In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Q: Context: To investigate whether preconditioning with high mobility group box 1 protein (HMGB1) could reduce myocardial ischemia-reperfusion (I/R) injury.', 'Infarct size, lactate dehydrogenase (LDH), creatine kinase (CK), tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were assessed. HMGB1 preconditioning reduced significantly the infarct size induced by I/R. The LDH, CK, TNF-α and IL-6 levels were significantly decreased by HMGB1 preconditioning compared to those in the I/R group.\Question: Does preconditioning with high mobility group box 1 protein protect against myocardial ischemia-reperfusion injury?

A: The present study suggested that preconditioning with HMGB1 could induce HMGB1 tolerance and protect against myocardial I/R injury.
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Q: Context: Perls' stain is routinely used to demonstrate iron in liver biopsies. We tested the hypothesis that it may be unnecessary in cases, where no iron or another similar pigment was seen on the routine hematoxylin and eosin (H and E) stained section.", "The aim of this study was to evaluate the efficiency of H and E stain in demonstrating iron in liver biopsies as well as to determine the possibility of replacing Perls' stain with H and E stain.", "Two hundred pairs of slides of liver biopsies were taken from the archival files of the Department of Pathology from 2006 to 2011. Perls' and H and E slides were independently reviewed for the presence of iron.", "Hundred and one cases showed the presence of iron using H and E stain. 84 of 86 cases showed positive iron using both Perls' and H and E stains. Seventeen cases were positive using H and E stain but negative with Perls'. Only two cases did not show the presence of iron using H and E stain. Ninety-seven cases were negative using both Perls' and H and E stains. H and E stain showed a sensitivity, specificity, accuracy, positive predictive valve, and negative predictive value of 97.67%, 85.08%, 90.5%, 83.16%, and 97.98%, respectively.\Question: Do hematoxylin and eosin stain shows a high sensitivity but sub-optimal specificity in demonstrating iron pigment in liver biopsies?

A: We demonstrate that the H and E stain is a sensitive method to detect iron pigment in liver biopsies, particularly when present in large quantities. A negative H and E stain might obviate the need for extra Perls' staining, thus saving costs and shortening report turn-around times.
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Q: Context: Genomic selection (GS) may improve selection response over conventional pedigree-based selection if markers capture more detailed information than pedigrees in recently domesticated tree species and/or make it more cost effective. Genomic prediction accuracies using 1748 trees and 6932 SNPs representative of as many distinct gene loci were determined for growth and wood traits in white spruce, within and between environments and breeding groups (BG), each with an effective size of Ne ≈ 20. Marker subsets were also tested.', 'Model fits and/or cross-validation (CV) prediction accuracies for ridge regression (RR) and the least absolute shrinkage and selection operator models approached those of pedigree-based models. With strong relatedness between CV sets, prediction accuracies for RR within environment and BG were high for wood (r = 0.71-0.79) and moderately high for growth (r = 0.52-0.69) traits, in line with trends in heritabilities. For both classes of traits, these accuracies achieved between 83% and 92% of those obtained with phenotypes and pedigree information. Prediction into untested environments remained moderately high for wood (r ≥ 0.61) but dropped significantly for growth (r ≥ 0.24) traits, emphasizing the need to phenotype in all test environments and model genotype-by-environment interactions for growth traits. Removing relatedness between CV sets sharply decreased prediction accuracies for all traits and subpopulations, falling near zero between BGs with no known shared ancestry. For marker subsets, similar patterns were observed but with lower prediction accuracies.\Question: Do genomic selection accuracies within and between environments and small breeding groups in white spruce?

A:
Given the need for high relatedness between CV sets to obtain good prediction accuracies, we recommend to build GS models for prediction within the same breeding population only. Breeding groups could be merged to build genomic prediction models as long as the total effective population size does not exceed 50 individuals in order to obtain high prediction accuracy such as that obtained in the present study. A number of markers limited to a few hundred would not negatively impact prediction accuracies, but these could decrease more rapidly over generations. The most promising short-term approach for genomic selection would likely be the selection of superior individuals within large full-sib families vegetatively propagated to implement multiclonal forestry.
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