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Record W1969787676 · doi:10.1139/o04-129

The cardiac Na-H exchanger: a key downstream mediator for the cellular hypertrophic effects of paracrine, autocrine and hormonal factors

2004· review· en· W1969787676 on OpenAlexaffvenue
Larry Fliegel, Morris Karmazyn

Bibliographic record

VenueBiochemistry and Cell Biology · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParacrine signallingMediatorAutocrine signallingHormoneDownstream (manufacturing)Cell biologyBiologyKey (lock)Internal medicineEndocrinologyMedicineBiochemistryBusinessEcologyReceptor

Abstract

fetched live from OpenAlex

The major mechanism by which the heart cell regulates intracellular pH is the Na(+)-H(+) exchanger (NHE) with the NHE-1 isoform as the primary cardiac subtype. Although NHE-1 has been implicated in mediating ischemic injury, more recent evidence implicates the antiporter as a key mediator of hypertrophy, which is produced by various autocrine, paracrine and hormonal factors such as endothelin-1, angiotensin II, and alpha(1) adrenoceptor agonists. These agonists activate the antiporter via phosphorylation-dependent processes. NHE-1 inhibition is likely conducive to attenuating the remodelling process after myocardial infarction. These effects probably occur independently of infarct size reduction and involve attenuation of subsequent postinfarction heart failure. As such, inhibitors of NHE offer substantial promise for clinical development that will attenuate acute responses to myocardial postinfarction and chronic pos t infarction, which evolve toward heart failure. The regulation of NHE-1 is discussed as is its potential role in mediating cardiomyocyte hypertrophy.

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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations56
Published2004
Admission routes2
Has abstractyes

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