MKP-1 reduces Aβ generation and alleviates cognitive impairments in Alzheimer’s disease models
Bibliographic record
Abstract
Abstract Mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) is an essential negative regulator of MAPKs by dephosphorylating MAPKs at both tyrosine and threonine residues. Dysregulation of the MAPK signaling pathway has been associated with Alzheimer’s disease (AD). However, the role of MKP-1 in AD pathogenesis remains elusive. Here, we report that MKP-1 levels were decreased in the brain tissues of patients with AD and an AD mouse model. The reduction in MKP-1 gene expression appeared to be a result of transcriptional inhibition via transcription factor specificity protein 1 (Sp1) cis -acting binding elements in the MKP-1 gene promoter. Amyloid-β (Aβ)-induced Sp1 activation decreased MKP-1 expression. However, upregulation of MKP-1 inhibited the expression of both Aβ precursor protein (APP) and β-site APP-cleaving enzyme 1 by inactivating the extracellular signal-regulated kinase 1/2 (ERK)/MAPK signaling pathway. Furthermore, upregulation of MKP-1 reduced Aβ production and plaque formation and improved hippocampal long-term potentiation (LTP) and cognitive deficits in APP/PS1 transgenic mice. Our results demonstrate that MKP-1 impairment facilitates the pathogenesis of AD, whereas upregulation of MKP-1 plays a neuroprotective role to reduce Alzheimer-related phenotypes. Thus, this study suggests that MKP-1 is a novel molecule for AD treatment.
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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 | 0.000 |
| 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".