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Record W2090376677 · doi:10.1139/y01-034

Comparative molecular biology of natriuretic peptide receptors

2001· article· en· W2090376677 on OpenAlexvenueno aff
Shigehisa Hirose, Hiromi Hagiwara, Yoshio Takei

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2001
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsNatriuretic peptideNPR2ReceptorNPR1SubfamilyBiologyPeptideBrain natriuretic peptideCell biologyInternal medicineEndocrinologyBiochemistryGeneMedicine

Abstract

fetched live from OpenAlex

Analysis of the mammalian natriuretic peptide system has established the presence of three types of receptors with distinct structural and functional features and tissue distributions. To clarify the physiological role of each subtype, we studied the natriuretic peptide system in animals with specialized anatomical and physiological features. In this review, following a brief description of the comparative and evolutionary aspects of the ligands, we will analyze the structure and distribution of natriuretic peptide receptors in lower vertebrates, as well as those of rats with essential and salt-sensitive hypertension, and discuss the evolutionary aspects of the natriuretic peptide systems in mammals and fishes. Emphasis is placed on our series of studies with eel receptors that revealed (i) interesting variations in the pattern of intra- and inter-molecular disulfide bonding; (ii) dense chondrocyte localization of NPR-C, which opened a new field of study for natriuretic peptides and bone metabolism; and (iii) the presence of a new receptor subtype, NPR-D, which is abundant in the brain and a member of the receptor subfamily with a short cytoplasmic C-terminal tail.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.326
Teacher spread0.305 · 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

Citations35
Published2001
Admission routes1
Has abstractyes

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