Tetraspanin 6: a pivotal protein of the multiple vesicular body determining exosome release and lysosomal degradation of amyloid precursor protein fragments
Bibliographic record
Abstract
BACKGROUND: The mechanisms behind Aβ-peptide accumulation in non-familial Alzheimer's disease (AD) remain elusive. Proteins of the tetraspanin family modulate Aβ production by interacting to γ-secretase. METHODS: We searched for tetraspanins with altered expression in AD brains. The function of the selected tetraspanin was studied in vitro and the physiological relevance of our findings was confirmed in vivo. RESULTS: Tetraspanin-6 (TSPAN6) is increased in AD brains and overexpression in cells exerts paradoxical effects on Amyloid Precursor Protein (APP) metabolism, increasing APP-C-terminal fragments (APP-CTF) and Aβ levels at the same time. TSPAN6 affects autophagosome-lysosomal fusion slowing down the degradation of APP-CTF. TSPAN6 recruits also the cytosolic, exosome-forming adaptor syntenin which increases secretion of exosomes that contain APP-CTF. CONCLUSIONS: TSPAN6 is a key player in the bifurcation between lysosomal-dependent degradation and exosome mediated secretion of APP-CTF. This corroborates the central role of the autophagosomal/lysosomal pathway in APP metabolism and shows that TSPAN6 is a crucial player in APP-CTF turnover.
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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".