Dynamic regulation of TREK1 gating by Polycystin 2 via a Filamin A-mediated cytoskeletal Mechanism
Bibliographic record
Abstract
Mechanosensing is essential for several physiological functions including touch and pain sensations, osmoregulation, and controlling the myogenic tone of resistance arteries. Understanding how mechanosensitive ion channels (MSCs) are gated can provide important information regarding these processes. We have previously demonstrated that during pathological conditions such as polycystic kidney disease, polycystin 2 (TRPP2) inhibits the activity of potassium-selective MSCs through a filamin A-mediated cytoskeletal effect, and renders tubular epithelial cells susceptible to apoptosis. However, the nature of this cytoskeletal inhibition remains poorly understood. In this study we use a combination of electrophysiology, structured illumination microscopy, and fluorescence recovery after photobleaching (FRAP) to examine the dynamic nature of the TRPP2-mediated cytoskeletal inhibition of the potassium-selective MSC TREK1. Our data indicate that this inhibition of MSC activity occurs through an accelerated cytoskeletal inhibition, and ultimately decreases the open probability of the TREK1 channel. These results shed light on a novel mode of regulation of MSCs gating, which may be at play in several physiological functions.
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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 | 0.001 |
| 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".