Impact of dietary protein on lipid metabolism in hamsters is source-dependent and associated with changes in hepatic gene expression
Bibliographic record
Abstract
This study tested the hypothesis that protein source is a factor determining the impact of the diet on lipid metabolism in hamsters. Twenty-eight hamsters of similar body weight were assigned for a period of 8 weeks to one of the following four diets (seven per group) containing either 20 % (w/w) casein (CAS), beef protein (BF), wheat gluten (WG) or soya protein (SOY). The fat composition of the diet was the same (15.5 % w/w) in all groups and provided SFA, MUFA and PUFA representative of the average Canadian diet. After an overnight fast, blood and liver were collected for the measurement of serum lipids, fatty acid composition of liver phospholipids and mRNA levels of selected genes involved in lipid metabolism. WG resulted in lower total cholesterol, HDL-cholesterol and non-HDL-cholesterol but, along with SOY, in higher mRNA levels of cholesterol 7 alpha-hydroxylase and LDL receptor. Furthermore, both WG and SOY resulted in lower 18 : 3n-3, 20 : 4n-6, total n-6 PUFA, 18 : 1n-9 and total MUFA, but higher 22 : 6n-3, total n-3 PUFA, 22 : 6n-3/18 : 3n-3 and 22 : 5n-3/18 : 3n-3 ratios in liver phospholipids, and higher hepatic Delta6-desaturase mRNA levels. These results show that the impact of dietary protein on lipid metabolism is source-dependent and associated with changes in mRNA abundances of key hepatic enzymes and receptors.
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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) | 0.001 | 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 | 0.000 |
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 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".