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Excitation-contraction coupling in pulmonary vascular smooth muscle involves tyrosine kinase and Rho kinase

2001· article· en· W2138214694 on OpenAlexaff
Luke J. Janssen, Hwa Lu-Chao, Stuart J. Netherton

Bibliographic record

VenueAmerican Journal of Physiology-Lung Cellular and Molecular Physiology · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRho-associated protein kinaseCalphostin CTyrosine kinaseChelerythrineInternal medicineEndocrinologyChemistryCyclopiazonic acidProtein kinase CBiologySignal transductionIntracellularBiochemistryMedicine

Abstract

fetched live from OpenAlex

We investigated the mechanisms that underlie the responses to norepinephrine (NE) and thromboxane (Tx) A(2) (TxA2) in the canine pulmonary vasculature with fura 2 fluorimetric, intracellular microelectrode, and force transduction techniques. KCl, caffeine, and cyclopiazonic acid elevated intracellular Ca2+ concentration levels and tone, indicating that Ca2+ mobilization is sufficient to produce contraction. However, contractions evoked by NE or the TxA2 mimetic U-46619 were unaffected by nifedipine or by omitting external Ca2+ and were reduced only partially by depleting the internal Ca2+ store; furthermore, NE-evoked depolarization was subthreshold for voltage-dependent Ca2+ currents. Agonist-evoked contractions were insensitive to inhibitors of protein kinase C (calphostin C and chelerythrine), mitogen-activated protein kinase kinase (PD-98059), and p38 kinase (SB-203580) but were abolished by the tyrosine kinase inhibitor genistein and the Rho kinase inhibitor Y-27632. We conclude that, although Ca2+ influx and Ca2+ release are sufficient for contraction, they are not necessary for adrenergic or TxA2 contractions. Instead, excitation-contraction coupling involves the activation of tyrosine kinase and Rho kinase, leading to enhanced Ca2+ sensitivity of the contractile apparatus.

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 categoriesMeta-epidemiology (narrow)
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 score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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.

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

Citations76
Published2001
Admission routes1
Has abstractyes

Explore more

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