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Record W2131276542 · doi:10.1172/jci15316

Different mechanisms underlying the stimulation of KCa channels by nitric oxide and carbon monoxide

2002· article· en· W2131276542 on OpenAlexafffund
Lingyun Wu, Kun Cao, Yanjie Lu, Rui Wang

Bibliographic record

VenueJournal of Clinical Investigation · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsNitric oxideChemistryBiophysicsStimulationProtein subunitCarbon monoxideAgonistPharmacologyNitric oxide synthaseCell biologyBiochemistryInternal medicineMedicineBiologyReceptorGene

Abstract

fetched live from OpenAlex

The molecular mechanisms underlying the effects of nitric oxide (NO) and carbon monoxide (CO), individually and collectively, on large-conductance calcium-activated K(+) (K(Ca)) channels were investigated in rat vascular smooth muscle cells (SMCs). Both NO and CO increased the activity of native K(Ca) channels. Dehydrosoyasaponin-I, a specific agonist for beta subunit of K(Ca) channels, increased the open probability of native K(Ca) channels only when it was delivered to the cytoplasmic surface of membrane. CO, but not NO, further increased the activity of native K(Ca) channels that had been maximally stimulated by dehydrosoyasaponin-I. After treatment of SMCs with anti-K(Ca),beta subunit antisense oligodeoxynucleotides, the stimulatory effect of NO, but not of CO, on K(Ca) channels was nullified. CO, but not NO, enhanced the K(Ca) current densities of heterologously expressed cloned K(Ca),alpha subunit, showing that the presence of K(Ca),beta subunit is not a necessity for the effect of CO but essential for that of NO. Finally, pretreatment of SMCs with NO abolished the effects of subsequently applied CO or diethyl pyrocarbonate on K(Ca) channels. In summary, the stimulatory effects of CO and NO on K(Ca) channels rely on the specific interactions of these gases with K(Ca),alpha and K(Ca),beta subunits.

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 score0.579
Threshold uncertainty score0.244

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 head0.092
GPT teacher head0.327
Teacher spread0.235 · 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

Citations100
Published2002
Admission routes2
Has abstractyes

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