Loss of insulin-induced inhibition of glucagon gene transcription in hamster pancreatic islet alpha cells by long-term insulin exposure
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Diabetes mellitus type 2 is characterised by hyperglucagonaemia, resulting in hepatic glucose production and hyperglycaemia. Considering that insulin inhibits glucagon secretion and gene transcription, hyperglucagonaemia in the face of hyperinsulinaemia in diabetes mellitus type 2 suggests that there is insulin resistance also at the glucagon-producing pancreatic islet alpha cells. However, the molecular mechanism of alpha cell insulin resistance is unknown. Therefore, the effect of molecules implicated in conferring insulin resistance in some other tissues was investigated on insulin-induced inhibition of glucagon gene transcription in alpha cells. METHODS: Reporter gene assays and biochemical techniques were used in the glucagon-producing hamster pancreatic islet alpha cell line InR1-G9. RESULTS: From among 16 agents tested, chronic insulin treatment was found to abolish insulin-induced inhibition of glucagon gene transcription. Overproduction of constitutively active protein kinase B (PKB) still inhibited glucagon gene transcription after chronic insulin treatment; together with a markedly reduced insulin-induced phosphorylation and, thus, activation of PKB, this indicates that targets upstream of PKB within the insulin signalling pathway are affected. Indeed, chronic insulin treatment markedly reduced IRS-1 phosphorylation, insulin receptor (IR) autophosphorylation and IR content. Cycloheximide and in vivo labelling experiments attributed IR downregulation to enhanced degradation. CONCLUSIONS/INTERPRETATION: These results show that an extended exposure of alpha cells to insulin induces IR downregulation and loss of insulin-induced inhibition of glucagon gene transcription. They suggest that hyperinsulinaemia, through IR downregulation, may confer insulin resistance to pancreatic islet alpha cells in diabetes mellitus type 2.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".