University of Lorraine

About: University of Lorraine is a education organization based out in Nancy, France. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 11942 authors who have published 25010 publications receiving 425227 citations. The organization is also known as: Lorraine University.

Soil Diversity and Hydration as Observed by ChemCam at Gale Crater, Mars

Abstract: The ChemCam instrument, which provides insight into martian soil chemistry at the submillimeter scale, identified two principal soil types along the Curiosity rover traverse: a fine-grained mafic type and a locally derived, coarse-grained felsic type. The mafic soil component is representative of widespread martian soils and is similar in composition to the martian dust. It possesses a ubiquitous hydrogen signature in ChemCam spectra, corresponding to the hydration of the amorphous phases found in the soil by the CheMin instrument. This hydration likely accounts for an important fraction of the global hydration of the surface seen by previous orbital measurements. ChemCam analyses did not reveal any significant exchange of water vapor between the regolith and the atmosphere. These observations provide constraints on the nature of the amorphous phases and their hydration.

Compared performance of high-sensitivity cameras dedicated to myocardial perfusion SPECT: a comprehensive analysis of phantom and human images.

Abstract: Differences in the performance of cadmium-zinc-telluride (CZT) cameras or collimation systems that have recently been commercialized for myocardial SPECT remain unclear. In the present study, the performance of 3 of these systems was compared by a comprehensive analysis of phantom and human SPECT images. Methods: We evaluated the Discovery NM 530c and DSPECT CZT cameras, as well as the Symbia Anger camera equipped with an astigmatic (IQ⋅SPECT) or parallel-hole (conventional SPECT) collimator. Physical performance was compared on reconstructed SPECT images from a phantom and from comparable groups of healthy subjects. Results: Classifications were as follows, in order of performance. For count sensitivity on cardiac phantom images (counts⋅s−1⋅MBq−1), DSPECT had a sensitivity of 850; Discovery NM 530c, 460; IQ⋅SPECT, 390; and conventional SPECT, 130. This classification was similar to that of myocardial counts normalized to injected activities from human images (respective mean values, in counts⋅s−1⋅MBq−1: 11.4 ± 2.6, 5.6 ± 1.4, 2.7 ± 0.7, and 0.6 ± 0.1). For central spatial resolution: Discovery NM 530c was 6.7 mm; DSPECT, 8.6 mm; IQ⋅SPECT, 15.0 mm; and conventional SPECT, 15.3 mm, also in accordance with the analysis of the sharpness of myocardial contours on human images (in cm−1: 1.02 ± 0.17, 0.92 ± 0.11, 0.64 ± 0.12, and 0.65 ± 0.06, respectively). For contrast-to-noise ratio on the phantom: Discovery NM 530c had a ratio of 4.6; DSPECT, 4.1; IQ⋅SPECT, 3.9; and conventional SPECT, 3.5, similar to ratios documented on human images (5.2 ± 1.0, 4.5 ± 0.5, 3.9 ± 0.6, and 3.4 ± 0.3, respectively). Conclusion: The performance of CZT cameras is dramatically higher than that of Anger cameras, even for human SPECT images. However, CZT cameras differ in that spatial resolution and contrast-to-noise ratio are better with the Discovery NM 530c, whereas count sensitivity is markedly higher with the DSPECT.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Abstract: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.