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Record W2162780800 · doi:10.1074/jbc.m304879200

Compensatory Anion Currents in Kv1.3 Channel-deficient Thymocytes

2003· article· en· W2162780800 on OpenAlexafffund
Pandelakis A. Koni, Rajesh Khanna, Martin C. Chang, Michael D. Tang, Leonard K. Kaczmarek, Lyanne C. Schlichter, Richard A. Flavell

Bibliographic record

VenueJournal of Biological Chemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersNational Institute on Deafness and Other Communication DisordersNatural Sciences and Engineering Research Council of Canada
KeywordsIon channelBiophysicsIonChemistryChannel (broadcasting)Cell biologyBiologyInternal medicineNeuroscienceComputer scienceBiochemistryMedicineTelecommunications

Abstract

fetched live from OpenAlex

Kv1.3 is a voltage-gated potassium channel with roles in human T cell activation/proliferation, cell-mediated cytotoxicity, and volume regulation and is thus a target for therapeutic control of T cell responses. Kv1.3 is also present in some mouse thymocyte subsets and splenocytes, but its role in the mouse is less well understood. We report the generation and characterization of Kv1.3-deficient (Kv1.3-/-) mice. In contrast to wild-type cells, the majority of Kv1.3-/- thymocytes had no detectable voltage-dependent potassium current, although RNA and protein for several potassium channel subunits were found in the thymocyte population. Surprisingly, the level of chloride current in the Kv1.3-/- thymocytes was increased approximately 50-fold over that in wild-type cells. There were no abnormalities in lymphocyte types or absolute numbers in thymus, spleen, and lymph nodes and no obvious defect in thymocyte apoptosis or T cell proliferation in the Kv1.3-/- animals. The compensatory effects of the enhanced chloride current may account for the apparent lack of immune system defects in Kv1.3-/-mice.

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 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 score0.037
Threshold uncertainty score0.352

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 integrity0.0000.000
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 head0.027
GPT teacher head0.263
Teacher spread0.236 · 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 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

Citations88
Published2003
Admission routes2
Has abstractyes

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