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189 results for “dehydration”
MicroCT scans of a hybrid poplar leaf dehydrating, with annotated slices for model training
<p>Dataset of a leaf segment of a hybrid poplar (<em>P. maximowiczii x P. nigra</em> ‘Max3’) leaf scanned using microcomputed tomography (microCT) over time as it dehydrates.</p> <p> </p> <p><strong>Data acquisition methodology</strong></p> <p>Plants were brought to the TOMCAT tomographic beamline of the Swiss Light Source at the Paul Scherrer Institute (Villigen, Switzerland). Before microCT scanning, a young fully expanded leaf was detached from the plant and a short strip (0.4 x 1.5 cm) was cut between second-order veins. The base of the strip was wrapped in polyimide tape and inserted into a styrofoam block fixed on a sample holder. The strip was immediately scanned by imaging 1801 projections of 100 ms under a beam energy of 21 keV and a magnification of 40x, yielding a final voxel size of 0.1625 µm (field of view: ~416x416x312 µm). The leaf was left to dehydrate in the holder and additional scans were taken 10, 20, 25, and 30 minutes after the initial scan. Scanned projections were reconstructed to a transverse view using both absorption (gridrec; Marone <em>et al.</em> 2012) and phase contrast enhancement (Paganin <em>et al.</em> 2002) reconstruction.</p> <p> </p> <p><strong>Dataset description</strong></p> <p>On the reconstructed images a region of interest was identified using a paradermal view (i.e. top to bottom of the leaf) and used to manually align the scans of each time step. Thereafter, all images were cropped to that ROI, ensuring that the same region of the leaf was present in all image stacks.</p> <p>For all stacks, files start with:<br> <em>DEHYDRATION_small_Leaf4_time_N_</em><br> where N is the time point, with values from 1 to 5 equaling 0, 10, 20, 25, and 30 minutes.</p> <p>Following this prefix is either GRID (gridrec reconstruction), PAGANIN (phase contrast enhancement reconstruction), or LABELLED (hand labelled slices or ground truth). For GRID and PAGANIN, 8-bit grayscale stacks are provided. The AOI suffix indicates the region of interest.</p> <p>Stacks have been hand labelled over three orientations (for visual examples of the orientations see <a href="https://zenodo.org/api/files/6f06d15b-3ee9-412d-82ca-a20336c4bffa/Labeled_Sections_order_time1.png?versionId=26fc15aa-702e-4052-b162-702cc567634c">Labeled_Sections_order_time1.png</a> and <a href="https://zenodo.org/api/files/6f06d15b-3ee9-412d-82ca-a20336c4bffa/Labeled_Sections_order_time2.png">Labeled_Sections_order_time2.png</a>):</p> <ol> <li>CROSS (cross sectional, or transverse, view)</li> <li>LONGI (longitudinal view: similar to cross sectional view but starting normal to it, i.e. along the depth of the stack starting from the left of the cross-sectional view)</li> <li>PARADERMAL (top to bottom view: starting at the upper epidermis)</li> </ol> <p>A general idea of the slice range within one LABELLED stack is presented after the orientation, as:<br> <em>STARTtoENDbyRANGE</em><br> The exact position of the labelled slices for each time point can be found in the <a href="https://zenodo.org/api/files/6f06d15b-3ee9-412d-82ca-a20336c4bffa/Labeled_slices_positions.txt?versionId=93d7e22f-9f07-4f98-8c49-d93e9a2e1ce5">Labeled_slices_positions.txt </a>file. <strong>Note that one-based indexing is used (as in ImageJ), not zero-based indexing (as in e.g. Python).</strong></p> <p> </p> <p><strong>References</strong></p> <p>Marone F, Stampanoni M. 2012. Regridding reconstruction algorithm for realtime tomographic imaging. Journal of Synchrotron Radiation 19: 1029–1037.</p> <p>Paganin D, Mayo SC, Gureyev TE, Miller PR, Wilkins SW. 2002. Simultaneous phase and amplitude extraction from a single defocused image of a homogeneous object. Journal of Microscopy 206: 33–40.</p>
Data, multiscale dataset and supplementary information for 'Pulsed fluid release from subducting slabs caused by a scale-invariant dehydration process'
<p>This repository contains the analytical Supplementary Information, the data, the multiscale dataset and the codes used to construct the dataset and plot figures used in the manuscript 'Pulsed fluid release from subducting slabs caused by a scale-invariant dehydration process' (accepted in Earth and Planetary Science Letters). </p> <p> </p> <p> </p>
Repeatability of energy metabolism and resistance to dehydration in the invasive slug Limax maximus
<p>Dataset from the paper "Repeatability of energy metabolism and resistance to dehydration in the invasive slug <em>Limax maximus"</em></p> <p>It contains metabolic rates and body mass assessed on 30 individuals of L. maximus in three different trials. Metabolic rates are in CO2 ml/m</p>
Datasets used for analysis and plotting in the study by Zhou et al. "Antarctic vortex dehydration in 2023 as a substantial removal pathway for Hunga Tonga-Hunga Ha'apai water vapour"
<p>These data are model simulated water vapour (H2O) and ozone (O3) model mixing ratios between 2022 and 2023 that were used to create figures for the study by Zhou et al. "Antarctic vortex dehydration in 2023 as a substantial removal pathway for Hunga Tonga-Hunga Ha'apai water vapour".</p><p>We use the TOMCAT/SLIMCAT 3-D off-line chemical transport model (Chipperfield, 2006) to represent the Hunga Tonga-Hunga Ha'apai (HTHH) H2O plume and quantify its longevity and ozone impacts. The model was run at a horizontal resolution of 2.8 degrees and 32 levels from the surface to about 60 km forced with ECMWF ERA5 meteorology. </p><p>A control simulation (file name with "MPC741") without treatment of HTHH was integrated from 1980 to October 2023. Output from run control for January 1st, 2022 was used to intialise a HTHH H2O perturbed run (run HT, file name with "MPC744") until October 2023 with the injection of 150 Tg of H2O into the low-mid stratosphere at southern subtropical latitudes. To test the possible future evolution of the HTHH H2O three further model runs were performed. These were integrated from January 1st, 2023 until 2030 using repeating ERA-5 meteorology for 2022. Run Con_2022 (file name with "MPC741__2022pd") was an extension of run control; run HT2022 was an extension of run HT (file name with "MPC744_2022pd")<i>, </i>and run HT2022ns (file name with "MPC744_2022pdns") was the same as run HT_2022 but had sedimentation of PSC particles turned off. Please see our paper for more information about the simulations.</p>
Data from: The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests
<p>Heatwaves exert disproportionately strong and sometimes irreversible impacts on forest ecosystems. These impacts remain poorly understood at the tree and species level and across large spatial scales. Here, we investigate the effects of the record-breaking 2018 European heatwave on tree growth and tree water status using a collection of high-temporal resolution dendrometer data from 21 species across 53 sites. Relative to the two preceding years, annual stem growth was not consistently reduced by the 2018 heatwave but stems experienced twice the temporary shrinkage due to depletion of water reserves. Conifer species were less capable of rehydrating overnight than broadleaves across gradients of soil and atmospheric drought, suggesting less resilience toward transient stress. In particular, Norway spruce and Scots pine experienced extensive stem dehydration. Our high-resolution dendrometer network was suitable to disentangle the effects of a severe heatwave on tree growth and desiccation at large-spatial scales in situ, and provided insights on which species may be more vulnerable to climate extremes.</p>
Blood Donation Japanese Tweets - Dehydrated versions
<p>These datasets contains tweets collected through Twitter API with the previously available Research Account, during May 2023. Data was collected by using the “(献血 OR kenketsu OR けんけつ OR ラブラッド OR LoveBlood OR #献血 OR #けんけつ OR #kenketsu OR #ラブラッド OR #LoveBlood) lang:ja” search string, which containts the japanese words related to Blood Donation in japanese, and the name of the official blood donation application from Japan, LoveBlood.</p> <p>The Twitter_labeled_dataset contains tweets from the year 2022 randomly selected to prepare for manual labeling, while the other two datasets contain the tweets collected from October 2022 to April 2023 for automatized classification. Dataset_unlabeled_2023_full references to the raw collected tweets, while Data_classified_full has the final group of tweets after preprocessing and additional filtering.</p> <p>Considering the privacy recommendations when using Twitter data, all datasets has been "dehydrated," meaning they only contains the tweet IDs and not the associated content. To use this data, you will need to reassociate the IDs with their corresponding data (rehydration).</p>
Figure 1. - Nesting habitat of Xylocopanasalis; A nesting habitat of Xylocopanasalis on a makeshift roof of a restaurant in Suan Pheung district, Ratch Buri province, Thailand. The red arrows indicate locations where the bamboo culms were arranged ca. 2.50 m above the ground (1a and 1b). At the nest entrance, the female of Xylocopanasalis was dehydrating the nectar previously foraged (1c).
Figure 1. - Nesting habitat of Xylocopanasalis; A nesting habitat of Xylocopanasalis on a makeshift roof of a restaurant in Suan Pheung district, Ratch Buri province, Thailand. The red arrows indicate locations where the bamboo culms were arranged ca. 2.50 m above the ground (1a and 1b). At the nest entrance, the female of Xylocopanasalis was dehydrating the nectar previously foraged (1c).
Automated analysis of HPLC chromatograms obtained during the dehydration of N-Acetylglucosamine into 3-Acetamido-5-acetylfurane using Python
<p><strong>Content: </strong>This dataset contains High Performance Liquid Chromatography (HPLC) chromatograms, obtained while studying the dehydration of N-Acetylglucosamine into 3-Acetamido-5-acetylfurane in DMAc, DMF and NMP employing various catalysts and screening different reaction conditions. Reaction conditions can be retrieved from the metadata attached. Importantly, a python script to automatically extract, plot and analyze the HPLC-data obtained is provided.</p><p><strong>Acknowledgements</strong>: The authors acknowledge support by the German Research Foundation (DFG) within NFDI4Cat (ID 441926934). Parts of this work were funded by the Cluster of Excellence Fuel Science Center (EXC 2186, ID: 390919832) funded by the Excellence Initiative by the German federal and state governments. Furthermore, the authors thank Jens Heller and Frederic Thilmany for performing the HPLC measurements.</p><p> </p>
Corticosterone and immune responses to dehydration in squamate reptiles
<p class="MsoListParagraph">Many environments present some degree of seasonal water limitations; organisms that live in such environments must be adapted to survive periods without permanent water access. Often this involves the ability to tolerate dehydration, which can have adverse physiological effects and is typically considered a physiological stressor. While having many functions, the hormone corticosterone (CORT) is often released in response to stressors, yet increasing plasma CORT while dehydrated could be considered maladaptive, especially for species that experience predictable bouts of dehydration and have related coping mechanisms. Elevating CORT could reduce immunocompetence and have other negative physiological effects. Thus, such species likely have CORT and immune responses adapted to experiencing seasonal droughts. We evaluated how dehydration affects CORT and immune function in eight squamate species that naturally experience varied water limitation.</p> <p class="MsoListParagraphCxSpLast">We tested whether hydric state affected plasma CORT concentrations and aspects of immunocompetence (lysis, agglutination, bacterial killing ability, and white blood cell counts) differently among species based on how seasonally water limited they are and whether this is constrained by phylogeny. The species represented four familial pairs, with one species of each pair inhabiting environments with frequent access to water and one naturally experiencing extended periods (>30 days) with no access to standing water.</p> <p class="MsoNormal">The effects of dehydration on CORT and immunity varied among species. Increases in CORT were generally not associated with reduced immunocompetence, indicating CORT and immunity might be decoupled in some species. Interspecies variations in responses to dehydration were more clearly grouped by phylogeny than habitat type.</p>
Duplex Underplating, Sediment Dehydration and Quartz Vein Mineralization in the Deep Tremor Source Region
<p>Data for Duplex Underplating, Sediment Dehydration and Quartz Vein Mineralization in the Deep Tremor Source Region</p>
The 2021-2022 Fukushima-Oki Earthquakes in Northeastern Japan: Dehydration Triggered Fault Reactivation Boosted by Slab Segmentation
<p>codes.rar: codes of double-difference seismic tomography</p> <p>catalog.dat: earthquake phase catalog used in the DD tomography</p> <p>station.dat: station coordinates of the seismic network </p> <p>MOD: grids in the initial Vp and Vp/Vs models</p> <p>Vp_model.dat: inverted 3-D Vp model</p> <p>Vs_model.dat: inverted 3-D Vs model</p> <p>VpVs_model.dat: inverted 3-D Vp/Vs model</p> <p>earthquake.reloc: relocations of the earthquakes</p>
Differential transcriptomic regulation in sweet orange fruit (Citrus sinensis L. Osbeck) following dehydration and rehydration conditions leading to peel damage
<p>Water stress is the most important environmental agent causing crop productivity and quality losses globally. In citrus, water stress is a main driver of fruit peel disorders that impact quality and marketability. An increasingly present postharvest peel disorder is non-chilling peel pitting (NCPP). NCPP is manifested as collapsed areas of flavedo randomly scattered on the fruit and its incidence increases due to abrupt increases in environmental relative humidity (RH) during postharvest fruit manipulation. In this work we have used a custom-made cDNA microarray containing 44k unigenes from <em>Citrus sinensis</em> (L. Osbeck) covering for the first time the whole genome from this species, to study transcriptomic responses of mature citrus fruit to water stress. We have compared global gene expression profiles of flavedo from Navelate oranges subjected to severe water stress with those of fruit subjected to rehydration stress provoked by changes in RH during postharvest, which enhances the development of NCPP. Our results show that NCPP is a complex physiological process that shares molecular responses with those from prolonged dehydration in fruit, but the damage associated to NCPP may be explained by unique features of rehydration stress at the molecular level, including membrane disorganization, cell wall modification, and proteolysis.</p>
Terrestrial green algae show higher tolerance to dehydration than do their aquatic sister-species: Raw data and analysis files
<p>Diverse algae possess the ability to recover from extreme desiccation without forming specialized resting structures. Green algal genera such as <i>Tetradesmus</i> (Sphaeropleales, Chlorophyceae) contain temperate terrestrial, desert, and aquatic species, providing an opportunity to compare physiological traits associated with the transition to land in closely related taxa. We subjected six species from distinct habitats to three dehydration treatments varying in relative humidity (RH 5%, 65%, 80%) followed by short- and long-term rehydration. We tested the capacity of the algae to recover from dehydration using the effective quantum yield of photosystem II as a proxy for physiological activity. The degree of recovery was dependent both on the habitat of origin and the dehydration scenario, with terrestrial, but not aquatic species, recovering from dehydration. Distinct strains of each species responded similarly to dehydration and rehydration, with the exception of one aquatic strain that recovered from the mildest dehydration treatment. Cell ultrastructure was uniformly maintained in both aquatic and desert species during dehydration and rehydration, but staining with an amphiphilic styryl dye indicated damage to the plasma membrane from osmotically-induced water loss in the aquatic species. These analyses demonstrate that terrestrial <i>Tetradesmus</i> possess a vegetative desiccation tolerance phenotype, making these species ideal for comparative omics studies.</p>
Utility of Ultrasound Assessment of the Inferior Vena Cava in Patients With Sepsis and Dehydration
ClinicalTrials.gov study NCT02568189. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of Acute Mild Dehydration on Blood Pressure Control
ClinicalTrials.gov study NCT03560869. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Efficacy of Ostom-i Alert System at Decreasing Dehydration Related Complications
ClinicalTrials.gov study NCT02694757. IPD Sharing: NO. Countries: 1. Publications: 2.
High Purity Type I Collagen Based Skin Substitute Vs Dehydrated Human Amnion/Chorion Membrane in Treatment of DFUs
ClinicalTrials.gov study NCT06470087. IPD Sharing: NO. Countries: 1. Publications: 5.
Analysis of Sweat Secretion and Body Dehydration Monitoring
ClinicalTrials.gov study NCT03229109. IPD Sharing: NO. Countries: 1. Publications: 5.
Intravenous (IV) Solutions for Dehydration in Children With Gastroenteritis
ClinicalTrials.gov study NCT01234883. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Corticosterone and immune responses to dehydration in squamate reptiles
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