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Effect of dietary mannoheptulose on whole body glucose and energy metabolism in adult neutered male Labrador Retrievers

2013· article· en· W3171940376 on OpenAlexaffabout
Leslie L. McKnight, Elizabeth A. Flickinger, Gary M Davenport, J. France, Anna K. Shoveller

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEndocrinologyInternal medicineRespiratory quotientCarbohydrate metabolismMealInsulinMetabolismChemistryBiologyMedicine

Abstract

fetched live from OpenAlex

The objective of this study was to determine the effect of dietary mannoheptulose (MH) on glucose and energy metabolism in adult male neutered Labrador Retrievers (N = 6, 5.4 y). This study was designed as a cross‐over with each dog receiving both dietary treatments, control (CON) and MH (200 mg/kg), in random order. Fasting and post‐prandial respiratory quotient (RQ) and energy expenditure (EE) were determined by indirect calorimetry (d 16). Glucose kinetics were assessed during fasting and repeated meal feeding using indirect calorimetry and a primed continuous infusion of U‐13C‐glucose (d 18). A fasting biceps femoris muscle sample was obtained (d 21/22) to determine protein content of phosphorylated and total adenosine monophosphate‐activated protein kinase (AMPK) and acetyl CoA carboxylase (ACC). Diet did not affect plasma glucose, insulin, FFA or glucose turnover during fasting or repeated meal feeding. There were no diet‐related differences in glucose oxidation or energy metabolism in the fed state. However, there were trends for MH to increase RQ (p=0.14) and glucose oxidation (p=0.16) and to lower the ratio of phosphorylated to total AMPK protein content (P=0.08) during fasting. These findings suggest daily MH feeding may affect carbohydrate utilization during fasting. Grant Funding Source : Procter and Gamble Pet Care

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.265
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes2
Has abstractyes

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