Lipopolysaccharide Signals an Endothelial Apoptosis Pathway Through TNF Receptor-Associated Factor 6-Mediated Activation of c-Jun NH2-Terminal Kinase
Bibliographic record
Abstract
Inflammatory mediators such as TNF and bacterial LPS do not cause significant apoptosis of endothelial cells unless the expression of cytoprotective genes is blocked. In the case of TNF, the transcription factor NF-kappaB conveys an important survival signal. In contrast, even though LPS can also activate NF-kappaB, this signal is dispensable for LPS-inducible cytoprotective activity. LPS intracellular signals are transmitted through a member of the Toll-like receptor family, TLR4. This family of receptors transduces signals through a downstream molecule, TNFR-associated factor 6 (TRAF6). In this study, we demonstrate that the C-terminal fragment of TRAF6 (TRAF6-C) inhibits LPS-induced NF-kappaB nuclear translocation and c-Jun NH(2)-terminal kinase (JNK) activation in endothelial cells. In contrast, LPS activation of p38 kinase is not inhibited by TRAF6-C. TRAF6-C also inhibits LPS-initiated endothelial apoptosis, but potentiates TNF-induced apoptosis. LPS-induced loss of mitochondrial transmembrane potential, cytochrome c release, and caspase activation are all blocked by TRAF6-C. We demonstrate that TRAF6 signals apoptosis via JNK activation, since inhibition of JNK activation using a dominant-negative mutant also inhibits apoptosis. JNK inhibition blocks caspase activation, but the reverse is not true. Hence, JNK activation lies upstream of caspase activation in response to LPS stimulation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".