Nitric oxide synthase inhibitors modulate nerve growth factor‐mediated regulation of amyloid precursor protein expression in PC12 cells
Bibliographic record
Abstract
Nerve growth factor (NGF) can regulate nitric oxide synthase (NOS) expression and nitric oxide (NO) can modulate NGF-mediated neurotrophic responses. In this study, the role of NO in NGF-stimulated amyloid precursor protein (APP) levels was studied. PC12 cells were treated with either the non-selective NOS inhibitor N(omega)-nitro-L-arginine methylester (L-NAME) or the inducible NOS selective inhibitor s-methylisothiourea (S-MIU), and the effect on NGF-mediated increases in APP expression was determined. NGF significantly increased total APP protein levels following 96 h of treatment and this increase was prevented in cells pre-treated with S-MIU. Pre-treatment of cells with actinomycin D also blocked this NGF-mediated induction of APP, indicating de novo protein synthesis is necessary. Treatment with NGF increased APP promoter activity; however, this increase was only partially inhibited by pre-treatment with S-MIU and was increased in the presence of L-NAME. This suggests that NO may be modulating other aspects of APP expression in addition to transcription. Inhibition of NGF signaling pathways was also investigated using inhibitors of mitogen-activated protein (MAP) kinase (U0126), Akt (LY294002) and protein kinase C (PKC; U73122 and bisindolylmaleimide 1 (BIS-1)) activation. Inhibition of each of these pathways prevented NGF-mediated increases in APP protein expression; however, only BIS-1 attenuated NGF-mediated increases in promoter activation. This study indicates that NO is involved in the NGF-mediated regulation of APP, in part at the level of APP transcription and could involve the modulation of NGF signal transduction pathways.
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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) | 0.001 | 0.001 |
| 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".