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Record W4388640109 · doi:10.1016/j.heliyon.2023.e22280

Expression of the kidney anion exchanger 1 affects WNK4 and SPAK phosphorylation and results in claudin-4 phosphorylation

2023· article· en· W4388640109 on OpenAlexafffund
Rawad Lashhab, Grace Essuman, María Chávez‐Canales, R. Todd Alexander, Emmanuelle Cordat

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon Transport and Channel Regulation
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchConsejo Nacional de Ciencia y TecnologíaUniversidad Nacional Autónoma de MéxicoKidney Foundation of CanadaUniversity of Alberta
KeywordsParacellular transportClaudinPhosphorylationReabsorptionTranscellularCell biologyChemistryTight junctionBiologyBiochemistryKidneyEndocrinology

Abstract

fetched live from OpenAlex

In the renal collecting ducts, chloride reabsorption occurs through both transcellular and paracellular pathways. Recent literature highlights a functional interplay between both pathways. We recently showed that in polarized inner medullary collecting duct cells, expression of the basolateral kidney anion exchanger 1 (kAE1) results in a decreased transepithelial electrical resistance (TEER), in a claudin-4 dependent pathway. Claudin-4 is a paracellular sodium blocker and chloride pore. Here, we show that kAE1 expression in mouse inner medullary collecting duct cells triggers WNK4, SPAK and claudin-4 phosphorylation. Expression of a functionally dead kAE1 E681Q mutant has no effect on phosphorylation of these proteins. Expression of a catalytically inactive WNK4 D321A or chloride-insensitive WNK4 L319F mutant abolishes kAE1 effect on TEER, supporting a contribution of WNK4 to the process. We propose that variations of the cytosolic pH and chloride concentration upon kAE1 expression alter WNK4 kinase activity and tight junction properties.

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 score0.358
Threshold uncertainty score0.295

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 head0.010
GPT teacher head0.230
Teacher spread0.219 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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