Alpha- to Beta-Cell Transdifferentiation in Neonatal Compared with Adult Mouse Pancreas in Response to a Modest Reduction in Beta-Cells Using Streptozotocin
Bibliographic record
Abstract
Following the near-total depletion of pancreatic beta-cells with streptozotocin (STZ), a partial recovery of beta-cell mass (BCM) can occur, in part due to the alpha- to beta-cell transdifferentiation with an intermediary insulin/glucagon bi-hormonal cell phenotype. However, human type 2 diabetes typically involves only a partial reduction in BCM and it is not known if recovery after therapeutic intervention involves islet cell transdifferentiation, or how this varies with age. Here, we used transgenic mouse models to examine if islet cell transdifferentiation contributes to BCM recovery following only a partial depletion of BCM. Cell lineage tracing was employed using Glucagon-Cre/yellow fluorescent protein (YFP) transgenic mice treated with STZ (25 mg/kg-neonates; 70 mg/kg-adults) or vehicle alone on 3 consecutive days. Mice were euthanized 2-30 days later with a prior glucose tolerance test on day 30, and immunofluorescence histology performed on the pancreata. Beta-cell abundance was reduced by 30-40% two days post STZ in both neonates and adults, and subsequently partially recovered in adult but not neonatal mice. Glucose tolerance recovered in adult females, but not in males or neonates. Bi-hormonal cell abundance increased 2-3-fold in STZ-treated mice vs. controls in both neonates and adults, as did transdifferentiated cells expressing insulin and the YFP lineage tag, but not glucagon. Transdifferentiated cell presence was an order of magnitude lower than that of bi-hormonal cells. We conclude that alpha- to beta-cell transdifferentiation occurs in mice following only a moderate depletion in BCM, and that this was accompanied by a partial recovery of BCM in adults.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".