Modulation of single-nephron GFR in the <i>db/db</i> mouse model of type 2 diabetes mellitus. II. Effects of renal mass reduction
Bibliographic record
Abstract
This study examines for the first time the effects of uninephrectomy (Nx) on modulation of whole kidney glomerular filtration rate (GFR), single-nephron GFR (SNGFR), and progression of diabetic nephropathy in the db/db mouse model of type 2 diabetes mellitus. To characterize SNGFR and tubuloglomerular feedback (TGF) responses to Nx and chronic neuronal nitric oxide synthase inhibition in the db/db mouse, we studied the effects of Nx on whole kidney GFR, SNGFR, and TGF characteristics in db/db and wild-type (WT) mice after Nx or sham Nx. We also documented progression of glomerular changes over a 6-mo period. Whole kidney GFR and SNGFR were significantly higher in db/db Nx than db/db sham mice, without change in proximal tubule reabsorptive rates. The TGF responses, determined as proximal-distal SNGFR differences, were brisk: 12.1 +/- 1.0 vs. 8.4 +/- 0.6 nl/min in WT sham (P < 0.05), 15.7 +/- 1.0 vs. 12.0 +/- 1.0 nl/min in WT Nx (P < 0.05), and 17.8 +/- 1.3 vs. 14.3 +/- 1.0 nl/min in db/db Nx (P < 0.05) mice. Chronic ingestion of the neuronal nitric oxide synthase inhibitor S-methylthiocitrulline for 2-3 wk after Nx had no effect on SNGFR or the TGF response. These studies show further elevations in whole kidney GFR and SNGFR in these hyperglycemic morbidly obese db/db mice, with an intact TGF system after Nx. In addition, in the db/db Nx mice, 4-6 mo after Nx, there was an exacerbation of the lesions of diabetic nephropathy, as quantified by a significant increase in the ratio of mesangial surface area to total glomerular surface area.
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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 | 0.001 | 0.000 |
| 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".