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K<sup>+</sup>‐Dependent Na<sup>+</sup>/Ca<sup>2+</sup> Exchangers in the Brain

2002· article· en· W2092087068 on OpenAlexaff
Jonathan Lytton, Xiaofang Li, Hui Dong, Alexander Kraev

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsMount Sinai HospitalLunenfeld-Tanenbaum Research InstituteUniversity of Calgary
Fundersnot available
KeywordsHomeostasisSodium-calcium exchangerGene isoformContext (archaeology)ChemistryCalciumCell biologyBiophysicsBiochemistryGeneBiology

Abstract

fetched live from OpenAlex

Sodium-calcium exchange was first characterized in heart myocytes and squid axon more than 3 decades ago. Since then, it has been appreciated that functioning of the Na/Ca exchanger molecule plays a critical role in calcium homeostasis in neurons. Genome analysis indicates that Na/Ca exchangers are a superfamily encoded by 7 different genes divided into 2 groups: the Na/Ca exchangers (NCX; SLC8) and the Na/Ca+K exchangers (NCKX; SLC24). Two different NCX genes, NCX1 and NCX2, are highly expressed in brain. We recently described the widespread expression of 2 NCKX-type exchangers in brain, NCKX2 and NCKX3, and uncovered evidence for expression of another, NCKX4. The unique role that each different exchanger plays in neuronal calcium homeostasis, however, awaits further investigation. To begin exploring this central question, we examined both the expression pattern and the functional properties of the K-dependent Na/Ca exchanger isoforms expressed in brain and compared and contrasted these with NCX-type exchangers. Distinct patterns of transcript abundance, regional distribution, and developmental expression were noted for each isoform. Functional properties, including stoichiometry and the kinetic characteristics of ion binding, were determined for NCKX2 and are discussed in the context of cellular Ca2+ signaling.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.306
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations67
Published2002
Admission routes1
Has abstractyes

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