Reduced SCD1 activity alters markers of fatty acid reesterification, glyceroneogenesis, and lipolysis in murine white adipose tissue and 3T3-L1 adipocytes
Bibliographic record
Abstract
White adipose tissue (WAT) has a critical role in lipid handling. Previous work demonstrated that SCD1 is an important regulator of WAT fatty acid (FA) composition; however, its influence on the various interconnected pathways influencing WAT lipid handling remains unclear. Our objective was to investigate the role of SCD1 on WAT lipid handling using Scd1 knockout (KO) mice and SCD1-inhibited 3T3-L1 adipocytes by measuring gene, protein, and metabolite markers related to FA reesterification, glyceroneogenesis, and lipolysis. Triacylglycerol (TAG) content was higher in inguinal WAT (iWAT) from KO mice compared with wild-type, but significantly lower in epididymal WAT (eWAT). The SCD1 desaturation index was decreased in both WAT depots in KO mice. FA reesterification, as measured with a NEFA:glycerol ratio, was reduced in both WAT depots in KO mice, as well as SCD1-inhibited 3T3-L1 adipocytes. Pck1, Atgl, and Hsl gene expression was reduced in both WAT depots of KO mice, while Pck2 and Pdk4 gene expression showed depot-specific regulation. Pck1, Atgl, and Hsl gene expression was reduced, and phosphoenolpyruvate carboxykinase protein content was ablated, in SCD1-inhibited adipocytes. Our data provide evidence that SCD1 has a broad impact on WAT lipid handling by altering TAG composition in a depot-specific manner, reducing FA reesterification, and regulating markers of lipolysis and glyceroneogenesis.
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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 | 0.001 | 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 | 0.001 |
| 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".