Differential regulation of the high‐affinity choline transporter by wild‐type and Swedish mutant amyloid precursor protein
Bibliographic record
Abstract
The high-affinity choline transporter (CHT) is responsible for choline uptake into cholinergic neurons, with this being the rate-limiting step for acetylcholine production. Altering CHT protein disposition directly impacts choline uptake activity and cholinergic neurotransmission. Amyloid precursor protein (APP) interacts with CHT proteins and increases their endocytosis from the cell surface. The goal of this study was to examine regulation of CHT trafficking and activity by wild-type APP (APPwt) and determine if this differs with Swedish mutant APP (APPSwe) in SH-SY5Y human neuroblastoma cells. APPSwe differs from APPwt in its trafficking from the cell surface through endosomes. We report for the first time that CHT interacts significantly less with APPSwe than with APPwt. Surprisingly, however, CHT cell surface levels and choline uptake activity are decreased to the same extent and CHT co-localization to early endosomes increased similarly in cells expressing either APPwt or APPSwe. A critical observation is that CHT co-immunoprecipitates with βCTF from APPSwe-expressing cells. We propose that decreased CHT function is mediated differently by APPwt and APPSwe; APPwt interaction with CHT facilitates its endocytosis from the cell surface, whereas the effect of APPSwe on CHT is mediated indirectly potentially by binding to the βCTF fragment or by Aβ released from cells. High-affinity choline transporter (CHT) takes choline into cholinergic neurons for acetylcholine synthesis. Amyloid precursor protein (APP) interacts with CHT proteins, but this is decreased for Swedish mutant APP (APPSwe). CHT cell surface levels and localization to early endosomes, and choline uptake activity are changed similarly by APPwt or APPSwe. APPSwe mediates effects indirectly potentially by βCTF or Aβ.
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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) | 0.000 | 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".