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Isoform-specific regulation of the lactate transporters MCT1 and MCT4 by contractile activity

2000· article· en· W2118862416 on OpenAlexaff
Arend Bonen, Mio Tonouchi, Dragana Miskovic, Catherine Heddle, John J. Heikkila, Andrew P. Halestrap

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInternal medicineEndocrinologyMessenger RNAStimulationGene isoformMonocarboxylate transporterTransporterChemistryBiologyBiochemistryMedicineGene

Abstract

fetched live from OpenAlex

We examined the isoform-specific regulation of monocarboxylate transporter (MCT)1 and MCT4 expression by contractile activity in red and white tibialis anterior muscles. After 1 and 3 wk of chronic muscle stimulation (24 h/day), MCT1 protein expression was increased in the red muscles (+78%, P < 0.05). In the white muscles, MCT1 was increased after 1 wk (+191%) and then was decreased after 3 wk. In the red muscle, MCT1 mRNA accumulation was increased only after 3 wk (+21%; P < 0.05). In the white muscle, MCT1 mRNA was increased after 1 wk (+30%; P < 0.05) and 3 wk (+15%; P < 0.05). MCT4 protein was not altered in either the red or white muscles after 1 or 3 wk. MCT4 mRNA was transiently lowered (approximately 15%) in both muscles in the 1st wk, but MCT4 mRNA levels were back to control levels after 3 wk. In conclusion, chronic contractile activity induces the expression of MCT1 but not MCT4. This increase in MCT1 alone was sufficient to increase lactate uptake from the circulation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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 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

Citations111
Published2000
Admission routes1
Has abstractyes

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