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4,600 results for “vascular”

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edi60/100

Vascular Flora Surveys of Permanent Plots at the Harvard Farm at Harvard Forest since 2015

The objectives of this study were to: (1) Determine the species richness and cover of vascular flora in 27 permanent plots at the Harvard Farm (established in HF236). (2) Track any changes in species richness and species dominance in the plant communities at each plot over time. (3) Observe any changes in invasive species richness and cover over time. (4) Identify differences between plant community composition of plots in constant grazing, rotational grazing, and mowing areas. These data were collected by Harvard Forest interns and may include some misidentifications, but they should be considered accurate for larger scale analyses of changes in the density of growth forms and invasive species. For more accurate species-level information, please see data collected every five years by Glenn Motzkin (HF236 with data from 2014 and 2019).

openCC0Dec 2023View details →

edi56/100

Vascular Flora of the Harvard Farm at Harvard Forest 2014

The objectives of this study were to: (1) Inventory the vascular flora of the former Petersham Country Club (now the Harvard Farm). (2) Collect voucher specimens for the HF Herbarium of species that were not previously documented from Harvard Forest, or that were found historically at HF but were not recorded in 2004–2007 by Jenkins et al. (2008). (3) Establish and sample a series of permanent plots to characterize current vegetation composition, and to enable evaluation of vegetation change over time. (4) Sample soils within permanent plots to document initial conditions and to facilitate future work on soil dynamics and ecosystem processes.

openCC0Dec 2023View details →

edi56/100

Vascular Plant Species at Harvard Forest 1992

This dataset contains a list of vascular plant species found in 269 22.5 x 22.5 m plots sampled in the 1992 Prospect Hill vegetation survey. The species list was compiled on 5 May 1993.

openCC0Dec 2023View details →

zenodo52/100

Vascular Territory template and atlases in MNI space

Data Sixteen subjects (mean age (sd): 69.6 (8.2); 37.5% female) were recruited to generate a high-resolution template. The cohort consists of twelve stroke-free, non-demented patients with the sporadic form of cerebral amyloid angiopathy (CAA), and similarly-aged healthy controls (n=4). Each participant underwent high-resolution MRI with a Siemens Magnetom Prisma 3T scanner (using a 32-channel head coil) as part of a separate study. The standardized protocol included a Multiecho T1-weighted (voxel size: 1x1x1 mm3; Repetition Time [TR]: 2510 ms), a 3D-FLAIR (voxel size: 0.9x0.9x0.9 mm3; TR: 5000 ms; TE: 356 ms), and a T2-weighted Turbo Spin Echo (voxel size: 0.5x0.5x2.0 mm3; TR: 7500 ms; TE: 84 ms) sequence. Scans were manually assessed to ensure no gross pathology was present, such as hemorrhage or silent brain infarcts. Template and territorial map creation We employed Advanced Normalization Tools (ANTs) for image processing (Avants et al., 2010, 2011) for creating a brain template based on multimodal information using T1, T2 and 3D-FLAIR sequences. After template creation, we smoothed the resulting templates (FSL; Gaussian smoothing, sigma = 1) and registered the resulting templates into MNI space, again using ANTs (Avants et al., 2011). Vascular territories were outlined on the right hemisphere in the T1-weighted atlas image and contain anatomically validated ACA, MCA, and PCA territories supratentorially. The right hemispheric map was then mirrored onto the left hemisphere to create a full-brain vascular territory map, which was manually assessed and corrected where necessary.   For more details, please see the original publication that utilized the template. If you utilize this template, please also cite Schirmer, Markus D., et al. "Spatial signature of white matter hyperintensities in stroke patients." Frontiers in neurology 10 (2019): 208. <a href="https://doi.org/10.3389/fneur.2019.00208">https://doi.org/10.3389/fneur.2019.00208</a>   Files FLAIR template: caa_flair_in_mni_template_smooth.nii.gz FLAIR template after brain extraction and intensity normalization: caa_flair_in_mni_template_smooth_brain_intres.nii.gz T1 template: caa_t1_in_mni_template_smooth.nii.gz 27.7 Mb T2 template: caa_t2_in_mni_template_smooth.nii.gz 27.7 Mb Vascular territory map: mni_vascular_territories.nii.gz

opencc-by-4.0Mar 2019View details →

edi52/100

Species richness of vascular plants and bryophytes in nine grassland sites (Europe and California collected in 2013-2016)

We sampled vascular plants (VP) and bryophytes (non-vascular plant; NVP) 1×1 m experimental plots in nine sites belonging to the Nutrient Network. Three sites were in California, two in Finland and UK and one in Germany and Switzerland. The data were collected to compare the responses of NVPs and VPs to nutrient addition and grazing exclusion treatments. The NVP and VP cover sampling was conducted in March-August 2016, except for heron.uk and rook.uk, which had been sampled for VPs in 2013. NVPs were mostly identified to species, but in absence of necessary diagnostic characters (capsules, other reproductive organs, distinctive gametophytic features), some specimens were identified at morphospecies group, subgenus, or genus level. We calculated three plant diversity indices for NVPs, VPs and total (NVPs and VPs combined) in each plot. First, species richness (S) is the number of species per 1 m2 for NVPs and VPs. For plots having no NVPs, NVP richness is zero. Second, for plots having at least one NVP, we calculated Inverse Simpson’s index of diversity (referred to as species diversity), which is equivalent to the Probability of Interspecific Encounter or Effective Number of Species (ENSPIE). Third, we calculated Simpson’s evenness (E = ENSPIE/S; referred to as evenness), which was expected to reflect changes in species’ dominance. We also sampled aboveground plant biomass at peak biomass of vascular plants (in May- August, depending on local site level characteristics) by clipping at ground level and removing all aboveground vegetation (live and dead) from two 0.1 × 1 m strips, sorting the current year’s VP and NVP biomass from the previous year’s biomass (dead litter), drying the biomass to a constant mass at 60 °C, and weighing it to the nearest 0.01 g. Except for two sites (heron.uk and rook.uk), we also measured photosynthetically active radiation (PAR) at the ground surface and above grassland canopy at time of peak biomass and calculated the proportion of tra

openCC (other)Apr 2025View details →

edi52/100

Cover and frequency of biological soil crust community types, moss species, vascular plants, and abiotic land surface features, on gypsum & non-gypsum soils from the Chihuahuan and Mojave Deserts in 2023

This dataset contains raw and calculated percent cover and frequency data for biological soil crust (hereafter biocrust) functional groups, vascular plant functional groups, and abiotic land surface features on and off gypsum soils in the northern Chihuahuan and eastern Mojave Deserts. Abundance data were obtained from 20 study sites total, 10 located on soils derived from gypsum parent material and 10 located on soils derived from non-gypsum parent materials. Sites were grouped into 10 pairs, in which every gypsum site was partnered with a non-gypsum site located in the same region. Apart from soil type, partnered-site characteristics (topography, climate, elevation, slope, aspect, and presence of biocrusts) were held relatively constant. At each site, cover and frequency assessments were made using the line-point intercept method (LPI) and frequency quadrats (1.0 m^2), respectively. Biocrust functional groups included the following crusts: lichen, moss, incipient algal, light algal, dark algal, unknown photosynthetic crust, and vagrant cyanobacteria. Vascular plant categories included: perennial forbs, perennial graminoids, annual forbs, annual graminoids, subshrub, shrub, Yucca, and cacti. Abiotic land surface features included: woody litter, herbaceous litter, bare soil, rock, bedrock, and animal feces. Moss crusts identified within cover and frequency analyses were sampled, and classified to species level via microscopy. The resulting percent cover and frequency data was used to understand differences in biocrust and moss species abundance and diversity on and off gypsum soils; furthermore, how biocrust and moss species abundance was associated with the measured environmental variables. Soil physical and chemical data from this study can be accessed at knb-lter-jrn.210616002. This study and dataset are complete.

openCC (other)Oct 2024View details →

zenodo48/100

Histological Dataset for Microvascular Segmentation of Tissue-Engineered Vascular Grafts

Objectives: The pursuit of understanding vascular tissue regeneration within tissue-engineered vascular grafts (TEVGs) is of paramount importance due to the critical role these grafts play in replacing damaged or diseased blood vessels. TEVGs offer a promising alternative to traditional grafts, with the potential to integrate into the host's tissue and support the natural regenerative processes. However, challenges such as thrombosis, inflammation, and the need for grafts that can adapt to the dynamic biological environment remain. By studying the regenerative processes in TEVGs, researchers can gain insights into the mechanisms that underpin successful graft integration and function, which is essential for improving patient outcomes in vascular surgeries. This dataset, with its detailed annotations of histological features, provides a valuable resource for developing and refining machine-learning models that can analyze and predict patterns of vascular tissue regeneration. The ability to accurately segment and quantify microvessels and immune cells in regenerated arteries is a significant step forward in distinguishing between physiological and pathological regeneration, ultimately contributing to the design of more effective and reliable TEVGs for clinical use. Ethical Approval: Experimental strategy of the study is described in detail in <a href="https://www.mdpi.com/2073-4360/14/23/5149" target="_blank" rel="noopener">[1]</a> and <a href="https://www.mdpi.com/1422-0067/24/10/8540" target="_blank" rel="noopener">[2]</a>. The study was conducted according to the guidelines of the Declaration of Helsinki, and was approved by the Local Ethical Committee of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia, protocol code 2020/06, date of approval: 19 February 2020). Animal experiments were performed in accordance with the European Convention for the Protection of Vertebrate Animals (Strasbourg, 1986) and Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. For the implantation, we used female Edilbay sheep of 42–45 kg body weight which were received from the Animal Core Facility of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia) and selected for the surgery by Doppler ultrasonography to identify those having carotid artery diameter of 4.0 ± 0.2 mm. Description: The dataset comprises a collection of Whole Slide Images (WSIs) obtained from biodegradable TEVGs implanted into the carotid arteries of 20 sheep. A total of 104 WSIs were acquired, each measuring an average size of 135,000 x 123,000 pixels. These WSIs were stained using Hematoxylin and Eosin (H&E), a common practice for highlighting the structure of tissue sections, which facilitates the detailed examination of histological features. These WSIs were automatically sliced into 99,831 patches of 3,000 x 3,000 pixels and subsequently filtered, resulting in 1,401 selected patches for manual annotation. Annotation Method: Two pathologists independently selected and meticulously annotated the 1401 patches, identifying nine distinct histological features associated with vascular tissue regeneration. These features include arteriole lumen (AL), arteriole media (AM), arteriole adventitia (AA), venule lumen (VL), venule wall (VW), capillary lumen (CL), capillary wall (CW), immune cells (IC), and nerve trunks (NT). The annotations were performed using binary masks, delineating each feature within the patches. Subsequently, a senior pathologist conducted a triple verification process, reviewing and refining the annotations to ensure accuracy and consistency. The annotations are provided in the form of binary masks, meticulously defined for each feature within the patches. Dataset Split: Given the limited number of subjects studied, comprising 20 sheep, we employed a 5-fold cross-validation technique to split our dataset. This method was chosen because it allows for the efficient use of limited data, ensuring that each observation has the opportunity to be used in both the training and testing sets, thus reducing bias and providing a more accurate estimate of the model's performance. In this approach, each fold involved 16 sheep for training and the remaining 4 for testing (see Table 1 and Figure 3). This partitioning scheme was consistently applied to maintain the integrity of subject groups within each subset and to prevent data leakage. The 5-fold cross-validation is particularly beneficial for our study's objectives as it maximizes the training data available for developing robust machine learning models while also ensuring that the models are tested on unseen data, thereby enhancing the generalizability of our findings. Access to the Study: Further information about this study, including curated source code, dataset details, and trained models, can be accessed through the following repositories: <ul> <li>Source code: <a href="https://github.com/ViacheslavDanilov/histology_segmentation" target="_blank" rel="noopener">https://github.com/ViacheslavDanilov/histology_segmentation</a></li> <li>Dataset: <a href="https://doi.org/10.5281/zenodo.10838384" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838384</a></li> <li>Models: <a href="https://doi.org/10.5281/zenodo.10838431" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838431</a></li> </ul> <div> </div> <div>Table 1. Patch and feature distributions across folds and subsets <table> <tbody> <tr> <td> Fold </td> <td> Subset </td> <td> Patches </td> <td> AL </td> <td> AM </td> <td> AA </td> <td> VL </td> <td> VW </td> <td> CL </td> <td> CW </td> <td> IC </td> <td> NT </td> <td> Total </td> </tr> <tr> <td> 1 </td> <td> Train </td> <td> 1168 </td> <td> 510 </td> <td> 512 </td> <td> 220 </td> <td> 675 </td> <td> 648 </td> <td> 770 </td> <td> 765 </td> <td> 409 </td> <td> 448 </td> <td> 4957 </td> </tr> <tr> <td>1</td> <td> Test </td> <td> 233 </td> <td> 81 </td> <td> 84 </td> <td> 36 </td> <td> 186 </td> <td> 169 </td> <td> 178 </td> <td> 182 </td> <td> 91 </td> <td> 25 </td> <td> 1032 </td> </tr> <tr> <td> 2 </td> <td> Train </td> <td> 1053 </td> <td> 406 </td> <td> 411 </td> <td> 179 </td> <td> 678 </td> <td> 638 </td> <td> 743 </td> <td> 746 </td> <td> 423 </td> <td> 315 </td> <td> 4539 </td> </tr> <tr> <td>2</td> <td> Test </td> <td> 348 </td> <td> 185 </td> <td> 185 </td> <td> 77 </td> <td> 183 </td> <td> 179 </td> <td> 205 </td> <td> 201 </td> <td> 77 </td> <td> 158 </td> <td> 1450 </td> </tr> <tr> <td> 3 </td> <td> Train </td> <td> 1127 </td> <td> 507 </td> <td> 511 </td> <td> 222 </td> <td> 743 </td> <td> 702 </td> <td> 759 </td> <td> 760 </td> <td> 299 </td> <td> 423 </td> <td> 4926 </td> </tr> <tr> <td>3</td> <td> Test </td> <td> 274 </td> <td> 84 </td> <td> 85 </td> <td> 34 </td> <td> 118 </td> <td> 115 </td> <td> 189 </td> <td> 187 </td> <td> 201 </td> <td> 50 </td> <td> 1063 </td> </tr> <tr> <td> 4 </td> <td> Train </td> <td> 1064 </td> <td> 466 </td> <td> 472 </td> <td> 199 </td> <td> 611 </td> <td> 566 </td> <td> 759 </td> <td> 758 </td> <td> 423 </td> <td> 291 </td> <td> 4545 </td> </tr> <tr> <td>4</td> <td> Test </td> <td> 337 </td> <td> 125 </td> <td> 124 </td> <td> 57 </td> <td> 250 </td> <td> 251 </td> <td> 189 </td> <td> 189 </td> <td> 77 </td> <td> 182 </td> <td> 1444 </td> </tr> <tr> <td> 5 </td> <td> Train </td> <td> 1192 </td> <td> 475 </td> <td> 478 </td> <td> 204 </td> <td> 737 </td> <td> 714 </td> <td> 761 </td> <td> 759 </td> <td> 446 </td> <td> 415 </td> <td> 4989 </td> </tr> <tr> <td>5</td> <td> Test </td> <td> 209 </td> <td> 116 </td> <td> 118 </td> <td> 52 </td> <td> 124 </td> <td> 103 </td> <td> 187 </td> <td> 188 </td> <td> 54 </td> <td> 58 </td> <td> 1000 </td> </tr> </tbody> </table> </div>

opencc-by-4.0Mar 2024View details →

zenodo48/100

Plant Atlas 2020 — British and Irish vascular plant and charophyte 2 x 2 km grid square locations up to 2019

This resource provides the data behind the 2 × 2 km grid square (tetrad) British and Irish distribution maps, for 3,431 taxa, presented in both the Plant Atlas 2020 book and website (<a href="http://www.plantatlas2020.org">www.plantatlas2020.org</a>), up to 2019. These are presence-only data, indicating where a taxon was reported from a tetrad. These 2 km square presences are based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s.

opencc-by-4.0Apr 2024View details →

zenodo48/100

Plant Atlas 2020 — British and Irish vascular plant and charophyte 10 x 10 km grid square locations, subdivided by survey period, up to 2019

This resource provides the data behind the 10 × 10 km grid square (hectad) British and Irish distribution maps, for 3,497 taxa, presented in both the Plant Atlas 2020 book and website (<a href="http://www.plantatlas2020.org">www.plantatlas2020.org</a>), subdivided by time period<a>.</a> These are presence-only data, indicating where a taxon was reported from a hectad, within a given multi-year period, up to 2019. These time periods cover the 20th Century, but also extend back to the earliest botanical records known for Britain and Ireland in the first period (pre-1930). These 10 km square presences are based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s.

opencc-by-4.0Apr 2024View details →

zenodo48/100

Summary statistics accompanying the article "Genome-wide association study of the human brain functional connectome reveals strong vascular component underlying global network efficiency" in Scientific Reports (2022)

Summary statistics for genome-wide association studies reported in: Bell, S., Tozer, D.J., & Markus H.S. (2022). Genome-wide association study of the human brain functional connectome reveals strong vascular component underlying global network efficiency. Scientific Reports, DOI: <a href="https://dx.doi.org/10.1038/s41598-022-19106-7">10.1038/s41598-022-19106-7</a>.  Abstract Complex brain networks play a central role in integrating activity across the human brain, and such networks can be identified in the absence of any external stimulus. We performed 10 genome-wide association studies of resting state network measures of intrinsic brain activity in up to 36,150 participants of European ancestry in the UK Biobank. We found that the heritability of global network efficiency was largely explained by blood oxygen level-dependent (BOLD) resting state fluctuation amplitudes (RSFA), which are thought to reflect the vascular component of the BOLD signal. RSFA itself had a significant genetic component and we identified 24 genomic loci associated with RSFA, 157 genes whose predicted expression correlated with it, and 3 proteins in the dorsolateral prefrontal cortex and 4 in plasma. We observed correlations with cardiovascular traits, and single-cell RNA specificity analyses revealed enrichment of vascular related cells. Our analyses also revealed a potential role of lipid transport, store-operated calcium channel activity, and inositol 1,4,5-trisphosphate binding in resting-state BOLD fluctuations. We conclude that that the heritability of global network efficiency is largely explained by the vascular component of the BOLD response as ascertained by RSFA, which itself has a significant genetic component.   Further information on the files uploaded here can be found in the README. Users interested in bulk downloading these summary statistics may find <a href="https://github.com/dvolgyes/zenodo_get">zenodo_get</a> helpful.

opencc-by-4.0Aug 2022View details →

zenodo48/100

Arctic specimens in the NHMO DNA bank Vascular plants collection 2022

All Arctic specimens in the NHMO DNA bank Vascular plants collection as of August 2022. See Bjorå et al. 2023 "Collections of Arctic plants, lichens and fungi in the Natural History Museum, University of Oslo, Norway" for further details.

opencc-by-4.0Aug 2022View details →

zenodo48/100

Plant Atlas 2020 — British and Irish vascular plant and charophyte 10 x 10 km distribution trends for 1930–2019 (long-term) and 1987–2019 (short-term), including country-level breakdowns

Plant Atlas 2020 is the most comprehensive survey of plants (flowering plants, ferns and charophytes) ever undertaken in Britain and Ireland. It is based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s. This resource provides the data for the long- (1930–2019) and short- term (1987–2019) 10 x 10 km (“hectad”) distribution trends, presented in both the Plant Atlas 2020 book (Stroh et al., 2023) and website (www.plantatlas2020.org).

opencc-by-4.0May 2024View details →

zenodo44/100

Country Compendium of the Global Register of Introduced and Invasive Species: Standardization to Records in World Flora Online or the World Checklist of Vascular Plants

The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. This compendium is available via <a href="https://zenodo.org/records/6348164">Zenodo</a> and was described by Pagad et al. <a href="https://www.nature.com/articles/s41597-022-01514-z">2022</a>:<ul><li>Shyama Pagad, Stewart Bisset, & Melodie A. McGeoch. (2022). Country Compendium of the Global Register of Introduced and Invasive Species. Dataset. (V1_0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6348164">https://doi.org/10.5281/zenodo.6348164</a></li><li>Pagad, S., Bisset, S., Genovesi, P. et al. Country Compendium of the Global Register of Introduced and Invasive Species. Sci Data 9, 391 (2022). <a href="https://doi.org/10.1038/s41597-022-01514-z">https://doi.org/10.1038/s41597-022-01514-z</a></li></ul> Here I provide direct and fuzzy matches for species listed for the Plantae Kingdom in GRIIS with accepted plant names in World Flora Online (<a href="https://www.worldfloraonline.org/downloadData">version 2023.03</a>; Borsch et al. <a href="https://doi.org/10.1002/tax.12373">2020</a>) or the World Checklist of Vascular Plants (<a href="https://doi.org/10.34885/nswv-8994">version 10</a>; Govaerts et al. <a href="https://www.nature.com/articles/s41597-021-00997-6">2021</a>). Matching was done in R through the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>). The taxonomic standardization process was similar to the one completed <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">during the preparation of the third major release</a> of the <a href="https://apps.worldagroforestry.org/products/switchboard">Agroforestry Species Switchboard</a> and when preparing the GlobalUsefulNativeTrees database (GlobUNT; <a href="https://worldagroforestry.org/output/globalusefulnativetrees">https://worldagroforestry.org/output/globalusefulnativetrees</a>) .Where a matching species was found in GlobUNT, the species name in the GlobUNT database has been shown. GlobUNT has been described in the following publication: Kindt et al. (<a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration. Sci Rep 13, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a>.The developments of this dataset and GlobUNT were supported by the Darwin Initiative to project DAREX001 of <a href="https://www.darwininitiative.org.uk/project/DAREX001/">Developing a Global Biodiversity Standard certification for tree-planting and restoration</a> and by Norway's International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the <a href="https://www.worldagroforestry.org/project/provision-adequate-tree-seed-portfolio-ethiopia">Provision of Adequate Tree Seed Portfolio</a> project in Ethiopia.

opencc-by-4.0Nov 2023View details →

zenodo44/100

Deep and complex vascular anatomy in the rat brain described with Ultrasound Localization Microscopy in 3D

Abstract:Ultrasound Localization Microscopy (ULM) enables imaging microvessels in the brain with a resolution of a few tens of micrometers in vivo. The planar architecture of arterioles and venules was revealed with a 2D ultrasound scanner in the cortex of the rat brain. However, deeper in the brain, where the vascularization becomes tri-dimensional, 2D imaging remains limited by the elevation projection. In this study, volumetric ultrasound imaging was performed in the craniotomized rat brain to yield 3D ULM in vivo within 7.5 min of acquisition with a commercial system. For instance, it highlighted the thalamus or the circle of Willis with small vessels down to 21 µm. Microbubbles tracking also gave access to the 3D velocity vector of blood flow allowing to distinguish flow directions. Volumetric ULM resolved deep complex tri-dimensional vascular structures and was compared to 2D ULM. It is a safe, simple and repeatable system to image wide field of view in the brain.Data Description:Microbubbles have been detected, localized, and tracking with 3D ultrasound imaging in vivo in a rat brain with skull removal.Individual microbubble trajectories are described in 4 columns vectores: [z, x, y, time] for each position of the path. Space positions are given in [mm], and times are given in [ms]. Trajectories data are stored in .mat files (tracks_0xx.mat and zipped inside tracks.zip) as cell arrays.Tracks can be binned inside a volumetric grid with the sample code (ULM_rendering.m).Reference to be cited: Chavignon, Heiles, Hingot, Orset, Vivien and Couture.Deep and complex vascular anatomy in the rat brain described with Ultrasound Localization Microscopy in 3D.

opencc-by-4.0Nov 2023View details →

zenodo44/100

Trees of India Version 1: Standardization to Records in World Flora Online and the World Checklist of Vascular Plants, with matches in GlobalTreeSearch and GlobalUsefulNativeTrees

The Trees of India (ToI, Version-I) includes data on 3708 tree species distributed across 35 states/union territories of India. The database is based on systematic review of 313 literature sources published from 1872-2022.This compendium is available via <a href="https://figshare.com/articles/dataset/ToI_Ver_-I_Trees_of_India_Version-I/23226281">Figshare</a> and was described by Mugal et al. <a href="https://link.springer.com/article/10.1007/s10531-023-02659-y">2023</a>: <ul> <li>Khuroo, Anzar Ahmad; Mugal, Muzamil Ahmad; Wani, Sajad Ahmad (2023). ToI, Ver.-I : Trees of India, Version-I. figshare. Dataset. <a href="https://doi.org/10.6084/m9.figshare.23226281.v1">https://doi.org/10.6084/m9.figshare.23226281.v1</a></li> <li>Mugal, M.A., Wani, S.A., Dar, F.A. et al. Bridging global knowledge gaps in biodiversity databases: a comprehensive data synthesis on tree diversity of India. Biodivers Conserv 32, 3089–3107 (2023). <a href="https://doi.org/10.1007/s10531-023-02659-y">https://doi.org/10.1007/s10531-023-02659-y</a></li> </ul>   Here I provide direct and fuzzy matches for taxa listed with accepted plant names in World Flora Online (<a href="https://www.worldfloraonline.org/downloadData">version 2023.03</a>; Borsch et al. <a href="https://doi.org/10.1002/tax.12373">2020</a>) and the World Checklist of Vascular Plants (WCVP <a href="https://doi.org/10.34885/nswv-8994">version 10</a>; Govaerts et al. <a href="https://www.nature.com/articles/s41597-021-00997-6">2021</a>). Matching was done in R through the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>). The taxonomic standardization process was similar to the one completed <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">during the preparation of the third major release</a> of the <a href="https://apps.worldagroforestry.org/products/switchboard">Agroforestry Species Switchboard</a> and when preparing the GlobalUsefulNativeTrees database (GlobUNT; <a href="https://worldagroforestry.org/output/globalusefulnativetrees">https://worldagroforestry.org/output/globalusefulnativetrees</a>). After matching species with the WCVP, information was compiled on the native distribution documented in the WCVP for level-3 units of the <a href="https://github.com/tdwg/wgsrpd">World Geographical Scheme for Recording Plant Distributions</a> that correspond to India, including India (IND), Assam (ASS), West Himalaya (WHM), East Himalaya (EHM), Laccadive Is. (LDV), Andaman Is. (AND) and Nicobar Is. (NCB). Also included after matching with the WCVP is information on the geographic area, lifeform and main biome. Similar information is available when searching for species from <a href="https://powo.science.kew.org/">Plants of the World Online</a>. Where a matching species was found in GlobalTreeSearch (Beech et al. <a href="https://www.tandfonline.com/doi/full/10.1080/10549811.2017.1310049">2017</a>; <a href="https://tools.bgci.org/global_tree_search.php">https://tools.bgci.org/global_tree_search.php</a>; accessed on 28th June 2023) filtered for India, the species name in GlobalTreeSearch is shown. Note that GlobalTreeSearch documents the native country distribution of tree species. Where a matching species was found in the GlobalUsefulNativeTrees database (GlobUNT, version 2023.11) filtered for India, the species name in the GlobUNT database is shown. GlobUNT has been described in the following publication: Kindt et al. (<a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration. Sci Rep 13, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a>. See the metadata for information on versions.   <ul> <li>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., Güner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></li> <li>Govaerts, R., Nic Lughadha, E., Black, N. et al. The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. Sci Data 8, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></li> <li>E. Beech, M.Rivers, S. Oldfield & P. P. Smith (2017)GlobalTreeSearch: The first complete global database of tree species and country distributions, Journal of Sustainable Forestry, 36:5, 454-489, DOI: <a href="https://doi.org/10.1080/10549811.2017.1310049">10.1080/10549811.2017.1310049</a></li> <li>Kindt, R. 2020. WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data. Applications in Plant Sciences 8(9): e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></li> </ul>   The developments of this dataset and GlobUNT were supported by the Darwin Initiative to project DAREX001 of <a href="https://www.darwininitiative.org.uk/project/DAREX001/">Developing a Global Biodiversity Standard certification for tree-planting and restoration</a>.

opencc-by-4.0Nov 2023View details →

zenodo44/100

DCA and GNMDS output for 4640 subplots and 95 vascular plant species in four alpine grasslands

Ordination output from detrended correspondence analysis (DCA) and global non-metric multidimensional scaling (GNMDS). Analyses were performed in R with the vegan package (Oksanen 2022) for the entire data set of 4630 subplots and 95 species' occurrences ('global', indicated by global or missing site name in file names), and for each of four sites: Skjellingahaugen (skj), Gudmedalen (gud), Låvisdalen (lav), and Ulvehaugen (ulv). Access .Rds files with readRDS in R/RStudio. For GNMDS files, k indicates the chosen number of dimensions. See GitHub repository for scripts to produce and perform further analysis with the files in this archive. Analyses performed by EL with scripts based on originals by RH.

opencc-by-4.0Jun 2023View details →

zenodo44/100

Structural and Molecular Analysis of Adult Mouse Astrocytes and Vascular Connectivity in the Cortex and Hippocampus

After image acquisition (0-RAW_CL230331_E2_serie1) and deconvolution (1-Deconvolved_CL230331_E2_serie1) using confocal microscopy and the SVI Huygens software,respectively, the image processing was conducted using Imaris, Fiji, and Matlab software. This process involved a sequence of manual operations (2-Imaris_surfaces_CL230331_E2_serie1) and custom Groovy scripts (5-Groovy scripts). The dataset analysis (3-Imaris_final_CL230331_E2_serie1_ims) allowed for a deeper investigation of morphological and molecular properties of adult mouse astrocytes (4-Image analysis_CL230331_E2_serie1) in two brain regions, the Isocortex and the Hippocampus, known to be interconnected to support multiple cognitive functions.

opencc-by-4.0Jul 2023View details →

edi44/100

Vascular plant list on the Andrews Experimental Forest and nearby Research Natural Areas, 1958 to 1979

This list compiles all plant taxa which have been encountered in the the H.J. Andrews Experimental Forest, the 6000-hectare Lookout Creek drainage in the western Oregon Cascades. Habitat and abundance are described for most taxa.

openCustomDec 2013View details →

edi44/100

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 IV - Understory Vascular ANPP

This dataset contains net primary productivity (NPP, g/m2/yr) measurements for understory vascular components of the plant community collected at peak biomass in the summer of 2009 at the Alaskan peatland experiment. Two peatland types are included, a bog site and a fen site. Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. Samples at the bog were collected in a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.

openOpenAug 2011View details →

edi44/100

Alaska Peatland Experiment: 2010-2011 Root Respiration Experiment Vascular Green Area

This dataset includes vascular green area data collected at peak biomass during the 2010 and 2011 growing season along the wetland gradient. Data for 2010 was taken at the rich fen only and data for the 2011 season was taken at the rich fen and sedge/forb fen.

openOpenApr 2013View details →

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record