static pictures of basic facial emotions using the Multimodal Emotion Recognition Test and to assess the degree of their difficulty in the recognition task, while their electrodermal conductance was registered as an unconscious processing measure. Results: AD patients had lower objective recognition performances for disgust and fear, but only disgust was accompanied by decreased subjective FER in AD patients. The electrodermal response was similar in all groups. No significant effect of dynamic versus static emotion presentation on FER was found. Conclusion: Selective impairment in recognizing facial expressions of disgust and fear may indicate a nonlinear decline in FER capacity with increasing cognitive impairment and result from progressive though specific damage to neural structures engaged in emotional processing and facial emotion identification. Although our results suggest unchanged unconscious FER processing with increasing cognitive impairment, further investigations on unconscious FER and self-awareness of FER capacity in neurodegenerative disorders are required.

Intraobserver and interobserver variability of ascending aorta diameter as assessed with ECG-gated MDCT: automatic versus manual measurements

Purpose: Recently morphometric measurements of the ascending aorta have been done with ECG-gated MDCT to help the development of future endovascular therapies (TCT) [1]. However, the variability of these measurements remains unknown. It will be interesting to know the impact of CAD (computer aided diagnosis) with automated segmentation of the vessel and automatic measurements of diameter on the management of ascending aorta aneurysms. Methods and Materials: Thirty patients referred for ECG-gated CT thoracic angiography (64-row CT scanner) were evaluated. Measurements of the maximum and minimum ascending aorta diameters were obtained automatically with a commercially available CAD and semi-manually by two observers separately. The CAD algorithms segment the iv-enhanced lumen of the ascending aorta into perpendicular planes along the centreline. The CAD then determines the largest and the smallest diameters. Both observers repeated the automatic measurements and the semimanual measurements during a different session at least one month after the first measurements. The Bland and Altman method was used to study the inter/intraobserver variability. A Wilcoxon signed-rank test was also used to analyse differences between observers. Results: Interobserver variability for semi-manual measurements between the first and second observers was between 1.2 to 1.0 mm for maximal and minimal diameter, respectively. Intraobserver variability of each observer ranged from 0.8 to 1.2 mm, the lowest variability being produced by the more experienced observer. CAD variability could be as low as 0.3 mm, showing that it can perform better than human observers. However, when used in nonoptimal conditions (streak artefacts from contrast in the superior vena cava or weak lumen enhancement), CAD has a variability that can be as high as 0.9 mm, reaching variability of semi-manual measurements. Furthermore, there were significant differences between both observers for maximal and minimal diameter measurements (p<0.001). There was also a significant difference between the first observer and CAD for maximal diameter measurements with the former underestimating the diameter compared to the latter (p<0.001). As for minimal diameters, they were higher when measured by the second observer than when measured by CAD (p<0.001). Neither the difference of mean minimal diameter between the first observer and CAD nor the difference of mean maximal diameter between the second observer and CAD was significant (p=0.20 and 0.06, respectively). Conclusion: CAD algorithms can lessen the variability of diameter measurements in the follow-up of ascending aorta aneurysms. Nevertheless, in non-optimal conditions, it may be necessary to correct manually the measurements. Improvements of the algorithms will help to avoid such a situation.

The "speech of the 'intelligentsia" as the object of the study of Soviet social linguistics

В статье будут рассмотрены два исследования русского и советского лингвиста Е.Д. Поливанова, посвященные фонетике «интеллигентского языка». В начале 1930-ч гг. Поливанов выдвинул новаторскую теорию языка, основанную на изучении социолектов и групповых диалектов русского языка современности. Язык интеллигенции - один из излюбленных предметов исследований лингвиста. Поливанов доказывает, что изменениям подвержен не только словарный запас, но и фонетика, и приводит конкретные примеры фонетических изменений, вызванных революцией.

"Echoing approval": a new speech disorder.

We report the cases of two patients presenting a peculiar speech disorder, which we have named "echoing approval", in which the patients echo, in replying to questions in a dialogue with short phrases, the positive or negative syntactical construction of a question, or its positive or negative intonation, but without any repetition of whole or part of sentences. When asked about their symptoms, the patients replied 80% of the time with "yes, yes", "that's right", or "exactly" to positive questions and "no, no" or "absolutely not" to negative questions, regardless of their actual symptoms and oblivious to self-contradiction. In addition, when the examining doctor was speaking to a medical colleague in the patient's presence and using medical terminology that the patient did not understand, he/she agreed or disagreed with any sentence and technical word uttered in a way entirely dependent on the syntax or intonation used. To distinguish this speech disorder from echolalia or verbal perseverations, with which it may be superficially confused, we suggest that it be called "echoing approval", as it may be part one of the manifestations of the environment-dependency syndrome. This clinical picture was found to be associated with features of transcortical motor aphasia and frontal lobe signs. One patient had a bilateral callosofrontal malignant glioma and the other a probable multiple system atrophy with global deterioration, pre-eminent frontal release signs, diffuse leukoencephalopathy and multiple lacunes. On the basis of these clinical deficits and neuroimaging features, we are unable to delineate the common, or minimal, lesioned network required for this symptomatology to occur, especially in the absence of a series of patients, and with such a difference in both the location and causes of the lesions. However, bilateral frontosubcortical dysfunction was pre-eminent in the clinical picture in both patients, even though more diffuse brain pathology was seen in one, and it might be speculated that dysfunction of the bilateral orbitofrontal and frontomesial motor frontosubcortical circuits might be involved in the aetiology of this peculiar speech disorder.

Lesion Recognition in Multiple Sclerosis: A Sequence Comparison and Quantification Study at 3T

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.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Cre recombinase-mediated inactivation of H-2Dd transgene expression: evidence for partial missing self-recognition by Ly49A NK cells.

We have established H-2D(d)-transgenic (Tg) mice, in which H-2D(d) expression can be extinguished by Cre recombinase-mediated deletion of an essential portion of the transgene (Tg). NK cells adapted to the expression of the H-2D(d) Tg in H-2(b) mice and acquired reactivity to cells lacking H-2D(d), both in vivo and in vitro. H-2D(d)-Tg mice crossed to mice harboring an Mx-Cre Tg resulted in mosaic H-2D(d) expression. That abrogated NK cell reactivity to cells lacking D(d). In D(d) single Tg mice it is the Ly49A+ NK cell subset that reacts to cells lacking D(d), because the inhibitory Ly49A receptor is no longer engaged by its D(d) ligand. In contrast, Ly49A+ NK cells from D(d) x MxCre double Tg mice were unable to react to D(d)-negative cells. These Ly49A+ NK cells retained reactivity to target cells that were completely devoid of MHC class I molecules, suggesting that they were not anergic. Variegated D(d) expression thus impacts specifically missing D(d) but not globally missing class I reactivity by Ly49A+ NK cells. We propose that the absence of D(d) from some host cells results in the acquisition of only partial missing self-reactivity.

Education of Murine NK Cells Requires Both cis and trans Recognition of MHC Class I Molecules.

Although NK cells use invariant receptors to identify diseased cells, they nevertheless adapt to their environment, including the presence of certain MHC class I (MHC-I) molecules. This NK cell education, which is mediated by inhibitory receptors specific for MHC-I molecules, changes the responsiveness of activating NK cell receptors (licensing) and modifies the repertoire of MHC-I receptors used by NK cells. The fact that certain MHC-I receptors have the unusual capacity to recognize MHC-I molecules expressed by other cells (trans) and by the NK cell itself (cis) has raised the question regarding possible contributions of the two types of interactions to NK cell education. Although the analysis of an MHC-I receptor variant suggested a role for cis interaction for NK cell licensing, adoptive NK cell transfer experiments supported a key role for trans recognition. To reconcile some of these findings, we have analyzed the impact of cell type-specific deletion of an MHC-I molecule and of a novel MHC-I receptor variant on the education of murine NK cells when these mature under steady-state conditions in vivo. We find that MHC-I expression by NK cells (cis) and by T cells (trans), and MHC-I recognition in cis and in trans, are both needed for NK cell licensing. Unexpectedly, modifications of the MHC-I receptor repertoire are chiefly dependent on cis binding, which provides additional support for an essential role for this unconventional type of interaction for NK cell education. These data suggest that two separate functions of MHC-I receptors are needed to adapt NK cells to self-MHC-I.

Intracellular pattern-recognition receptors

The last ten years of research in the field of innate immunity have been incredibly fertile: the transmembrane Toll-like receptors (TLRs) were discovered as guardians protecting the host against microbial attacks and the emerging pathways characterized in detail. More recently, cytoplasmic sensors were identified, which are capable of detecting not only microbial, but also self molecules. Importantly, while such receptors trigger crucial host responses to microbial insult, over-activity of some of them has been linked to autoinflammatory disorders, hence demonstrating the importance of tightly regulating their actions over time and space. Here, we provide an overview of recent findings covering this area of innate and inflammatory responses that originate from the cytoplasm