Variation in Human Islet Viability Based on Different Membrane Integrity Stains
Bibliographic record
Abstract
Membrane integrity fluorescent staining is used routinely to evaluate islet viability. Results are used as one of the determining factors in islet product release criteria, and are used to assess the efficacy of different culture conditions. Recently, it has been observed that there is variation in the viability staining of freshly isolated islets based on which viability assay is used. This investigation compares three membrane integrity stains for the viability assessment of isolated human islets. Fluorescein diacetate/propidium iodide (FDA/ PI), the current standard method for assessing islet viability, demonstrates intense extracellular fluorescence, reducing the differential staining of intact islets. We further evaluated SYTO-13/ethidium bromide (SYTO/ EB) and calcein AM/ethidium homodimer (C/EthD) as alternative viability assays, and found considerable variation between FDA/PI and either SYTO/EB or C/EthD staining. Preparations of human islets were obtained from cadaveric pancreata after collagenase digestion, mechanical separation, and purification by continuous Ficoll gradient centrifugation. For each preparation, two replicate samples of 50 islets were counted for each stain, and the percent viability calculated. The results for SYTO/EB and C/EthD were nearly identical [57.6 +/- 7.3% and 57.9 +/- 7.2%, respectively (mean +/- SEM), N = 11]. FDA/PI-stained islets, however, showed consistently elevated values when compared to SYTO/EB. Accurate assessment of islet viability remains a critical determinant of islet product release. The discrepancies found between FDA/PI scoring and visual quality, compared with alternative stains, suggests that the FDA/PI stain may not be the optimal approach to assess islet viability.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".