Macronutrient and energy metabolism changes in domestic cats when fed cornstarch, whey protein, and, poultry fat
Bibliographic record
Abstract
Abstract There is a lack of knowledge available on how cats adjust their macronutrient partitioning due to the consumption of single-macronutrient meals. The objective of this study was to evaluate consumption of a single meal of ingredients that contained foods of strictly carbohydrates (CHO), fat (FAT) or protein (PRO), on energy expenditure (EE) and macronutrient metabolism in cats. Ten domestic shorthair adult cats (1·9 years; 4·12 kg) were fed 22–24 g of chicken fat (FAT), 56–62 g of whey protein solution (PRO) or 54–56 g of cornstarch solution (CHO) for a single day in a randomised complete block design. Indirect calorimetry was conducted for 24 h post-feeding. Mean average EE over 24 h was highest in cats fed PRO (44 kcal/kg BW) and FAT (43 kcal/kg BW) compared with that in cats fed CHO (42 kcal/kg BW; P < 0·01). During 0 to 4 h, cats fed FAT had greater EE (49 kcal/kg BW), suggesting that cats respond to oxidising more dietary fat over protein in the early postprandial stage. Mean 24 h respiratory quotient (RQ) was greatest for cats fed CHO (0·76) followed by PRO (0·75) and FAT (0·74; P < 0·05). During 4 to 8 h, the RQ of cats fed PRO was the greatest (0·77), suggesting that cats initially increase gluconeogenesis from amino acids for subsequent glucose oxidation. In comparison to omnivores and herbivores, obligate carnivores have unique responses to single macronutrient intake, where they apparently generate energy from carbohydrate metabolism and rely more on gluconeogenic precursors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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.
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 teacher head, 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".