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1.
J Anim Sci ; 90(7): 2222-32, 2012 Jul.
Article in English | MEDLINE | ID: mdl-22266992

ABSTRACT

It was hypothesized that a high-concentrate diet fed during early calfhood alters the expression of genes within the arcuate nucleus that subserve reproductive competence. Beef heifers (n = 12) were weaned at approximately 3 mo of age, and after acclimation, were allocated randomly to 1 of 2 nutritional groups: 1) High Concentrate/High Gain (HC/HG), a high concentrate diet fed to promote a gain of 0.91 kg/d; or 2) High Forage/Low Gain (HF/LG), a forage-based diet fed to promote a gain of 0.45 kg/d. Experimental diets were fed under controlled intake for 91 d. At the end of 91 d, heifers were slaughtered by humane procedures, blood samples were collected, brains were removed, liver weights were determined, and rumen fluid was collected for VFA analyses. Tissue blocks containing the hypothalamus were dissected from the brains, frozen, and cut using a cryostat, and frozen sections were mounted on slides. Tissue from the arcuate nucleus (ARC) was dissected from sections for mRNA extraction. Microarray analysis was used to assess genome-wide transcription in the ARC using a 60-mer oligonucleotide 44K bovine expression array. The ADG was greater (P < 0.001) in heifers fed the HC/HG diet than in heifers fed the HF/LG diet. At slaughter, mean propionate to acetate ratios in the ruminal fluid and liver weight as a percentage of BW were increased (P < 0.005) in HC/HG compared with HF/LG heifers. Mean serum concentrations of insulin (P < 0.05) and IGF-1 (P < 0.005) were greater, and leptin tended to be greater (P = 0.1) in HC/HG heifers compared with HF/LG heifers. Approximately 345 genes were observed to be differentially expressed in the HC/HG group with approximately two-thirds of the genes exhibiting increased expression in the HC/HG group. Genes exhibiting decreased expression in the HC/HG group included agouti-related protein and neuropeptide Y, products of which are known to regulate feed intake and energy expenditure. Functional annotation of enriched Gene Ontology terms indicates that a number of biological processes within the hypothalamus are affected by consumption of high-concentrate diets, including those related to control of feed intake, regulation of cellular metabolic processes, receptor and intracellular signaling, and neuronal communication. In summary, dietary treatments shown previously to accelerate the timing of pubertal onset in heifers increased ruminal propionate, promoted enhanced metabolic hormone secretion, and altered gene expression in the ARC.


Subject(s)
Animal Feed/analysis , Arcuate Nucleus of Hypothalamus/metabolism , Cattle/physiology , Diet/veterinary , Gene Expression Regulation/physiology , Animal Nutritional Physiological Phenomena , Animals , Arcuate Nucleus of Hypothalamus/drug effects , Body Fluids/chemistry , Fatty Acids, Volatile/chemistry , Female , Oligonucleotide Array Sequence Analysis/veterinary , RNA/genetics , RNA/metabolism , Reverse Transcriptase Polymerase Chain Reaction , Rumen , Sexual Maturation
2.
Article in English | MEDLINE | ID: mdl-19390645

ABSTRACT

There has been considerable interest recently in the application of bagging in the classification of both gene-expression data and protein-abundance mass spectrometry data. The approach is often justified by the improvement it produces on the performance of unstable, overfitting classification rules under small-sample situations. However, the question of real practical interest is whether the ensemble scheme will improve performance of those classifiers sufficiently to beat the performance of single stable, nonoverfitting classifiers, in the case of small-sample genomic and proteomic data sets. To investigate that question, we conducted a detailed empirical study, using publicly-available data sets from published genomic and proteomic studies. We observed that, under t-test and RELIEF filter-based feature selection, bagging generally does a good job of improving the performance of unstable, overfitting classifiers, such as CART decision trees and neural networks, but that improvement was not sufficient to beat the performance of single stable, nonoverfitting classifiers, such as diagonal and plain linear discriminant analysis, or 3-nearest neighbors. Furthermore, as expected, the ensemble method did not improve the performance of these classifiers significantly. Representative experimental results are presented and discussed in this work.

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