Small Interfering RNA–Mediated Suppression of Proislet Amyloid Polypeptide Expression Inhibits Islet Amyloid Formation and Enhances Survival of Human Islets in Culture
Bibliographic record
Abstract
OBJECTIVE: Islet amyloid, formed by aggregation of the beta-cell peptide islet amyloid polypeptide (IAPP; amylin), is a pathological characteristic of pancreatic islets in type 2 diabetes. Toxic IAPP aggregates likely contribute to the progressive loss of beta-cells in this disease. We used cultured human islets as an ex vivo model of amyloid formation to investigate whether suppression of proIAPP expression would inhibit islet amyloid formation and enhance beta-cell survival and function. RESEARCH DESIGN AND METHODS: Islets from cadaveric organ donors were transduced with a recombinant adenovirus expressing a short interfering RNA (siRNA) designed to suppress human proIAPP (Ad-hProIAPP-siRNA), cultured for 10 days, and then assessed for the presence of islet amyloid, beta-cell apoptosis, and beta-cell function. RESULTS: Thioflavine S-positive amyloid deposits were clearly present after 10 days of culture. Transduction with Ad-hProIAPP-siRNA reduced proIAPP expression by 75% compared with nontransduced islets as assessed by Western blot analysis of islet lysates 4 days after transduction. siRNA-mediated inhibition of IAPP expression decreased islet amyloid area by 63% compared with nontransduced cultured islets. Cell death assessed by transferase-mediated dUTP nick-end labeling staining was decreased by 50% in transduced cultured human islets, associated with a significant increase in islet insulin content (control, 100 +/- 4 vs. +Ad-siRNA, 153 +/- 22%, P < 0.01) and glucose-stimulated insulin secretion (control, 222 +/- 33 vs. +Ad-siRNA, 285 +/- 21 percent basal, P < 0.05). CONCLUSIONS: These findings demonstrate that inhibition of IAPP synthesis prevents amyloid formation and beta-cell death in cultured human islets. Inhibitors of IAPP synthesis may have therapeutic value in type 2 diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".