14-3-3σ associates with cell surface aminopeptidase N in the regulation of matrix metalloproteinase-1
Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) are implicated in the degradation of the extracellular matrix during development and tissue repair, as well as in pathological conditions such as tumor invasion and fibrosis. MMP expression by stromal cells is partly regulated by signals from the neighboring epithelial cells. Keratinocyte-releasable 14-3-3sigma, or stratifin, acts as a potent MMP-1-stimulatory factor in fibroblasts. However, its mechanism of transmembrane signaling remains unknown. Ectodomain biotin labeling, serial affinity purification and mass spectroscopy analysis revealed that the stratifin associates with aminopeptidase N (APN), or CD13, at the cell surface. The transient knockdown of APN in fibroblasts eliminated the stratifin-mediated p38 MAP kinase activation and MMP-1 expression, implicating APN in a receptor-mediated transmembrane signaling event. Stratifin deletion studies implicated its C-terminus as a potential APN-binding site. Furthermore, the dephosphorylation of APN ectodomains reduced its binding affinity to the stratifin. The presence of a phosphorylated serine or threonine residue in APN has been implicated. Together, these findings provide evidence that APN is a novel cell surface receptor for stratifin and a potential target in the regulation of MMP-1 expression in epithelial-stromal cell communication.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".