Effects of 9cis,11trans and 10trans,12cis CLA on osteoclast formation and activity from human CD14+ monocytes
Bibliographic record
Abstract
BACKGROUND: Mixed CLA isomers variably affect bone resorption in animals and decrease osteoclast formation and activity in murine osteoclasts. These variable effects may be due to the different isomers present in commercial preparations of CLA, and the effects of the predominant individual isomers, 9cis,11trans (9,11) and 10trans,12cis (10,12) CLA are not clear. The objectives of this study were to determine the effects of the individual CLA isomers on osteoclast formation and activity from human CD14+ monocytes, and to determine whether any changes are accompanied by changes in cathepsin K, matrix metalloproteinase-9 (MMP-9), receptor activator of NF-kappaB (RANK) and tumour necrosis factor alpha (TNFalpha) gene expression. Osteoclasts were identified as TRAP+ multinucleated cells. Osteoclast activity was quantified by the amount of TRAP in the cultured media. RESULTS: At 50 microM, 9,11 CLA inhibited osteoclast formation by approximately 70%, and both 9,11 and 10,12 CLA decreased osteoclast activity by approximately 85-90%. Both isomers inhibited cathepsin K (50 microM 9,11 by approximately 60%; 10,12 by approximately 50%) and RANK (50 microM 9,11 by approximately 85%; 50 microM 10,12 by approximately 65%) expression, but had no effect on MMP-9 or TNFalpha expression. CONCLUSION: 9,11 CLA inhibits osteoclast formation and activity from human cells, suggesting that this isomer may prevent bone resorption in humans. Although 10,12 CLA did not significantly reduce osteoclast formation, it reduced osteoclast activity and cathepsin K and RANK expression, suggesting that this isomer may also affect bone resorption.
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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) | 0.002 | 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".