SORLA mediates endocytic uptake of proIAPP and protects against islet amyloid deposition
Bibliographic record
Abstract
Abstract Aims/ hypothesis Sorting-related receptor with type A repeats (SORLA) is a neuronal sorting receptor that prevents accumulation of amyloid-beta peptides, the main constituent of senile plaques in Alzheimer disease. Recent transcriptomic studies show that SORLA transcripts are also found in pancreatic islet beta cells, yet the role of SORLA in islets is unclear so far. Based on its protective role in reducing amyloid burden in the brain, we hypothesized that SORLA may have a similar function in the pancreas, regulating islet amyloid plaque formation from islet amyloid polypeptide (IAPP). Methods We generated human IAPP transgenic mice lacking SORLA (hIAPP:SORLA KO) to assess the consequences of receptor deficiency for islet histopathology and function in vivo . Using both primary islet cells and established cell lines, we further investigated the molecular mechanisms whereby SORLA controls the cellular metabolism and accumulation of IAPP. Results Loss of SORLA activity in hIAPP:SORLA KO resulted in a significant increase in islet amyloid deposits and associated islet cell death as compared to hIAPP:SORLA WT animals expressing the receptor. Aggravated islet amyloid deposition was observed in mice fed a normal chow diet, not requiring high-fat diet feeding typically needed to induce islet amyloidosis in mouse models. Further in vitro studies showed that SORLA binds to and mediates the endocytic uptake of proIAPP, but not mature IAPP, delivering the propeptide to an endolysosomal fate. Conclusions/interpretation SORLA functions as a clearance receptor specific for proIAPP, protecting against islet amyloid deposition and associated cell death caused by IAPP.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".