Cell Loss in Isolated Human Islets Occurs by Apoptosis
Bibliographic record
Abstract
Purified islet allografts have largely failed to maintain long-term glucose homeostasis in human recipients, and the reasons for this are unclear. It is noteworthy, however, that islet isolation destroys or removes cellular and noncellular elements of the pancreas that could play an important role in supporting islet survival. The purpose of this study was to determine whether human islet isolation leads to the induction of programmed cell death. Human islets were enzymatically isolated from cadaveric donor pancreata using Liberase or Collagenase P, purified over a discontinuous BSA gradient, then cultured in RPMI 1640 at 37 degrees C in 5% CO2 for < or = 7 days. Islets were examined daily by routine histology and immunocytochemistry for islet hormones, DNA fragmentation [cell death; enzyme-linked immunosorbent assay (ELISA) and TUNEL assay] and for transglutaminase (TG) activity, two indicators of apoptosis. TG activity and DNA fragmentation increased by 1,000% and 1,890%, respectively (p < 0.05) This corresponded to the appearance of pyknotic nuclei on light microscopy, the presence of apoptotic bodies on electron microscopy, and the demonstration of TUNEL-positive cells. These were present primarily in a distribution that corresponded to the insulin-immunoreactive cells. At 5 days, 31.4 +/- 2.2% of islet cells were TUNEL positive. In summary, apoptosis of islet cells appears soon after islet isolation, and involves primarily the beta cell. This is the first report of apoptosis of islet cells after human islet isolation. The loss of beta-cell mass could be implicated in the failure of islet transplantation and merits further investigation.
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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".