Evaluation of glomerular hemodynamic changes by sodium-glucose-transporter 2 inhibition in type 2 diabetic rats using in vivo imaging
Bibliographic record
Abstract
The mechanisms responsible for glomerular hemodynamic regulation with sodium-glucose co-transporter 2 (SGLT2) inhibitors in kidney disease due to type 2 diabetes remain unclear. Therefore, we investigated changes in glomerular hemodynamic function using an animal model of type 2 diabetes, treated with an SGLT2 inhibitor alone or in combination with a renin-angiotensin-aldosterone system inhibitor using male Zucker lean (ZL) and Zucker diabetic fatty (ZDF) rats. Afferent and efferent arteriolar diameter and single-nephron glomerular filtration rate (SNGFR) were evaluated in ZDF rats measured at 0, 30, 60, 90, and 120 minutes after the administration of a SGLT2 inhibitor (luseogliflozin). Additionally, we assessed these changes under the administration of the adenosine A1 receptor (A1aR) antagonist (8-cyclopentyl-1,3-dipropylxanthine), along with coadministration of luseogliflozin and an angiotensin II receptor blocker (ARB), telmisartan. ZDF rats had significantly increased SNGFR, and afferent and efferent arteriolar diameters compared to ZL rats, indicating glomerular hyperfiltration. Administration of luseogliflozin significantly reduced afferent vasodilatation and glomerular hyperfiltration, with no impact on efferent arteriolar diameter. Urinary adenosine levels were increased significantly in the SGLT2 inhibitor group compared to the vehicle group. A1aR antagonism blocked the effect of luseogliflozin on kidney function. Co-administration of the SGLT2 inhibitor and ARB decreased the abnormal expansion of glomerular afferent arterioles, whereas the efferent arteriolar diameter was not affected. Thus, regulation of afferent arteriolar vascular tone via the A1aR pathway is associated with glomerular hyperfiltration in type 2 diabetic kidney disease.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".