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Record W2903879517 · doi:10.1093/jas/sky404.355

PSXIII-9 Essential amino acid intake in obese cats before and after weight loss on a veterinary therapeutic food intended for maintenance and weight loss.

2018· article· en· W2903879517 on OpenAlexaffabout
Crystal Yates, Anna K. Shoveller, Shauna L. Blois, Marica Bakovic, Adronie Verbrugghe

Bibliographic record

VenueJournal of Animal Science · 2018
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWeight lossCATSMedicineValineAnimal scienceIsoleucineArginineBreedLeucineInternal medicineAmino acidEndocrinologyObesityBiologyBiochemistry

Abstract

fetched live from OpenAlex

Insufficient data exists regarding provision of adequate amounts of essential nutrients to obese cats during energy restriction. This study aimed to investigate predicted dietary intake of essential amino acids (AA) in obese cats undergoing energy restriction for weight loss and compare with National Research Council (NRC) 2006 recommendations. Sixteen obese cats, included in a non-randomized retrospective observational study, were fed a veterinary therapeutic food intended for maintenance and weight loss during a 4-week weight maintenance period (100Kcal/kg^0.67) followed by 10-weeks of energy restriction (0.6 x 130Kcal/kg^0.4). All procedures were approved by the University of Guelph Animal Care and Use Committee (AUP#2496). Essential AA including arginine, histidine, isoleucine, leucine, lysine, phenylalanine, tyrosine, threonine, tryptophan and valine were determined. Each cat’s minimum, maximum and average daily intake of AA were calculated from food logs, and compared to NRC recommended allowance (RA), and adequate intake (AI) for adult cats. Energy consumption was 221.5 ± 24.4 kcal/day during the weight maintenance period and 138.2 ± 10.2 kcal/ day during energy restriction. Cats lost 672 g ± 303 g during energy restriction, representing a weight loss rate of 0.94 ± 0.28 %/week. Intakes of all measured AA, except arginine, were within NRC RA per (kg ideal body weight)^0.67 for all 16 cats. During weight maintenance, average daily arginine intake was 8.42% below AI and RA for one cat and minimum intakes 24.74% (2.10–36.32%) below AI and RA for five cats. Minimum, maximum and average daily arginine intakes were 20.53% (12.11–27.9%), 16.84% (8.95–24.74%), and 19.47% (12.11–26.84%) below AI and RA respectively during energy restriction. Despite lower calculated intakes of arginine compared to published recommendations, cats remained clinically healthy and showed no clinical signs of deficiency. Arginine requirements and health risks associated with intakes below recommended allowances during energy restriction in obese cats warrant further investigation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.020
GPT teacher head0.297
Teacher spread0.278 · 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 designObservational
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
Published2018
Admission routes2
Has abstractyes

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