Elevated islet prohormone ratios as indicators of insulin dependency in islet transplant recipients
Bibliographic record
Abstract
Abstract Autologous pancreatic islet transplantation is an established therapy for patients with chronic pancreatitis. However, the long-term transplant outcomes are modest. Identifying indicators of graft function will aid the preservation of transplanted islets and glycemic control. To this end, we analyzed beta cell prohormone peptide levels in a retrospective cohort of total pancreatectomy autologous islet transplant patients (n=28). Proinsulin-to-C-peptide (PI/C) and proIAPP-to-total IAPP (proIAPP/IAPP) ratios measured at 3 months post-transplant were significantly higher in patients who remained insulin dependent at 1 year follow-up. In a mouse model of human islet transplantation, recipient mice that later became hyperglycemic displayed significantly higher PI/C ratios than mice that remained normoglycemic. Histological analysis of islet grafts showed reduced insulin- and proinsulin-positive area, but elevated glucagon-positive area in grafts that experienced greater secretory demand. Increased prohormone convertase 1/3 was detected in glucagon-positive cells, and glucagon-like peptide 1 (GLP-1) area was elevated in grafts from mice that displayed hyperglycemia or elevated plasma PI/C ratios, demonstrating intra-islet incretin production in metabolically challenged human islet grafts. These data indicate that in failing grafts, alpha cell prohormone processing is likely altered, and incomplete beta cell prohormone processing may be an early indicator of insulin dependency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".