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Energy Metabolism During Fatigue In Fdb Muscle Is Impaired By The Lack Of KAtp Channel Activity

2010· article· en· W2335621391 on OpenAlexaff
Kyle Scott, Zhen Li, Maria Benkhalti, Jean‐Marc Renaud

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGlycolysisKir6.2Internal medicineGlycogenATPaseChemistryEndocrinologySkeletal muscleMuscle fatigueATP-sensitive potassium channelMetaboliteMyosinMetabolismContraction (grammar)BiochemistryEnzymeBiologyMedicineElectromyographyGene

Abstract

fetched live from OpenAlex

PURPOSE: In skeletal muscle, the KATP channel is crucial in preventing fiber damage during exercise and fatigue. The channel is activated when energy levels fall and thus behaves as an energy sensor. Once activated, it directly reduces action potential amplitude, which then lowers Ca2+ release and force production. It is believed that together the latter effects lower the activity of the Ca2+ATPase and myosin ATPase in order to prevent damaging ATP depletion. So far, it remains unknown how the KATP channel affects energy metabolism during fatigue in skeletal muscle. The objective of this study was thus to determine whether the absence of KATP channel activity results in lower ATP levels and an impaired capacity to generate ATP during fatigue. METHODS: FDB bundles were fatigued with 1 tetanic contraction/sec for 180s at 37°C. KATP channel deficient fibers were obtained using fibers from Kir6.2-/- mice, which are null mice for the Kir6.2 gene that encodes for the protein forming the channel pore. Muscles were freeze-clamped in liquid nitrogen at different times during fatigue for metabolite determination. PCr, ATP and lactate were determined using enzymatic tests. The amount of glucosyl units entering glycolysis was calculated from glycogen breakdown and glucose uptake (using the 3H-2DG marker). The amount of unaccounted glucosyl units (or the total amount of intermediate metabolites) was calculated by subtracting the amount of lactate and 14CO2 (produced from 14C6-glucose) from the amount entering glycolysis. RESULTS: During fatigue the decreases in PCr were not different between W.T. and Kir6.2-/- FDB. ATP levels significantly decreased during the first 40 s of fatigue to a greater extent in Kir6.2-/- than W.T. FDB. It then reincreased during the next two min in W.T. but not in Kir6.2-/- FDB. Glucose uptake was greater while glycogen breakdown was smaller in W.T. than in Kir6.2-/- FDB. However, the amount of glucosyl units entering glycolysis was the same between the two muscle groups. Surprisingly, the amount of lactate produced was significantly greater in W.T. than in Kir6.2-/- FDB and the difference could not be explained by a greater difference in 14CO2 production. Consequently, the amount of unaccounted glucosyl units was greater in Kir6.2-/- than in W.T. FDB. CONCLUSION: The lack of KATP channel activity during fatigue significantly impaired energy metabolism in which the capacity of producing ATP during fatigue is reduced in Kir6.2-/- than W.T. FDB. This impairment may also be one of the causes of fiber damage in KATP channel deficient muscles.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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