Stepping over obstacles of different heights and varied shoe traction alter the kinetic strategies of the leading limb

This study aims to investigate the effects of shoe traction and obstacle height on friction during walking to better understand the mechanisms required to avoid slippage following obstacle clearance. Ten male subjects walked at a self-selected pace during eight different conditions: four obstacle heights (0%, 10%, 20%, and 40% of limb length) while wearing two different pairs of shoes (low and high traction). Frictional forces were calculated from the ground reaction forces following obstacle clearance, which were sampled with a Kistler platform at 960 Hz. All frictional peaks increased with increases in obstacle height. Low traction shoes yielded smaller peaks than high traction shoes. The transition from braking to propulsion occurred sooner due to altered control strategies with increased obstacle height. Collectively, these results provided insights into kinetic strategies of leading limb when confronted with low traction and high obstacle environments

The effects of shoe traction and obstacle height on lower extremity coordination dynamics during walking.

This study aims to investigate the effects of shoe traction and obstacle height on lower extremity relative phase dynamics (analysis of intralimb coordination) during walking to better understand the mechanisms employed to avoid slippage following obstacle clearance. Ten participants walked at a self-selected pace during eight conditions: four obstacle heights (0%, 10%, 20%, and 40% of limb length) while wearing two pairs of shoes (low and high traction). A coordination analysis was used and phasing relationships between lower extremity segments were examined. The results demonstrated that significant behavioral changes were elicited under varied obstacle heights and frictional conditions. Both decreasing shoe traction and increasing obstacle height resulted in a more in-phase relationship between the interacting lower limb segments. The higher the obstacle and the lower the shoe traction, the more unstable the system became. These changes in phasing relationship and variability are indicators of alterations in coordinative behavior, which if pushed further may have lead to falling

The Effects of Shoe Traction and Obstacle Height on Lower Extremity Coordination Dynamics During Walking

This study aims to investigate the effects of shoe traction and obstacle height on lower extremity relative phase dynamics (analysis of intralimb coordination) during walking to better understand the mechanisms employed to avoid slippage following obstacle clearance. Ten participants walked at a self-selected pace during eight conditions: four obstacle heights (0%, 10%, 20%, and 40% of limb length) while wearing two pairs of shoes (low and high traction). A coordination analysis was used and phasing relationships between lower extremity segments were examined. The results demonstrated that significant behavioral changes were elicited under varied obstacle heights and frictional conditions. Both decreasing shoe traction and increasing obstacle height resulted in a more in-phase relationship between the interacting lower limb segments. The higher the obstacle and the lower the shoe traction, the more unstable the system became. These changes in phasing relationship and variability are indicators of alterations in coordinative behavior, which if pushed further may have lead to falling

What's in your next-generation sequence data? An exploration of unmapped DNA and RNA sequence reads from the bovine reference individual.

BackgroundNext-generation sequencing projects commonly commence by aligning reads to a reference genome assembly. While improvements in alignment algorithms and computational hardware have greatly enhanced the efficiency and accuracy of alignments, a significant percentage of reads often remain unmapped.ResultsWe generated de novo assemblies of unmapped reads from the DNA and RNA sequencing of the Bos taurus reference individual and identified the closest matching sequence to each contig by alignment to the NCBI non-redundant nucleotide database using BLAST. As expected, many of these contigs represent vertebrate sequence that is absent, incomplete, or misassembled in the UMD3.1 reference assembly. However, numerous additional contigs represent invertebrate species. Most prominent were several species of Spirurid nematodes and a blood-borne parasite, Babesia bigemina. These species are either not present in the US or are not known to infect taurine cattle and the reference animal appears to have been host to unsequenced sister species.ConclusionsWe demonstrate the importance of exploring unmapped reads to ascertain sequences that are either absent or misassembled in the reference assembly and for detecting sequences indicative of parasitic or commensal organisms

Pan-cancer interrogation of MUTYH variants reveals biallelic inactivation and defective base excision repair across a spectrum of solid tumors

Purpose Biallelic germline pathogenic variants of the base excision repair (BER) pathway gene MUTYH predispose to colorectal cancer (CRC) and other cancers. The possible association of heterozygous variants with broader cancer susceptibility remains uncertain. This study investigated the prevalence and consequences of pathogenic MUTYH variants and MUTYH loss of heterozygosity (LOH) in a large pan-cancer analysis. Materials and Methods Data from 354,366 solid tumor biopsies that were sequenced as part of routine clinical care were analyzed using a validated algorithm to distinguish germline from somatic MUTYH variants. Results Biallelic germline pathogenic MUTYH variants were identified in 119 tissue biopsies. Most were CRCs and showed increased tumor mutational burden (TMB) and a mutational signature consistent with defective BER (COSMIC Signature SBS18). Germline heterozygous pathogenic variants were identified in 5,991 biopsies and their prevalence was modestly elevated in some cancer types. About 12% of these cancers (738 samples: including adrenal gland cancers, pancreatic islet cell tumors, nonglioma CNS tumors, GI stromal tumors, and thyroid cancers) showed somatic LOH for MUTYH, higher rates of chromosome 1p loss (where MUTYH is located), elevated genomic LOH, and higher COSMIC SBS18 signature scores, consistent with BER deficiency. Conclusion This analysis of MUTYH alterations in a large set of solid cancers suggests that in addition to the established role of biallelic pathogenic MUTYH variants in cancer predisposition, a broader range of cancers may possibly arise in MUTYH heterozygotes via a mechanism involving somatic LOH at the MUTYH locus and defective BER. However, the effect is modest and requires confirmation in additional studies before being clinically actionable

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

<p>Abstract</p> <p>Background</p> <p>Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.</p> <p>Methods</p> <p>Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.</p> <p>Results</p> <p>Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.</p> <p>Conclusions</p> <p>These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.</p

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.Results: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n is about 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesC[pi]) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.Conclusions: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.Peer reviewedAnimal Scienc