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.
122
datasets available to search
ShareScore release 0.9.0
Dataset results
122 results for “Cannabis sativa”
Cannabis sativa L. (BR0000012517572)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000011857716)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000011566021)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000011565970)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Co-Dispersion Delivery Systems with Solubilizing Carriers Improving the Solubility and Permeability of Cannabinoids (Cannabidiol, Cannabidiolic Acid, and Cannabichromene) from Cannabis sativa (Henola Variety) Inflorescences
<p>Article, Dataset for article</p> <p> </p> <h2>Abstract</h2> <div>Cannabinoids: cannabidiol (CBD), cannabidiolic acid (CBDA), and cannabichromene (CBC) are lipophilic compounds with limited water solubility, resulting in challenges related to their bioavailability and therapeutic efficacy upon oral administration. To overcome these limitations, we developed co-dispersion cannabinoid delivery systems with the biopolymer polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol (Soluplus) and magnesium aluminometasilicate (Neusilin US2) to improve solubility and permeability. Recognizing the potential therapeutic benefits arising from the entourage effect, we decided to work with an extract instead of isolated cannabinoids. <span>Cannabis sativa</span> inflorescences (Henola variety) with a confirming neuroprotective activity were subjected to dynamic supercritical CO<sub>2</sub> (scCO<sub>2</sub>) extraction and next they were combined with carriers (1:1 mass ratio) to prepare the co-dispersion cannabinoid delivery systems (HiE). In vitro dissolution studies were conducted to evaluate the solubility of CBD, CBDA, and CBC in various media (pH 1.2, 6.8, fasted, and fed state simulated intestinal fluid). The HiE-Soluplus delivery systems consistently demonstrated the highest dissolution rate of cannabinoids. Additionally, HiE-Soluplus exhibited the highest permeability coefficients for cannabinoids in gastrointestinal tract conditions than it was during the permeability studies using model PAMPA GIT. All three cannabinoids exhibited promising blood-brain barrier (BBB) permeability (P<sub>app</sub> higher than 4.0 × 10<sup>−6</sup> cm/s), suggesting their potential to effectively cross into the central nervous system. The improved solubility and permeability of cannabinoids from the HiE-Soluplus delivery system hold promise for enhancement in their bioavailability.</div> <div> <div> <div>Keywords: </div> <a href="https://www.mdpi.com/search?q=cannabidiol">cannabidiol</a>; <a href="https://www.mdpi.com/search?q=cannabidiolic+acid">cannabidiolic acid</a>; <a href="https://www.mdpi.com/search?q=cannabichromene">cannabichromene</a>; <a href="https://www.mdpi.com/search?q=cannabis">cannabis</a>; <a href="https://www.mdpi.com/search?q=solubility">solubility</a>; <a href="https://www.mdpi.com/search?q=permeability">permeability</a></div> </div>
Yields, Cannabinoids Quantification, and Predictive Programming Codes Using Machine Learning for Non-Psychoactive Cannabis Flowers and Extracts (Cannabis sativa L.) Cultivated in Ecuador.
<p>This publication presents data from various extraction methods, including maceration, Soxhlet, and supercritical fluids, performed on different cannabis flower varieties (Cannabis sativa L.) under varying operating conditions. We quantified the amounts of CBD, THC, CBG, and CBN in the extracts produced by each method using High-Performance Liquid Chromatography (HPLC). Using this data, we developed a machine learning algorithm in RStudio to make predictions and determine the best conditions and yields for each extraction method. The analysis focuses on different varieties of non-psychoactive cannabis cultivated in Ecuador at altitudes over 2,450 m.a.s.l.</p>
Supplementary material 1 from: McPartland JM, Small E (2020) A classification of endangered high-THC cannabis (Cannabis sativa subsp. indica) domesticates and their wild relatives. PhytoKeys 144: 81-112. https://doi.org/10.3897/phytokeys.144.46700
A classification of endangered high-THC cannabis (Cannabis sativa subsp. indica) domesticates and their wild relatives
Modeling cannabinoids from a large-scale sample of Cannabis sativa chemotypes
<p>The widespread legalization of <i>Cannabis</i> has opened the industry to using contemporary analytical techniques for chemotype analysis. Chemotypic data has been collected on a large variety of oil profiles inherent to the cultivars that are commercially available. The unknown gene regulation and pharmacokinetics of dozens of cannabinoids offer opportunities of high interest in pharmacology research. Retailers in many medical and recreational jurisdictions are typically required to report chemical concentrations of at least some cannabinoids. Commercial cannabis laboratories have collected large chemotype datasets of diverse <i>Cannabis</i> cultivars. In this work a data set of 17,600 cultivars tested by Steep Hill Inc., is examined using machine learning techniques to interpolate missing chemotype observations and cluster cultivars into groups based on chemotype similarity. The results indicate cultivars cluster based on their chemotypes, and that some imputation methods work better than others at grouping these cultivars based on chemotypic identity. Due to the missing data and to the low signal to noise ratio for some less common cannabinoids, their behavior could not be accurately predicted. These findings have implications for characterizing complex interactions in cannabinoid biosynthesis and improving phenotypical classification of <i>Cannabis</i> cultivars.</p>
Variant Call File (VCF) for Genome-wide polymorphism and genic selection in feral and domesticated lineages of Cannabis sativa
<p>A comprehensive understanding of the degree to which genomic variation is maintained by selection versus drift and gene flow is lacking in many important species such as <em>Cannabis</em> <em>sativa </em>(<em>C. sativa</em>), one of the oldest known crops to be cultivated by humans worldwide. We generated whole genome resequencing data across diverse samples of feralized (escaped domesticated lineages) and domesticated lineages of <em>C. sativa</em>. We performed analyses to examine population structure, and genome wide scans for FST, balancing selection, and positive selection. Our analyses identified evidence for sub-population structure and further support the Asian origin hypothesis of this species. Feral plants sourced from the U.S. exhibited broad regions on chromosomes 4 and 10 with high <span>𝐹̅</span>ST which may indicate chromosomal inversions maintained at high frequency in this sub-population. Both our balancing and positive selection analyses identified loci that may reflect differential selection for traits favored by natural selection and artificial selection in feral versus domesticated sub-populations. In the U.S. feral sub-population, we found six loci related to stress response under balancing selection and one gene involved in disease resistance under positive selection, suggesting local adaptation to new climates and biotic interactions. In the marijuana sub-population, we identified the gene <em>SMALLER TRICHOMES</em> <em>WITH VARIABLE BRANCHES 2 </em>to be under positive selection which suggests artificial selection for increased tetrahydrocannabinol yield. Overall the data generated, and results obtained from our study help to form a better understanding of the evolutionary history in <em>C. sativa</em>.</p>
Fig. 1 in Biosynthetic origins of unusual cannabimimetic phytocannabinoids in Cannabis sativa L: A review
Fig. 1. Topological arrangement and structural relationships of alkyl phytocannabinoids. (a) Alkyl phytocannabinoid isoprenyl subclasses and biosynthetic relationships. (b) Major pharmacophore and common structural features between the phytocannabinoid Δ 9-THC and the endocannabinoid anandamide (N-arachidonoylethanolamine; AEA).Compound subclass abbreviations: CBC - cannabichromene; CBD - cannabidiol; CBE - cannabielsoin; CBF - cannabifuran; CBG - cannabigerol; CBL - cannabicyclol; CBN - cannabinol; CBND - cannabinodiol; THC – Δ9 tetrahydrocannabinol; red colour phytocannabinoid moieties derived from a = resorcinol origin, blue colour = phytocannabinoid moieties derived from an isoprenoid origin. (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 Biosynthetic origins of unusual cannabimimetic phytocannabinoids in Cannabis sativa L: A review
Fig. 3. Schematic diagram of phytocannabinoid biosynthesis and precursor pathways. Grey arrows and text indicate putative precursor pathways and enzymes associated with recently reported in planta phytocannabinoid analogues. Coloured arrows and text indicate known biosynthetic pathways leading to the production of phytocannabinoids. Blue arrows and text indicate the methylerythritol phosphate pathway leading to the production of the isoprenoid intermediate geranyl diphosphate used in both monoterpenoid and phytocannabinoid biosynthesis. Red arrows and text indicate the alkylresorcinolic acid pathway leading to the production of the phytocannabinoid intermediate olivetolic acid. Green arrows and text indicate the phytocannabinoid pathway and enzymes leading to the production of monocyclic, dicyclic and tricyclic alkyl phytocannabinoids. Numbers in parentheses indicate compound numbers from Table 1 and their positions indicate putative branch points associated with phytocannabinoid analogue production. Question marks indicate uncertainty over either the transportation of metabolites between subcellular compartments or the catalytic mechanism leading to the biosynthesis of phytocannabinoid metabolites. Biochemical pathway abbreviations: AACT - acetyl-CoA C-acyltransferase (EC 2.3.1.16); ACCase - acetyl-CoA carboxylase (EC 6.4.1.2); ACP - acyl carrier protein; CBC - cannabichromene; CBCAS - cannabichromenic acid synthase; CBD - cannabidiol; CBDAS - cannabidiolic acid synthase (EC:1.21.3.8); CBG - cannabigerol; CMK - 4-(Cytidine 5′-diphospho)-2-C-methyl-Derythritol kinase (EC 2.7.1.148); CoA - coenzyme A; CsAAE1 - acyl-activating enzyme 1; CsOAC - olivetolic acid cyclase (EC:4.4.1.26); CsPT1 - geranylpyrophosphate: olivetolate geranyltransferase (EC 2.5.1.102); CsTKS - tetraketide synthase (EC:2.3.1.206); DMAPP - dimethylallyl diphosphate; DXR - 1-deoxy-D-xylulose-5-phosphate reductoisomerase (EC 1.1.1.267); DXS - 1-deoxy-D-xylulose 5 phosphate synthase (EC 2.2.1.7); ENR - enoyl-ACP reductase; FAD - fatty acid desaturase; FPPS - farnesyl pyrophosphate synthase (EC 2.5.1.10); G3P - glyceraldehyde 3-phosphate; GPPS - geranyl diphosphate synthase (EC:2.5.1.1); HD - 3-hydroxyacyl-ACP dehydratase; HDR - 1-Hydroxy-2-methyl-2-butenyl 4-diphosphate reductase (EC:1.17.7.4); HDS - 1-Hydroxy-2-methyl-2-butenyl 4-diphosphate synthase (EC 1.17.7.3); HMGR - hydroxymethylglutaryl-CoA reductase (EC 1.1.1.34); HMGS - hydroxymethylglutaryl-CoA synthase (EC 2.3.3.10); HPL - hydroperoxide lyase (EC:4.1.2.-); IPP - isopentenyl diphosphate; KAR - 3-ketoacyl-ACP reductase; KAS - β-ketoacyl-ACP synthase; LOX2 - 13S-lipoxygenase 2 (EC:1.13.11.12); MAT - malonyl-CoA: acyl carrier protein malonyltransferase (EC 2.3.1.39); MCT - 2-C-methyl-D-erythritol 4-phosphate cytidylyltransferase (EC 2.7.7.60); MDS - 2-Cmethyl-D-erythritol 2,4-cyclodiphosphate synthase (EC 4.6.1.12); MEP - methylerythritol phosphate; MK - mevalonate kinase (EC 2.7.1.36); MVA - mevalonate; OPP - diphosphate; PMK - phosphomevalonate kinase (EC 2.7.4.2); PPMD - diphosphomevalonate decarboxylase (EC 4.1.1.33); SCD - stearoyl-CoA desaturase (Delta- 9 desaturase) (EC:1.14.19.1); THC - Δ9 tetrahydrocannabinol; THCAS – Δ9 tetrahydrocannabinolic acid synthase (EC:1.21.3.7); 13(S)-HPODE - 13S-hydroperoxy- 9Z,11E-octadecadienoic acid. (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 Biosynthetic origins of unusual cannabimimetic phytocannabinoids in Cannabis sativa L: A review
Fig. 2. Summary of Cannabis sativa L. trichome morphotypes: (a) Non-glandular trichome on the adaxial surface of a floral bract. (b) Glandular trichomes on the adaxial surface of a vegetative leaf. (c) capitate stalked glandular trichome on the abaxial surface of a floral bract. (d) Approximate location of capitate stalked glandular trichome cell types and substructures, scale bar = 100 μm.
Safety and Efficacy on Spasticity Symptoms of a Cannabis Sativa Extract in Motor Neuron Disease
ClinicalTrials.gov study NCT01776970. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Analgesic Effects of a Treatment With Cannabis Sativa Extract in Patients With Knee Osteoarthritis - CANOA (Cannabis for Osteoarthritis)
ClinicalTrials.gov study NCT06588972. IPD Sharing: NO. Countries: 1. Publications: 1.
Widely assumed phenotypic associations in Cannabis sativa lack a shared genetic basis
Open the record for dataset details and reuse information.
Variant Call File (VCF) for Genome-wide polymorphism and genic selection in feral and domesticated lineages of Cannabis sativa
Open the record for dataset details and reuse information.
Modeling cannabinoids from a large-scale sample of Cannabis sativa chemotypes
Open the record for dataset details and reuse information.
Figure 1 from: McPartland JM, Small E (2020) A classification of endangered high-THC cannabis (Cannabis sativa subsp. indica) domesticates and their wild relatives. PhytoKeys 144: 81-112. https://doi.org/10.3897/phytokeys.144.46700
Figure 1 Line drawing adapted from Anderson (1980), courtesy of the Harvard University Herbaria and Botany Libraries.
Figure 5 from: McPartland JM, Small E (2020) A classification of endangered high-THC cannabis (Cannabis sativa subsp. indica) domesticates and their wild relatives. PhytoKeys 144: 81-112. https://doi.org/10.3897/phytokeys.144.46700
Figure 5 Type specimens of C. sativa subsp. indica var. afghanica. Neotype on left (a), epitype on right (b).
Figure 2 from: McPartland JM, Small E (2020) A classification of endangered high-THC cannabis (Cannabis sativa subsp. indica) domesticates and their wild relatives. PhytoKeys 144: 81-112. https://doi.org/10.3897/phytokeys.144.46700
Figure 2 Shifts in THC/CBD ratios over time; data from 47 numbered studies in Suppl. material 1: SF.9. Central Asian landraces in unitalicized red (n =13 studies); "Indica" in underlined unitalicized red (n= 9); South Asian landraces in italicized green (n =18 studies); "Sativa" in underlined italicized green (n =7 studies). Size of numeral reflects the number of accessions analyzed in that study.
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.