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BEPPI project - data, tables and figures on sow peripheral white blood cell epigenome
No full textThis folder includes the supplementary figures, tables and datas associated with an article submitted to Epigenetics (Mariana Mescouto Lopes, Gabriel Costa Monteiro Moreira, Aurélie Chaulot-Talmon, Anne Frambourg, Valentin Costes, Julie Demars, Elodie Merlot, Hélène Jammes. The effect of environmental enrichment on immune cell DNA methylation profiles depends on the parity of sows
Dataset of untargeted metabolomics analysis of bronchoalveolar lavage samples from severe asthmatic and age-matched control children
No full textThis dataset presents raw data and intensities of metabolites detected in broncho-alveolar lavages (BAL) collected from children presenting severe asthma (n=20) and age-matched disease control children (n=10).
Untargeted metabolomics was performed using liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) following an established workflow for sample preparation, data acquisition and treatment (DOI: 10.1016/j.jchromb.2014.04.025). LC-HRMS was performed on an Ultimate 3000 chromatographic system coupled to a Q-Exactive mass spectrometer (Thermo Fisher Scientific, Courtaboeuf, France) fitted with an electrospray source operating in the positive ionization mode (ESI+). Ultra-high performance LC (UHPLC) separation was performed using C18 column (Hypersil GOLD C18, 1.9 µm, 2.1 mm × 150 mm column, Thermo Fisher Scientific). Raw data was converted to .mzXML format using MSconvert (“ProteoWizard”, version 3.0.21079), and data extraction was performed using XCMS R package (https://workflow4metabolomics.org/), then providing one raw data file per sample (CLASSE_METABOLOME_RAW_DATA.zip). Raw data from quality controls (“QC”), corresponding to mix of equal volume from all samples that were analysed every 6 randomized samples, from QC dilutions, from buffer only (“Blanc”; injected 5 times at the very beginning and once at the end of sequence analysis) and from an extraction blank (sterile NaCl 0.9 % extracted and treated as samples), are also provided : all those controls are used for data normalization/standardization purposes. After filtration based on three quality criteria (phenomis R package, version 1.0.2), metabolites were annotated using an internal spectral database and confirmed by MS/MS experiments (DOI: 10.1021/ac300829f), allowing the highest confident level of identification (DOI: 10.1007/s11306-007-0082-2). In total, we identified 88 metabolites in BAL fluids (Intensities_annotated_metabolites_BAL.xlsx), which intensities in individual samples are provided as a first table. Metabolites characteristics are provided in a separate table (mass to charge ratio (m/z), retention time (rt), KEGG identifier and class of annotated metabolites).
Our aim is to identify a local signature of severe asthma by conducting comprehensive multi-omics analysis of BALs from children with severe asthmatic versus non-asthmatic controls. Corresponding multi-omics data will be described in a data paper under submission, also describing all corresponding metadata
Dataset for publication entitled "Declared agroecological levers and pesticide use in French vineyards: a step toward modelling transition pathways"
No full textFor each growing system, compile a list of boolean entries indicating whether the lever is activated or not, along with the total TFI at the growing system level.
Data tables available:
- Computed data at farm level : levers and TFI (Treatment Frequency Index)
- Glossary of the level labels used
All data have been stored and produced via the Agrosyst information system, then selected and consolidated by the authors
High resolution spectra of the Silicon at 5665 Å and 5684 Å in the Sun
No full textWe present a dataset of high resolution spectra of the Sun of the SiI lines at 5665.563 Å and 5684.5 Å. These solar spectra (resolution respectively of 11.153 mÅ and 10.995 mÅ) were obtained in the quiet Sun at various distances from the disk centre with the ground based CNRS Themis telescope and are useful for the research of Silicon abundance. The spectra shown here are freely available in FITS format to the research community. See also https://doi.org/10.57745/9HRBAG for the centre to limb variation of OI forbidden lines at 6300 Å and 6364 Å, and https://doi.org/10.57745/U1MQZB for the centre to limb variation of the OI triplet at 7774 Å
Data associated with the publication 'Microscopic and stochastic simulations of chemically active droplets'
No full textThese files contain the data that were generated to produced the plots shown on Figures 2, 3, 4, 5, S1, S2 and S3 in our manuscript 'Microscopic and stochastic simulations of chemically active droplets' and its Supplemental Material. Each folder corresponds to one sfigure. The data was produced using the software LAMMPS and analyzed with homemade Python scripts, as described in the manuscript
Effective mortality thresholds for reporting suspicion of highly pathogenic avian influenza in mule ducks - scripts and data
No full textThe scripts and data held in this repository were used to run the analyses and to produce the results of the manuscript: Lambert S., Godard C., Vergne T. Effective mortality thresholds for reporting suspicion of highly pathogenic avian influenza in mule ducks
Phenotypic characterization in boosting orphan legumes from the Mediterranean Basin: INRAE 2024 trial datasets
No full textResults of the greenhouse trial on the observed phenotypic traits in the six accessions at INRAE-Versailles/ France
The trial was conducted from september 2023 to March 2024.
These data refer to phenotypic traits such as the biomass quantity, the number of pods and seeds and the day of first flowering.
Each column corresponds to either categorical or numerical data.
The dataset is organised following the MIAPPE (Minimum Information About Plant Phenotyping Experiments https://www.miappe.org/ ) template.
The "Species_ID" column refers to the specy of the study.
The "Accessions" column refers to the accession used for the study.
The "Treatment_ID" column refers to the treatment that is applied.
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Simulated hydrological variables and flow intermittence indicators for the projection period (1985-2100) for the 6 European catchments studied in the DRYvER project
No full textHydrological models outputs for the projection period (1985-2100) for the 6 European catchments studied in the DRYvER project
Ensemble des indicateurs des changements par niveaux de réchauffement TRACC issus des narratifs des projections hydrologiques Explore2 (référence 1976-2005)
No full textEnsemble des indicateurs des changements par niveaux de réchauffement TRACC associés aux chaînes de simulations de débits journaliers issus des 9 modèles hydrologiques pour la sélection des narratifs hydrologiques Explore2. Ces fichiers résultent de l'agrégation temporelle des simulations hydrologiques sous runs historiques (avant 2005) et des projections hydrologiques (post 2005), fichiers NetCDF disponibles au téléchargement dans la collection Explore2 - Projections hydrologiques.
Ce dépôt regroupe un tableau par indicateur, niveau de réchauffement et chaîne de simulation, c'est-à-dire, couple GCM/RCM et modèle hydrologique HM. Ces données sont brutes et contiennent donc des chaînes de projections jugées aberrantes / horsains qu'il est possible de filtrer grâce à des métadonnées supplémentaires. Pour des raisons techniques, ces indicateurs sont regroupés par dossiers compressés selon les différentes phases du régime hydrologique.
La description des chaines de modélisation du climat et celle des modèles hydrologiques sont, respectivement, disponibles dans le rapport https://doi.org/10.57745/PUR7ML et dans les annexes du rapport https://doi.org/10.57745/S6PQXD. Retrouvez le diagnostic des modèles hydrologiques résumé à l'échelle des régions hydrologiques dans les fiches téléchargeables ici : https://doi.org/10.57745/DMFUXW.
Définition des narratifs hydrologiques : L'ensemble des descriptions des narratifs hydrologiques définis dans le cadre de la TRACC par niveaux de réchauffement et secteurs hydrographiques est défini ici : https://doi.org/10.57745/KAHIWJ.
Métadonnées supplémentaires : Récapitulatif de l'ensemble des indicateurs hydrologiques : https://doi.org/10.57745/JVNHQL Récapitulatif de l'ensemble des chaînes de simulation : https://doi.org/10.57745/R6HG5X Description de l'ensemble des points de simulation : https://doi.org/10.57745/UTKWR5 Liste des chaînes de modélisation jugées aberrantes / horsains : https://doi.org/10.57745/YZNENQ Récapitulatif des années pivots utilisées pour la TRACC : https://doi.org/10.57745/DCOQM6
Décomposition des chaînes de caractères formant le nom des fichiers parquet, séparées par des "_" : {1} Indicateur : Le nom de l’indicateur, du type de statistique calculée {2} Échantillonnage : Échantillonnage temporel sur laquelle est calculé l’indicateur → {1}_{2} Variable : Variable résultante d'un indicateur temporellement contextualisé {3} RWL : Niveau de réchauffement TRACC (RWL-(20|27|40)) → {1}_{2}_{3} Changement : Changement d'une variable pour un niveau de réchauffement TRACC par rapport à une période de référence, défini dans le récapitulatif des indicateurs hydrologiques {4} EXP : Identifiant de l’expérience historique (post 2005) ou future (post 2005) {5} GCM : Identifiant du GCM forçeur {6} RCM : Identifiant du RCM {7} BC : Identifiant de la méthode de correction de biais statistique {8} HM : Identifiant du modèle hydrologique {9} Référence : Période de référence (ref-YYYYMMDD-YYYYMMDD)
Les colonnes des fichiers parquet sont : EXP : Voir ci-dessus GCM : Voir ci-dessus RCM : Voir ci-dessus BC : Voir ci-dessus HM : Voir ci-dessus SH : Secteur hydrographique qui contient le point de simulation fourni dans la description des régions et secteurs hydrographiques code : Code à 10 caractères du point de simulation fourni dans la description des points de simulation *Changement* : Voir ci-dessus
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