The in Vivo Brain Interactome of the Amyloid Precursor Protein
Bibliographic record
Abstract
Despite intense research efforts, the physiological function and molecular environment of the amyloid precursor protein has remained enigmatic. Here we describe the application of time-controlled transcardiac perfusion cross-linking, a method for the in vivo mapping of protein interactions in intact tissue, to study the interactome of the amyloid precursor protein (APP). To gain insights into the specificity of reported protein interactions the study was extended to the mammalian amyloid precursor-like proteins (APLP1 and APLP2). To rule out sampling bias as an explanation for differences in the individual datasets, a small scale quantitative iTRAQ (isobaric tags for relative and absolute quantitation)-based comparison of APP, APLP1, and APLP2 interactomes was carried out. An interactome map was derived that confirmed eight previously reported interactions of APP and revealed the identity of more than 30 additional proteins that reside in spatial proximity to APP in the brain. Subsequent validation studies confirmed a physiological interaction between APP and leucine-rich repeat and Ig domain-containing protein 1, demonstrated a strong influence of Ig domain-containing protein 1 on the proteolytic processing of APP, and consolidated similarities in the biology of APP and p75.
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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 | 0.001 | 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 | 0.000 |
| 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".