A new role for matrix metalloproteinase-3 in the NGF metabolic pathway: Proteolysis of mature NGF and sex-specific differences in the continuum of Alzheimer's pathology
Bibliographic record
Abstract
Matrix metalloproteinase-3 (MMP-3) has been associated with risk of Alzheimer's disease (AD). In this study we introduce a novel role for MMP-3 in degrading nerve growth factor (NGF) in vivo and examine its mRNA and protein expression across the continuum of AD pathology. We provide evidence that MMP-3 participates in the degradation of mature NGF in vitro and in vivo and that it is secreted from the rat cerebral cortex in an activity-dependent manner. We show that cortical MMP-3 is upregulated in the McGill-R-Thy1-APP transgenic rat model of AD-like amyloidosis. A similar upregulation was found in AD and MCI brains as well as in cognitively normal individuals with elevated amyloid deposition. We also observed that frontal cortex MMP-3 protein levels are higher in males. MMP-3 protein correlated with more AD neuropathology, markers of NGF metabolism, and lower cognitive scores in males but not in females. These results suggest that MMP-3 upregulation in AD might contribute to NGF dysmetabolism, and therefore to cholinergic atrophy and cognitive deficits, in a sex-specific manner. MMP-3 should be further investigated as a biomarker candidate or as a therapeutic target in AD.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".