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Dataset results
660 results for “Cannabis”
Effectiveness Study of Dronabinol and BRENDA for the Treatment of Cannabis Withdrawal
ClinicalTrials.gov study NCT00480441. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Social Media Intervention for Cannabis Use in Emerging Adults
ClinicalTrials.gov study NCT04187989. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of Inhaled Cannabis on Driving Performance
ClinicalTrials.gov study NCT01620177. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Pain Inflammation and Cannabis in HIV
ClinicalTrials.gov study NCT05554146. IPD Sharing: NO. Countries: 1. Publications: 34.
Combined Pharmacotherapy for Cannabis Dependency
ClinicalTrials.gov study NCT01020019. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study to Compare Sublingual Cannabis Based Medicine Extracts With Placebo to Treat Brachial Plexus Injury Pain
ClinicalTrials.gov study NCT01606189. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Vaporized Cannabis and Spinal Cord Injury Pain
ClinicalTrials.gov study NCT01555983. IPD Sharing: YES. Countries: 1. Publications: 5.
N-Acetylcysteine for Youth Cannabis Use Disorder
ClinicalTrials.gov study NCT03055377. IPD Sharing: NO. Countries: 1. Publications: 1.
The Impact and Detection of Driving Impairments Associated With Acute Cannabis Smoking
ClinicalTrials.gov study NCT02849587. IPD Sharing: YES. Countries: 1. Publications: 12.
Cannabis Effects on Driving-related Skills of Young Drivers
ClinicalTrials.gov study NCT01592409. IPD Sharing: Not stated. Countries: 1. Publications: 15.
Simulated cannabis days-of-use data
Open the record for dataset details and reuse information.
Accumulation and re-accumulation of commercial tobacco, electronic cigarette, and cannabis waste in San Diego County
Open the record for dataset details and reuse information.
A sleepy cannabis constituent: cannabinol and its active metabolite influence sleep architecture in rats
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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>
Dataset of well-known Thai cannabis plants
<p>Cannabis Classes in Thailand are well recognized. In order to be useful for researchers or interested people, Plants of 8 Thai cannabis classes are shared in this data set. The pictures of data set are plants of cannabis. </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>
Input files of various genomic analyses used to unravel the domestication history of Cannabis
<p>Cannabis sativa has long been an important source of fiber extracted from hemp and both medicinal and recreational drugs based on cannabinoid compounds. Here, we investigated its poorly known domestication history using whole-genome resequencing of 110 accessions from worldwide origins. We show that C. sativa was first domesticated in early Neolithic times in East Asia and that all current hemp and drug cultivars diverged from an ancestral gene pool currently represented by feral plants and landraces in China. We identified candidate genes associated with traits differentiating hemp and drug cultivars, including branching pattern and cellulose/ lignin biosynthesis. We also found evidence for loss of function of genes involved in the synthesis of the two major biochemically competing cannabinoids during selection for increased fiber production or psychoactive properties. Our results provide a unique global view of the domestication of C. sativa and offer valuable genomic resources for ongoing functional and molecular breeding research.</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.)
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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.
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.