14-LB: Somatostatin Receptor 2 Antagonism Enhances Plasma Glucagon Levels during Insulin-Induced Hypoglycemia in a Rodent Model of Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Somatostatin Receptor 2 antagonists (SSTR2a) increase glucagon counter-regulation to hypoglycemia in various rodent models of type-1 diabetes mellitus. Here we investigated the efficacy of SSTR2a in improving glucagon counter-regulation in a rat model of type-2 diabetes mellitus (T2DM). For this, male Sprague Dawley rats (n=18) were given a high fat diet for 3 weeks, followed by low-dose streptozotocin exposure (35 mg/kg, IP) to induce T2DM. Rats were then divided into SSTR2a treatment (PRL-2903, 10 mg/kg) or vehicle (n=9 for each) 1-hour before insulin-induced hypoglycemia (3 IU/kg NovoRapid). This process was repeated 1 week later in a cross-over design, with the data pooled over SSTR2a and vehicle treatments. A group of normal-chow-fed rats (n=3) served as nondiabetic controls. Mean blood glucose levels were higher at 20, 30, 40, and 50 minutes post insulin administration in the T2DM rats treated with PRL-2903, as compared to vehicle (p ≤ 0.05). The number of T2DM rats that developed biochemical hypoglycemia (blood glucose ≤ 3.5 mmol/L) tended to be less with PRL-2903 (5/18) vs. vehicle (9/18). Compared with vehicle treatment, PRL-2903 promoted higher plasma glucagon counter-regulation, as indicated by area under curve (AUC) analysis (p < 0.05). Thus, SSTR2a treatment improves the attenuated glucagon response to hypoglycemia in T2DM rats. Disclosure M. Nejad-Mansouri: None. P. Zaree Bavani: None. J. Aiken: None. N.C. DSouza: None. E.G. Hoffman: None. R. Liggins: None. M. Riddell: Advisory Panel; Self; Xeris Pharmaceuticals, Inc. Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; Insulet Corporation, Medtronic MiniMed, Inc. Stock/Shareholder; Self; Zucara Therapeutics Inc. Funding National Research Council Canada; Zucara Therapeutics
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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 | 0.000 | 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 | 0.002 |
| 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".