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Andrew T. Miller

Researcher at Waltham Centre for Pet Nutrition

Publications -  8
Citations -  348

Andrew T. Miller is an academic researcher from Waltham Centre for Pet Nutrition. The author has contributed to research in topics: Postprandial & Insulin. The author has an hindex of 6, co-authored 8 publications receiving 317 citations.

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Journal ArticleDOI

Geometric analysis of macronutrient selection in the adult domestic cat, Felis catus

TL;DR: It is shown that cats have a ceiling for carbohydrate intake, which limits ingestion and constrains them to deficits in protein and fat intake (relative to their target) on high-carbohydrate foods.
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Geometric analysis of macronutrient selection in breeds of the domestic dog, Canis lupus familiaris

TL;DR: It is shown that the macronutrient content of the diet was regulated to a protein:fat:carbohydrate ratio of approximately 30:63:7% by energy, a value that was remarkably similar across breeds, and interpreted in relation to the evolutionary history of domestic dogs and equivalent studies on domestic cats.
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Consistent proportional macronutrient intake selected by adult domestic cats (Felis catus) despite variations in macronutrient and moisture content of foods offered

TL;DR: Results indicate that a mammalian obligate carnivore, the domestic cat, is able to regulate food selection and intake to balance macronutrient intake despite differences in moisture content and textural properties of the foods provided.
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The effect of dietary starch level on postprandial glucose and insulin concentrations in cats and dogs.

TL;DR: The time lag between eating the HS diet and the subsequent prolonged elevation of plasma glucose concentration seen in cats may reflect metabolic adaptations that result in a slower digestive and absorptive capacity for complex carbohydrate.
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Accuracy of the use of triaxial accelerometry for measuring daily activity as a predictor of daily maintenance energy requirement in healthy adult Labrador Retrievers

TL;DR: Improved accuracy in estimations of MER could be made for each dog if an accelerometer was used to record its daily activity, and a marked improvement in predictive accuracy of the regression model, compared with that for a model that used only body weight.