PSX-A-5 Late-Breaking: Branched chain amino acid and threonine requirements for puppy (>14 wk-9mo) Labrador Retrievers using the indicator amino acid oxidation (IAAO) technique
Bibliographic record
Abstract
Abstract Branched chain amino acids are heavily involved in protein synthesis and turnover, emphasizing the need to establish requirement for growing animals. On the other hand, threonine is vital for supporting proteins necessary for gut health. Thus, it is very important to supply branched chain amino acids and threonine in appropriate amounts to growing animals. In this experiment, the indicator amino acid oxidation (IAAO) technique was utilized to determine valine, isoleucine, leucine, and threonine requirements in six puppy Labrador Retrievers (>14wk-9mo). Puppies were subjected to diets ranging from deficient to excess, with each of the indispensable amino acids formulated at 1.6x NRC values. The control diet was fed for two days of adaptation, followed by one experimental day in which the test diet was fed. On the test day, a breath sample was collected using a using a respiration mask (Oxymax, Columbus Instruments). A priming dose of L-[1-^13C]phenylalanine (Cambridge Isotope Laboratories, Inc.) based on body weight was supplied to each puppy, followed by [1-^13C]Phe doses every 30 minutes, for a four hour period. ^13CO[2] was collected after each dose and enrichment was determined by isotope ratio mass spectrometry (IRMS). Results from IRMS were converted to atom percent excess (APE) and analyzed using a segmented line model (JMP^® Pro 16). Each of the Four Rivers mean and population requirements were as follows: 1.72 ± 0.11 g/1000 kcal ME for valine; 1.43 ± 0.24 g/1000 kcal ME for isoleucine; 2.25 ± 0.15 g/1000 kcal ME for leucine; 1.74 ± 0.16 g/1000 kcal ME for threonine (mean ± 2SD). The knowledge gained from this study is highly useful as the lean mass deposited as a puppy influences the animal throughout their lifetime.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".