30 research outputs found

    The relationship between cadence, pedalling technique and gross efficiency in cycling

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    Technique and energy saving are two variables often considered as important for performance in cycling and related to each other. Theoretically, excellent pedalling technique should give high gross efficiency (GE). The purpose of the present study was to examine the relationship between pedalling technique and GE. 10 well-trained cyclists were measured for GE, force effectiveness (FE) and dead centre size (DC) at a work rate corresponding to ~75% of VO2max during level and inclined cycling, seat adjusted forward and backward, at three different cadences around their own freely chosen cadence (FCC) on an ergometer. Within subjects, FE, DC and GE decreased as cadence increased (p < 0.001). A strong relationship between FE and GE was found, which was to great extent explained by FCC. The relationship between cadence and both FE and GE, within and between subjects, was very similar, irrespective of FCC. There was no difference between level and inclined cycling position. The seat adjustments did not affect FE, DC and GE or the relationship between them. Energy expenditure is strongly coupled to cadence, but force effectiveness, as a measure for pedalling technique, is not likely the cause of this relationship. FE, DC and GE are not affected by body orientation or seat adjustments, indicating that these parameters and the relationship between them are robust to coordinative challenges within a range of cadence, body orientation and seat position that is used in regular cycling

    RNA expression of TLR10 in normal equine tissues

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    Background: Toll like receptors are one of the major innate immune system pathogen recognition systems. There is little data on the expression of the TLR10 member of this family in the horse. Results: This paper describes the genetic structure of the Equine TLR10 gene and its RNA expression in a range of horse tissues. It describes the phylogenetic analysis of the Equine TLR1,6,10,2 annotations in the horse genome, firmly identifying them in their corresponding gene clades compared to other species and firmly placing the horse gene with other TLR10 genes from odd-toed ungulates. Additional 3’ transcript extensions to that annotated for TLR10 in the horse genome have been identified by analysis of RNAseq data. RNA expression of the equine TLR10 gene was highest in peripheral blood mononucleocytes and lymphoid tissue (lymph nodes and spleen), however some expression was detected in all tissues tested (jejunum, caudal mesenteric lymph nodes, bronchial lymph node, spleen, lung, colon, kidney and liver). Additional data on RNAseq expression of all equine TLR genes (1–4 and 6–10) demonstrate higher expression of TLR4 than other equine TLRs in all tissues. Conclusion: The equine TLR10 gene displays significant homology to other mammalian TLR10 genes and could be reasonably assumed to have similar fuctions. Its RNA level expression is higher in resting state PBMCs in horses than in other tissues

    Identification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the BovineSNP50 BeadChip

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    Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n = 1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n = 878) and loci under selection (n = 190) were identified with the FST-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1−30.1 million years before present)

    Big data for bipolar disorder

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    Analysis of genome-wide DNA arrays reveals the genomic population structure and diversity in autochthonous Greek goat breeds

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    Goats play an important role in the livestock sector in Greece. The national herd consists mainly of two indigenous breeds, the Eghoria and Skopelos. Here, we report the population structure and genomic profiles of these two native goat breeds using Illumina's Goat SNP50 BeadChip. Moreover, we present a panel of candidate markers acquired using different genetic models for breed discrimination. Quality control on the initial dataset resulted in 48,841 SNPs kept for downstream analysis. Principal component and admixture analyses were applied to assess population structure. The rate of inbreeding within breed was evaluated based on the distribution of runs of homozygosity in the genome and respective coefficients, the genomic relationship matrix, the patterns of linkage disequilibrium, and the historic effective population size. Results showed that both breeds exhibit high levels of genetic diversity. Level of inbreeding between the two breeds estimated by the Wright's fixation index FST was low (Fst = 0.04362), indicating the existence of a weak genetic differentiation between them. In addition, grouping of farms according to their geographical locations was observed. This study presents for the first time a genome-based analysis on the genetic structure of the two indigenous Greek goat breeds and identifies markers that can be potentially exploited in future selective breeding programs for traceability purposes, targeted genetic improvement schemes and conservation strategies
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