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Record W1482544899 · doi:10.1159/000058806

Molecular Mechanisms in Eosinophil Activation

2000· review· en· W1482544899 on OpenAlexaff
Redwan Moqbel, Paige Lacy

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReceptorHeterologousDesensitization (medicine)NPR1Vascular smooth muscleInternal medicineHomologous desensitizationGuanylate cyclase 2CChemistryEndocrinologyHormoneBiologyCyclaseNatriuretic peptideBiochemistrySmooth muscleMedicine

Abstract

fetched live from OpenAlex

Two atrial natriuretic factor (ANF) receptor subtypes are present in vascular nooth muscle cells: the B receptors (or biologically active) coupled to a guanylate cyclase ad the C receptors (clearance) representing 95% of the total number of ANF binding sites but noncoupled to a guanylate cyclase. Using binding experiments with 125I-ANF and measurement of cGMP production stimulated by ANF, we were able to demonstrate that ANF receptors are sensitive to homologous (induced by ANF) and heterologous regulation (induced by angiotensin II, All) in rat cultured vascular smooth muscle cells. The effect of the two hormones showed marked differences, in their time course, their reversibility and their consequence on guanylate cyclase activity. Although both ANF and All reduced the total umber of ANF binding sites after 18 h, ANF induced a desensitization of the guanylate cyclase whereas All elicited a potentialization of this system. From these results, we have included that in vascular cells B receptors are sensitive to homologous regulation and C receptors are sensitive to heterologous regulation by All. This also highlights a specific interaction between ANF and All at the receptor level.

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 score0.003
Threshold uncertainty score0.009

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.028
GPT teacher head0.325
Teacher spread0.297 · 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

Citations12
Published2000
Admission routes1
Has abstractyes

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