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Record W2804481279 · doi:10.1016/j.celrep.2018.04.090

Trpv4 Mediates Hypotonic Inhibition of Central Osmosensory Neurons via Taurine Gliotransmission

2018· article· en· W2804481279 on OpenAlexafffund
Sorana Ciura, Masha Prager‐Khoutorsky, Zahra S. Thirouin, Joshua C. Wyrosdic, James E. Olson, Wolfgang Liedtke, Charles W. Bourque

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchMcGill University Health CentreMcGill UniversityHeart and Stroke Foundation of Canada
KeywordsTransient receptor potential channelTRPV4TonicityAgonistCell biologyChemistryOsmoreceptorTRPV1TaurineReceptorHomeostasisInternal medicineEndocrinologyBiophysicsNeuroscienceBiologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

The maintenance of hydromineral homeostasis requires bidirectional detection of changes in extracellular fluid osmolality by primary osmosensory neurons (ONs) in the organum vasculosum laminae terminalis (OVLT). Hypertonicity excites ONs in part through the mechanical activation of a variant transient receptor potential vanilloid-1 channel (dn-Trpv1). However, the mechanism by which local hypotonicity inhibits ONs in the OVLT remains unknown. Here, we show that hypotonicity can reduce the basal activity of dn-Trpv1 channels and hyperpolarize acutely isolated ONs. Surprisingly, we found that mice lacking dn-Trpv1 maintain normal inhibitory responses to hypotonicity when tested in situ. In the intact setting, hypotonicity inhibits ONs through a non-cell-autonomous mechanism that involves glial release of the glycine receptor agonist taurine through hypotonicity activated anion channels (HAAC) that are activated subsequent to Ca2+ influx through Trpv4 channels. Our study clarifies how Trpv4 channels contribute to the inhibition of OVLT ONs during hypotonicity in situ.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.024
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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

Citations32
Published2018
Admission routes2
Has abstractyes

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