Voltage-activated Ca2+ channels in rat renal afferent and efferent myocytes: no evidence for the T-type Ca2+ current
Bibliographic record
Abstract
AIMS: Based on indirect methods, it has been suggested that both L- and T-type Ca(2+) channels mediate signalling in the renal afferent arteriole and that T-type Ca(2+) channels are involved in signalling in the efferent arteriole. However, Ca(2+) currents have never been studied in these two vessels. Our study was initiated to directly determine the type of Ca(2+) channels in these vessels for the first time, using patch clamp. METHODS AND RESULTS: Native myocytes were obtained from individually isolated rat renal afferent and efferent arterioles and from rat tail arteries (TA). TA myocytes, which possess both L- and T-type Ca(2+) currents, served as a positive control. Inward Ca(2+) and Ba(2+) currents (I(Ca) and I(Ba)) were measured in 1.5 mmol/L Ca(2+) and 10 mmol/L Ba(2+), respectively, using the whole-cell configuration. By exploiting known differences in activation and inactivation characteristics and differing sensitivities to nifedipine and kurtoxin, the presence of both L- and T-type Ca(2+) channels in TA myocytes was readily demonstrated. Afferent arteriolar myocytes exhibited relatively large I(Ca) densities (-2.0 ± 0.2 pA/pF) in physiological Ca(2+) and the I(Ba) was 3.6-fold greater. These currents were blocked by nifedipine, but not by kurtoxin, and did not exhibit the activation and inactivation characteristics of T-type Ca(2+) channels. Efferent arteriolar myocytes did not exhibit a discernible voltage-activated I(Ca) in physiological Ca(2+). CONCLUSION: Our findings support the physiological role of L-type Ca(2+) channels in the afferent, but not efferent, arteriole, but do not support the premise that functional T-type Ca(2+) channels are present in either vessel.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".