Apoptosis Induced by p75NTR Overexpression Requires Jun Kinase-Dependent Phosphorylation of Bad
Bibliographic record
Abstract
The p75 neurotrophin receptor (p75NTR), a member of the tumor necrosis factor receptor superfamily, facilitates apoptosis during development and after injury to the CNS. The signaling cascades activated by p75NTR that result in apoptosis remain poorly understood. In this study, we show that overexpression of p75NTR in primary cortical neurons, in pheochromocytoma cell line (PC12) cells, and in glioma cells results in activation of Jun kinase (JNK), accumulation of cytochrome c within the cytosol, and activation of caspases 9, 6, and 3. To link p75NTR-dependent JNK activation to mitochondrial cytochrome c release, regulation of BH3-domain-only family members was examined. Transcription of BH3-domain-only family members was not induced by p75NTR, but p75NTR-dependent JNK activation resulted in phosphorylation and oligomerization of the BH3-domain-only family member Bad. Loss of function experiments using Bad dominant negatives or RNA interference demonstrated a requirement for Bad in p75NTR-induced apoptosis. Together, these studies provide the first data linking apoptosis induced by p75NTR to the phosphorylation of BH3-domain-only family members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".