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Record W4212819070 · doi:10.3389/fphys.2022.833665

Mechanosensitivity of Murine Lung Slowly Adapting Receptors: Minimal Impact of Chemosensory, Serotonergic, and Purinergic Signaling

2022· article· en· W4212819070 on OpenAlexafffund
Nicolle J. Domnik, Sandra G. Vincent, John T. Fisher

Bibliographic record

VenueFrontiers in Physiology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsQueen's UniversityWestern University
FundersCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of TorontoQueen's University
KeywordsPurinergic receptorSerotonergicReceptorPurinergic signallingLungNeuroscienceSignal transductionCell biologyBiologyChemistryMedicinePharmacologySerotoninInternal medicineAdenosine receptorAgonist

Abstract

fetched live from OpenAlex

Murine slowly adapting receptors (SARs) within airway smooth muscle provide volume-related feedback; however, their mechanosensitivity and morphology are incompletely characterized. We explored two aspects of SAR physiology: their inherent static mechanosensitivity and a potential link to pulmonary neuroepithelial bodies (NEBs). SAR mechanosensitivity displays a rate sensitivity linked to speed of inflation; however, to what extent static SAR mechanosensitivity is tuned for the very rapid breathing frequency (Bf) of small mammals (e.g., mouse) is unclear. NEB-associated, morphologically described smooth muscle-associated receptors (SMARs) may be a structural analog for functionally characterized SARs, suggesting functional linkages between SARs and NEBs. We addressed the hypotheses that: (1) rapid murine Bf is associated with enhanced in vivo SAR static sensitivity; (2) if SARs and NEBs are functionally linked, stimuli reported to impact NEB function would alter SAR mechanosensitivity. We measured SAR action potential discharge frequency (AP f, action potentials/s) during quasi-static inflation [0–20 cmH2O trans-respiratory pressure (PTR)] in NEB-relevant conditions of hypoxia (FIO2 = 0.1), hypercarbia (FICO2 = 0.1), and pharmacologic intervention (serotonergic 5-HT3 receptor antagonist, Tropisetron, 4.5 mg/kg; P2 purinergic receptor antagonist, Suramin, 50 mg/kg). In all protocols, we obtained: (1) AP f vs. PTR; (2) PTR threshold; and (3) AP f onset at PTR threshold. The murine AP f vs. PTR response comprises high AP f (average maximum AP f: 236.1 ± 11.1 AP/s at 20 cmH2O), a low PTR threshold (mean 2.0 ± 0.1 cmH2O), and a plateau in AP f between 15 and 20 cmH2O. Murine SAR mechanosensitivity (AP f vs. PTR) is up to 60% greater than that reported for larger mammals. Even the maximum difference between intervention and control conditions was minimally impacted by NEB-related alterations: Tropisetron −7.6 ± 1.8% (p = 0.005); Suramin −10.6 ± 1.5% (p = 0.01); hypoxia +9.3 ± 1.9% (p < 0.001); and hypercarbia −6.2 ± 0.9% (p < 0.001). We conclude that the high sensitivity of murine SARs to inflation provides enhanced resolution of operating lung volume, which is aligned with the rapid Bf of the mouse. We found minimal evidence supporting a functional link between SARs and NEBs and speculate that the <10% change in SAR mechanosensitivity during altered NEB-related stimuli is not consistent with a meaningful physiologic role.

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 score0.004

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 integrity0.0000.001
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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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