Metalloprotease Meprin β Generates Nontoxic N-terminal Amyloid Precursor Protein Fragments in Vivo
Bibliographic record
Abstract
Identification of physiologically relevant substrates is still the most challenging part in protease research for understanding the biological activity of these enzymes. The zinc-dependent metalloprotease meprin β is known to be expressed in many tissues with functions in health and disease. Here, we demonstrate unique interactions between meprin β and the amyloid precursor protein (APP). Although APP is intensively studied as a ubiquitously expressed cell surface protein, which is involved in Alzheimer disease, its precise physiological role and relevance remain elusive. Based on a novel proteomics technique termed terminal amine isotopic labeling of substrates (TAILS), APP was identified as a substrate for meprin β. Processing of APP by meprin β was subsequently validated using in vitro and in vivo approaches. N-terminal APP fragments of about 11 and 20 kDa were found in human and mouse brain lysates but not in meprin β(-/-) mouse brain lysates. Although these APP fragments were in the range of those responsible for caspase-induced neurodegeneration, we did not detect cytotoxicity to primary neurons treated by these fragments. Our data demonstrate that meprin β is a physiologically relevant enzyme in APP processing.
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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 | 0.000 |
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".