Ca<sub>V</sub>3.1 T-Type Ca<sup>2+</sup>Channels Contribute to Myogenic Signaling in Rat Retinal Arterioles
Bibliographic record
Abstract
PURPOSE: Although L-type Ca2+ channels are known to play a key role in the myogenic reactivity of retinal arterial vessels, the involvement of other types of voltage-gated Ca2+ channels in this process remains unknown. In the present study we have investigated the contribution of T-type Ca2+ channels to myogenic signaling in arterioles of the rat retinal microcirculation. METHODS: Confocal immunolabeling of whole-mount preparations was used to investigate the localization of CaV3.1-3 channels in retinal arteriolar smooth muscle cells. T-type currents and the contribution of T-type channels to myogenic signaling were assessed by whole-cell patch-clamp recording and pressure myography of isolated retinal arteriole segments. RESULTS: Strong immunolabeling for CaV3.1 was observed on the plasma membrane of retinal arteriolar smooth muscle cells. In contrast, no expression of CaV3.2 or CaV3.3 could be detected in retinal arterioles, although these channels were present on glial cell end-feet surrounding the vessels and retinal ganglion cells, respectively. TTA-A2-sensitive T-type currents were recorded in retinal arteriolar myocytes with biophysical properties distinct from those of the L-type currents present in these cells. Inhibition of T-type channels using TTA-A2 or ML-218 dilated isolated, myogenically active, retinal arterioles. CONCLUSIONS: CaV3.1 T-type Ca2+ channels are functionally expressed on arteriolar smooth muscle cells of retinal arterioles and play an important role in myogenic signaling in these vessels. The work has important implications concerning our understanding of the mechanisms controlling blood flow autoregulation in the retina and its disruption during ocular disease.
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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".