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S169 Investigating the effect of baricitinib on neutrophilic inflammation in an ex vivo lung perfusion (EVLP) model of acute respiratory distress syndrome

2025· article· W4416101763 on OpenAlexaboutno aff
Delia Dorrian, Julie Strickland, A Boyle, S Tandel, Rebecca C. Coll, Daniel F. McAuley, Cecilia O’Kane

Bibliographic record

Venuenot available
Typearticle
Language
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsEx vivoBronchoalveolar lavageLungDiffuse alveolar damagePlaceboARDSInflammationMechanical ventilation

Abstract

fetched live from OpenAlex

Background Acute respiratory distress syndrome (ARDS) is driven by uncontrolled neutrophilic inflammation in the alveolar space with resultant damage to the epithelial and endothelial barrier, resulting in pulmonary oedema. Baricitinib is a JAK1/2 inhibitor which inhibits inflammation in experimental lung injury in animal models and reduces mortality in COVID related respiratory failure. The effect of baricitinib on human lung injury outside of COVID is unknown. Hypothesis JAK1/2 inhibition with baricitinib reduces LPS (lipopolysaccharide)-induced lung injury in ex vivo perfused and ventilated human lungs. Methods Human lungs unsuitable for transplantation, for which there was consent for use in research, were ventilated and perfused ex vivo, using a modified Toronto protocol. Lungs with intact alveolar fluid clearance at baseline were injured by instilling 6 mg LPS (E coli) into a lobe and adding whole blood to the perfusate at a final concentration of 1/10. Lungs were randomised to receive either baricitinib or placebo in the perfusate (final concentration baricitinib=50ng/ml to correspond with Cmax obtained in healthy volunteers receiving 4 mg/day, the standard dose of baricitinib, and that used in the treatment of COVID in RECOVERY). Bronchoalveolar lavage was carried out at 4 hours after LPS instillation. Total cell count in BAL was measured using an Eve Automated cell counter (NanoEntek) and differential white cell count carried out on cytospins prepared from BAL. Ethical approval was obtained from NRES (REC 14 LO 0250) and Queen’s University of Belfast School of Medicine Ethics Committee (SREC14/08). Results 13 pairs of lungs (26 in total) were obtained. Baseline fluid clearance was impaired in 3 lungs and these were excluded from the study. 12 lungs were randomised to receive placebo and 11 baricitinib. Baricitinib reduced BAL neutrophil count at 4 hours from median 5.76 (IQR 2.74–9.16) x104/ml to 2.02 (IQR 1.73–4.73) x104/ml (figure 1), *p=0.0489, Wilcoxon rank-sum test. The effect of baricitinib on markers of permeability, alveolar epithelial and endothelial injury will be measured. Conclusion Baricitinib reduces neutrophil count in the alveolar space in a human EVLP model of LPS-induced lung injury, supporting its potential to inhibit alveolar neutrophilic inflammation in non-COVID related ARDS.

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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.022
GPT teacher head0.334
Teacher spread0.312 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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