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335 results for “disease resistance”
Spironolactone With Patiromer in the Treatment of Resistant Hypertension in Chronic Kidney Disease
ClinicalTrials.gov study NCT03071263. IPD Sharing: NO. Countries: 9. Publications: 4.
Study of Vitamin D and Effect on Heart Disease and Insulin Resistance
ClinicalTrials.gov study NCT01093417. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Nutrition, Inflammation and Insulin Resistance in End Stage Renal Disease-Aim 2
ClinicalTrials.gov study NCT02278562. IPD Sharing: NO. Countries: 1. Publications: 1.
Putative resistance and tolerance mechanisms have little impact on disease progression for an emerging salamander pathogen
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Data from: Symbiotic immuno-suppression: is disease susceptibility the price of bleaching resistance?
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Long-read-based draft genome sequence of Indian black gram IPU-94-1 ‘Uttara’: Insights into disease resistance and seed storage protein genes
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Quantitative disease resistance in wild Silene vulgaris to its endemic pathogen Microbotryum silenes-inflatae collection sites
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Data from: Resistance, tolerance and environmental transmission dynamics determine host extinction risk in a load-dependent amphibian disease
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Bees bred for Varroa sensitive hygiene trait demonstrate resistance to chalkbrood disease
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Pierce's disease vector transmission-preference experiment on PdR1 resistant grapevines
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Data from: Experimental evolution for improved post-infection survival selects for increased disease resistance in Drosophila melanogaster
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Dataset - A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress
<p>Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in <em>Arabidopsis thaliana</em> the genetic bases of robust resistance mechanisms to the devastating pathogen<em> Ralstonia solanacearum</em> under heat stress. A local mapping population was phenotyped against the <em>R. solanacearum</em> GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin <em>SOLO DANCERS</em> gene was validated by a reverse genetic approach as involved in QDR to <em>R. solanacearum </em>at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.</p>
Data from: Polyandry and paternity affect disease resistance in eusocial wasps
<p>One of several hypotheses proposed to explain polyandry in eusocial insects is the parasite–pathogen hypothesis (PPH), in which a colony of workers with multiple patrilines due to queen polyandry is less likely to fall victim to a parasite or pathogen threat because of genetic variability of the colony's workforce. We challenged colonies with different strains of an entomopathogenic fungus to determine pathogen virulence and worker survival. We found that workers from different patrilines differed in their survival following the pathogen challenge, supporting the hypothesis that a major benefit of multiple mating by queen wasps is in disease resistance for the benefit of the colony.</p> <p>We infected isolated workers with the entomopathogenic fungus <i>Beauveria bassiana</i> and quantified their survival in the laboratory. We used five fungal strains (A–E) of <i>B. bassiana</i> for experiment 1, and then selected the two most lethal strains (A and C) for experiment 2. We used nine microsatellite markers to determine patriline membership, we analyzed microsatellite genotypes using the software Colony v2.0.6.5 (Wang 2004).</p>
Measuring resilience and resistance in aging and Alzheimer disease using residual methods: A systematic review and meta-analysis
<p>Objective: There is currently a lack of consensus on how to optimally define and measure resistance and resilience in brain and cognitive aging. Residual methods use residuals from regression analysis to quantify the capacity to avoid (resistance) or cope (resilience) "better or worse than expected" given a certain level of risk or cerebral damage. We reviewed the rapidly-growing literature on residual methods in the context of aging and Alzheimer's disease (AD), and performed meta-analyses to investigate associations of residual-method based resilience and resistance measures with longitudinal cognitive and clinical outcomes.</p> <p>Methods: A systematic literature search of PubMed and Web-of-Science databases (consulted until March 2020) and subsequent screening led to 54 studies fulfilling eligibility criteria, including 10 studies suitable for the meta-analyses.</p> <p>Results: We identified articles using residual methods aimed at quantifying resistance (n=33), cognitive resilience (n=23) and brain resilience (n=2). Critical examination of the literature revealed that there is considerable methodological variability in how the residual measures were derived and validated. Despite methodological differences across studies, meta-analytic assessments showed significant associations of levels of resistance (HR[95%CI]=1.12[1.07-1.17], p<0.0001) and levels of resilience (HR[95%CI]=0.46[0.32-0.68], p<0.001) with risk of progression to dementia/AD. Resilience was also associated with rate of cognitive decline (β[95%CI]=0.05[0.01-0.08], p<0.01).</p> <p>Conclusion: This review and meta-analysis supports the usefulness of residual methods as appropriate measures of resilience and resistance, as they capture clinically meaningful information in aging and AD. More rigorous methodological standardization is needed, however, to increase comparability across studies and, ultimately, application in clinical practice.</p>
Data from: Will natural resistance result in populations of ash trees remaining in British woodlands after a century of ash dieback disease?
Novel pests and diseases are becoming increasingly common, and often cause additional mortality to host species in the newly contacted communities. This can alter the structure of the community up to, and including, the extinction of host species. In the last twenty years, ash dieback disease (ADB) has spread into Europe from East Asia. It has caused substantial mortality in ash tree (Fraxinus excelsior L.) populations. However, a proportion of the individuals in most populations appears to be less susceptible to ADB and resistance seems to have high heritability. These observations have led to suggestions that ash populations may be sustainable after the disease. In order to test this hypothesis, I modified an existing model of UK woodland (parameterised for Wytham Woods, Oxfordshire) to take into account the impact of ADB, and allowed offspring to inherit resistance traits from their parent. The results suggest that ash populations would still exist in 100 years but at lower levels than they are currently. For example, when the initial proportion of resistant individuals is about 10% and heritability of resistance is 0.5, then the population of ash falls to about one third of present levels. The proportion of individuals initially resistant to ADB had a larger effect on population size after 100 years than the heritability of resistance. The fact that the initial size of the resistant population is important to achieving a high population size in the presence of ADB suggests that a selective breeding programme with the intention of augmenting the natural ash populations would be beneficial.
Data from: Relatedness severely impacts accuracy of marker- assisted selection for disease resistance in hybrid wheat
The accuracy of genomic selection depends on the relatedness between the members of the set in which marker effects are estimated based on evaluation data and the types for which performance is predicted. Here, we investigate the impact of relatedness on the performance of marker-assisted selection for fungal disease resistance in hybrid wheat. A large and diverse mapping population of 1,739 elite European winter wheat inbred lines and hybrids was evaluated for powdery mildew, leaf rust, and stripe rust resistance in multi-location field trials and fingerprinted with 9k and 90k SNP arrays. Comparison of the accuracies of prediction achieved with data sets from the two marker arrays revealed a crucial role for a sufficiently high marker density in genome-wide association mapping. Cross- validation studies using test sets with varying degrees of relationship to the corresponding estimation sets unraveled that close relatedness leads to a substantial increase in the proportion of total genotypic variance explained by the identified QTL and, consequently, to an overoptimistic judgment of the prospected precision of marker-assisted selection.
Sustainable Development of Sorghum through the Promotion of Microbial Symbiosis and Disease Resistance: Supplemental Data
<p>Supplemental data for Chapter 3 of the dissertation titled: "Sustainable Development of Sorghum through the Promotion of Microbial Symbiosis and Disease Resistance"</p>
Wheat Enhanced Disease Resistance EMS-Mutants Include Lesion-mimics With Adult Plant Resistance to Stripe Rust
<h3>The datasets for '<strong>Wheat Enhanced Disease Resistance EMS-Mutants Include Lesion-mimics With Adult Plant Resistance to Stripe Rust</strong>'.</h3> <p> </p> <p><strong>Main datasets</strong></p> <ul> <li>Kr620_GATK.zip</li> <li>Kr620_QTLseq.zip</li> </ul> <p><strong>Kr620_GATK.zip</strong> includes vcf files generated by mapping wild type Kronos and resistant or susceptible Kr620 into the Kronos genome. <strong>Kr620_QTLseq.zip </strong>includes the bulk segregation analysis outputs using QTL-seq. </p>
Long-read genome sequencing of bread wheat facilitates disease resistance gene cloning
<p>Cloning agronomically important genes from large, complex crop genomes remains challenging. Here, we generate a 14.7-gigabase chromosome-scale<i> </i>assembly of the South African bread wheat (<i>Triticum aestivum</i>) cultivar Kariega by combining high-fidelity long reads, optical mapping, and chromosome conformation capture. The resulting assembly is an order of magnitude more contiguous than previous wheat assemblies. Kariega shows durable resistance against the devastating fungal stripe rust disease. We identified the race-specific disease resistance gene <i>Yr27</i>, encoding an intracellular immune receptor, as a major contributor to this resistance. <i>Yr27</i> is allelic to the leaf rust resistance gene <i>Lr13,</i> with the Yr27 and Lr13 proteins sharing 97% sequence identity. Our results thus demonstrate the feasibility of generating chromosome-scale wheat assemblies to clone genes and also exemplify that highly similar alleles of a single-copy gene can confer resistance to different pathogens, which might provide a basis for engineering <i>Yr27</i> alleles with multiple recognition specificities in future.</p>
Genomic Selection Paves Way for the Identification of Rust Disease Resistant Genotypes in Bread Wheat (Triticum aestivum).
<p><span>In the last two decades, genomic prediction (GP) or Genomic Selection (GS) methods have been widely adopted in various plant and animal breeding programs globally. GP/GS is a promising method that employs genomic markers to calculate genomic-estimated breeding values (GEBVs) to select best individuals. To evaluate the performance of different genomic selection (GS) models, we examined six different models namely, ridge regression (RR), least absolute shrinkage and selection operator (LASSO), genomic best linear unbiased prediction (GBLUP), elastic net (EN), reproducing kernel Hilbert spacing (RKHS), and random forest (RF) models, for seedling and adult plant resistance to leaf, stem and stripe rust of wheat using a panel of 347 wheat germplasm accessions. The GBLUP and RF models performed noticeably better than the other GS models, with mean predictive abilities of 0.5 and 0.4 for seedling resistance and 0.4 and 0.3 for adult plant resistance (APR) for leaf and stem rust, respectively. Unfortunately, except for a few environments, the performance of GP models in the current study is quite low for stripe rust for both seedling and APR. The outcomes of this study revealed the capability of GP to be applied for breeding initiatives aimed at developing wheat varieties resistant to rust diseases. </span><span>Moreover, based on favorable allele analysis we also identified a total of 2 lines (CRP-165/42, HGP1-470) that showed resistance to most of the pathotypes at seedling and adult plant stage to all three rusts.<strong><span> </span></strong>These lines can serve as valuable resources for future breeding programs focused on rust resistance.</span></p> <p><strong><span>Keywords: </span></strong><span>GS;</span><strong><span> </span></strong><span>GEBVs; leaf rust; stem rust; stripe rust; seedling resistance; APR</span></p>
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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.