Endothelial Cell Surface Expressed Chemotaxis and Apoptosis Regulator (ECSCR) Regulates Lipolysis in White Adipocytes via the PTEN/AKT Signaling Pathway
Bibliographic record
Abstract
Elevated plasma triglycerides are associated with increased susceptibility to heart disease and stroke, but the mechanisms behind this relationship are unclear. A clearer understanding of gene products which influence plasma triglycerides might help identify new therapeutic targets for these diseases. The Endothelial Cell Surface expressed Chemotaxis and apoptosis Regulator (ECSCR) was initially studied as an endothelial cell marker, but has recently been identified in white adipocytes, the primary storage cell type for triglycerides. Here we confirm ECSCR expression in white adipocytes and show that Ecscr knockout mice show elevated fasting plasma triglycerides. At a cellular level, cultured 3T3-L1 adipocytes silenced for Ecscr show a blunted Akt phosphorylation response. Additionally we show that the phosphatase and tensin homology containing (PTEN) lipid phosphatase association with ECSCR is increased by insulin stimulation. These data suggest a scenario by which ECSCR contributes to control of white adipocyte lipolysis. In this scenario, white adipocytes lacking Ecscr display elevated PTEN activity, thereby reducing AKT activation and impairing insulin-mediated suppression of lipolysis. Collectively, these results suggest that ECSCR plays a critical function in regulating lipolysis in white adipose tissue.
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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".