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.
5,794
datasets available to search
ShareScore release 0.9.0
Dataset results
5,794 results for “exposures”
Fig. 3 in Comparison of the modified agglutination test and real-time PCR for detection of Toxoplasma gondii exposure in feral cats from Phillip Island, Australia, and risk factors associated with infection
Fig. 3. Predicted lines of fit for the multivariable logistic regression model plotted as probability of Toxoplasma gondii qPCR positivity in feral cats on Phillip Island (Victoria) versus body weight for each season. Dashed lines show 95% confidence intervals.
Fig. 1 in Comparison of the modified agglutination test and real-time PCR for detection of Toxoplasma gondii exposure in feral cats from Phillip Island, Australia, and risk factors associated with infection
Fig. 1. Location and Toxoplasma gondii infection status, as detected by real-time PCR (qPCR), of feral cats trapped on Phillip Island (Victoria) from July 2016 to December 2017. Map shows the distribution of different location types (Park, Agricultural, Residential) used in multivariable regression analysis. A circular spread of points around a location marked with 'x' indicates multiple animals were sampled at the same site (i.e. same GPS coordinates). Red = T. gondii qPCR positive, white = T. gondii qPCR negative. Map created using Quantum GIS, version 3.8. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Rickettsiae exposure related to habitats of the oriental house rat (Rattus tanezumi, Temminck, 1844) in Salaya suburb, Thailand
Fig. 1. The oriental house rat (Rattus tanezumi) trapped in a location of Salaya suburb, near Bangkok shown in a map of Thailand (scale bar; 200 km) and the satellite view of Salaya suburb (scale bar; 2 km); showing six trap site of three distinct oriental house rat habitats including I) an agriculture field (red pin): fruit tree (a) and paddy field (b); II) an animal shelter (yellow pin): dog shelter (c) and horse stable (d) and III) a human residence (green pin): residential area (e) and fresh market (f). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1. A. A in Comparison of exposure ages and spectral properties of rock surfaces in steep, high alpine rock walls of Aiguille du Midi, France
Fig. 1. A. A slab from Maysville, KY (CMC IP50706) with a drilled specimen of the stylophoran mitrate Enoploura popei Caster, 1952. The hole indicated by an arrow. B. Close up of the drilled specimen. C. Detail of the borehole.
Fig. 2 in Comparison of exposure ages and spectral properties of rock surfaces in steep, high alpine rock walls of Aiguille du Midi, France
Fig. 2. Horizontal boring on the slab from Maysville, KY (CMC IP50706). A. Overlapping burrows in the shell of the brachiopod Rafinesquina. B. Burrows in a bryozoan. Scale bars 10 mm.
Figure 5 in Predator exposure and size-related variation in web-building and web-decorating behavior in Argiope appensa
Figure 5. Frequency distribution of cruciate-patterned web decorations from spiders in Rota and Guam. Stacks represent size class of spiders.
Figure 1 in Predator exposure and size-related variation in web-building and web-decorating behavior in Argiope appensa
Figure 1. Web decoration in A. appensa: (A) close-up of web decoration; (B) linear/ diagonal pattern; (C) cruciate pattern.
Figure 3 in Predator exposure and size-related variation in web-building and web-decorating behavior in Argiope appensa
Figure 3. Variation in web-building behavior in A. appensa between locations and between spider size class categories, (A) web diameter, SNK: small <medium <large; and (B) web decoration length, SNK: small = medium <large. Dashed lines represent the mean for each location with all the size classes pooled.
Fig. 4 in Filtration and respiration responses of mussels (Mytilus edulis) to trematode parasite infections (Renicola roscovita) and transient heat exposure
Fig. 4. Filtration rate in relation to infection intensity (metacercariae mussel– 1) for small (A) and large (B) mussels. Generalized Additive Mixed Models (GAMMs) predictions (lines) and 95 % CIs (shaded area) are conditioned on the average time points. Each point represents filtration measurement per minute and each stratum shows temporal filtration of one mussel.
Fig. 3 in Filtration and respiration responses of mussels (Mytilus edulis) to trematode parasite infections (Renicola roscovita) and transient heat exposure
Fig. 3. Linear mixed models of filtration and respiration rates of small (A, C) and large (B, D) M. edulis, either uninfected (light blue) or infected (light pink) with Renicola roscovita under a constant temperature of 17 ◦C. The bottom red line in the subplot B indicates the interval of significant difference between smoothers. The shaded area represents 95 % CIs. Each point represents the filtration or respiration rate measured minutely. The sample size for each group of small or large mussels was 9–18 and 9–16 for infected and uninfected, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Filtration and respiration responses of mussels (Mytilus edulis) to trematode parasite infections (Renicola roscovita) and transient heat exposure
Fig. 2. Post-warming scaled mussel filtration (A) and respiration (B) in relation to infection intensity. Generalized Additive Mixed Models (GAMMs) predictions (lines) and 95 % CIs (shaded area) are conditioned on the average post-warming time points. Individual points represent filtration or respiration measured every 5 min and each stratum represents measurements of one mussel.
Fig. 1. Mussel filtration and respiration responses during Experiment 1 in Filtration and respiration responses of mussels (Mytilus edulis) to trematode parasite infections (Renicola roscovita) and transient heat exposure
Fig. 1. Mussel filtration and respiration responses during Experiment 1. Generalized Additive Mixed Models (GAMMs) of responses of small size mussels uninfected and infected with Renicola roscovita during exposure to a constant mild temperature (for 5 h) followed by a 24-h thermal fluctuation. Each point represents filtration or respiration measurement per 5 min (shaded areas represent 95 % CIs). Sample size for each group was 8 and 11 for infected and uninfected, respectively. The negative values recorded during the metabolic depression phase are due to extra random variation in the measurement, variability between individuals and the white noise of oximeter device.
Fig. 3 in The threat of pesticide and disease co-exposure to managed and wild bee larvae
Fig. 3. Pesticide research bias across bee genera depending on pesticide type based on Web of Science searches. The number of studies per search term is indicated for each genus with at least 10 studies across search terms; Understudied is a cumulative group including genera which contain less than 10 studies; Unexplored is a cumulative group including genera which have no published papers for any pesticide exposure category. Warmer colours are used to indicate a higher number of studies related to a genus for the corresponding pesticide search term, while colder colours indicate a lower number of studies found. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in The threat of pesticide and disease co-exposure to managed and wild bee larvae
Fig. 4. Brood pathogens studies per bee genera found from Web of Science searches using search terms "brood disease", "brood pathogen", "brood virus", "larvae disease", "larvae pathogen" and "larvae virus" across bee genera. Red squares indicate that a pathogen on the x-axis has been found to infect at least one species in the bee genus corresponding to its position in the phylogeny shown on the y-axis; yellow squares indicate that the pathogen on the x-axis has been found in individuals from at least one species in the genus on the y-axis but no symptoms were reported in the studies; dark grey squares indicate that the pathogen on the x-axis has been tested for in at least one species in the genus corresponding on the yaxis, however has not been found; white squares indicate that the searches found no studies where any bee species of the genus on the y-axis were tested for in the corresponding pathogens on the x-axis. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in The threat of pesticide and disease co-exposure to managed and wild bee larvae
Fig. 2. Proportion of results per search term across bee genera on the Web of Science search engine (n = the total number of studies corresponding to each search term). Search terms related to brood disease (A) and pesticide exposure (B) are both compared to species diversity at the genus level. Genera with less than 5 studies in any brood disease search term (A) and less than 10 studies across any pesticide exposure search term (B) have been classified as 'Understudied' (brown) and grouped. Genera with no studies related to any brood disease search term (A) and no studies related to any pesticide exposure search term (B) have been classified as 'Unexplored' (grey) and grouped. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in The threat of pesticide and disease co-exposure to managed and wild bee larvae
Fig. 1. Flowers contaminated with brood pathogens and pesticides can lead to simultaneous exposure to pesticides and brood pathogens from flowers in adult foraging bees (A). This leads to brood being co-exposed to the stressors via food provisioning (B). Pesticides may increase larval mortality from brood infections directly through compromised immunocompetence (C), and/or indirectly through manipulating microbial communities and compromising food provisions from adult bees (D) (Icons8, 2022).
An Assessment of the Ocular Toxicity of Two Major Sources of Environmental Exposure
<p>These data contain information on chemicals released in to the air from burn pits in Iraq (waste disposal areas for US military bases) and the 2023 Ohio train derailment in East Palestine. The goals of the study were to 1) predict the effects of exposure to these chemicals on the ocular surface and 2) to call attention to the relationship between environmental events and long-term damage to the surface of the eye—in particular, dry eye disease, which is a known result of workplace chemical exposures. The study employed in silico methods through the ACD Labs Percepta platform, using data from the European Chemical Inventory and the Registry of Toxic Effects of Chemical Substances to model the chemicals’ probability of ocular irritation. Variables include the names of compounds identified from the burn pits and the train derailment, along with their chemical formulas, simplified molecular input line entry system (abbreviated to SMILES), and probability of causing eye irritation.</p>
FIGURE 4 in A typical enzyme activity for glutathione conjugation indicates exposure of pacu to pollutants
FIGURE 4 |GST specific activities in kidney cytosol from Piaractus mesopotamicus injected with benzo[a]pyrene (15 mg kg-1). Assays were carried out with 1-chloro-2,4-dinitrobenzene (CDNB), ethacrynic acid (ETHA) or 2-dichloro-4-nitrobenzene (DCNB) 7 and 14 days after the injection. Bars represent the means ± S.E.M. of determinations from nine fish injected with corn oil (clear) or benzo[a]pyrene (dark grey). Significant different from controls are indicated as *(P <0.05) and ***(P <0.001).
FIGURE 3 in A typical enzyme activity for glutathione conjugation indicates exposure of pacu to pollutants
FIGURE 3 |GST specific activities in liver cytosol from Piaractus mesopotamicus injected with benzo[a]pyrene (15 mg kg-1). Assays were carried out with 1-chloro-2,4-dinitrobenzene (CDNB), ethacrynic acid (ETHA) or 2-dichloro-4-nitrobenzene (DCNB) 7 and 14 days after the injection. Bars represent the means ± S.E.M. of assays from nine fish injected with corn oil (clear) or benzo[a]pyrene (dark grey). Significant different from controls are indicated as ***(P <0.001).
FIGURE 2 in A typical enzyme activity for glutathione conjugation indicates exposure of pacu to pollutants
FIGURE 2 |GST specific activities in kidney cytosol from Piaractus mesopotamicus injected with methyl parathion (8 mg kg-1). Assays were carried out with 1-chloro-2,4-dinitrobenzene (CDNB), ethacrynic acid (ETHA) or 2-dichloro-4-nitrobenzene (DCNB) at 24, 48 and 96 hours after the injection. Bars represent the means ± S.E.M. of assays from five fish injected with corn oil (clear) or methyl parathion (dark grey).
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.