Failure of a dietary model to affect markers of inflammation in domestic cats
Bibliographic record
Abstract
BACKGROUND: Oxidative stress and inflammation can be altered by dietary factors in various species. However, little data are available in true carnivorous species such as domestic cats. As numerous anti-inflammatory and anti-oxidative additives become available and might be of use in cats with chronic low-grade inflammatory diseases, the current study aimed to develop a model of diet-induced inflammation by use of two opposite diets. It was hypothesized that a high fat diet enhanced in n-6 PUFA and with lower concentrations of antioxidants would evoke inflammation and oxidative stress in domestic cats. RESULTS: Sixteen healthy adult cats were allocated to two groups. One group received a moderate fat diet, containing pork lard and salmon oil (AA:(EPA + DHA) ratio 0.19) (MFn-3), while the other group was fed a high fat diet, containing pork lard and chicken fat (AA:(EPA + DHA) ratio 2.06) (HFn-6) for 12 weeks. Prior to and 2, 4, 6, 8, 10 and 12 weeks after starting the testing period, blood samples were collected. Erythrocytic fatty acid profile showed clear alterations in accordance to the dietary fatty acid profile. Serum thiobarbituric acid reactive substances was higher when fed MFn-3 compared to the HFn-6, suggesting augmented oxidative stress. This was associated with a reduced serum vitamin E status, as serum α-tocopherol concentrations were lower with MFn-3, even with higher dietary levels of vitamin E. Serum cytokine and serum amyloid A concentrations were not influenced by diet. CONCLUSION: These results point towards a resistance of cats to develop dietary fat-induced inflammation, but also suggest a high susceptibility to oxidative stress when fed a fish oil-supplemented diet even with moderate fat level and additional vitamin E.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".