Publications by authors named "M Hollifield"

Background: With the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs.

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Estimating heritabilities with large genomic models by established methods such as restricted maximum likelihood (REML) or Bayesian via Gibbs sampling is computationally expensive. Alternatively, heritability can be estimated indirectly by method R and by maximum predictivity, referred to as MaxPred here, at a much lower computing cost. By method R, the heritability used for predictions with whole and partial data is considered the best estimate when the predictions based on partial data are unbiased relative to those with the complete data.

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Importance: Current interventions for posttraumatic stress disorder (PTSD) are efficacious, yet effectiveness may be limited by adverse effects and high withdrawal rates. Acupuncture is an emerging intervention with positive preliminary data for PTSD.

Objective: To compare verum acupuncture with sham acupuncture (minimal needling) on clinical and physiological outcomes.

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Protein S (PS), the critical plasma cofactor for the anticoagulants tissue factor (TF) pathway inhibitor (TFPI) and activated protein C (APC), circulates in two functionally distinct pools: free (anticoagulant) or bound to complement component 4b-binding protein (C4BP) (anti-inflammatory). Acquired free PS deficiency is detected in several viral infections, but its cause is unclear. Here, we identified a shear-dependent interaction between PS and von Willebrand Factor (VWF) by mass spectrometry.

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Evaluations using single-step genomic BLUP require blending the genomic relationship matrix () with a positive definite matrix to ensure nonsingularity for solving the mixed model equations. Many organizations blend with a proportion of the numerator relationship matrix for genotyped animals ( ) to improve stability and possibly add a residual polygenic effect. However, when nearly all the polygenic variance is explained by , blending with may cause inflation and add excess computing time; thus, blending with an identity matrix () multiplied by a small value may be a better solution.

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