<i>Trans</i>-8,<i>cis</i>-10+<i>cis</i>-9,<i>trans</i>-11-conjugated linoleic acid mixture alters body composition in Syrian golden hamsters fed a hypercholesterolaemic diet
Bibliographic record
Abstract
The effectiveness of conjugated linoleic acid (CLA) as a weight-loss nutraceutical continues to be debatable, suggesting that there may be value in exploring the physiological effects of the lesser-known isomers. The effects of the minor isomer, trans-8, cis-10 (t8, c10)-CLA, in the form of an equimolar mixture with the cis-9, trans-11 (c9, t11) isomer, on body weight and body composition, circulating glucose and lipid concentrations, and liver weights were studied in sixty male Syrian golden hamsters. Animals were randomised to receive for 28 d a semi-purified, hypercholesterolaemic diet (5% dietary fat and 0.25% cholesterol) supplemented at the 2% level with either the t8, c10+c9, t11-CLA mixture, c9, t11-CLA or trans-10, cis-12 (t10, c12)-CLA replacing lard and safflower-seed oil (control). Results show that compared with control, the t8, c10+c9, t11-CLA mixture and t10, c12-CLA-fed animals had lower (P < 0.0001) fat mass following supplementation. Animals consuming t10, c12-CLA also possessed higher lean mass compared with control and c9, t11-CLA groups (P < 0.001). However, the livers of these animals were larger (P < 0.0001) compared with those in the control and other CLA groups. Body weights of the hamsters did not differ across the experimental groups. CLA treatments had no effect on serum glucose or lipid profile, except for inducing higher (P < 0.05) non-HDL-cholesterol concentration with t10, c12-CLA compared with the c9, t11 isomer. Overall, these results indicate that in male hamsters fed a hypercholesterolaemic diet, the t8, c10+c9, t11-CLA mixture does not have an impact on blood lipid profile, but is able to effectively reduce fat mass, without incurring an accompanying liver enlargement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".