Modelling groundwater-dependent vegetation patterns using ensemble learning

International audienceVegetation patterns arise from the interplay between intraspecific and interspecific biotic interactions and from different abiotic constraints and interacting driving forces and distributions. In this study, we constructed an ensemble learning model that, based on spatially distributed environmental variables, could model vegetation patterns at the local scale. The study site was an alluvial floodplain with marked hydrologic gradients on which different vegetation types developed. The model was evaluated on accuracy, and could be concluded to perform well. However, model accuracy was remarkably lower for boundary areas between two distinct vegetation types. Subsequent application of the model on a spatially independent data set showed a poor performance that could be linked with the niche concept to conclude that an empirical distribution model, which has been constructed on local observations, is incapable to be applied beyond these boundaries

“Not in the mood”: The fear of being laughed at is better predicted by humor temperament traits than diagnosis in neurodevelopmental conditions

BACKGROUND: Research has shown that autistic individuals seem to be more prone to develop gelotophobia (i.e., the fear of being laughed at) than typically developing individuals. The goals of the present study were to discover whether the high levels of gelotophobia found in autism in previous studies were replicated here, to expand the research to Down syndrome (DS) and Williams syndrome (WS), and to assess the relation between individual differences and social impairments, affective predispositions, and humor temperament. METHODS: Questionnaires were distributed to parents of autistic individuals (N = 48), individuals with DS (N = 139), and individuals with WS (N = 43) aged between 5 and 25 years old. RESULTS: Autistic individuals were shown to frequently experience at least a slight level of gelotophobia (45%), compared to only 6% of individuals with DS and 7% of individuals with WS. Interestingly, humorless temperament traits (i.e., seriousness and bad mood) manifested as the strongest predictors of gelotophobia. This relation even transcended group differences. CONCLUSION: The results confirm that gelotophobia seems to be particularly concerning for autistic individuals, whereas individuals with DS and WS seem to be more protected from developing such a fear. Moreover, it appears that gelotophobia seems to be more linked to high seriousness and irritability than diagnosis

T2 lesion location really matters: a 10 year follow-up study in primary progressive multiple sclerosis

Objectives: Prediction of long term clinical outcome in patients with primary progressive multiple sclerosis (PPMS) using imaging has important clinical implications, but remains challenging. We aimed to determine whether spatial location of T2 and T1 brain lesions predicts clinical progression during a 10-year follow-up in PPMS. Methods: Lesion probability maps of the T2 and T1 brain lesions were generated using the baseline scans of 80 patients with PPMS who were clinically assessed at baseline and then after 1, 2, 5 and 10 years. For each patient, the time (in years) taken before bilateral support was required to walk (time to event (TTE)) was used as a measure of progression rate. The probability of each voxel being ‘lesional’ was correlated with TTE, adjusting for age, gender, disease duration, centre and spinal cord cross sectional area, using a multiple linear regression model. To identify the best, independent predictor of progression, a Cox regression model was used. Results: A significant correlation between a shorter TTE and a higher probability of a voxel being lesional on T2 scans was found in the bilateral corticospinal tract and superior longitudinal fasciculus, and in the right inferior fronto-occipital fasciculus (p<0.05). The best predictor of progression rate was the T2 lesion load measured along the right inferior fronto-occipital fasciculus (p=0.016, hazard ratio 1.00652, 95% CI 1.00121 to 1.01186). Conclusion: Our results suggest that the location of T2 brain lesions in the motor and associative tracts is an important contributor to the progression of disability in PPMS, and is independent of spinal cord involvement

Spectroscopic and thermal properties of GeS2-based chalcohalide glasses

The low phonon energy of germanium sulphide glasses makes them ideal candidates as hosts for 1.3µm fibre amplifier applications. However, the GeS2 glass host suffers from a major drawback of poor rare-earth ion solubility. In an efficient device, the solubility of Pr ions has to be enhanced, without adversely affecting either the thermal or the spectroscopic properties of the glass. In the present investigation, we report the synthesis and optical properties of modified GeS2-based chalcohalide glasses with excellent thermal characteristics suitable for drawing low-loss optical fibres

Experimental evidence of differences in the absorption spectra of clustered and isolated ions in erbium doped fibers

The absorption spectra of clustered and isolated ions in erbium-doped germanosilicate fibers have been experimentally studied. The ground state absorption spectra broaden as the degree of erbium-ion clustering increases, indicating that the absorption spectra of clustered ions is significantly different from that of the homogeneous ions. This is confirmed by comparing the broadened absorption spectra with the fibre unbleachable loss spectrum; a direct measurement of the clustered ions. This is the first experimental evidence indicating different absorption cross-sections for the two species of ions in germanosilicate glass, an assumption used in the theoretical description of self-pulsing in erbium doped fiber lasers, but in direct contradiction to the pair-induced quenching model widely used to characterise EDFAs

GABI-Kat SimpleSearch: new features of the Arabidopsis thaliana T-DNA mutant database

T-DNA insertion mutants are very valuable for reverse genetics in Arabidopsis thaliana. Several projects have generated large sequence-indexed collections of T-DNA insertion lines, of which GABI-Kat is the second largest resource worldwide. User access to the collection and its Flanking Sequence Tags (FSTs) is provided by the front end SimpleSearch (http://www.GABI-Kat.de). Several significant improvements have been implemented recently. The database now relies on the TAIRv10 genome sequence and annotation dataset. All FSTs have been newly mapped using an optimized procedure that leads to improved accuracy of insertion site predictions. A fraction of the collection with weak FST yield was re-analysed by generating new FSTs. Along with newly found predictions for older sequences about 20 000 new FSTs were included in the database. Information about groups of FSTs pointing to the same insertion site that is found in several lines but is real only in a single line are included, and many problematic FST-to-line links have been corrected using new wet-lab data. SimpleSearch currently contains data from ∼71 000 lines with predicted insertions covering 62.5% of the 27 206 nuclear protein coding genes, and offers insertion allele-specific data from 9545 confirmed lines that are available from the Nottingham Arabidopsis Stock Centre

Characteristics of Two-Dimensional Quantum Turbulence in a Compressible Superfluid

Under suitable forcing a fluid exhibits turbulence, with characteristics strongly affected by the fluid's confining geometry. Here we study two-dimensional quantum turbulence in a highly oblate Bose-Einstein condensate in an annular trap. As a compressible quantum fluid, this system affords a rich phenomenology, allowing coupling between vortex and acoustic energy. Small-scale stirring generates an experimentally observed disordered vortex distribution that evolves into large-scale flow in the form of a persistent current. Numerical simulation of the experiment reveals additional characteristics of two-dimensional quantum turbulence: spontaneous clustering of same-circulation vortices, and an incompressible energy spectrum with $k^{-5/3}$ dependence for low wavenumbers $k$ and $k^{-3}$ dependence for high $k$.Comment: 7 pages, 7 figures. Reference [29] updated for v

An objective reduction technique of proteomic mass spectra based on multi-scale fuzzy thresholding

A proteomic approach offers a powerful and complementary tool to genomics. It allows to index and characterize proteins, and, for example, to compare their levels of expression between healthy and pathological states. Proteomic analyses are mainly based on the separation of proteins by two-dimensional gel electrophoresis and their subsequent identification by comparing the data from Mass Spectrometry (SM) analyses to the theoretical ones contained in databases. In mass spectrometry, the detector noise, the electronic and chemical noise, sometimes the small amount of peptides that has to be treated and finally the spectrum reduction noise (due to bad filtering and/or thresholding), can induce Parasitic Mass Peaks (PMP) and/or hide some Useful Mass Peaks (UMP) of low intensities. The immediate consequence is that the presence of the PMP and the absence of the UMP will be detrimental to the protein identification quality. In this article, we propose an original algorithm eliminating the PMP, detecting and amplifying those which are useful. The preprocessing principle uses a multi-scale analysis technique coupled to a fuzzy thresholding (multi-scale fuzzy thresholding), a local amplification of the UMP, and finally an adaptive Base Line Correction. The associated frequencies with the PMP are distributed on all the spectrum pass bandwidth. This leads us to a dyadic tree structure subband decomposition. The algorithm principle consists of dividing the frequential pass bandwidth of each masses spectrum into two subbands, a Low and High Frequency (LF,HF) subband, then each subband is in turn divided into two subbands etc. The HF subbands are then thresholded according to the minimization criterion of the Shannon fuzzy entropy, and then amplified locally; the base line is calculated in an adaptive way and subtracted from reconstructed spectrum. To evaluate the quality of this algorithm, we present a comparison of the results obtained by our algorithm, and those obtained by the DataExplorer software. The latter is a reduction software provided within the MALDI-TOF spectrometer software package.La protéomique offre une approche puissante et complémentaire à la génomique. Elle permet de répertorier et caractériser les protéines, de comparer leur niveau d’expression entre un état physiologique sain et malade par exemple. L’analyse protéomique se fait essentiellement par l’utilisation de la technique d’électrophorèse bidimensionnelle couplée à la technique d’analyse par Spectrométrie de Masse (SM). La première, aidée par l’imagerie protéomique, conduit à la localisation des protéines candidates à une analyse par SM. La comparaison des spectres de masses obtenus à des bases de données protéiques, conduit à l’identification des protéines d’intérêt en terme de peptides. Le problème qui se pose souvent est que les spectres sont bruités et pauvres en masses. En effet, le bruit du détecteur, le bruit électronique et chimique, la présence de peu de matériel protéique et enfin le bruit de la réduction des spectres (mauvais filtrage et/ou seuillage), tous ces bruits peuvent induire des Pics de Masses Parasites (PMP) et/ou supprimer des Pics de Masses Utiles (PMU) de faible intensité. La conséquence immédiate est que la présence des PMP et l’absence des PMU seront utilisées au dépens de la qualité d’identification de la protéine. Dans cet article, nous proposons un algorithme original éliminant les PMP, détectant et amplifiant ceux utiles. Le principe du pré-traitement utilise une Analyse Multirésolution (AM) couplée à un seuillage basé sur la logique floue (seuillage flou multi-échelle), une amplification locale des PMU, et enfin une correction adaptative de la Ligne de Base (LB). Les fréquences associées aux PMP sont réparties sur toute la bande passante du spectre, ce qui nous conduit à une AM dite en arbre. Le principe consiste à découper la bande passante fréquentielle de chaque spectre de masses en deux sous-bandes, une Basse Fréquence (BF), l’autre Haute Fréquence (HF), ensuite chaque sous-bande est à son tour découpée en deux sous-bandes etc. Les sous-bandes HF sont seuillées selon le critère de minimisation de l’entropie floue de Shannon et amplifiées localement, la ligne de base est calculée automatiquement et soustraite du spectre reconstruit. Pour évaluer la qualité de cet algorithme, nous présentons une comparaison des résultats obtenus par notre algorithme, et ceux fournis par le spectromètre MALDI-TOF (Matrix Assisted Laser Desorption/Ionisation-Time Of Flight), qui utilise le logiciel « DataExplorer » comme logiciel de réduction

GLUT3 is induced during epithelial-mesenchymal transition and promotes tumor cell proliferation in non-small cell lung cancer.

BACKGROUND: Alterations in glucose metabolism and epithelial-mesenchymal transition (EMT) constitute two important characteristics of carcinoma progression toward invasive cancer. Despite an extensive characterization of each of them separately, the links between EMT and glucose metabolism of tumor cells remain elusive. Here we show that the neuronal glucose transporter GLUT3 contributes to glucose uptake and proliferation of lung tumor cells that have undergone an EMT. RESULTS: Using a panel of human non-small cell lung cancer (NSCLC) cell lines, we demonstrate that GLUT3 is strongly expressed in mesenchymal, but not epithelial cells, a finding corroborated in hepatoma cells. Furthermore, we identify that ZEB1 binds to the GLUT3 gene to activate transcription. Importantly, inhibiting GLUT3 expression reduces glucose import and the proliferation of mesenchymal lung tumor cells, whereas ectopic expression in epithelial cells sustains proliferation in low glucose. Using a large microarray data collection of human NSCLCs, we determine that GLUT3 expression correlates with EMT markers and is prognostic of poor overall survival. CONCLUSIONS: Altogether, our results reveal that GLUT3 is a transcriptional target of ZEB1 and that this glucose transporter plays an important role in lung cancer, when tumor cells loose their epithelial characteristics to become more invasive. Moreover, these findings emphasize the development of GLUT3 inhibitory drugs as a targeted therapy for the treatment of patients with poorly differentiated tumors