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Record W2171831420 · doi:10.1183/09031936.06.00112605

Beyond the dogma: novel β<sub>2</sub>-adrenoceptor signalling in the airways

2006· review· en· W2171831420 on OpenAlexaff
M A Giembycz, Robert Newton

Bibliographic record

VenueEuropean Respiratory Journal · 2006
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsInstitute of Infection and ImmunityUniversity of Calgary
Fundersnot available
KeywordsMedicineSignallingAdrenergic receptorβ2 adrenergic receptorReceptorInternal medicineCell biologyAgonist

Abstract

fetched live from OpenAlex

beta(2)-Adrenoceptor agonists evoke rapid bronchodilatation and are the mainstay of the treatment of asthma symptoms worldwide. The mechanism of action of this class of compounds is believed to involve the stimulation of adenylyl cyclase and subsequent activation of the cyclic adenosine monosphosphate (cAMP)/cAMP-dependent protein kinase cascade. This classical model of beta(2)-adrenoceptor-mediated signal transduction is deeply entrenched, but there is compelling evidence that agonism of beta(2)-adrenoceptors can lead to the activation of multiple effector pathways, which now compels researchers in academia and the pharmaceutical industry alike to think beyond the traditional dogma. Therefore, the regulation by beta(2)-adrenoceptor agonists of responses, including airways smooth muscle tone and the secretory capacity of the epithelium and pro-inflammatory/immune cells, may be highly complex, involving both cAMP-dependent and -independent mechanisms that, in many cases, may act in concert. In this article, the current status of beta(2)-adrenoceptor-mediated signalling in the airways is reviewed in the context of understanding mechanisms that may underlie both the beneficial and detrimental effects of these drugs in asthma symptom management.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.094
GPT teacher head0.309
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations142
Published2006
Admission routes1
Has abstractyes

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