Metabotropic glutamate receptor 5 knockout reduces cognitive impairment and pathogenesis in a mouse model of Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) pathology occurs in part as the result of excessive production of β-amyloid (Aβ). Metabotropic glutamate receptor 5 (mGluR5) is now considered a receptor for Aβ and consequently contributes to pathogenic Aβ signaling in AD. RESULTS: Genetic deletion of mGluR5 rescues the spatial learning deficits observed in APPswe/PS1ΔE9 AD mice. Moreover, both Aβ oligomer formation and Aβ plaque number are reduced in APPswe/PS1ΔE9 mice lacking mGluR5 expression. In addition to the observed increase in Aβ oligomers and plaques in APPswe/PS1ΔE9 mice, we found that both mTOR phosphorylation and fragile X mental retardation protein (FMRP) expression were increased in these mice. Genetic deletion of mGluR5 reduced Aβ oligomers, plaques, mTOR phosphorylation and FMRP expression in APPswe/PS1ΔE9 mice. CONCLUSIONS: Thus, we propose that Aβ activation of mGluR5 appears to initiate a positive feedback loop resulting in increased Aβ formation and AD pathology in APPswe/PS1ΔE9 mice via mechanism that is regulated by FMRP.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".