Involvement of Insulin-Like Growth Factor 1 Receptor Signaling in the Amyloid-β Peptide Oligomers-Induced p75 Neurotrophin Receptor Protein Expression in Mouse Hippocampus
Bibliographic record
Abstract
The p75 neurotrophin receptor (p75NTR) has been thought to play a critical role in amyloid-β peptide (Aβ)-mediated neurodegeneration and Aβ metabolism in Alzheimer's disease (AD) brains. Our previous report showed that membrane-associated p75NTR protein expression was significantly increased in the hippocampi of two different strains of transgenic AD mice and was associated with the age-dependent elevation of Aβ1-42 levels. Here, we provide evidence that the Aβ1-42 oligomers known as ADDLs (Aβ-derived diffusible ligands) induce p75NTR protein expression through insulin-like growth factor 1 receptor (IGF-1R) phosphorylation in SH-SY5Y human neuroblastoma cells. An in vivo microinjection study demonstrated that microinjected ADDLs increased the p75NTR protein expression by 1.4-fold in the ipsilateral hippocampus compared to the contralateral hippocampus. In addition, ADDLs microinjected into mouse hippocampi facilitated IGF-1R phosphorylation within 30 min and the co-administration of picropodophyllin, an IGF-1R kinase inhibitor, blocked ADDLs-induced p75NTR expression. We examined the possible involvement of IGF-1R in the increased p75NTR protein expression in the hippocampi of 6-month-old AβPPswe/PS1dE9 AD model mice that had accumulated significant amounts of Aβ1-42 and showed significantly higher p75NTR expression than age-matched wild-type mice. We found that IGF-1R phosphorylation in these transgenic mice was higher than that in the wild-type mice. These findings indicate that Aβ1-42 oligomers stimulate the p75NTR protein expression in the hippocampus through IGF-1R signaling. Thus, Aβ1-42 oligomers-mediated IGF-1R activation may trigger an increase in p75NTR protein expression in the hippocampus of AD brain during the early stages of disease development.
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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 | 0.001 | 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".