MétaCan
Menu
Back to cohort
Record W2006426743 · doi:10.1086/320428

Aerobic Capacity of Frog Skeletal Muscle during Hibernation

2001· article· en· W2006426743 on OpenAlexfundno aff
Julie St‐Pierre, Robert G. Boutilier

Bibliographic record

VenuePhysiological and Biochemical Zoology · 2001
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHibernation (computing)Skeletal muscleCitrate synthaseBiologyAdenosine triphosphateInternal medicineAerobic capacityCytochrome c oxidaseEndocrinologyATP synthaseGlycolysisMitochondrionCellular respirationLactate dehydrogenaseBiochemistryMetabolismEnzyme

Abstract

fetched live from OpenAlex

Frogs submerged at 3°C in hypoxic water (Po2 = mmHg) depress their metabolic rate to 25% of that seen in control animals with access to air. The hypometabolic state of the skeletal muscle in such cold‐submerged frogs is thought to be the most important contributor to the overall metabolic depression. The aim of this study was to determine whether the aerobic capacity of frog skeletal muscle became altered during 1–4 mo of hibernation to match the reduction in adenosine triphosphate (ATP) demand. To this end, the activities of key mitochondrial enzymes were measured in the skeletal muscle and in isolated mitochondria of frogs at different stages during hibernation. We also measured the activity of lactate dehydrogenase (LDH) as an indicator of glycolytic capacity. The activities of cytochrome c oxidase, citrate synthase, and LDH were significantly lower in frog skeletal muscle after 4 mo of hibernation compared with control conditions. The reduction in skeletal muscle aerobic capacity is apparently due to changes in the intrinsic properties of the mitochondria. Overall, these results indicate an important reorganisation of ATP‐producing pathways during long‐term metabolic depression to match the lowered ATP demand.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.278

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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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

Citations61
Published2001
Admission routes1
Has abstractyes

Explore more

Same venuePhysiological and Biochemical ZoologySame topicAdipose Tissue and MetabolismFrench-language works237,207