Use of a structural alphabet for analysis of short loops connecting repetitive structures

BACKGROUND: Because loops connect regular secondary structures, analysis of the former depends directly on the definition of the latter. The numerous assignment methods, however, can offer different definitions. In a previous study, we defined a structural alphabet composed of 16 average protein fragments, which we called Protein Blocks (PBs). They allow an accurate description of every region of 3D protein backbones and have been used in local structure prediction. In the present study, we use this structural alphabet to analyze and predict the loops connecting two repetitive structures. RESULTS: We first analyzed the secondary structure assignments. Use of five different assignment methods (DSSP, DEFINE, PCURVE, STRIDE and PSEA) showed the absence of consensus: 20% of the residues were assigned to different states. The discrepancies were particularly important at the extremities of the repetitive structures. We used PBs to describe and predict the short loops because they can help analyze and in part explain these discrepancies. An analysis of the PB distribution in these regions showed some specificities in the sequence-structure relationship. Of the amino acid over- or under-representations observed in the short loop databank, 20% did not appear in the entire databank. Finally, predicting 3D structure in terms of PBs with a Bayesian approach yielded an accuracy rate of 36.0% for all loops and 41.2% for the short loops. Specific learning in the short loops increased the latter by 1%. CONCLUSION: This work highlights the difficulties of assigning repetitive structures and the advantages of using more precise descriptions, that is, PBs. We observed some new amino acid distributions in the short loops and used this information to enhance local prediction. Instead of describing entire loops, our approach predicts each position in the loops locally. It can thus be used to propose many different structures for the loops and to probe and sample their flexibility. It can be a useful tool in ab initio loop prediction

Assessing seasonal and interannual changes in carbonate chemistry across two time-series sites in the North Western Mediterranean Sea

Sustained time-series measurements are crucial to understand changes in oceanic carbonate chemistry. In the North Western Mediterranean Sea, the temporal evolution of the carbonate system is here investigated based on two 10-year time-series (between January 2010 and December 2019) of monthly carbonate parameters measurements at two sampling sites in the Ligurian Sea (ANTARES and DYFAMED). At seasonal timescale, the seawater partial pressure of CO2 (pCO2) within the mixed layer is mostly driven by temperature at both sites, and biological processes as stated by the observed relationships between total inorganic carbon (CT), nitrate and temperature. This study suggests also that mixing and water masses advection could play a role in modulating the CT content. At decadal timescale, significant changes in ocean chemistry are observed with increasing trends in CT (+3.2 ± 0.9 µmol.kg−1.a−1 – ANTARES; +1.6 ± 0.8 µmol.kg−1.a−1 – DYFAMED), associated with increasing pCO2 trends and decreasing trends in pH. The magnitude of the increasing trend in CT at DYFAMED is consistent with the increase in atmospheric pCO2 and the anthropogenic carbon transport of water originating from the Atlantic Ocean, while the higher trends observed at the ANTARES site could be related to the hydrological variability induced by the variability of the Northern Current

Report on demo mission and dissemination pathways of obtained data based on different observational platforms

This document describes the deployment of instrumentation in the Eastern tropical Atlantic area and shows the preliminary data acquired

Repertoire of Intensive Care Unit Pneumonia Microbiota

Despite the considerable number of studies reported to date, the causative agents of pneumonia are not completely identified. We comprehensively applied modern and traditional laboratory diagnostic techniques to identify microbiota in patients who were admitted to or developed pneumonia in intensive care units (ICUs). During a three-year period, we tested the bronchoalveolar lavage (BAL) of patients with ventilator-associated pneumonia, community-acquired pneumonia, non-ventilator ICU pneumonia and aspiration pneumonia, and compared the results with those from patients without pneumonia (controls). Samples were tested by amplification of 16S rDNA, 18S rDNA genes followed by cloning and sequencing and by PCR to target specific pathogens. We also included culture, amoeba co-culture, detection of antibodies to selected agents and urinary antigen tests. Based on molecular testing, we identified a wide repertoire of 160 bacterial species of which 73 have not been previously reported in pneumonia. Moreover, we found 37 putative new bacterial phylotypes with a 16S rDNA gene divergence ≥98% from known phylotypes. We also identified 24 fungal species of which 6 have not been previously reported in pneumonia and 7 viruses. Patients can present up to 16 different microorganisms in a single BAL (mean ± SD; 3.77±2.93). Some pathogens considered to be typical for ICU pneumonia such as Pseudomonas aeruginosa and Streptococcus species can be detected as commonly in controls as in pneumonia patients which strikingly highlights the existence of a core pulmonary microbiota. Differences in the microbiota of different forms of pneumonia were documented

A propos de la prévention de la iatrogénie médicamenteuse chez les personnes âgées en ALD, en médecine générale

LILLE2-BU Santé-Recherche (593502101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Evolution of dissolved O2, nutrients and carbonate system variables in the northwestern Mediterranean Sea using a machine learning method

International audienc