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Influence of tension time on muscle fiber sarcolemmal injury in rat diaphragm

2000· article· en· W84677969 on OpenAlexaff
Ercheng Zhu, Alain Steve Comtois, Liwei Fang, Norman Comtois, A. Grassino

Bibliographic record

VenueJournal of Applied Physiology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSarcolemmaStimulationChemistryDiaphragm (acoustics)EndocrinologyInternal medicineAnatomyMedicineMembraneBiochemistry

Abstract

fetched live from OpenAlex

We hypothesized that the amount of sarcolemmal injury is directly related to the total tension time (TT(tot)), calculated as mean tension x total stimulation time. Diaphragm strips from Sprague-Dawley rats were superfused at optimal muscle length with Krebs containing procion orange to identify sarcolemmal injury. TT(tot) was induced by stimulation with 100 Hz for 3 min at duty cycles of 0.02, 0.15, 0.3, and 0.6, or with continuous contractions at 0.2, 0.4, 0.6, and 1.0 of maximal tension. A significant positive correlation between TT(tot) and the percentage of fibers with injured sarcolemma (r(2) = 0.63, P < 0.05) is seen. Stimulation (at 100 Hz, duty cycle = 1) resulted in fast fatigue with low injury, likely caused by altered membrane conductivity. Stimulations inducing the largest injury are those showing progressive force loss and high TT(tot), where injury may be due to activation of membrane degradative enzymes. The maximal tension measured at 20 min poststimulation was inversely related to the number of fibers injured, suggesting loss of force is caused by cellular injury.

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: Observational · Consensus signal: none
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 head0.003
GPT teacher head0.218
Teacher spread0.214 · 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 designObservational
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

Citations16
Published2000
Admission routes1
Has abstractyes

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