Pyochelin enantiomers and their outer-membrane siderophore transporters in fluorescent pseudomonads: structural bases for unique enantiospecific recognition.

Pyochelin (Pch) and enantiopyochelin (EPch) are enantiomeric siderophores, with three chiral centers, produced under iron limitation conditions by Pseudomonas aeruginosa and Pseudomonas fluorescens , respectively. After iron chelation in the extracellular medium, Pch-Fe and EPch-Fe are recognized and transported by their specific outer-membrane transporters: FptA in P. aeruginosa and FetA in P. fluorescens . Structural analysis of FetA-EPch-Fe and FptA-Pch-Fe, combined with mutagenesis and docking studies revealed the structural basis of the stereospecific recognition of these enantiomers by their respective transporters. Whereas FetA and FptA have a low sequence identity but high structural homology, the Pch and EPch binding pockets do not share any structural homology, but display similar physicochemical properties. The stereospecific recognition of both enantiomers by their corresponding transporters is imposed by the configuration of the siderophore's C4'' and C2'' chiral centers. This recognition involves specific hydrogen bonds between the Arg91 guanidinium group and EPch-Fe for FetA and between the Leu117-Leu116 main chain and Pch-Fe for FptA. FetA and FptA are the first membrane receptors to be structurally described with opposite binding enantioselectivities for their ligands, giving insights into the structural basis of their enantiospecificity.

Natural killer cell mediated missing-self recognition can protect mice from primary chronic myeloid leukemia in vivo.

Background: Natural Killer (NK) cells are thought to protect from residual leukemic cells in patients receiving stem cell transplantation. However, multiple retrospective analyses of patient data have yielded conflicting conclusions regarding a putative role of NK cells and the essential NK cell recognition events mediating a protective effect against leukemia. Further, a NK cell mediated protective effect against primary leukemia in vivo has not been shown directly.Methodology/Principal Findings: Here we addressed whether NK cells have the potential to control chronic myeloid leukemia (CML) arising based on the transplantation of BCR-ABL1 oncogene expressing primary bone marrow precursor cells into lethally irradiated recipient mice. These analyses identified missing-self recognition as the only NK cell-mediated recognition strategy, which is able to significantly protect from the development of CML disease in vivo.Conclusion: Our data provide a proof of principle that NK cells can control primary leukemic cells in vivo. Since the presence of NK cells reduced the abundance of leukemia propagating cancer stem cells, the data raise the possibility that NK cell recognition has the potential to cure CML, which may be difficult using small molecule BCR-ABL1 inhibitors. Finally, our findings validate approaches to treat leukemia using antibody-based blockade of self-specific inhibitory MHC class I receptors.

Laser scanning-based recognition of rotational movements on a deep seated gravitational instability: The Cinque Torri case (North-Eastern Italian Alps)

The Cinque Torri group (Cortina d'Ampezzo, Italy) is an articulated system of unstable carbonatic rock monoliths located in a very important tourism area and therefore characterized by a significant risk. The instability phenomena involved represent an example of lateral spreading developed over a larger deep seated gravitational slope deformation (DSGSD) area. After the recent fall of a monolith of more than 10 000 m3, a scientific study was initiated to monitor the more unstable sectors and to characterize the past movements as a fundamental tool for predicting future movements and hazard assessment. To achieve greater insight on the ongoing lateral spreading process, a method for a quantitative analysis of rotational movements associated with the lateral spreading has been developed, applied and validated. The method is based on: i) detailed geometrical characterization of the area by means of laser scanner techniques; ii) recognition of the discontinuity sets and definition of a reference frame for each set, iii) correlation between the obtained reference frames related to a specific sector and a stable external reference frame, and iv) determination of the 3D rotations in terms of Euler angles to describe the present settlement of the Cinque Torri system with respect to the surrounding stable areas. In this way, significant information on the processes involved in the fragmentation and spreading of a former dolomitic plateau into different rock cliffs has been gained. The method is suitable to be applied to similar case studies.

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.

Hard instances of algorithms and proof systems

"Vegeu el resum a l'inici del document del fitxer adjunt."

Approximation algorithms for two-state anti-ferromagnetic spin systems on bounded degree graphs

In a seminal paper [10], Weitz gave a deterministic fully polynomial approximation scheme for counting exponentially weighted independent sets (which is the same as approximating the partition function of the hard-core model from statistical physics) in graphs of degree at most d, up to the critical activity for the uniqueness of the Gibbs measure on the innite d-regular tree. ore recently Sly [8] (see also [1]) showed that this is optimal in the sense that if here is an FPRAS for the hard-core partition function on graphs of maximum egree d for activities larger than the critical activity on the innite d-regular ree then NP = RP. In this paper we extend Weitz's approach to derive a deterministic fully polynomial approximation scheme for the partition function of general two-state anti-ferromagnetic spin systems on graphs of maximum degree d, up to the corresponding critical point on the d-regular tree. The main ingredient of our result is a proof that for two-state anti-ferromagnetic spin systems on the d-regular tree, weak spatial mixing implies strong spatial mixing. his in turn uses a message-decay argument which extends a similar approach proposed recently for the hard-core model by Restrepo et al [7] to the case of general two-state anti-ferromagnetic spin systems.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Specific antibody levels and antigenic recognition of Wistar rats inoculated with distinct isolates of Trypanosoma evansi

"Mal de Cadeiras", an enzootic disease caused by Trypanosoma evansi, is one of the most important trypanosomiases in the Brazilian Pantanal region. The disease affects mainly horses, which are widely used in extensive cattle production, an activity of greatest economical significance for the region. The parasite also infects sylvan (coatis and capybaras) and domestic (dogs) animals, respectively considered wild and domestic reservoirs of T. evansi. For a better understanding of the interaction of T. evansi with its rodent host, we evaluated the differences in the specific antibody level patterns and in the parasitic peptides recognition patterns of experimentally infected Wistar rats. The rats experimentally infected with T. evansi isolates obtained from coatis, dogs and horses were submitted to indirect immunofluorescence test (IgM e IgG) and Western blotting. The serological titers for IgM and IgG ranged between 1:40 and 1:160. The most recognized polypeptide profiles were in a range of 17 and 74 kDa. Our data suggest that the humoral immune response in Wistar rats is not sufficient for granting an effective control of T. evansi infections.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

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.