Insulin-Deficient Mouse<i>β</i>-Cells Do Not Fully Mature but Can Be Remedied Through Insulin Replacement by Islet Transplantation
Bibliographic record
Abstract
Insulin receptor (IR) insufficiency in β-cells leads to impaired insulin secretion and reduced β-cell hyperplasia in response to hyperglycemia. Selective IR deficiency in β-cells in later embryological development may lead to compensatory β-cell hyperplasia. Although these findings suggest insulin signaling on the β-cell is important for β-cell function, they are confounded by loss of signaling by the insulinlike growth factors through the IR. To determine whether insulin itself is necessary for β-cell development and maturation, we performed a characterization of pancreatic islets in mice with deletions of both nonallelic insulin genes (Ins1-/-Ins2-/-). We immunostained neonatal Ins1-/-Ins2-/- and Ins1+/+Ins2+/+ pancreata and performed quantitative polymerase chain reaction on isolated neonatal islets. Insulin-deficient islets had reduced expression of factors normally expressed in maturing β-cells, including muscoloaponeurotic fibrosarcoma oncogene homolog A, homeodomain transcription factor 6.1, and glucose transporter 2. Ins1-/-Ins2-/-β-cells expressed progenitor factors associated with stem cells or dedifferentiated β-cells, including v-myc avian myolocytomatosis viral oncogene lung carcinoma derived and homeobox protein NANOG. We replaced insulin by injection or islet transplantation to keep mice alive into adulthood to determine whether insulin replacement was sufficient for the completed maturation of insulin-deficient β-cells. Short-term insulin glargine (Lantus®) injections partially rescued the β-cell phenotype, whereas long-term replacement of insulin by isogenic islet transplantation supported the formation of more mature β-cells. Our findings suggest that tightly regulated glycemia, insulin species, or other islet factors are necessary for β-cell maturation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".