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"Laval, Thierry"
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Look & find at school
\"Readers can take an imaginary journey to the classroom, the playground, the lunchroom, and more in this colorful collection of look-and-find illustrations. Can you find a coloring book? A jump rope? A puppet show?\"--Publisher's description.
BOOK
Capybara and Brush Cutter Involvement in Q Fever Outbreak in Remote Area of Amazon Rain Forest, French Guiana, 2014
We investigated a Q fever outbreak that occurred in an isolated area of the Amazon Rain Forest in French Guiana in 2014. Capybara fecal samples were positive for Coxiella burnetii DNA. Being near brush cutters in use was associated with disease development. Capybaras are a putative reservoir for C. burnetii.
Journal Article
Look & find transportation
\"Introduces the reader to modes of transportation\"-- Provided by publisher.
Book
Detection of Sargassum from Sentinel Satellite Sensors Using Deep Learning Approach
Since 2011, the proliferation of brown macro-algae of the genus Sargassum has considerably increased in the North Tropical Atlantic Sea, all the way from the Gulf of Guinea to the Caribbean Sea and the Gulf of Mexico. The large amount of Sargassum aggregations in that area cause major beaching events, which have a significant impact on the local economy and the environment and are starting to present a real threat to public health. In such a context, it is crucial to collect spatial and temporal data of Sargassum aggregations to understand their dynamics and predict stranding. Lately, indexes based on satellite imagery such as the Maximum Chlorophyll Index (MCI) or the Alternative Floating Algae Index (AFAI), have been developed and used to detect these Sargassum aggregations. However, their accuracy is questionable as they tend to detect various non-Sargassum features. To overcome false positive detection biases encountered by the index-thresholding methods, we developed two new deep learning models specific for Sargassum detection based on an encoder–decoder convolutional neural network (CNN). One was tuned to spectral bands from the multispectral instrument (MSI) onboard Sentinel-2 satellites and the other to the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3 satellites. This specific new approach outperformed previous generalist deep learning models, such as ErisNet, UNet, and SegNet, in the detection of Sargassum from satellite images with the same training, with an F1-score of 0.88 using MSI images, and 0.76 using OLCI images. Indeed, the proposed CNN considered neighbor pixels, unlike ErisNet, and had fewer reduction levels than UNet and SegNet, allowing filiform objects such as Sargassum aggregations to be detected. Using both spectral and spatial features, it also yielded a better detection performance compared to algal index-based techniques. The CNN method proposed here recognizes new small aggregations that were previously undetected, provides more complete structures, and has a lower false-positive detection rate.
Journal Article
Location and timing govern tripartite interactions of fungal phytopathogens and host in the stem canker species complex
Abstract Background Leptosphaeria maculans “brassicae” (Lmb) and Leptosphaeria biglobosa “brassicae” (Lbb) make up a species complex involved in the stem canker (blackleg) disease of rapeseed ( Brassica napus ). They coinfect rapeseed together, from the early stage of infection on leaves to the final necrotic stage at the stem base, and both perform sexual crossings on plant residues. L. biglobosa is suggested to be a potential biocontrol agent against Lmb, but there has been no mechanistic investigation of the different types of interactions that may occur between the plant and the two fungal species. Results We investigated the bi- or tripartite interaction mechanisms by (i) confronting Lmb and Lbb in culture conditions or during cotyledon infection, with different timing and/or spore concentration regimes, (ii) performing RNA-Seq experiments in vitro or on the kinetics of infection of cotyledons infected by Lmb and/or Lbb to evaluate the transcriptomic activity and the plant response when both fungal species are inoculated together. Lbb infection of B. napus cotyledons was typical of a necrotrophic behavior, with a very early setup of one pathogenicity program and very limited colonization of tissues. This contrasted with the complex succession of pathogenicity programs of the hemibiotroph Lmb. During simultaneous co-infection by both species, Lmb was strongly impacted in its growth and transcriptomic dynamics both in vitro and in planta , while Lbb was unaffected by the presence of Lmb. However, the drastic inhibition of Lmb growth by Lbb was ineffective in the case of delayed inoculation with Lbb or a lower amount of spores of Lbb compared to Lmb. Conclusions Our data suggest that Lmb growth inhibition by Lbb is the result of a combination of factors that may include competition for trophic resources, the generation by Lbb of an environment unsuitable for the lifecycle of Lmb or/and the effect on Lmb of plant defense responses induced by Lbb. It indicates that growth inhibition occurs in very specific conditions (i.e., co-inoculation at the same place of an equal amount of inoculum) that are unlikely to occur in the field where their coexistence does not prevent any species from completing their life cycle.
Journal Article
Automated Interpretation of Pulmonary Function Tests in Adults with Respiratory Complaints
Background: The use of pulmonary function tests is primarily based on expert opinion and international guidelines. Current interpretation strategies are using predefined cutoffs for the description of a typical pattern. Objectives: We aimed to explore the predicted disease outcome based on the American Thoracic Society/European Respiratory Society (ATS/ERS) interpreting strategy. Subsequently, we investigated whether an unbiased machine learning framework integrating lung function with clinical variables may provide alternative decision trees resulting in a more accurate diagnosis. Methods: Our study included data from 968 subjects admitted for the first time to a pulmonary practice. The final clinical diagnosis was based on the combination of complete pulmonary function with the investigations that were decided at the physician's discretion. Clinical diagnoses were separated into 10 different groups and validated by an expert panel. Results: The ATS/ERS algorithm resulted in a correct diagnostic label in 38% of the subjects. Chronic obstructive pulmonary disease (COPD) was detected with an acceptable accuracy (74%), whereas all other diseases were poorly identified. The new data-based decision tree improved the general accuracy to 68% after 10-fold cross-validation when detecting the most common lung diseases, with a significantly higher positive predictive value and sensitivity for COPD, asthma, interstitial lung disease, and neuromuscular disorder (83/78, 66/82, 52/59, and 100/54%, respectively). Conclusions: Our data show that the current algorithms for lung function interpretation can be improved by a computer-based choice of lung function and clinical variables and their decision-making thresholds.
Journal Article
Voltage-gated sodium channels from the bees Apis mellifera and Bombus terrestris are differentially modulated by pyrethroid insecticides
Recent experimental and in-field evidence of the deleterious effects of insecticides on the domestic honey bee Apis mellifera have led to a tightening of the risk assessment requirements of these products, and now more attention is being paid to their sublethal effects on other bee species. In addition to traditional tests, in vitro and in silico approaches may become essential tools for a comprehensive understanding of the impact of insecticides on bee species. Here we present a study in which electrophysiology and a Markovian multi-state modelling of the voltage-gated sodium channel were used to measure the susceptibility of the antennal lobe neurons from Apis mellifera and Bombus terrestris, to the pyrethroids tetramethrin and esfenvalerate. Voltage-gated sodium channels from Apis mellifera and Bombus terrestris are differentially sensitive to pyrethroids. In both bee species, the level of neuronal activity played an important role in their relative sensitivity to pyrethroids. This work supports the notion that honey bees cannot unequivocally be considered as a surrogate for other bee species in assessing their neuronal susceptibility to insecticides.
Journal Article