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Surfactant Supplementation With Synthetic Mixture of Phospholipids and Synthetic Surfactant Protein B Analog in Murine Influenza

2025· article· en· W4410274466 on OpenAlexaff
R. Duncan Hite, Ruud A. W. Veldhuizen, Cathy E. Lloyd, J.P. Bridges, Evan Goldin, Rachel Lehrman

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPulmonary surfactantMedicineVirologyBiochemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Rationale: Degradation and dysfunction of pulmonary surfactant mediated by acute inflammation contribute significantly to ARDS pathophysiology. Surfactant replacement therapy (SRT) in premature newborns lowers neonatal mortality, but SRT trials in adults with ARDS have yet to improve outcomes. Advances in this potentially impactful therapeutic intervention depend on developing stable synthetic alternatives to commercially available natural surfactants. Depletion of the hydrophobic surfactant protein B (SP-B) and phosphatidylglycerol (PG), the most abundant anionic surfactant phospholipid (PL), is common in lavage fluid of patients with ARDS. Congenital absence of SP-B is a lethal condition, and SP-B requires the presence of anionic PL. This study examines the impact of targeted SRT using a novel synthetic SP-B analog (sSP-B) combined with PG-containing PLs in mice infected with influenza. Methods:Influenza Infection: Influenza H1N1 (A/PR/8/34) was instilled i.n. into 8-10 week old Balb/c mice under ketamine anesthesia (Day 0). Surfactant Pellet (SP) Preparation: Whole lung lavage (3 x 1 ml) was collected on Day 7, pooled and separated using sequential centrifugation (remove cells) and ultracentrifugation (separate SP from supernatant). Total PL content in SP was quantified using inorganic phosphorous. Surfactant Function: Adsorption (γads) and minimum surface tension (γmin) were measured using a constrained sessile droplet surfactometer (CDS) at 37⁰C and 1 cycle/sec. Ex vivo SRT: CDS was completed using pooled SP from flu mice (n=3-7) either alone or supplemented (10-50% total PL) with an SRT: Infasurf™ (bovine natural surfactant, OnyBiotech), PL mix (DPPC:POPG, 7:3) or PL mix plus sSP-B dimer (2%, BioSuperior Technology). All measurements were at final total PL = 2.0 mg/ml. CDS of each SRT (100% total PL) was separately performed. Mice treated with i.n. saline served as controls. Results: At 7 days post influenza, SPs demonstrate marked surfactant dysfunction (increased γmin) as compared to sham (Table 1). Ex vivo SRT of influenza SPs with PL mix plus 2% sSP-B significantly lowers γmin at 50% total PL with efficacy equivalent to Infasurf. Lesser reductions in γmin are seen at 10% and 25% total PL (p < 0.05, data not shown). In contrast, SRT with the PL mix alone does not improve γmin. Adsorption surface tensions do not differ significantly between sham and influenza mice (with or without SRT). Conclusion: Supplementation of dysfunctional surfactants with a synthetic mixture of phospholipids and a synthetic SP-B analog restores surface tension lowering activity ex vivo. Future in vivo SRT studies in mice with influenza are warranted.

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 score0.002

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 integrity0.0010.001
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 head0.020
GPT teacher head0.370
Teacher spread0.349 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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