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Record W2054992221 · doi:10.1513/pats.200808-078rm

Disrupting Actin-Myosin-Actin Connectivity in Airway Smooth Muscle as a Treatment for Asthma?

2009· review· en· W2054992221 on OpenAlexaff
Tera Lavoie, M. L. Dowell, Oren Lakser, William T. Gerthoffer, Jeffrey J. Fredberg, Chun Y. Seow, Richard W. Mitchell, Julian Solway

Bibliographic record

VenueProceedings of the American Thoracic Society · 2009
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of British Columbia
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsMyosinMedicineActinMuscle contractionContraction (grammar)AsthmaCell biologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Breathing is known to functionally antagonize bronchoconstriction caused by airway muscle contraction. During breathing, tidal lung inflation generates force fluctuations that are transmitted to the contracted airway muscle. In vitro, experimental application of force fluctuations to contracted airway smooth muscle strips causes them to relengthen. Such force fluctuation-induced relengthening (FFIR) likely represents the mechanism by which breathing antagonizes bronchoconstriction. Thus, understanding the mechanisms that regulate FFIR of contracted airway muscle could suggest novel therapeutic interventions to increase FFIR, and so to enhance the beneficial effects of breathing in suppressing bronchoconstriction. Here we propose that the connectivity between actin filaments in contracting airway myocytes is a key determinant of FFIR, and suggest that disrupting actin-myosin-actin connectivity by interfering with actin polymerization or with myosin polymerization merits further evaluation as a potential novel approach for preventing prolonged bronchoconstriction in asthma.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.055
GPT teacher head0.402
Teacher spread0.347 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the American Thoracic SocietySame topicAsthma and respiratory diseasesFrench-language works237,207