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Record W2055492722 · doi:10.1159/000138020

Characterization and Autoradiographic Distribution of the β-Adrenergic Receptor in the Rat Lung

2008· article· en· W2055492722 on OpenAlexaff
Mitchell S. Finkel, Rémi Quirion, Candace B. Pert, Randolph E. Patterson

Bibliographic record

VenuePharmacology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsPropranololDihydroalprenololAlprenololPindololEndocrinologyInternal medicineAdrenergic receptorTerbutalineChemistryReceptorEpinephrineAdrenergicLungNorepinephrineRadioligandDistribution (mathematics)IodocyanopindololBiologyMedicineAntagonistPartial agonistAgonistIntrinsic activityDopamine

Abstract

fetched live from OpenAlex

An unexpected distribution of the beta-adrenergic receptor in the rat lung was revealed by an autoradiographic technique. [3H]-Dihydroalprenolol binding was stereoselective. L-propranolol was 300 times more potent than D-propranolol in competition experiments. Scatchard analysis revealed a Kd of 1.1 nM and Bmax of 14 fmol/mg wet weight. Relative potencies of beta-adrenergic ligands were: propranolol greater than alprenolol greater than timolol greater than pindolol greater than isoproterenol greater than epinephrine greater than soterenol greater than metoprolol greater than terbutaline greater than norepinephrine. The autoradiograms generated revealed a diffuse pattern with binding always associated with tissue structures. We conclude that beta-adrenergic receptors are extensively distributed in the lung, being present in large and small airways and blood vessels.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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