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208
datasets available to search
ShareScore release 0.9.0
Dataset results
208 results for “Blueberry”
The Health Effects of a Blueberry Enriched Diet on Obese Children
ClinicalTrials.gov study NCT01809795. IPD Sharing: Not stated. Countries: 1. Publications: 17.
Impacts of Wild Blueberries on Appetite and Weight Regulation
ClinicalTrials.gov study NCT05736432. IPD Sharing: NO. Countries: 1. Publications: 7.
The Health Effects of Blueberry Anthocyanins in Metabolic Syndrome (the CIRCLES-study)
ClinicalTrials.gov study NCT02035592. IPD Sharing: Not stated. Countries: 2. Publications: 3.
Blueberry Consumption Improves Vascular Function and Lowers Blood Pressure in Postmenopausal Women With Pre- and Stage 1-hypertension
ClinicalTrials.gov study NCT01686282. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of Blueberry-polyphenols on Endothelial Function, Absorption and Metabolism
ClinicalTrials.gov study NCT02520830. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Dose-dependent Effects of Blueberry Polyphenols on Endothelial Function in Healthy Individuals
ClinicalTrials.gov study NCT01829542. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of Blueberry on Gut Microbiota and Metabolic Syndrome
ClinicalTrials.gov study NCT03266055. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Blueberries for Improving Vascular Endothelial Function in Postmenopausal Women With Elevated Blood Pressure
ClinicalTrials.gov study NCT03370991. IPD Sharing: NO. Countries: 1. Publications: 2.
Long-term Effects of Blueberry Supplementation on Brain Health in Older Adults
ClinicalTrials.gov study NCT05764824. IPD Sharing: NO. Countries: 1. Publications: 0.
Effect of Blueberries on Cognition and Body Composition in Elderly With Mild Cognitive Decline
ClinicalTrials.gov study NCT01515098. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Metabolic Benefits of Drinking Blueberry Tea in Type 2 Diabetes
ClinicalTrials.gov study NCT02629952. IPD Sharing: NO. Countries: 1. Publications: 5.
Characterization of Wild Blueberry Polyphenols Bioavailability and Kinetic Profile Over 24-hour Period
ClinicalTrials.gov study NCT02167555. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
The effect of dietary supplementation with blueberry, cyanidin-3-O-β-glucoside, yoghurt and its peptides on gene expression associated with glucose metabolism in skeletal muscle obtained from a high-fat-high-carbohydrate diet induced obesity model
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Data from: Mitigation of pollen limitation in the lowbush blueberry agroecosystem: effect of augmenting natural pollinators
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Fitness costs and oviposition choice of C. nenuphar on blueberry and peach
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Data from: Insights into the genetic basis of blueberry fruit-related traits using diploid and polyploid models in a GWAS context
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Self-compatible blueberry cultivars require fewer floral visits to maximise fruit production than a partially self-incompatible cultivar
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Optimizing whole-genomic prediction for autotetraploid blueberry breeding
<p><span><span><span><span><span><span><span><span><span><span><span><span><span>Blueberry (<em>Vaccinium</em> spp.) is an important autopolyploid crop with significant benefits for human health. Apart from its genetic complexity, the feasibility of genomic prediction has been proven for blueberry, </span></span><span><span>enabling a reduction in the breeding cycle time and increasing genetic gain. </span></span>However, as for other polyploid crops<span><span>, </span></span>sequencing <span><span>costs still hinder the implementation of genome-based breeding methods for blueberry.</span></span> This motivated us to evaluate the effect of training population sizes and composition, as well as the impact of marker density and sequencing depth on phenotype prediction for the species. For this, data from a large real breeding population of 1 804 individuals was used. Genotypic data from 86 930 markers and three traits with different genetic architecture (fruit firmness, fruit weight, and total yield) were evaluated. Herein, we suggested that marker density, sequencing depth, and training population size can be substantially reduced with no significant impact on model accuracy. Our results can help guide decisions towards resource allocation (e.g., genotyping and phenotyping) in order to maximize prediction accuracy. These findings have the potential to allow for a faster and more accurate release of varieties with a substantial reduction of resources for the application of genomic prediction in blueberry. We anticipate that the benefits and pipeline described in our study <span><span>can be applied to optimize genomic prediction for other diploid and polyploid species.</span></span></span></span></span></span></span></span></span></span></span></span></span></p>
The more the merrier: evaluating managed pollinators in highbush blueberry
As the global stock of Apis mellifera colonies is growing slower than agricultural demands for pollination services, there is great interest in managing alternative species. Highbush blueberry floral morphology limits the access of bees to nectar and pollen, requiring growers to rent a considerable number of beehives. Recently, the South American bumblebee Bombus pauloensis is increasingly managed alongside honeybees. Herein, we evaluated their foraging patterns, in relation to the potential pollen transfer between two blueberry co-blooming varieties grown under open high tunnels during two seasons considering different colony densities. Both managed pollinators showed different foraging patterns, influenced by the cultivar identity which varied in their floral morphology and nectar production. Our results demonstrate that both species are efficient foragers on highbush blueberry and further suggest that they contribute positively to its pollination in complementary ways: while bumblebees were more effective at the individual level (visited more flowers and carried more pollen), the greater densities of honeybee foragers overcame the difficulties imposed by the flower morphology, irrespective of the stocking rate. This study supports the addition of managed native bumblebees alongside honeybees to enhance pollination services and emphasizes the importance of examining behavioural aspects to optimize management practices in pollinator-dependent crops.
Probing the molecular basis of fruit firmness in southern highbush blueberry (Vaccinium corymbosum hybrid) through RNA sequencing
<p><span>Blueberries (<em>Vaccinium corymbosum L</em>.) benefit from increased fruit firmness because of consumer preference and machine harvestability. However, the genetic component of fruit texture and skin thickness and their relationship to firmness have yet to be deciphered. This study used bulked segregant RNA-seq (BSR-seq) for differential gene expression analysis. Previously an F1 population of a cross between firm-fruited southern highbush cv. 'Reveille' and soft-fruited cv. 'Arlen' was developed in our laboratory. The total RNA of the parents, the two softest, and the two firmest progenies, were extracted at the breaker and fully ripe stages. Next-generation sequencing cDNA libraries were constructed and subjected to Illumina short-read sequencing. Subsequently, the short reads were mapped to a blueberry genome, and differentially expressed genes (DEGs) were identified in immature and mature fruit coded for potentially biologically significant proteins such as expansins, polygalacturonase, polygalacturonase-inhibiting protein, and mannosidase. Additionally, DEGs corresponding to cysteine proteases and S-adenyl methyltransferases (SAM-MTases) that were previously reported as candidate genes for blueberry firmness were identified in this study. Our results indicated that BSR-seq is a promising method for identifying major candidate genes controlling complex traits in blueberry. </span></p>
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DANDI Archive for NWB datasets
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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.