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741 results for “chicken”
Supplementary dataset to publication: "Elevated platforms with integrated weighing beams allow automatic monitoring of usage and activity in broiler chickens"
<p>The dataset supplements the journal article "Elevated platforms with integrated weighing beams allow automatic monitoring of usage and activity in broiler chickens" by H. Schomburg, J. Malchow, O. Sanders, J. Knöll and L. Schrader, that appeared in Smart Agricultural Technology 3 (2023), https://doi.org/10.1016/j.atech.2022.100095. The file archives trial1.zip and trial2.zip contain csv files with platform weighing system data measured from June 19, 2019 to July 22, 2019 (trial 1) and from September 9, 2019 to October 14, 2019 (trial 2) in a broiler chicken barn at Friedrich-Loeffler-Institut, Institute of Animal Welfare and Animal Husbandry, Celle. A detailed description of data structure is given in 00_hl_weighing_system_data_overview.txt.</p>
CPC01 Annual census of Greater Prairie Chickens on leks at Konza Prairie
Location of leks and number of birds per lek are censused during late April and early May across Konza Prairie to document year to year densities of greater prairie chickens. This dataset is continued by CPC02 after 04/19/1999.
CPC02 Census of greater prairie chicken on leks at Konza Prairie
Location of leks and number of birds per lek are censused during late April and early May across Konza Prairie to document year to year densities of greater prairie chickens.
Chicken Immunoglobulin Gene Conversion Full Dataset
<p>Full dataset containing PacBio sequencing data and gene conversion information output from Brepconvert, for the immunoglobulin heavy and light chain of six 3 week old Rhode Island Red chickens studied as part of the publication Diversification of Antibodies by Gene Conversion in the Domestic Chicken (Gallus gallus domesticus). </p>
Data, scripts, and figures of the article: Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 2. Developing prediction models
<p>This data set contains the data, JMP scripts, and figures of the article titled "Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 2. Developing prediction models" to be published in the journal Animal - Open Space.</p>
Data, scripts, and figures of the article: Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 1. Weight changes due to fasting, bleeding, and chilling
<p>This data set contains the data, JMP scripts, and figures of the article titled "Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 1. Weight changes due to fasting, bleeding, and chilling" to be published in the journal Animal - Open Space. </p>
Increased egg shell temperature during incubation leads to changes in transcriptional and epigenetic profiles in chicken lungs
<p>These RDS files contain <strong>DESeqDataSet </strong>objects subsets per broiler age and treatment. These objects are the result of DESeq2::DESeq( … ,betaPrior=FALSE).The .txt-objects contain the normalized sequencing counts per broiler age and treatment group. These objects are the result of DESeq2::counts( … , normalized=TRUE). Data was generated using STAR v2.7.10a and DESeq2 v1.36. Metadata is included as Excel file.</p> <p>Sequencing data is deposited at NCBI-SRA under BioProject: PRJNA949139. </p> <p> </p> <p><strong>Study abstract</strong></p> <p>D. Schokker, J. de Vos, P.B. Stege, O. Madsen, H.J. Wijnen, S.K. Kar, and J.M.J. Rebel</p> <p>Health and resilience against respiratory diseases are important features for broiler chicken. In this study, epigenetic and transcriptomic changes in the lungs of broiler chickens of different ages during rearing that were either exposed to elevated egg shell temperature (HIGH) of 38.9°C during mid-incubation or normal egg shell temperature (control; CON). The objective was to better understand how environmental challenges, such as heat stress during egg incubation, affect the development of the immune system and health of broiler chicken at later age. To this end we generated both epigenetic and transcriptomic data of lung tissue of elevated HIGH and CON chicken, furthermore these chicken were challenged by introducing either an infectious E. coli or an IBV vaccination to monitor the respiratory response. Thousands of differential methylated sites were observed at days 15 and 33, when comparing HIGH vs. CON. Pathway enrichment analysis of HIGH vs. CON showed that differentially expressed genes were mainly involved in cilium, cytoskeleton, and immune processes. These findings provide insight into the underlying biological mechanisms of early life conditions, like elevated EST, and their potential role in health of broilers.</p>
Chicken intestinal development is affected by different dietary interventions
<p>These RDS files contain <strong>DESeqDataSet </strong>objects subset into broiler groups of 4, 12 and 33 days post-hatch.<br> These objects are the result of DESeq2::DESeq( … ,betaPrior=FALSE).The .txt-objects contain the normalized sequencing counts per broiler age group. These objects are the result of DESeq2::counts( … , normalized=TRUE). Data was generated using STAR v2.7.9a and DESeq2 v1.34. Metadata is included as Excel file.</p> <p>Sequencing data is deposited at NCBI-SRA under BioProject: PRJNA949454. </p> <p> </p> <p><strong>Study abstract</strong></p> <p>Dirkjan Schokker, Soumya K. Kar, Paul Stege, Norbert Stockhofe, Alex Bossers, Vera Perricone, Annemarie Rebel, Ingrid de Jong</p> <p>Gut health is a prerequisite for broiler welfare. In this study, we investigated the effect of three dietary interventions on small intestinal development in broilers and special emphasis on immunity. Morphometry and immunostaining showed no significant differences in any of the treatments, however, gene expression revealed significant differences in the LPHF and MCFA treatments. Pathway enrichment analysis showed a few main pathways involved in regulation of cellular processes, cell structural processes, and cell protection, as well as a putative link to inflammatory processes. Taken together, these findings suggest that dietary interventions can modulate gut health and functionality in chicken.</p>
Figs 9–13 in Gallancyra gen. nov. (Phthiraptera: Ischnocera), with an overview of the geographical distribution of chewing lice parasitizing chicken
Figs 9–13. Gallancyra dentata (Sugimoto, 1934) gen. et comb. nov. ex Gallus gallus (Linnaeus, 1758) (NHMUK010682393). 9. Male head, dorsal and ventral views. 10. Female antenna, ventral view. 11. Male genitalia, dorsal view. 12. Male paramere, dorsal view. 13. Male mesosome, ventral view. Female antenna at same scale as male head. Abbreviations: ads = anterior dorsal seta; as2 = anterior seta 2; pst1–2 = parameral setae 1–2. All genitalic component drawn at same scale.
Fig. 2 in Gallancyra gen. nov. (Phthiraptera: Ischnocera), with an overview of the geographical distribution of chewing lice parasitizing chicken
Fig. 2. Geographical distribution of four species of ischnoceran chewing lice parasitizing wild and domestic chicken (Gallus spp.). Each circle is divided into four sectors, representing the four louse species: upper left = Lipeurus caponis (Linnaeus, 1758); upper right = Lipeurus tropicalis Peters, 1931; lower left = Cuclotogaster heterographus (Nitzsch, 1866); lower right = Lagopoecus sinensis (Sugimoto, 1930). Black sectors indicate that this louse species is known from this country, whereas hollow sectors indicate that we have found no published records of this species in this country. Presence of the four species of chewing lice in a country is based on the reports summarized in Table 1.
Supplementary material for: "Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations"
<p>Supplementary material for the publication "Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations"</p> <p>The realated preprint can be found at Research Square (<a href="https://doi.org/10.21203/rs.3.rs-861830/v1">https://doi.org/10.21203/rs.3.rs-861830/v1</a>)</p> <p>Supplementary file 1: Supplementary results, tables and figures.</p> <p>Supplementary file 2: MultiQC report.</p> <p>Supplementary file 3: Observer concordance of the visual filtering step.</p> <p>Supplementary file 4: Snakemake workflow and scripts.</p> <p> </p>
Fig. 1 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 1. Menopon gallinae: ♀: 1 — forehead; 2 — temporal lobe; 3 — antenna; 4 — eyes; 5 — abdomen (×400); ♂: 1 — forehead; 2 — temporal lobe; 3 — antenna; 4 — foot; 5 — bristles; 6 — abdomen posterior (×300).
Fig. 4 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 4. Morphology of Goniocotes hologaster: ♀: 1 — forehead; 2 — eyes; 3 — bristles on head; 4 — the rear of the abdomen (×300); ♂: 1 — head; 2 — temporal edges; 3 — overall oval body; 4 — the last segment of the abdomen blade-shaped (×250).
Fig. 3 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 3. Morphology of Menacanthus cornutus: ♀: 1 — forehead; 2 — temporal lobe; 3 — sternal plate; 4 — crop; 5 — posterior part of the abdomen with bristles; ♂: 2 — eye; 3 — prothorax with foots; 4 — mesothorax; 5 — metathorax; 6 — abdomenal bristles; 7 — oval shape of the rear of the abdomen; 8 — ejaculatory ducts (×400).
Fig. 2 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 2. Morphology Menacanthus stramineus: ♀: 1 — forehead; 2 — temporal lobe; 3 — prothorax; 4 — mesothorax; 5 — metathorax; 6 — tarse; 7 — crop; 8 — the egg chamber; ♂: 1 — prothorax foot; 2 — foot mesothorax; 3 — foot metathorax; 4 — testes; 5 — crop (×400).
Prevalence and Factors Associated with Salmonellosis in Chicken Brooding Farms in and Around Arba Minch Town, Gamo Zone of Ethiopia
<p>We all authors have done this research entitled ‘’<strong>Prevalence and Factors Associated with Salmonellosis in Chicken Brooding Farms in and Around Arba Minch Town, Gamo Zone of Ethiopia’’ </strong>for disseminating the result of our finding to the scientific community. The research has its strength as we did on chicken brooding farms which are the emerging production system in Ethiopia context and women and young cooperatives are highly engaged in this business but they have faced health-related problems in their management system. Therefore, this research was initiated based on practical challenges observed by the authors during professional support to brooding farm owners. This research aimed to estimate the prevalence of Salmonellosis and its potential factors with their antibiotic resistance pattern in the study area because there is irrational use of antibiotics among human and animal health in the study area this might have a source of development of drug resistance in Ethiopia and the study area in particular. Furthermore the study focus on bacteriological analysis, risk factor association and drug sensitivity test due to the limitation of resource that can be baseline data for characterization.</p>
Data, scripts, and figures of the article: Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 3. Validation of prediction models
<p>This data set contains the data, JMP scripts, and figures of the article titled "Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 3. Validation of prediction models" to be published in the journal Animal - Open Space.</p>
Cone-Beam Computed Tomography Dataset of a Chicken Bone Imaged at 4 Different Dose Levels
<p><strong>Summary</strong></p> <p>This dataset is a collection of X-ray projection images of a chicken leg bone imaged in a cone-beam computed tomography (CBCT) scanner, using four different dose levels. The dataset also includes a metadata file for each of the scans, specifying the scan geometry and other important scan parameters.</p> <p> </p> <p><strong>Description</strong></p> <p><em>Sample Information</em></p> <p>The sample is a chicken bone obtained from a cooked chicken. The bone was boiled to remove soft tissues, after which it was left to dry in room temperature for several months to remove extra moisture. For the scan the sample was placed directly into the rotation stage and secured with a screw.</p> <p><em>Scanner</em></p> <p>The measurements were acquired using a cone-beam computed tomography scanner designed and constructed in-house in the Industrial Mathematics Computed Tomography Laboratory at the University of Helsinki. The scanner consists of a molybdenum target X-ray tube (Oxford Instruments XTF5011), a motorized rotation stage (Thorlabs CR1-Z7), and a 12-bit, 2240x2368 pixel, energy-integrating flat panel detector (Hamatsu Photonics C7942CA-22).</p> <p><em>Scan Settings</em></p> <p>The dataset consists of four different scans of the same sample. For each scan 721 X-ray projections were acquired using an angle increment of 0.5 degrees. The X-ray source was set at 40 kV with a 0.5 mm aluminum filter. For the different scans, the relative doses, tube currents, and exposure times were:</p> <ul> <li>100 % relative dose: tube current 1 mA, exposure time 2000 ms,</li> <li>50 % relative dose: tube current 1 mA, exposure time 1000 ms,</li> <li>25 % relative dose: tube current 0.5 mA, exposure time 1000 ms,</li> <li>10 % relative dose: tube current 0.2 mA, exposure time 1000 ms.</li> </ul> <p>The scans were made in sequence, proceeding from the lowest dose to the highest dose.</p> <p><em>Data Post-Processing</em></p> <p>Before the scans, two correction images were acquired for each scan setting. A dark current image was created by averaging 100 images taken with the X-ray source off. A flat-field image was created by averaging 100 images taken with the X-ray source switched on with no sample placed in the scanner. After the scan, dark current and flat-field corrections were applied to each projection image using the Hamamatsu HiPic imaging software version 9.3.</p> <p><em>Data Format</em></p> <p>The X-ray projections are stored in .tif format. The metadata are contained in .txt files with formatting that is both human-readable and machine-readable.</p> <p><em>Notes</em></p> <p>Due to a slightly misaligned center of rotation in the scanner, the CT reconstructions can appear blurry. It was empirically observed that this problem can be compensated for quite well by shifting each projection left by 4 pixels, using circular boundary conditions, before performing any other operations on the projections. It was also observed that the scans are not entirely aligned, with a small angular discrepancy between each reconstruction.</p> <p> </p> <p><strong>Research Group</strong></p> <p>This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland: <a href="https://www2.helsinki.fi/en/researchgroups/inverse-problems">https://www2.helsinki.fi/en/researchgroups/inverse-problems</a>.</p> <p> </p> <p><strong>Additional Links</strong></p> <p>To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected in the Industrial Mathematics Computed Tomography Laboratory, and available at <a href="https://github.com/Diagonalizable/HelTomo">https://github.com/Diagonalizable/HelTomo</a>.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.</p>
A copro-antigen ELISA for the detection of ascarid infections in chickens
<p>Dataset for the infection experiments to evaluate the performance of copro-antigen ELISA to assess nematode infections. Chickens were divided into three groups. One group was kept as uninfected control, and the birds of the other two groups were either experimentally infected with 100 or 1,000 embryonated/infective eggs of either <em>Ascaridia galli</em> or <em>Heterakis gallinarum</em></p>
Dataset: Chicken Soup for the Soul Entertainment, Inc. (CSSEP) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.