Novel regulatory roles of carboxylesterase 3 in lipid metabolism and browning in 3T3-L1 white adipocytes
Bibliographic record
Abstract
The role of carboxylesterase 3 (Ces3) in the lipolysis of adipocytes has been overlooked, as 2 major lipolytic enzymes, hormone-sensitive lipase and adipose triglyceride lipase, play more powerful roles in lipolysis. In this study, we explored the effects of Ces3 in lipid metabolism by activating and inhibiting, as well as silencing, Ces3-encoding gene in 3T3-L1 cell model. Our results demonstrated that activation of Ces3 increased adipogenesis, and attenuated lipogenesis, whereas it promoted lipolysis and fatty acid oxidation. In addition, activated Ces3 led to enhanced expression of core fat browning marker genes and proteins, suggesting that Ces3 may play a pivotal role in fat browning and thermogenesis. In contrast, deficiency of Ces3 nullified the browning effect in white adipocytes, along with decreased adipogenesis in 3T3-L1 adipocytes. Interestingly, the expression pattern of adipose triglyceride lipase was in line with Ces3, whereas hormone-sensitive lipase was independently regulated irrespective of Ces3 expression levels, suggesting that Ces3 may play an important and compensatory role in the breakdown of triglycerides in white adipocytes. In conclusion, we provide the first evidence that activation of Ces3 contributes in the browning of white adipocytes, and maintains a balance in lipid metabolism, which could be a potential strategy in fighting against obesity.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".