PSXIII-B-3 Determining Phenylalanine and Tyrosine Amino Acid Requirements in Growing Labrador Retrievers Using the Direct Amino Acid Oxidation Technique
Bibliographic record
Abstract
Abstract Phenylalanine and tyrosine are important amino acids for synthesis of proteins, catecholamine neurotransmitters, and melanin in canines. Since phenylalanine (Phe) is converted to tyrosine (Tyr), this experiment used the direct amino acid oxidation (DAAO) technique to determine the phenylalanine requirement and phenylalanine plus tyrosine requirements for growing Labrador Retrievers. The Phe requirement was separated from Phe plus Tyr requirement by supplementing the test diets utilized for Phe requirements with 1.48% crystalline Tyr. A total of twelve dogs were used in two trials to determine the Phe and Phe + Tyr requirements in growing puppies ( >14wk-1yr). Control diet was fed for two days, followed by a testing day where an experimental diet was fed, a tracer amino acid was supplied, and breath samples were collected. On test day, a priming dose of L-[1-13C] phenylalanine (Cambridge Isotope Laboratories, Inc.) based on the dog’s body weight was supplied, followed by enteral feeding of [1-13C]Phe every 30 minutes, spanning a four hour period. Respiration masks were placed on each subject every 30 minutes (Oxymax, Columbus Instruments), 13CO2 collected, and enrichment determined by isotope ratio mass spectrometry (IRMS). Results for IRMS were converted to atom percent excess (APE) and analyzed using a segmented model (JMP® Pro 15). Results showed that Phe mean and population safe requirements were 1.29 +/- 0.26 g/1000 kcal, while the Phe + Tyr requirements were 1.95 +/- 0.65 g/1000 kcal. Knowledge gathered through these studies is invaluable as both the Phe and Phe plus Tyr dietary requirements for growing Labrador Retriever puppies were determined.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".