Stress-induced expression of the p75 neurotrophin receptor is regulated by O-GlcNAcylation of the Sp1 transcription factor
Bibliographic record
Abstract
Injury-induced expression of p75 neurotrophin receptor (p75NTR) in the CNS induces neuronal apoptosis and prevents neuronal regrowth. The mechanisms regulating injury-induced p75NTR expression are poorly characterized but previous studies have established that reductions in extracellular osmolarity which mimic cytotoxic edema induce p75NTR gene expression through pathways that activate the Sp1 transcription factor. In this report, we examined how extracellular osmolarity converges on Sp1 to regulate p75NTR expression. We report that levels of O-linked N-acetylglucosamine (O-GlcNAc) transferase (OGT), the enzyme that mediates O-linked attachment of GlcNAc, are reduced by extracellular hypo-osmolarity and that global levels of protein O-GlcNAcylation and of Sp1 show a corresponding decline. We demonstrate that chemical and RNAi-based treatments that reduce cellular O-GlcNAcylation facilitate p75NTR induction by hypo-osmolarity, directly linking protein O-GlcNAcylation to p75NTR induction. To determine if Sp1 O-GlcNAc content regulates p75NTR expression, we replaced endogenous Sp1 with a Sp1 mutated at O-GlcNAc target residues. This O-GlcNAc-deficient form of Sp1-enhanced p75NTR expression, demonstrating that O-GlcNAcylation of Sp1 negatively regulates p75NTR expression. We conclude that a stress-induced decline in the O-GlcNAc content of Sp1 drives expression of p75NTR.
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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) | 0.001 | 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".