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Record W2085451734 · doi:10.1159/000047800

Regulation of Kv1.3 Channels in Activated Human T Lymphocytes by Ca<sup>2+</sup>-Dependent Pathways

2001· article· en· W2085451734 on OpenAlexaff
Martin C. Chang, Rajesh Khanna, Lyanne C. Schlichter

Bibliographic record

VenueCellular Physiology and Biochemistry · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsLymphoblastCalmodulinSignal transductionProtein kinase ACell biologyKinaseChemistryTyrosine kinaseBiologyMolecular biologyBiochemistryCell cultureEnzyme

Abstract

fetched live from OpenAlex

Activated T lymphoblasts respond more effectively to mitogenic stimuli than resting T cells, partly through differences in Ca(2+) signaling, which in turn depend on K(+) channel activity. Both Kv1.3 and Ca(2+)-activated K(+) (SK4) channels are up-regulated in T lymphoblasts. Since Ca(2+)- and calmodulin (CaM)-dependent signal-ing are key pathways in T-cell activation, we investigated their involvement in regulating the Kv1.3 current. Kv1.3 in lymphoblasts was significantly inhibited by elevating internal Ca(2+) to the micromolar level. It was also reduced in a Ca(2+)-dependent manner by inhibiting CaM with W-7 or calmidazolium. Part of the CaM-dependence is likely through CaM kinase since the current was also inhibited by the antagonist, KN-62, but not by the inactive analogue, KN-04. Kinase inhibition, unlike CaM inhibition, was only effective at physiological temperatures, a difference that implies involvement of more than one mechanism. We demonstrated a biochemical association of Kv1.3 protein in lymphoblasts with the multifunctional type II CaM kinase, but not with calmodulin. Thus, Kv1.3 forms a multi-protein complex with CaM kinase II (which binds to Ca(2+)/CaM) and previously identified proteins (e.g., PSD-95, src tyrosine kinase) that position the channel to respond to signaling pathways that are crucial for T-cell activation and proliferation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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.

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

Citations9
Published2001
Admission routes1
Has abstractyes

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