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5,191 results for “feeding”
Dataset of Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy
<p>The dataset includes search results used in article “Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy” biorXiv, 2022.01.17.476562, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. <a href="https://doi.org/10.1101/2022.01.17.476562">https://doi.org/10.1101/2022.01.17.476562</a></p> <p> </p> <p>Search Results Description: Please use Figure 1 from paper to trace the data made available and experimental group.</p> <p>The excel “raw data 2022-06-24” file contains the following data</p> <ol> <li>Body weight of each rabbit on a weekly basis</li> <li>Analysis of breeding parameters at mid-pregnancy</li> <li>Histological areas of each mammry tissue measured</li> <li>Optical density values obtained for biochemical leptin concentration determination</li> <li>Optical density values obtained for biochemical triglyceride concentration determination</li> <li>Optical density values obtained for biochemical glucose concentration determination</li> <li>Optical density values obtained for biochemical cholesterol concentration determination</li> <li>RT-qPCR results (Ct) from QuantStudio export for milk protein analysis</li> <li>RT-qPCR results (Ct) from QuantStudio export for lipid metabolism analysisen</li> </ol> <p>“Statistical analysis.doc” contained the description of the statistics used in Excel and the description of the linear mixed model analysis , the reference of the script available by the CRAN project is also include.The R scipt file for using the linear mixed model in R added with the "data-croissance-analysis" file.</p>
EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (Annexes A, B, C, D)
<p>Raw data of phase I and II experiments and PBK model input data and simulation of the EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (OC/EFSA/SCER/2021/14).</p>
Data and R script for 'Evaluating the cyclic ratio schedule as an assay of feeding behaviour in the European starling (Sturnus vulgaris)'
<p>Data files and R script for Dunn et al. "Evaluating the cyclic ratio schedule as an assay of feeding behaviour in the European starling (<em>Sturnus vulgaris</em>)"</p> <p>Includes a single R script that produces all the analyses in the paper. The script makes use of three different .csv data files.</p>
Feeding trials of Leptagrion andromache and prey species
<p>We quantified the consumption rate for one damselfly larvae predator and many of its prey. The top predator Leptagrion andromache (Zygoptera: Odonata, dry mass = 3.31 mg, se = 2.45, n = 29) was fed several densities of each prey. The prey were chosen because they were the most abundant prey in bromeliads. All prey are aquatic insect larvae. We chose Culex sp 1 (Culicidae: Diptera, density range = 1- 50, mean dry mass = 0.17 mg, se = 0.04, n = 25), Culex sp 2 (Culicidae: Diptera, 1-20, 0.09 mg, 0.02, 14), Forcipomyia (Ceratopogonidae: Diptera, 1-60, 0.07 mg, 0.01, 5), Dero superterrenus (Naididae: Haplotaxida, 1-60, 0.12 mg, 0.01, 2), Psychodidae (Psychodidae: Diptera, 1-30, 0.22 mg, 0.11, 18), Scirtes sp 1 (Scirtidae: Coleoptera, 1-30, 0.33 mg, 0.12, 13), Scirtes sp 2 (Scirtidae: Coleoptera, 1-6, 0.43 mg, 0.27, 65), and Trentepohlia (Tipulidae: Diptera, 1-7, 0.29 mg, 0.19, 43).</p>
Data and code for: Growth, development and survival in the brown widow spider, Latrodectus geometricus under different feeding regimes.
<p><span>Here, we compared mortality, growth and development of the brown widow spider, <em>Latrodectus geometricus</em>, from neonate to adult under two different prey availability regimes. </span></p>
Fruit-feeding butterfly community data analysed in "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration"
<p>Community data of fruit-feeding butterflies collected from Kibale National Park, Uganda, in the periods 2011-2012 and 2020-2021 analysed in our paper Korkiatupa et al. 2023: "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration" (<em>Ecosphere</em> <span>14</span>(<span>5</span>): e4514. <a href="https://doi.org/10.1002/ecs2.4514">https://doi.org/10.1002/ecs2.4514</a>).</p> <p>The table consists of two parts. First part shows counts of individuals of butterfly species in each study site. Second part shows the metadata: code of studysite, census (2011-2012/2020-2021), planting year (planting year or "Primary forest"), and coordinates (WGS 84 coordinate system).</p>
Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model
<p>This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oil on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model" to be published in the journal Animal - Open Space.</p>
Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions
<p>This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions" to be published in the journal Animal - Open Space.</p>
Genome-scale community modelling reveals key metabolic cross-feedings in epipelagic bacterioplankton communities (Supplementary Materials)
<p>A comprehensive catalog of 19,791 marine prokaryotic isolates (WGS), single-amplified genomes (SAGs) and metagenomic-assembled genomes (MAGs) compiled from MarRef v4.0 (N=943, mostly high-quality WGS), MarDB v4.0 (N=12,963), and the aquatic representative genomes from the ProGenomes database v1.0 (N=566). This collection of well-documented genomes was complemented by 5,319 MAGs assembled from four distinct studies, namely: Parks et al. 2017 (<a href="https://doi.org/10.1038/s41564-017-0012-7">DOI</a>; N=1,765; downloaded from EBI), Tully et al. 2017/2018 (<a href="https://doi.org/10.7717/peerj.3558">DOI</a> and <a href="https://10.1038/sdata.2017.203">DOI</a>; N=2,597; downloaded from EBI), and Delmont et al. 2018 (<a href="https://doi.org/10.1038/s41564-018-0176-9">DOI</a>; N=957; downloaded from FIGSHARE). The Parks et al. study contained genomes reconstructed from non-marine biomes. Thus, a selection of 1,765 genomes was extracted by searching for specific keywords: “tara|marine|sea|ocean|mediterranean” (case insensitive). Note that depending on their study of origin, included MAGs may have been reconstructed using different assembling and binning methods.</p> <p>The archive includes:</p> <ul> <li>a metadata file describing the quality and redundancy of the genomes named `EcoSysMic_metadata.tsv`</li> <li>sequences of the 19,791 (redundant) genomes in `All/WGS`</li> <li>companion files in `All/Data` and `dRep95/Data` (see Methods in the associated paper), including <ul> <li>predicted CDS and EggNOG functional annotations</li> <li>predicted GTDB taxonomy</li> <li>CarveMe reconstructed metabolic models and their MEMOTE quality</li> </ul> </li> </ul> <p>The 7,658 non-redundant species-level genomes (delineated by a 95% ANI threshold over 60% of genome length) that were used in the associated paper are defined by the column `is_drep95` in the metadata file.</p>
Data supporting Comparison of feeding niches between Arctic and northward moving sub-Arctic marine mammals in Greenland
<p>Data supporting the paper:</p> <blockquote> <p>Land-Miller, H., A. Roos, M. Simon, R. Dietz, C. Sonne, S. Pedro, A. Rosing-Asvid, F. Rigét, and M. McKinney. 2023. Comparison of feeding niches between Arctic and northward moving sub-Arctic marine mammals in Greenland. Marine Ecology Progress Series.</p> </blockquote> <p>This data is in five files:</p> <p>1. <strong>greenland_marmam_metadata.csv</strong> contains metadata for all samples used in this project, including sample identifiers:</p> <ul> <li><em>Sample: </em>unique sample ID per individual animal</li> <li><em>Species</em></li> </ul> <p>and details of collection, including <em>Year, Location </em>(general area), <em>Lat, </em><em>Long, </em>and<em> </em><em>Date. </em>It also includes other data on the animal (<em>Sex, Age, Length</em>), when available, as well as the co-author who provided the sample to the project (<em>Sample sender</em>) and the tissues available/analyzed for each individual (<em>Tissues received</em>).</p> <p>2. <strong>all_sample_locations.csv</strong> includes latitude/longitude of each sample for mapping. Latitude and longitude are consistent with the full metadata file when coordinates were available, and estimated based on general sampling area (<em>Location </em>or <em>Area</em>) when not. The variable <em>estimate</em><strong> </strong>denotes samples for which coordinates were estimated.</p> <p>3. <strong>fatty_acids_greenland_marmams.csv </strong>contains fatty acid data for all samples. Variables <em>8:00</em> to <em>24:1n9</em> represent the proportion of each individual fatty acid, out of total fatty acids in that sample. Data are represented as whole number percents (i.e., 10 = 10% and all fatty acids sum to 100 for each sample). </p> <p>4. <strong>CNS_greenland_McGill.csv</strong> contains bulk stable isotope data for all samples analyzed at McGill. In addition to <em>Sample</em> and <em>Species</em>, this includes:</p> <ul> <li><em>treatment</em>: whether a sample was lipid-extracted (<em>LE</em>) or non-lipid-extracted (<em>nLE</em>) prior to analysis</li> <li><em>d15N</em>: stable isotope ratio δ<sup>15</sup>N</li> <li><em>d13C: </em>stable isotope ratio δ<sup>13</sup>C</li> <li><em>d34S: </em>stable isotope ratio δ<sup>34</sup>S</li> <li><em>perc.C: </em>mass percent of carbon in the sample</li> <li><em>perc.N: </em>mass percent of nitrogen in the sample</li> <li><em>perc.S: </em>mass percent of sulfur in the sample</li> <li><em>C.N.ratio: </em>mass ratio of carbon to nitrogen in the sample </li> </ul> <p>5. <strong>CN_greenland_nLE_copenhagen.csv</strong> contains stable isotope data for non-lipid-extracted samples analyzed at the University of Copenhagen for δ<sup>13</sup>C and δ<sup>15</sup>N. Variables <em>treatment</em>, <em>d13C</em>, and <em>d15N</em> are consistent with CNS_greenland_McGill.csv. </p>
Source data for "Feed-forward metabotropic signaling by Cav1 Ca2+ channels supports pacemaking in pedunculopontine cholinergic neurons"
<p><strong>Fig.1A_ChAT.tif</strong></p><p>Confocal image (green channel, anti-ChAT staining) for Fig.1A</p><p> </p><p><strong>Fig.1A_tdTomato.tif </strong></p><p>Confocal image (red channel, tdTomato) for Fig.1A</p><p> </p><p><strong>Fig.1B_ChAT.tif</strong></p><p>Confocal image (green channel, anti-ChAT staining) for Fig.1B</p><p> </p><p><strong>Fig.1B_tdTomato.tif</strong></p><p>Confocal image (red channel, tdTomato) for Fig.1B</p><p> </p><p><strong>Fig.1C_DIC.png</strong></p><p>Differential interference contrast micrograph for Fig.1C left</p><p> </p><p><strong>Fig.1C_Fluo.png</strong></p><p>Epifluorescent illumination micrograph for Fig. 1C right</p><p> </p><p><strong>Fig.1DEH.xlsx</strong></p><p>Numerical data for the charts in Fig. 1D, Fig.1E, Fig.1H</p><p> </p><p><strong>Fig.1F.tif</strong></p><p>MAX projection of z-stack of 2PLSM images (red channel, Alexa 594) used to generate Fig.1F </p><p> </p><p><strong>Fig.1F_inset.tif</strong></p><p>2PLSM image (green channel, Fura-2) for the right inset of Fig.1F</p><p> </p><p><strong>Fig.2A_inset.tif</strong></p><p>Confocal image (green channel, GFP) for the higher magnification inset of Fig.2A</p><p> </p><p><strong>Fig.2A.tif</strong></p><p>Confocal image (green channel, GFP) for Fig.2A</p><p> </p><p><strong>Fig.2B_bottom.tif</strong></p><p>Confocal image (green channel, GFP) for Fig.2B (bottom and overlay panels)</p><p> </p><p><strong>Fig.2B_top.tif</strong></p><p>Confocal image (red channel, td Tomato) for Fig.2B (top and overlay panels)</p><p> </p><p><strong>Fig.2CE.xlsx</strong></p><p>Numerical data for the charts in Fig. 2C, Fig. 2E</p><p> </p><p><strong>Fig.3B.tif</strong></p><p>Confocal image (green channel, MitoGCaMP6) for Fig.3B and overlay in Fig.3D</p><p> </p><p><strong>Fig.3C.tif</strong></p><p>Confocal image (red channel, tdTomato) for Fig.3C and overlay in Fig.3D</p><p> </p><p><strong>Fig.3E.tif</strong></p><p>2PLSM image (green channel, MitoGCaMP6) for Fig.3E</p><p> </p><p><strong>Fig.3GIJ.xlsx</strong></p><p>Numerical data for the charts in Fig. 3G, Fig. 3I, Fig.3J</p><p> </p><p><strong>Fig.4B.tif</strong></p><p>2PLSM image (green channel, MitoGCaMP6) for Fig.4B</p><p> </p><p><strong>Fig.4DFG.xlsx</strong></p><p>Numerical data for the charts in Fig.4D, Fig.4F, Fig.4G</p><p> </p><p><strong>Fig.5A.tif</strong></p><p>Confocal image (green channel, PercevalHR) for Fig.5A and overlay in Fig.5C</p><p> </p><p><strong>Fig.5B.tif</strong></p><p>Confocal image (red channel, tdTomato) for Fig.5B and overlay in Fig.5C</p><p> </p><p><strong>Fig.5D.tif</strong></p><p>2PLSM image (green channel, PercevalHR) for Fig.5D</p><p> </p><p><strong>Fig.5GHJ.xlsx</strong></p><p>Numerical data for the charts in Fig.5G, Fig.5H, Fig.5J</p><p> </p><p><strong>Fig.6BCD.xlsx</strong></p><p>Numerical data for the charts in Fig.6b, Fig.6C, Fig.6D</p><p> </p><p><strong>Fig.7A.tif</strong></p><p>Confocal image (green channel, mito-roGFP) for Fig.7A and overlay in Fig.7C</p><p> </p><p><strong>Fig.7B.tif</strong></p><p>Confocal image (red channel, tdTomato) for Fig.7B and overlay in Fig.7C</p><p> </p><p><strong>Fig.7D.tif</strong></p><p>2PLSM image (green channel, mito-roGFP) for Fig.7D</p><p> </p><p><strong>Fig.7F.xlsx</strong></p><p>Numerical data for the charts in Fig.7F</p>
UCSB SONGS Mitigation Monitoring: Wetland Survey - Bird Feeding Activity
These data describe annual estimates of shorebird bird feeding activity, measured as the percentage of birds observed feeding, collected as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to evaluate compliance of the restoration project with conditions of the SONGS permit. Monitoring began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County. Bird feeding activity was estimated for twenty plots in each wetland having at least one targeted shorebird species present on the ground. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
Hubbard Brook Experimental Forest: Gastropod lichen feeding trials
Herbivory by terrestrial gastropods, particularly Arion sp., can alter lichen communities; however, little is known about this interaction in forests of North America. This data set reports the results of two feeding trials with slugs and snails from Hubbard Brook on seven lichen species. In feeding trials two common lichens, Hypogymnia physodes and Platismatia glauca, were grazed more heavily by both native and non-native slugs than other lichen species.
FIG. 50 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 50. — Lateral view of the right pelvic bones of some extant mysticetes. A, Balaenoptera musculus; B, Balaenoptera musculus; C, Megaptera novaeangliae; D, E, Balaena mysticetus. The iliac, pubic and ischial portions are, respectively, in blue, yellow and green. Modified from Struthers (1893).
FIG. 49 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 49. — Lateral view of innominate of some extinct cetaceans. A, Georgiacetus vogtlensis (GSM 350); B, Basilosaurus isis (CGM 42176, cast); C, Basilosaurus cetoides (USNM 12261); D, Chrysocetus healyorum (SCSM 87-195, cast, right innominate, reversed); E, Mystacodon selenensis (MUSM 1917). Not to scale.
FIG. 48 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 48. — Mystacodon selenensis (MUSM 1917, holotype). Left innominate: A, lateral view; B, dorsal view; C, medial view; D, ventral view. Scale bar: 5 cm.
FIG. 39 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 39. — Ribs transverse sections of Mystacodon, basilosaurids, and chaeomysticetes. A, Mystacodon selenensis (MUSM 1917, holotype): section of an anterior-median (right?) rib of the thoracic cage in the median region of the diaphysis; B, Dorudon atrox (UM 101222): section of a left R4 at mid-diaphysis (reversed); C, Basilosaurus isis (WH 074): section of a left R4 at mid-diaphysis. B and C are reproduced from Houssaye et al. (2015). D, Piscobalaena nana (MNHN.F. SAS1618). E, Balaenoptera acutorostrata (IRSNB uncatalogued). Abbreviations: ant, anterior; med, medial. Scale bar: 1 cm.
FIG. 42 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 42. — Mystacodon selenensis (MUSM 1917, holotype). Right humerus: A, lateral view; B, medial view; C, anterior view; D, posterior view. Scale bar: 5 cm.
FIG. 6 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 6. — Lateral view of the skull of Mystacodon selenensis (MUSM 1917, holotype). Oblique lines and grey-shaded regions indicate respectively broken and reconstructed parts. Scale bar: 20 cm.
FIG. 1 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 1. — Views of the extraction of the postcranial skeleton of Mystacodon selenensis (MUSM 1917 holotype) at Playa Media Luna (Ica Department, Peru).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.