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Record W2774677287 · doi:10.1038/s41598-017-16540-w

Dynamic regulation of TREK1 gating by Polycystin 2 via a Filamin A-mediated cytoskeletal Mechanism

2017· article· en· W2774677287 on OpenAlexafffund
Steven Li Fraine, Amanda Patel, Fabrice Duprat, Reza Sharif‐Naeini

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsCytoskeletonMechanosensitive channelsCell biologyFilaminGatingIon channelPotassium channelChemistryBiologyBiophysicsBiochemistryCellReceptor

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.260
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2017
Admission routes2
Has abstractyes

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