Sex-specific Effects of SGLT2 Inhibition in a Kidney with Reduced Nephron Number: Modeling and Analysis
Bibliographic record
Abstract
Abstract The kidney plays an essential role in regulating the homeostasis of electrolytes, acid-base species, and fluids. Kidney structure and function are significantly affected in diabetes. These pathophysiological changes include glomerular hyperfiltration and tubular hypertrophy, and ultimately leading to diabetic kidney disease. A class of medications that have shown promise in slowing the progression to diabetic kidney disease are the sodium-glucose cotransporter 2 (SGLT2) inhibitors. SGLT2 inhibitors target Na + and glucose reabsorption along the proximal convoluted tubule, enhance urinary glucose, Na + and fluid excretion, and lower hyperglycemia in diabetes. We postulate that both diabetes-induced and SGLT2 inhibition-induced changes in kidney may exhibit significant sex differences, because the distribution of renal transporters along the nephron may be markedly different between women and men, as recently shown in rodents. The goals of this study are to (i) analyze how kidney function is altered in male and female patients with diabetes, (ii) assess the renal effects, in women and men, of an anti-hyperglycemic therapy that inhibits the sodium-glucose cotransporter 2 (SGLT2) in the proximal convoluted tubules, and (iii) study how those renal effects are altered in uninephrectomy. To accomplish these goals, we have developed computational models of kidney function, separate for male and female patients with diabetes and/or uninephredctomy. The simulation results indicate that by inducing osmotic diuresis in the proximal tubules, SGLT2 inhibition reduces paracellular transport, eventually leading to diuresis and natriuresis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".