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2,817 results for “Fats”
Multiscale assessment of the effect of a stearic-palmitic sucrose ester on the crystallization of anhydrous milk fat
<p>Dataset belonging to publication 'Multiscale assessment of the effect of a stearic-palmitic sucrose ester on the crystallization of anhydrous milk fat'.</p> <p>Available via: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.foodres.2024.115243" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.foodres.2024.115243</a>.</p> <p> </p> <p>PLM = polarized light microscopy</p> <p>CryoSEM = cryo-scanning electron microscopy</p> <p>> data obtained after de-oiling fat samples with isobutanol (4x) and aceton (1x), see publication</p> <p>SAXS = small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>WAXS = wide-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>USAXS = ultra-small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of the capillary at 70°C, see publication</p> <p>DSC = differential scanning calorimetry</p> <p>> Samples are heated at 70°C for 10 min, and then crystallized following a certain protocol (see publication).</p> <p>> Samples are maintained one hour at their respective isothermal crystallization temperature.</p> <p>> Samples are rehaeted at 5°C/min to 70°C.</p> <p>SE = sucrose ester (SP30, HLB6)</p> <p>AMF = anhydrous milk fat</p> <p>AMFE = anhydrous milk fat + 0.5 wt% SE</p> <p>FC = fast cooling (20°C/min)</p> <p>SC = slow cooling (1°C/min)</p> <p> </p> <p>Project funding agency: Fonds Wetenschappelijk Onderzoek (FWO). Grant number: 1128923N. </p>
Data and script for Van Berkel et al: Can starlings use a reliable cue of future food deprivation to adaptively modify foraging and fat reserves?
<p>Supporting materials for:</p> <p><strong>Can starlings use a reliable cue of future food deprivation to adaptively modify foraging and fat reserves?</strong></p> <p>Menno van Berkel<sup>a</sup>, Melissa Bateson<sup>a</sup>, Daniel Nettle<sup>a</sup> and Jonathon Dunn<sup>a</sup>*</p> <p><sup>a</sup>Centre for Behaviour and Evolution & Institute of Neuroscience, Newcastle University, Newcastle, UK</p> <p>*Author for correspondence (email: jonathon.dunn@newcastle.ac.uk; telephone: (+44)7730015855; postal address: Institute of Neuroscience, Henry Wellcome Building, The Medical School, Framlington Place, Newcastle University, Newcastle upon Tyne, UK, NE2 4HH).</p> <p>R script and 3 .csv files.</p>
Crystallization behavior and structural build-up of palm stearin - wax hybrid fat blends
<p>This dataset was used in the publication <em>"Crystallization behavior and structural build-up of palm stearin - wax hybrid fat blends"</em>. An overview of the abbreviations and the dataset can be found below.</p>
Manipulation of photoperiod induces fat storage, but not fat mobilization in the migratory songbird, Dumetella carolinensis (Gray Catbird).
<p>Associated R code and data sets for analyses related to the "Manipulation of photoperiod induces fat storage, but not fat mobilization in the migratory songbird, Dumetella carolinensis (Gray Catbird)." publication. </p>
Investigating the Effect of Positional Variation on Mid-Lactation Mammary Gland Transcriptomics in Mice Fed Either a Low-Fat or High-Fat Diet
<p>Investigating the Effect of Positional Variation on Mid-Lactation Mammary Gland Transcriptomics in Mice Fed Either a Low-Fat or High-Fat Diet.</p>
Multi-Site Fat-Water Phantom MRI Data
<p><strong>Dataset description:</strong> Accompanying data for manuscript “Multi-Site,</p> <p>Multi-Vendor Validation of the Accuracy and Reproducibility of</p> <p>Proton-Density Fat-Fraction Quantification at 1.5T and 3T using a</p> <p>Fat-Water Phantom”, submitted for publication in Magnetic Resonance in</p> <p>Medicine in January 2016.</p> <p> </p> <p><strong>Details:</strong> The 'datasets' folder contains multiple MATLAB MAT-files</p> <p>files with chemical shift-encoded (CSE) MRI data for validation of fat</p> <p>quantification techniques in a fat-water phantom. Data was acquired at</p> <p>six sites with different MRI vendors, two field strengths (1.5T and</p> <p>3T) per site, and two protocols per field strength. The goal of these</p> <p>techniques is to measure proton-density fat-fraction (PDFF) accurately</p> <p>and reproducibly. Data from site 1 was acquired both at the beginning</p> <p>(October 2014) and at the end (December 2015) of this study, in order</p> <p>to evaluate the integrity of the phantom. </p> <p> </p> <p>Details on the vendors, platforms and protocols are described in the</p> <p>file 'vendors_platforms_protocols.pdf' in this same folder.</p> <p> </p> <p>The phantom consists of 11 vials with different fat concentrations</p> <p>(PDFF = 0%, 2.6%, 5.3%, 7.9%, 10.5%, 15.7%, 20.9%, 31.2%, 20.9%,</p> <p>31.2%, 41.3%, 51.4% and 100%, respectively). At each magnet, the vials</p> <p>were arranged horizontally along the B0 field and scanned with axial</p> <p>slices using a 3D multi-echo spoiled gradient echo pulse sequence.</p> <p> </p> <p>Each of the MAT-files contains the acquired complex-valued images over</p> <p>the three central slices within the phantom vials. The structure</p> <p>'imDataAll' contains the acquired data, with the following fields:</p> <p>'TE' (echo times), 'FieldStrength' (in Tesla), 'PrecessionIsClockwise'</p> <p>(describing whether water has higher resonance frequency than fat</p> <p>according to the reconstruction convention), 'echo_polarity' (relative</p> <p>polarity of the acquired echoes, ie: monopolar vs bipolar readouts),</p> <p>'images' (five-dimensional array containing the complex valued images,</p> <p>coil-combined in datasets received with multiple channels, with</p> <p>dimensions X x Y x Slices x Coils x Echoes).</p> <p> </p> <p>Additionally, the MAT-files contain reconstruction results as</p> <p>described in the manuscript, in the arrays 'fwmc_*' of size X x Y x</p> <p>Slices. Note that the nomenclature 'fwmc' stands for 'Fat-Water</p> <p>separated with Magnitude fitting (performed after complex fitting in</p> <p>order to obtain full 0-100% range of PDFF while avoiding errors</p> <p>related to phase shifts in the data), and a Common initial phase for</p> <p>the water and fat signals. The specific arrays are 'fwmc_ff' (PDFF</p> <p>map), 'fwmc_r2star' (R2*=1/T2* decay rate), 'fwmc_w' (water image),</p> <p>'fwmc_f' (fat image).</p>
Fat oxidation rates and cardiorespiratory responses during exercise in different subject populations with post-acute sequelae of SARS-CoV-2 infection: a comparison with normative percentile values
<p>INTRODUCTION: Post-acute sequelae of SARS-CoV-2 infection (PASC) presents a spectrum of symptoms following acute COVID-19, with exercise intolerance being a prevalent manifestation likely linked to disrupted oxygen metabolism and mitochondrial function. This study aims to assess maximal fat oxidation (MFO) and exercise intensity at MFO (FATmax) in distinct PASC subject groups and compare these findings with normative data.</p> <p>METHODS: Eight male subjects with PASC were involved in this study. The participants were divided in two groups: “endurance-trained” subjects (V̇O<sub>2</sub>max > 55 ml/min/kg) and “recreationally-active” subjects (V̇O<sub>2</sub>max < 55 ml/min/kg). Each subject performed a graded exercise test until maximal oxygen consumption (V̇O<sub>2</sub>max) to measure fat oxidation. Subsequently, MFO was assessed and FATmax calculated as the ratio between V̇O<sub>2 </sub>at MFO and V̇O<sub>2</sub>max.</p> <p>RESULTS: The MFO and FATmax of “endurance-trained” subjects were 0.85, 0.89, 0.71 and 0.42, and 68%, 69%, 64% and 53%, respectively. Three out of four subjects showed both MFO and FATmax values placed over the 80<sup>th</sup> percentile of normative data. The MFO and FATmax of “recreationally-active” subjects were 0.34, 0.27, 0.35 and 0.38, and 47%, 39%, 43% and 41%, respectively. All MFO and FATmax values of those subjects placed below the 20<sup>th</sup> percentile or between the 20<sup>th</sup> and 40<sup>th</sup> percentile.</p> <p>DISCUSSION: Significant differences in MFO and FATmax values between 'endurance-trained' and “recreationally-active” subjects suggest that specific endurance training, rather than simply an active lifestyle, may provide protective effects against alterations in mitochondrial function during exercise in subjects with PASC.</p>
Genotyping and phenotyping data for Genome-wide analyses of body fat reserves in ewes
<p><strong>Among the adaptive capacities of animals, the management of energetic body reserves (BR) through the BR mobilization and accretion processes (BR dynamics, BRD) has become an increasingly valuable attribute for livestock sustainability, allowing animals to cope with more variable environments. BRD has previously been reported to be heritable in ruminants. In the present study, we conducted genome-wide studies (GWAS) in sheep to determine genetic variants associated with BRD. BR levels and BR changes over time were obtained through body condition score measurements at eight physiological stages throughout each productive cycle in Romane ewes (n=1034) and were used as phenotypes for GWAS. After quality controls and imputation, 48,513 single nucleotide polymorphisms (SNP) were included in the GWAS. Among the QTLs identified, a major QTL associated with BR levels during pregnancy and lactation was identified on chromosome 1. In this region, several significant SNPs mapped to the leptin receptor gene (LEPR), among which one SNP mapped to the coding sequence. The point mutation induces the p.P1019S substitution in the cytoplasmic domain, close to tyrosine phosphorylation sites. The frequency of the SNP associated with increased BR levels was 32%, and the LEPR genotype explained up to 5% of the variance of the trait. These results provide strong evidence for involvement of LEPR in the regulation of BRD in sheep and highlight it as a major candidate for improving adaptive capacities.</strong></p>
Data from: Robust Estimation of Field Inhomogeneity Map Following Magnitude-Based Water-Fat Separation with Resolved Ambiguity
<p>These data have been uploaded and shared as part of "Robust Estimation of Field Inhomogeneity Map Following Magnitude-Based Water-Fat Separation with Resolved Ambiguity". The data may be used for field inhomogeneity mapping and PDFF/R2* reconstruction. </p> <p>These data were acquired by Perspectum Ltd (https://perspectum.com/) on a healthy volunteer. Informed consent was obtained from the participant. The dataset includes a localizer series and a multi-slice series (magnitude and phase) acquired from a volunteer covering the dome of the liver, heart and lungs:</p> <ul> <li>1-localizer_haste_bh</li> <li>2-I_6_Echo_3D_32_Slice_IDEAL</li> <li>3-I_6_Echo_3D_32_Slice_IDEAL</li> </ul> <p>These data were gathered using a Siemens Prisma 3 Tesla scanner. The main dataset comprises an acquisition with thirty-two slices including the abdominal region, with slices placed away from the isocenter. The acquisition consisted of a 6‐echo (TE1=1.3 ms, ΔTE=1 ms) gradient-recalled echo (GRE) protocol designed to minimize T1 bias (3° flip angle), Pixel Bandwidth = 1565 Hz, and 232 x 256 reconstructed image size, with 5 mm slice thickness and 1.72 x 1.72 mm^2 in-plane resolution. </p>
Time to run: Late rather than early exercise training in mice promotes fat mass loss and reduces atherosclerosis development
<p>This dataset contains forward and reverse reads of 16S sequencing of the V3-V4 region of caecal bacteria. As indicated in the metadata file, mice are divided into three groups - SED (sedentary mice, E-SED for early sedentary and L-SED for late sedentary), E-RUN (early runners) and L-RUN (late runners). For more information about the groups, sequencing etc., consult the manuscript.</p>
ATR Spectra of Human Milk Fat
<p>ATR spectra of human milk fat.</p> <p>This dataset was employed in the paper "Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk" published in MDPI Foods, DOI: <a href="https://doi.org/10.3390/foods11233906">https://doi.org/10.3390/foods11233906</a>.</p>
Infection-nutrition feedbacks: fat supports pathogen clearance but pathogens reduce fat in a wild mammal
<p>Though far less obvious than direct effects (clinical disease or mortality), the indirect influences of pathogens are difficult to estimate but may hold fitness consequences. Here, we disentangle the directional relationships between infection and energetic reserves, evaluating the hypotheses that energetic reserves influence infection status of the host and that infection elicits costs to energetic reserves. Using repeated measures of fat reserves and infection status in individual bighorn sheep (<em>Ovis canadensis</em>) in the Greater Yellowstone Ecosystem, we documented that fat influenced ability to clear pathogens (<em>Mycoplasma ovipneumoniae</em>) and infection with respiratory pathogens was costly to fat reserves. Costs of infection approached, and in some instances exceeded, costs of rearing offspring to independence in terms of reductions to fat reserves. Fat influenced probability of clearing pathogens, pregnancy, and over-winter survival; from an energetic perspective, an animal could survive for up to 23 days on the amount of fat that was lost to high levels of infection. Cost of pathogens may amplify tradeoffs between reproduction and survival. In the absence of an active outbreak, the influence of resident pathogens often is overlooked. Nevertheless, the energetic burden of pathogens likely has consequences for fitness and population dynamics, especially when food resources are insufficient.</p> <p><span> </span></p>
Figure 4 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 4. Body weight on the 120th offspring from mothers submitted the control diet or the high-fat diet. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiple-comparison test. *p<0,05; **p<0,005.
Figure 3 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 3. Body weight on the second day life's of offspring from mothers submitted the control diet (C) or the high-fat diet (H). Values are presented as mean + SEM using Student t-test. C: n = 23; H: n = 23.
Figure 2 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 2. Pomc (A) and npy (B) gene expression in the hypothalamus of offspring exposed or not to a control diet or high-fat diet during perinatal and/or postnatal period. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiplecomparison test. Level of significance: *p<0,05; "a": compared to CC, "b": compared to CH; "c": compared to HC; "d": compared to HH.
Figure 1. Drd1 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 1. Drd1 (A) and drd2 (B) gene expression in the nucleus accumbens of offspring exposed or not to a control diet or high-fat diet during perinatal and/or postnatal period. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiplecomparison test. Level of significance: *p<0,05; "a": compared to CC, "b": compared to CH; "c": compared to HC; "d": compared to HH.
Dataset: FAT Brands Inc. (FATBP) 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.
Dataset: FAT Brands Inc. (FATBW) 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.
Dataset: FAT Brands Inc. (FAT) 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.
Dataset: Aura FAT Projects Acquisition Corp (AFARW) 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.
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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.