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Record W4321368021 · doi:10.1016/j.isci.2023.106258

Osmotically evoked PLCδ1-dependent translocation of ΔN-TRPV1 channels in rat supraoptic neurons

2023· article· en· W4321368021 on OpenAlexafffund
Kirk D. Haan, Sung Jin Park, Yoshikazu Nakamura, Kiyoko Fukami, Thomas E. Fisher

Bibliographic record

VenueiScience · 2023
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsUniversity of Saskatchewan
FundersCollege of Education, University of SaskatchewanNatural Sciences and Engineering Research Council of CanadaSaskatchewan Health Research Foundation
KeywordsVasopressinOsmoregulationExocytosisCell biologyHomeostasisChromosomal translocationPlasma osmolalityChemistryTRPV1OsmoreceptorHypertonic salineSupraoptic nucleusInternal medicineTonicityEndocrinologyBiophysicsBiologyBiochemistrySecretionTransient receptor potential channelMedicine

Abstract

fetched live from OpenAlex

Osmoregulation is an essential homeostatic process that requires constant release of vasopressin during sustained increases in plasma osmolality. The magnocellular neurosecretory cells (MNCs) respond to increases in external osmolality through increases in the activity of ΔN-TRPV1 channels, which leads to increased action potential firing and vasopressin release. We show that sustained exposure of acutely isolated rat and mouse MNCs to hypertonic solutions (90 min) causes a reversible translocation of ΔN-TRPV1 channels from internal stores to the plasma membrane that depends on the activation of phospholipase C and on SNARE-dependent exocytosis. ΔN-TRPV1 channel translocation is absent in MNCs isolated from transgenic mice lacking the PLCδ1 isoform, suggesting that PLCδ1 is essential for triggering this process. The translocation of ΔN-TRPV1 channels to the cell surface could contribute to the maintenance of MNC excitability during sustained increases in osmolality. Our data therefore have important implications for the mechanisms underlying mammalian osmoregulation.

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 score0.028
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.286
Teacher spread0.243 · 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

Citations7
Published2023
Admission routes2
Has abstractyes

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