NKCC Inhibitors Furosemide and Bumetanide Directly Attenuate Afferent Arteriolar Myogenic Reactivity Independent of Actions on Tubuloglomerular Feedback.
Bibliographic record
Abstract
The Na/K/2Cl‐cotransporter (NKCC) plays a key role in tubuloglomerular feedback (TGF) signaling at the macula densa and NKCC inhibitors are thus frequently used to assess the impact of blockade of TGF on renal hemodynamics. However, NKCC is also implicated in establishing the chloride gradient in smooth muscle myocytes and pharmacologic inhibitors can have direct effects on vascular responses. In the present study we investigated the effects of the NKCC inhibitors, furosemide (F) and bumetanide (B), on myogenic responses of the renal afferent arteriole using the in vitro perfused hydronephrotic rat kidney. This preparation has no tubules and thus no TGF. F and B inhibited myogenic responses over concentrations of 0.1–10 μM (IC 50 20 μM) and 0.01–1 μM (IC 50 1.0 μM), respectively. Responses evoked by increasing renal arterial pressure from 80 to 160 mmHg were significantly attenuated at concentrations as low as 0.1 μM ( P =0.03, F; P =0.002 B). At the highest concentrations employed, F (10 μM) and B (1.0 μM) inhibited responses by 72±4% and 68±5%, respectively. The maximal level of inhibition was not affected by nitric oxide synthase inhibition (100 μM L‐NAME), but the time course for the dilation was slowed (t ½ = 4.0 ±0.5 min to 8.3±1.7 min, P =0.04, B), suggesting an involvement of NO. RT‐PCR performed on single renal arterioles isolated from the normal rat kidney revealed the expression of NKCC1. These results indicate that NKCC is expressed in the afferent arteriole and that NKCC inhibition attenuates myogenic responses by both NO‐independent and NO‐dependent mechanisms. These effects do not involve a modulation of TGF.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".