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Record W2039367580 · doi:10.1183/09031936.02.00276702

Sepsis and hyperoxia effects on the pulmonary surfactant system in wild-type and iNOS knockout mice

2002· article· en· W2039367580 on OpenAlexaff
Timothy C. Bailey, Chelsea Cavanagh, Sanjay Mehta, J. F. Lewis, Ruud A. W. Veldhuizen

Bibliographic record

VenueEuropean Respiratory Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsHyperoxiaPulmonary surfactantSepsisNitric oxide synthaseNitric oxidePathophysiologyLungInternal medicineMedicineChemistryImmunologyEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

Alterations of pulmonary surfactant and increases in inducible nitric oxide synthase (iNOS) have been implicated in the pathophysiology of acute lung injury. It was hypothesised that these two observations are related and that alterations of the endogenous surfactant, due to either sepsis or hyperoxia, would be reduced in mice lacking the iNOS gene compared to wild-type mice. Wild-type and iNOS (-/-) mice were randomised into sham or sepsis, and in a separate experiment animals were randomised to normoxia or hyperoxia exposure for 48 h. Lungs were lavaged and analysed for total surfactant levels and surfactant subfractions (large (LA) and small (SA) aggregates). Both sepsis groups had decreased SA compared to sham groups with no significant difference between the two genotypes. Mice exposed to hyperoxia had a decreased amount of total surfactant when compared to normoxia controls and there was no significant difference between the two genotypes. It is concluded that inducible nitric oxide synthase does not influence the amount of pulmonary surfactant or surfactant subfractions recovered in lavage after 18 h of sepsis or 48 h of hyperoxia.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.057
GPT teacher head0.298
Teacher spread0.241 · 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

Citations18
Published2002
Admission routes1
Has abstractyes

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