Nitric oxide-angiotensin II interactions and renal hemodynamic function in patients with uncomplicated type 1 diabetes
Bibliographic record
Abstract
The objective is to elucidate the effect of nitric oxide (NO)-renin-angiotensin system (RAS) interactions on renal hemodynamic function in uncomplicated, type 1 diabetes mellitus (DM). In 14 salt-replete, male healthy volunteers (C) and 9 male DM patients on euglycemia, glomerular filtration rate (GFR), renal blood flow (RBF), filtration fraction (FF), and sodium excretion (UNaV) were measured at baseline and during a 90-min infusion of 3.0 μg·kg⁻¹·min⁻¹ NG-nitro-L-arginine-methyl-ester (L-NAME) after 3 days of pretreatment with either placebo (PL) or 50 mg losartan (LOS). Baseline GFR, RBF, and FF were higher in DM (P < 0.005). In the C group, PL + L-NAME caused declines in GFR (101 ± 3 to 90 ± 3 ml·min⁻¹·1.73 m⁻²), RBF (931 ± 22 to 754 ± 31 ml·min⁻¹·1.73 m⁻²), and UNaV (158 ± 12 to 82 ± 18 μmol/min) and an increase in FF (0.19 ± 0.02 to 0.21 ± 02; P < 0.001), which were not influenced by LOS pretreatment (P > 0.05 for LOS + L-NAME-C vs. PL + l-NAME-C). In DM, PL + L-NAME resulted in exaggerated renal effects, with changes in GFR (128 ± 3 to 104 ± 3 ml·min⁻¹·1.73 m⁻²), RBF (1,019 ± 27 to 699 ± 34 ml·min⁻¹·1.73 m⁻²), UNaV (150 ± 13 to 39 ± 14 μmol/min), and FF (0.22 ± 0.03 to 0.26 ± 0.02) that were significantly greater vs. PL + L-NAME-C (P < 0.005). LOS pretreatment blunted GFR, RBF, FF, and UNaV responses to L-NAME in DM (P < 0.005 vs. PL + L-NAME-DM), resulting in a response profile that was similar to PL + L-NAME and LOS + L-NAME in C (P > 0.05). Renal responses to L-NAME in uncomplicated, type 1 DM are exaggerated vs. C, consistent with an upregulation of NO bioactivity. LOS, without effects in C, prevents the accentuated actions of L-NAME in DM, thus indicating an augmented role for NO-RAS interactions in renal hemodynamic function in DM.
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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 | 0.000 |
| 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) | 0.001 | 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".