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Record W2105276739 · doi:10.1152/ajplung.00391.2002

Early surfactant administration protects against lung dysfunction in a mouse model of ARDS

2003· article· en· W2105276739 on OpenAlexaff
Vijay P. A. Rasaiah, Jaret Malloy, James F. Lewis, Ruud A. W. Veldhuizen

Bibliographic record

VenueAmerican Journal of Physiology-Lung Cellular and Molecular Physiology · 2003
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsARDSMedicinePulmonary surfactantLungPulmonary complianceMechanical ventilationSepsisVentilation (architecture)AnesthesiaPerforationLigationPharmacologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

Sepsis can predispose the lung to insults such as mechanical ventilation (MV). It was hypothesized that treating the lung with exogenous surfactant early in the development of sepsis will reduce the lung dysfunction associated with MV 18 h later. Mice underwent sham or cecal ligation and perforation (CLP) surgery. Immediately after surgery, mice were either untreated or given 100 mg/kg of bovine lipid extract surfactant intratracheally. Eighteen hours later, the lungs were removed and analyzed either immediately or following ventilation ex vivo for 2 h by an "injurious" mode of ventilation (20 ml/kg, 0 cm positive end-expiratory pressure). In nonventilated lungs, exogenous surfactant had no impact on compliance or IL-6 concentrations in the lungs. In the ventilated groups, the administered surfactant had a significant protective effect on the lung dysfunction induced by MV, but only in the CLP lungs. We conclude that administration of exogenous surfactant at the time of a systemic insult can protect the lung from the damaging effects of MV 18 h later.

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)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Physiology-Lung Cellular and Molecular PhysiologySame topicRespiratory Support and MechanismsFrench-language works237,207