SCD1 mediates the influence of exogenous saturated and monounsaturated fatty acids in adipocytes: Effects on cellular stress, inflammatory markers and fatty acid elongation
Bibliographic record
Abstract
Palmitate (PA), stearate (SA), palmitoleate (PMA) and oleate (OA) are among the most abundant fatty acids (FAs) in adipose tissue (AT). These FAs differentially regulate AT inflammation by altering adipocyte signalling pathways and the secretion of proinflammatory cytokines. Intracellular levels of these FAs are controlled, in part, by stearoyl-CoA desaturase 1 (SCD1). Therefore, SCD1 may have an important role mediating FA-regulation of adipocyte inflammation. Given this, we hypothesized that the influence of PA, SA, PMA and OA on inflammation and cellular stress, as well as FA metabolism, would be exacerbated with reduced SCD1 activity. Real-time RT-PCR, immunoassays, gas chromatography and western blotting were used to examine the expression and secretion of common inflammatory markers, as well as FA profiles and markers of cellular stress, in 3T3-L1 adipocytes. FA treatments differentially affected inflammatory markers and FA profiles in SCD1-inhibited adipocytes. Specifically, SA significantly increased the expression of Ccl5 (5.3-fold) and Mcp-1 (3.2-fold), and the secretion of IL-6 (17.8-fold) and MCP-1 (4.0-fold) in SCD1-inhibited adipocytes compared to controls. The proinflammatory effects observed with SA are particularly notable given that SCD1-inhibited adipocytes increased elongation of PA to SA, as determined using U-(13)C-PA. The effects of PA, PMA and OA were not as substantial as those of SA, although PA did significantly increase Ccl5 (2.7-fold) and Mcp-1 (1.2-fold) expression in SCD1-inhibited adipocytes. None of the FAs altered markers of cellular stress. Collectively, these results emphasize the differential effects of individual FAs and highlight how SCD1 influences their regulation of adipocyte inflammation.
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 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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".