Metformin attenuates olanzapine-induced hepatic, but not peripheral insulin resistance
Bibliographic record
Abstract
Antipsychotics (APs) are linked to diabetes, even without weight gain. Whether anti-diabetic drugs are efficacious in reversing the direct effects of APs on glucose pathways is largely undetermined. We tested two metformin (Met) doses to prevent impairments seen following a dose of olanzapine (Ola) (3 mg/kg); glucokinetics were measured using the hyperinsulinemic-euglycemic clamp (HIEC). Met (150 mg/kg; n=13, or 400 mg/kg; n=11) or vehicle (Veh) (n=11) was administered through gavage preceding an overnight fast, followed by a second dose prior to the HIEC. Eleven additional animals were gavaged with Veh and received a Veh injection during the HIEC (Veh/Veh); all others received Ola. Basal glucose was similar across treatment groups. The Met 400 group had significantly greater glucose appearance (Ra) in the basal period (i.e., before Ola, or hyperinsulinemia) vs other groups. During hyperinsulinemia, glucose infusion rate (GINF) to maintain euglycemia (reflective of whole-body insulin sensitivity) was higher in Veh/Veh vs other groups. Met 150/Ola animals demonstrated increased GINF relative to Veh/Ola during early time points of the HIEC. Glucose utilization during hyperinsulinemia, relative to basal conditions, was significantly higher in Veh/Veh vs other groups. The change in hepatic glucose production (HGP) from basal to hyperinsulinemia demonstrated significantly greater decreases in Veh/Veh and Met 150/Ola groups vs Veh/Ola. Given the increase in basal Ra with Met 400, we measured serum lactate (substrate for HGP), finding increased levels in Met 400 vs Veh and Met 150. In conclusion, Met attenuates hepatic insulin resistance observed with acute Ola administration, but fails to improve peripheral insulin resistance. Use of supra-therapeutic doses of Met may mask metabolic benefits by increasing lactate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".