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Impacts of strain, age, and temperature on respiratory pattern and rhythm<i>in vivo</i>in the neonatal rat

2025· article· en· W4411880128 on OpenAlexaffabout
William K. Milsom

Bibliographic record

VenuePhysiology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIn vivoRhythmStrain (injury)Respiratory systemBiologyPhysiologyInternal medicineMedicineAnatomyBiotechnology

Abstract

fetched live from OpenAlex

Variability in breathing rhythm and pattern are hallmarks of the early neonatal period in mammals. Despite this being well described in the literature, occurring both in in-vitro nerve recordings from reduced preparations as well as in the whole animal, there is little data documenting how this variability changes and stabilizes into a regular respiratory rhythm over the early neonatal period. It is also not clear how external factors such as species and temperature play a role in the degree of variability. Using impedance electrodes, we measured breathing pattern and frequency in two strains of neonatal rat pups (Sprague Dawley and Long Evans) exposed to two different temperatures (33 and 27C) on postnatal days 0, 1, 2, and 4. Age strongly influenced breathing frequency, with a significant increase in frequency and decrease in both short and long-term variability between P0 and P1 in both strains. Temperature did not have a significant effect on frequency or variability across age groups or between strains. This sudden change in frequency and variability may be due to a rapid shift in populations of inhibitory neurotransmitters within the respiratory pacemaker network in the brainstem. Further neurophysiological experiments will aid in identifying the key neurotransmitters responsible for mediating this shift and further our understanding of the broader significance of this rapid transition during early mammalian development. Funded by the NSERC of Canada.s This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.264

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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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