Linoleic acid supplementation of cell culture media influences the phospholipid and lipid profiles of human reconstructed adipose tissue
Bibliographic record
Abstract
Reconstructed human adipose tissues represent novel tools available to perform in vitro pharmaco-toxicological studies. We used adipose-derived human stromal/stem cells to reconstruct, using tissue engineering techniques, such an adipose tridimensional model. To determine to what extent the in vitro model is representative of its native counterpart, adipogenic differentiation, triglycerides accumulation and phospholipids profiles were analysed. Ingenuity Pathway Analysis software revealed pathways enriched with differentially-expressed genes between native and reconstructed human adipose tissues. Interestingly, genes related to fatty acid metabolism were downregulated in vitro, which could be explained in part by the insufficient amount of essential fatty acids provided by the fetal calf serum used for the culture. Indeed, the lipid profile of the reconstructed human adipose tissues indicated a particular lack of linoleic acid, which could interfere with physiological cell processes such as membrane trafficking, signaling and inflammatory responses. Supplementation in the culture medium was able to influence the lipid profile of the reconstructed human adipose tissues. This study demonstrates the possibility to directly modulate the phospholipid profile of reconstructed human adipose tissues. This reinforces its use as a relevant physiological or pathological model for further pharmacological and metabolic studies of human adipose tissue functions.
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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) | 0.001 | 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".