p75 Neurotrophin Receptor Protects Primary Cultures of Human Neurons against Extracellular Amyloid β Peptide Cytotoxicity
Bibliographic record
Abstract
The cytotoxicity of extracellular amyloid beta peptide (Abeta) has been clearly demonstrated in many cell types. In contrast, primary human neurons in culture are resistant to extracellular Abeta-mediated toxicity. Here, we investigate the involvement of p75 neurotrophin receptor (p75NTR) in Abeta-treated human neurons. We find that Abeta1-40 and Abeta1-42, but not the reverse control peptide, Abeta40-1, rapidly increase the levels of p75NTR in a specific and dose-dependent manner. In contrast to observations in cell lines, enhanced expression of p75NTR in human neurons via a herpes simplex virus amplicon vector does not increase the susceptibility of neurons to Abeta. Unexpectedly, inhibition of p75NTR expression with an antisense expression construct or incubation of the cells with an antibody to the extracellular domain of p75NTR sensitizes human neurons to extracellular nonfibrillar or fibrillar Abeta1-42 cytotoxicity. Unlike intracellular Abeta, extracellular Abeta toxicity is independent of p53 and Bax activity. However, Abeta toxicity is inhibited by caspase inhibitors and the glycogen synthase kinase 3beta inhibitor lithium. Neuroprotection against Abeta is phosphatidylinositide 3-kinase dependent but Akt independent. These results are consistent with a neuroprotective role for p75NTR against extracellular Abeta toxicity in human neurons.
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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) | 0.002 | 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".