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Amplification of Transducer Gain by Angiotensin II-Mediated Enhancement of Cortical Actin Density in Osmosensory Neurons

2008· article· en· W1991374167 on OpenAlexafffund
Zizhen Zhang, Charles W. Bourque

Bibliographic record

VenueJournal of Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalMontreal General Hospital
FundersCanadian Institutes of Health ResearchMcGill University Health CentreMcGill UniversityHeart and Stroke Foundation of Canada
KeywordsSupraoptic nucleusAngiotensin IIActinActin remodeling of neuronsCell biologyBiologyNeuroscienceChemistryActin cytoskeletonReceptorCytoskeletonNucleusCellBiochemistry

Abstract

fetched live from OpenAlex

Osmosensory neurons transduce osmotic signals into a neural spike code that commands behavioral and endocrine responses that mediate body fluid homeostasis. Although changes in osmoregulatory reflex gain are known to occur under physiological and pathological conditions, the basis for this modulation is unknown. Here, we show that angiotensin II amplifies osmosensory transduction by enhancing the proportional relationship between osmolality, receptor potential, and action potential firing in rat supraoptic nucleus neurons. This effect is mediated by a phospholipase C- and protein kinase C-dependent increase in cellular mechanosensitivity that is associated with a rapid increase in cortical actin filament density. Preventing this increase with cytochalasin D eliminated the enhancement of mechanosensitivity, whereas enhancing actin filament density with jasplakinolide potentiated mechanosensitivity and occluded the effects of angiotensin II. These results indicate that a receptor-mediated increase in cortical actin density can enhance osmosensitivity in acutely isolated supraoptic neurons.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.065
GPT teacher head0.311
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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

Citations48
Published2008
Admission routes2
Has abstractyes

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