Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12,751
datasets available to search
ShareScore release 0.9.0
Dataset results
12,751 results for “blood”
Fig. 1 in Uncovering Trypanosoma spp. diversity of wild mammals by the use of DNA from blood clots
Fig. 1. Methodological algorithm employed for the identification of trypanosomes in blood clot samples.
Fig. 3 in New record of a blood-feeding terrestrial leech, Haemadipsa rjukjuana Oka, 1910 (Haemadipsidae, Arhynchobdellida) on Heuksando Island and possible habitat estimation in the current and future Korean Peninsula using a Maxent model
Fig. 3. Current (A and F) and future distribution models (B-E, G-J) for Haemadipsa rjukjuana in Korea. Dark gray represents over 0.5 MaxEnt value (suitable habitat) and light gray represents below 0.5 (unsuitable habitat). A is projected to the current climate conditions (2020), and F was built with the restricted spatial area between Heuksando Island and Gageodo Island. B-E are projections of the Maxent model to SSP585 of GISS-E2-1 climate scenarios by NASA and G-J were SSP585 of INM-CM4-8 scenarios by The Institute of Numerical Mathematics. B-E and G-J are respectively 2040, 2060, 2080, and 2100.
Fig. 2 in New record of a blood-feeding terrestrial leech, Haemadipsa rjukjuana Oka, 1910 (Haemadipsidae, Arhynchobdellida) on Heuksando Island and possible habitat estimation in the current and future Korean Peninsula using a Maxent model
Fig. 2. Projection of MaxEnt Haemadipsa rjukjuana distribution model from Heuksando Island and Gageodo Island to the current climate condition of South Korea. Red color (lower value) represents less suitable habitats and blue (higher value close to 1.0) represents suitable habitats for H. rjukjuana.
Fig. 1 in New record of a blood-feeding terrestrial leech, Haemadipsa rjukjuana Oka, 1910 (Haemadipsidae, Arhynchobdellida) on Heuksando Island and possible habitat estimation in the current and future Korean Peninsula using a Maxent model
Fig. 1. The map of study sites (inset) and the Korean Peninsula. Haemadipsa rjukjuana was identified from the regions shaded in gray.
ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans
<p>This dataset contains all processed data used in analyses reported in the manuscript, ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans. This project is part of a larger study focused on investigating the role of stress, discrimination, genetic variants, and other sociocultural factors in hypertension in African Americans.</p> <p> </p> <p> </p> <p>Variable Names and Descriptions:</p> <p>HHID: Participant Identification number</p> <p>sbp-10: Average of two Systolic Blood Pressure readings without 10 point correction for blood pressure medication (mmHg)</p> <p>sbp: Average of two Systolic Blood Pressure readings with 10 point correction for blood pressure medication (mmHg)</p> <p>dbp-5: Average of two Diastolic Blood Pressure readings without 5 point correction for blood pressure medication (mmHg)</p> <p>dbp: Average of two Diastolic Blood Pressure readings with 5 point correction for blood pressure medication (mmHg)</p> <p>ACE.Genotype: ACE genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>WNK1.Genotype: WNK1 Genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>age: age (years)</p> <p>sex: sex (Male =1, Female = 2)</p> <p>bpmedtake: Whether the participant uses blood pressure medication</p> <p>bmi: Body Mass Index (calculated from height and weight)</p> <p>ALTER GENDER|Answer:Male|Value:0|Count: Number of male alters (social network members)</p> <p>Alter Gender Male: Percentage of alters that are male</p> <p>ALTER GENDER|Answer:Female|Value:1|Count: Number of female alters (social network members)</p> <p>Alter Gender Female: Percentage of alters that are female</p> <p>Closeness_Mean: Average closeness centrality of the network</p> <p>Between_Mean: Average between-ness centrality of the network</p> <p>percentage of family in structural percentage: Percentage of central network positions occupied by family members</p> <p>relationship max close family: The most close (centrally) network member is a family member</p> <p>Average distance: Average distance of individuals in a network</p> <p>Hap B: ACE gene haplotypes</p> <p> </p>
Time-averaged simulation results and in vivo measurements to show the impact of red blood cells on the flow field in the cortical microvasculature
<p>The dataset contains 5 files. 4 of them are time-averaged results of blood flow simulations with discrete red blood cell (RBC) tracking in realistic microvascular networks. The 5th file contains median values of RBC velocity measurements at capillary bifurcations in the somatosensory cortex of the mouse.</p> <p>Further notes on the simulation results:<br> - The realistic microvascular networks are from the mouse parietal cortex and have first been published in Blinder et al., 2013, Nature Neuroscience (<a href="https://doi.org/10.1038/nn.3426">https://doi.org/10.1038/nn.3426</a>).<br> - The numerical model to simulate blood flow in realistic microvascular networks has been described in Schmid et al., 2017, PLOS Computational Biology (<a href="https://doi.org/10.1371/journal.pcbi.1005392">https://doi.org/10.1371/journal.pcbi.1005392</a>).<br> - MVN1 and MVN2 stands for microvascular network 1 and 2, respectively.<br> - wRBCs and wpPs stands for 'with red blood cells' and 'with passive particles'. These terms describe two different numerical models: The wRBC-model accounts for all RBC related flow phenomena. The wpP neglects the phase-separation and the Fahraeus-Lindqvist effect, i.e. RBCs and flow are decoupled. Further details are available from Schmid et al. (2019, <a href="https://doi.org/10.1371/journal.pcbi.1007231">https://doi.org/10.1371/journal.pcbi.1007231</a>)</p> <p><strong>File format: </strong>pickle (Python)</p> <p><strong>Files 1 - 4 </strong>(Time-averaged simulation results):<br> Filenames: MVN1_wpPs.tar.bz2, MVN2_wpPs.tar.bz2, MVN1_wRBCs.tar.bz2, MVN2_wRBCs.tar.bz2</p> <p>Each compressed folder contains two files:<br> <br> edgesDict.pkl: dictionary with edge/vessel related data: </p> <ul> <li>flow: Flow rate in vessel [um^3/ms]</li> <li>length: Vessel length [um] (Tortuosity is considered)</li> <li>htt: Tube hematocrit in vessel [-]</li> <li>diameter: Effective vessel diameter [um]</li> <li>connectivity: Vertex indices, e.g. start and end vertex of the corresponding vessel</li> </ul> <p>verticesDict.pkl: dictionary with vertex/bifurcation related data:</p> <ul> <li>index: Index of the current vertex </li> <li>coords: Coordinates to describe the position of the vertex [um]</li> <li>pressure: Pressure at the vertex [mmHg]</li> </ul> <p> </p> <p><strong>File 5</strong> (in vivo RBC velocity measurements):<br> Filename: measurementDict.pkl</p> <p>keys:</p> <ul> <li>divergent_d1: divergent bifurcation, RBC velocity measurement in daughter vessel 1</li> <li>divergent_d2: divergent bifurcation, RBC velocity measurement in daughter vessel 2</li> <li>convergent_m1: convergent bifurcation, RBC velocity measurement in mother vessel 1</li> <li>convergent_m2: convergent bifurcation, RBC velocity measurement in mother vessel 2</li> </ul> <p><br> Data structure: list of list,<br> e.g. daughter vessel 1:<br> [[bif.1 - measure.1, bif.1 - measure.2, bif.1 - measure.3], [bif.2 - measure.1, bif.2 - measure.2, bif.2 - measure.3],...]<br> bif.: bifurcation, measure.: measurement.<br> The order of bifurcations is the same for 'divergent_d1' and 'divergent_d2' (and for 'convergent_m1' and 'convergent_m2'). </p> <p> </p>
High Resolution Retinal Blood Vessels Datasets of Diabetic Retinopathy Patients
<p>This dataset contains 89 high resolution image files of blood vessels extracted from publicly available retina images available in DIARETDB1</p>
Data underpinning "Coupling between cerebral blood flow and cerebral blood volume: Contributions of different vascular compartments"
<p>The data in this archive was acquired to investigate the coupling between cerebral blood flow and cerebral blood volume across different vascular compartments. These results will form the basis of a forthcoming publication. Please reference this dataset (version v1.1.0) if you use it in your work. Wesolowski R, Blockley NP, Driver ID, Francis ST, Gowland PA. Data underpinning "Coupling between cerebral blood flow and cerebral blood volume: Contributions of different vascular compartments". Zenodo 2018. doi: 10.5281/zenodo.1411018. </p> <p>This dataset contains measurements of the haemodynamic responses of different compartments to a visual stimulus (8Hz red LED goggles, 19.2s ON, 40.8s OFF). Time course data are cycle averaged for the following haemodynamic properties;</p> <ol> <li>Arterial cerebral blood volume (CBVa) measured using Look-Locker Flow-sensitive Alternating Inversion Recovery (LL-FAIR) sensitised to CBVa.</li> <li>Cerebral blood flow (CBF) measured using Look-Locker Flow-sensitive Alternating Inversion Recovery (LL-FAIR) sensitised to CBF.</li> <li>Total cerebral blood volume (CBVtot) measured using bolus injections of a Gadolinium based contrast agent combined with T2* weighed gradient echo EPI.</li> </ol> <p>In addition, weighted mean and standard deviation of the changes in these parameters are presented using time windows of 9.6–19.2s and 40.8–60s for ON and OFF, respectively. Weighting is performed with respect to the number of voxels present in each of the subjects regions of interest.</p> <p>Time course data were extracted from two different regions of interest;</p> <ol> <li>ROI<sub>CBF</sub>: defined using a CBF localiser</li> <li>ROI<sub>COMMON</sub>: defined using the overlap of CBF, CBV<sub>a</sub> and CBV<sub>tot</sub> localisers</li> </ol> <p>Furthermore, the transit times for CBF and CBVa were estimated for an average stimulus cycle and mean values extracted using time windows of 9.6–19.2s and 40.8–60s for ON and OFF, respectively. These data were extracted from ROI<sub>CBF</sub>.</p> <p>Changes</p> <p>- Addition of propagation of uncertainty for CBVv and the Grubb constants alpha_tot and alpha_a.</p> <p> </p>
Allocation of rhodamine-loaded nanocapsules from blood circulatory system to adjacent tissues assessed in vivo by fluorescence spectroscopy
<p>Modern fluorescent modalities play an important role in the functional diagnostic of various physiological processes in living tissues. Utilizing the fluorescence spectroscopy approach we observe the circulation of fluorescent-labelled nanocapsules with rhodamine tetramethylrhodamine in a microcirculatory blood system. The measurements were conducted transcutaneously on the surface of healthy Wistar rat thighs in vivo. The administration of the preparation capsule suspension with a rhodamine concentration of 5 mg kg−1 of the animal weight resulted in a two-fold increase of fluorescence intensity relative to the baseline level. The dissemination of nanocapsules in the adjacent tissues via the circulatory system was observed and assessed quantitatively. The approach can be used for the transdermal assessment of rhodamine-loaded capsules in vivo.</p>
Figures 3-4 in Blood metabolites as predictors to evaluate the body condition of Neopelma pallescens (Passeriformes: Pipridae) in northeastern Brazil
Figures 3-4. Spearman's correlation between Body Condition Index (BCI) and glucose concentration for breeding (3) (N = 28) and non-breeding (4) (N = 46) individuals of N. pallescens in Reserva Biológica de Guaribas, PB. The breeding period of N. pallescens started at the end of July (P1) and climaxed in January (P3). It occurred throughout Figure 2. Monthly samples sizes of captured individuals of N. palles- the rainy and dry seasons. Glucose concentrations showed cens in Reserva Biológica de Guaribas, PB. Recaptured individuals significant variation during the developmental phases of brood are not included. patches with a higher concentration in P3 (Fig. 5) (ANOVA, F = 5.39, p = 0.01). Tukey's test showed significant values only The glucose concentration was negatively correlated with between P1 and P3 (Tukey's Test, P2-P1: p = 0.76, P3-P1 = 0.01, body condition (Table 1). Further analyses showed that the glu- P3-P2: p = 0.05).
Figure 6 in Blood-feeding behavior of Anopheles species (Diptera: Culicidae) in the district of Ilha de Santana, state of Amapá, eastern Brazilian Amazon
Figure 6 Absolute frequency by time of the main species of Anopheles captured in collections to evaluate anthropophilic and zoophilic behavior in the district of Ilha de Santana, municipality of Santana, state of Amapá; A) Anopheles albitarsis s.l.; B) Anopheles braziliensis; C) Anopheles darlingi; D) Anopheles nuneztovari s.l. Significant difference between the number of anthropophilic and zoophilic individuals was observed only for A. albitarsis s.l. (Student's t test [3] = -2.67; p = 0.03). Graph with standard deviation bars.
Figure 5 in Blood-feeding behavior of Anopheles species (Diptera: Culicidae) in the district of Ilha de Santana, state of Amapá, eastern Brazilian Amazon
Figure 5 Species of Anopheles captured in collections to evaluate anthropophilic and zoophilic behavior during 24 months in the district of Ilha de Santana, municipality of Santana, state of Amapá. Graph with standard deviation bars.
Figure 4 in Blood-feeding behavior of Anopheles species (Diptera: Culicidae) in the district of Ilha de Santana, state of Amapá, eastern Brazilian Amazon
Figure 4 Species of Anopheles captured in collections to evaluate anthropophilic and zoophilic behavior by month, during 24 months in the district of Ilha de Santana, municipality of Santana, state of Amapá. A) Anopheles albitarsis s.l.; B) Anopheles braziliensis; C) Anopheles darlingi; D) Anopheles nuneztovari s.l. Graph with standard deviation bars.
Figure 1 in Blood-feeding behavior of Anopheles species (Diptera: Culicidae) in the district of Ilha de Santana, state of Amapá, eastern Brazilian Amazon
Figure 1 Map indicating the location of the district of Ilha de Santana, state of Amapá, Brazil. In right corner is the smaller map of Brazil showing the localization of the State of Amapá (in red); Below map of the State of Amapá showing the study area (red circle). Satellite image of the district of Ilha de Santana with the 52 collection sites indicated according to the three collection categories (For interpretation of the references to color in this figure legend).
Figure 5 in Temporal variation in the reproductive pattern of blood cockle Anadara antiquata from Pakistan (northern Arabian Sea)
Figure 5. Temporal variation in gonad index (GI) of male and female A. antiquata from Phitti Creek and Sonmiani.
Figure 3 in Temporal variation in the reproductive pattern of blood cockle Anadara antiquata from Pakistan (northern Arabian Sea)
Figure 3. Photomicrographs of A. antiquata: A–D: stages of spermatogenesis; E–H: stages of oogenesis. A, E: Developing; B, F: Ripe; C, G: Spawned out; D, H: Resorbing. Abbreviations: F - Follicle, Sc - Spermatocytes; St - Spermatids; Sz - Spermatozoa; Ef - Empty follicle; Ct - Connective tissue; Og - Oogonia; Pvo - Previtellogenic oocyte; Vo - Vitellogenic oocyte; N - Nucleus; n - nucleolus; Mo - Mature oocyte; Ao - Atretic oocyte.
Figs. 5–8 in First elucidation of a blood fluke (Electrovermis zappum n. gen., n. sp.) life cycle including a chondrichthyan or bivalve
Figs. 5–8. Sporocyst and cercaria of Electrovermis zappum Warren and Bullard n. gen., n. sp. (Digenea: Aporocotylidae) infecting variable coquina clam, Donax variabilis Say, 1822 (Bivalvia: Cardiida: Donacidae). (5) Sporocyst showing four cercarial bodies among several germ bodies, ventral view. (6) Photo of live sporocyst showing three germ bodies (*). (7) Body of live cercaria, ventral view. (8) Body of mounted cercaria (USNM No. 1578578–1578583), ventral view. Mouth (mo), concentric spines (cs), dorsal fin fold (df), penetration gland (pg), lateral body spines (s), gonadal anlage (ga), excretory duct (ed), tail stem (ts), nuclei (n), and furca (f).
Fig. 6 in Differences in infection patterns of vector-borne blood-stage parasites of sympatric Malagasy primate species (Microcebus murinus, M. ravelobensis)
Fig. 6. Phylogenetic tree of 33 filarial nematode species constructed on the basis of partial COI sequences using the Maximum Likelihood method. The percentage of replicate trees in which the associated species clustered together in the bootstrap test (1000 replicates) is shown next to the branches. Branch lengths is measured in the number of substitutions per site. Thelazia callipaeda was included as an outgroup. The sequence of the present study is framed in red.
Fig. 5 in Differences in infection patterns of vector-borne blood-stage parasites of sympatric Malagasy primate species (Microcebus murinus, M. ravelobensis)
Fig. 5. Phylogenetic tree of Onchocercidae species constructed on the basis of partial ITS1 sequences using the Maximum Likelihood method. The percentage of replicate trees in which the associated species clustered together in the bootstrap test (1000 replicates) is shown next to the branches. Branch lengths is measured in the number of substitutions per site. The sequences of the present study are framed in red. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Differences in infection patterns of vector-borne blood-stage parasites of sympatric Malagasy primate species (Microcebus murinus, M. ravelobensis)
Fig. 3. Number of samples (blood smears) per month. Microfilaria positive samples are shown in dark blue for M. murinus and dark brown for M. ravelobensis, microfilaria negative samples in light blue for M. murinus and light brown for M. ravelobensis. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
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.