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Record W2262842780 · doi:10.1152/jappl.2000.88.2.573

Contractile and fatigue properties of the rat diaphragm musculature during the perinatal period

2000· article· en· W2262842780 on OpenAlexaff
Miguel Martin‐Caraballo, P Campagnaro, Yuan Gao, John J. Greer

Bibliographic record

VenueJournal of Applied Physiology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiaphragm (acoustics)Phrenic nerveContraction (grammar)Neuromuscular transmissionElectrophysiologyMuscle contractionAnatomyNeuromuscular junctionDiaphragm muscleCurareStimulationChemistryMedicineRespiratory systemAnesthesiaInternal medicineBiologyNeuroscience

Abstract

fetched live from OpenAlex

The following two hypotheses regarding diaphragm contractile properties in the perinatal rat were tested. First, there is a major transformation of contractile and fatigue properties during the period between the inception of inspiratory drive transmission in utero and birth. Second, the diaphragm muscle properties develop to functionally match changes occurring in phrenic motoneuron electrophysiological properties. Muscle force recordings and intracellular recordings of end-plate potentials were measured by using phrenic nerve-diaphragm muscle in vitro preparations isolated from rats on embryonic day 18 and postnatal days 0-1. The following age-dependent changes occurred: 1) twitch contraction and half relaxation times decreased approximately two- and threefold, respectively; 2) the tetanic force levels increased approximately fivefold; 3) the ratio of peak twitch force to maximum tetanic force decreased 2.3-fold; 4) the range of forces generated by the diaphragm in response to graded nerve stimulation increased approximately twofold; 5) the force-frequency curve was shifted to the right; and 6) the propensity for neuromuscular transmission failure decreased. In conclusion, the diaphragm contractile and phrenic motoneuron repetitive firing properties develop in concert so that the full range of potential diaphragm force recruitment can be utilized and problems associated with diaphragm fatigue are minimized.

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 score0.003

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Citations23
Published2000
Admission routes1
Has abstractyes

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