Lipopolysaccharide initiates a TRAF6-mediated endothelial survival signal
Bibliographic record
Abstract
Similar to tumor necrosis factor (TNF), bacterial lipopolysaccharide (LPS) elicits parallel apoptotic and antiapoptotic pathways in endothelial cells. The overall result is that there is minimal endothelial cell death in response to LPS without inhibition of the cytoprotective pathway. While the TNF-induced death and survival pathways have been relatively well elucidated, much remains to be learned about LPS signaling events in this regard. It is known that the transcription factor nuclear factor-kappaB (NF-kappaB) provides a critical cell survival signal in response to TNF, but is not an essential component of the LPS-induced survival pathway. The TNF receptor-associated factor 6 (TRAF6) is a major effector of multiple LPS-induced signals, including a c-Jun N-terminal kinase (JNK)-mediated apoptotic response. In this report we demonstrate that following LPS stimulation, TRAF6 also transmits an important endothelial cell survival signal in a situation of complete NF-kappaB blockade. In response to LPS, TRAF6 activates the phosphatidylinositol 3'-kinase (PI3K)/Akt pathway, but not ERK1/2 mitogen-activated protein kinases (MAPKs) in endothelial cells. Activation of PI3K signals a critical antiapoptotic pathway in response to LPS in endothelial cells, whereas ERK1/2 does not. Thus TRAF6 acts as a bifurcation point of the LPS-initiated death and survival signals in endothelial cells.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".