P4339SGLT2 inhibition improves coronary microvascular function and contractile function in pre-diabetic mice
Bibliographic record
Abstract
Background: Treatment with SGLT2i have been suggested to be beneficial on cardiovascular health in patients with cardiovascular comorbidities. However, mechanisms for the observed dramatic CV benefit remains unclear. We hypothesized that SGLT2 inhibition may have direct effects on coronary microcirculation and cardiac performance via metabolic modulation. To test this hypothesis, we used the ob/ob−/− mice, which is an obesity, insulin resistant model, lacking atherosclerosis formation, with only mild diabetes progression. It is a rodent model of pre-diabetes, which we have previously shown to display coronary microvascular dysfunction. Purpose: We aimed to evaluate the effect of SGLT2i on coronary vascular function in ob/ob−/− male mice from Jackson using Doppler ultrasound imaging. Methods: Non-invasive Doppler guided ultrasound imaging (Vevo 2100 VisualSonics, Inc Toronto, Ontario, Canada) was used to characterise coronary flow velocity reserve (CFVR) and fractional area change (FAC) over time (baseline, 5 and 10 weeks post treatment). The mice were 9 weeks of age at baseline (22 ob/ob−/− male mice treated with Empagliflozin and 21 untreated ob/ob−/−). Velocity profile in the left coronary artery was measured in the long-axis view and measurement of left ventricle dimensions performed in the short axis view. Spot urine was analysed for glucose, albumin, creatinine, sodium and potassium at all time points as well as blood HbA1c.
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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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".