A gap junction inhibitor, carbenoxolone, induces spatiotemporal dispersion of renal cortical perfusion and impairs autoregulation
Bibliographic record
Abstract
Renal autoregulation dynamics originating from the myogenic response (MR) and tubuloglomerular feedback (TGF) can synchronize over large regions of the kidney surface, likely through gap junction-mediated electrotonic conduction and reflecting distributed operation of autoregulation. We tested the hypotheses that inhibition of gap junctions reduces spatial synchronization of autoregulation dynamics, abrogates spatial and temporal smoothing of renal perfusion, and impairs renal autoregulation. In male Long-Evans rats, we infused the gap junction inhibitor carbenoxolone (CBX) or the related glycyrrhizic acid (GZA) that does not block gap junctions into the renal artery and monitored renal blood flow (RBF) and surface perfusion by laser speckle contrast imaging. Neither CBX nor GZA altered RBF or mean surface perfusion. CBX preferentially increased spatial and temporal variation in the distribution of surface perfusion, increased spatial variation in the operating frequencies of the MR and TGF, and reduced phase coherence of TGF and increased its dispersion. CBX, but not GZA, impaired dynamic and steady-state autoregulation. Separately, infusion of the Rho kinase inhibitor Y-27632 paralyzed smooth muscle, grossly impaired dynamic autoregulation, and monotonically increased spatial variation of surface perfusion. These data suggest CBX inhibited gap junction communication, which in turn reduced the ability of TGF to synchronize among groups of nephrons. The results indicate that impaired autoregulation resulted from degraded synchronization, rather than the reverse. We show that network behavior in the renal vasculature is necessary for effective RBF autoregulation.
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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) | 0.001 | 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".