Somatostatin Receptor Antagonism Reverses Glucagon Counterregulatory Failure in Recurrently Hypoglycemic Male Rats
Bibliographic record
Abstract
Recent antecedent hypoglycemia is a known source of defective glucose counter-regulation in diabetes; the mechanisms perpetuating the cycle of progressive α-cell failure and recurrent hypoglycemia remain unknown. Somatostatin has been shown to suppress the glucagon response to acute hypoglycemia in rodent models of type 1 diabetes. We hypothesized that somatostatin receptor 2 antagonism (SSTR2a) would restore glucagon counterregulation and delay the onset of insulin-induced hypoglycemia in recurrently hypoglycemic, nondiabetic male rats. Healthy, male, Sprague-Dawley rats (n = 39) received bolus injections of insulin (10 U/kg, 8 U/kg, 5 U/kg) on 3 consecutive days to induce hypoglycemia. On day 4, animals were then treated with SSTR2a (10 mg/kg; n = 17) or vehicle (n = 12) 1 hour prior to the induction of hypoglycemia using insulin (5 U/kg). Plasma glucagon level during hypoglycemia was ~30% lower on day 3 (150 ± 75 pg/mL; P < .01), and 68% lower on day 4 in the vehicle group (70 ± 52 pg/mL; P < .001) compared with day 1 (219 ± 99 pg/mL). On day 4, SSTR2a prolonged euglycemia by 25 ± 5 minutes (P < .05) and restored the plasma glucagon response to hypoglycemia. Hepatic glycogen content of SSTR2a-treated rats was 35% lower than vehicle controls after hypoglycemia induction on day 4 (vehicle: 20 ± 7.0 vs SSTR2a: 13 ± 4.4 µmol/g; P < .01). SSTR2a treatment reverses the cumulative glucagon deficit resulting from 3 days of antecedent hypoglycemia in healthy rats. This reversal is associated with decreased hepatic glycogen content and delayed time to hypoglycemic onset. We conclude that recurrent hypoglycemia produces glucagon counterregulatory deficiency in healthy male rats, which can be improved by SSTR2a.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".