The Islet Size to Oxygen Consumption Ratio Reliably Predicts Reversal of Diabetes Posttransplant
Bibliographic record
Abstract
β-Cell replacement therapy by either whole-organ pancreas or islets of Langerhans transplantation can restore carbohydrate control to diabetic patients and reduces complications associated with the disease. One of the variables inherent in islet transplantation is the isolation of functional islets from donor pancreata. Islet isolations fail to consistently produce good-quality functional islets. A rapid pretransplant assay to determine posttransplant function of islets would be an invaluable tool. We have tested the novel hypothesis that modified oxygen consumption rates (OCR), standardized to DNA quantity (nmol/min-mg DNA), would serve as a pretransplant assessment of the metabolic potency of the islets postisolation. This study compares the ability of current in vitro assays to predict in vivo restoration of normoglycemia in a diabetic nude mouse posttransplantation of adult pig islets. There is known to be a diversity of islet sizes within each preparation. This parameter has not heretofore been effectively considered a critical factor in islet engraftment. Our results suggest a surprising finding that islet size influences the probability of restoring carbohydrate control. Based on this observation, we thus developed a novel predictor of islet graft function that combines the effects of both islet OCR and size. When OCR was divided by the islet index (size), a highly significant predictor of graft function was established (p = 0.0002, n = 75). Furthermore, when OCR/islet index values exceeded 70.0 nmol/min-mg DNA/islet index, an effective threshold of diabetes reversal was observed. This assay can be performed with as few as 1,000 islet equivalents (IEQ) and conducted in less than 60 min. Our data suggest that, using this novel method to assess islet cell function prior to transplantation, OCR/islet index thresholds provide a valuable tool in identifying which islet preparations are most likely to restore glycemic control posttransplant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".