Studies on alpha-synuclein and islet amyloid polypeptide interaction
Bibliographic record
Abstract
Introduction: Parkinson’s disease and type 2 diabetes have both elements of local amyloid depositions in their pathogenesis. In Parkinson’s disease, alpha-synuclein (aSyn) forms insoluble Lewy bodies and Lewy neurites in brain neurons, and in type 2 diabetes, islet amyloid polypeptide (IAPP) comprises the amyloid in the islets of Langerhans. In this study, we assessed the interaction between aSyn and IAPP in human pancreatic tissues, both ex vivo and in vitro. Material and Methods: The antibody-based detection techniques, proximity ligation assay (PLA), and immuno-TEM were used for co-localization studies. Bifluorescence complementation (BiFC) was used for interaction studies between IAPP and aSyn in HEK 293 cells. The Thioflavin T assay was used for studies of cross-seeding between IAPP and aSyn. ASyn was downregulated with siRNA, and insulin secretion was monitored using TIRF microscopy. Results: We demonstrate intracellular co-localization of aSyn with IAPP, while aSyn is absent in the extracellular amyloid deposits. ASyn reactivity is present in the secretory granules of β-cells and some α-cells in human islets. The BiFC-expression of aSyn/aSyn and IAPP/IAPP in HEK293 cells resulted in 29.3% and 19.7% fluorescent cells, respectively, while aSyn/IAPP co-expression resulted in ∼10% fluorescent cells. Preformed aSyn fibrils seeded IAPP fibril formation in vitro, but adding preformed IAPP seeds to aSyn did not change aSyn fibrillation. In addition, mixing monomeric aSyn with monomeric IAPP did not affect IAPP fibril formation. Finally, the knockdown of endogenous aSyn did not affect β cell function or viability, nor did overexpression of aSyn affect β cell viability. Discussion: Despite the proximity of aSyn and IAPP in β-cells and the detected capacity of preformed aSyn fibrils to seed IAPP in vitro, it is still an open question if an interaction between the two molecules is of pathogenic significance for type 2 diabetes.
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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".