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Record W2546152069 · doi:10.7717/peerj.2635

Synthetic lung surfactants containing SP-B and SP-C peptides plus novel phospholipase-resistant lipids or glycerophospholipids

2016· article· en· W2546152069 on OpenAlexaff
Robert H. Notter, Rohun Gupta, Adrian L. Schwan, Zhengdong Wang, Mohanad Shkoor, Frans J. Walther

Bibliographic record

VenuePeerJ · 2016
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of Guelph
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood Institute
KeywordsPulmonary surfactantChemistryPOPCGlycerophospholipidsIn vivoChromatographyBiochemistryPhospholipidBiology

Abstract

fetched live from OpenAlex

Background This study examines the biophysical and preclinical pulmonary activity of synthetic lung surfactants containing novel phospholipase-resistant phosphonolipids or synthetic glycerophospholipids combined with Super Mini-B (S-MB) DATK and/or SP-Css ion-lock 1 peptides that replicate the functional biophysics of surfactant proteins (SP)-B and SP-C. Phospholipase-resistant phosphonolipids used in synthetic surfactants are DEPN-8 and PG-1, molecular analogs of dipalmitoyl phosphatidylcholine (DPPC) and palmitoyl-oleoyl phosphatidylglycerol (POPG), while glycerophospholipids used are active lipid components of native surfactant (DPPC:POPC:POPG 5:3:2 by weight). The objective of the work is to test whether these novel lipid/peptide synthetic surfactants have favorable preclinical activity (biophysical, pulmonary) for therapeutic use in reversing surfactant deficiency or dysfunction in lung disease or injury. Methods Surface activity of synthetic lipid/peptide surfactants was assessedin vitroat 37 °C by measuring adsorption in a stirred subphase apparatus and dynamic surface tension lowering in pulsating and captive bubble surfactometers. Shear viscosity was measured as a function of shear rate on a Wells-Brookfield micro-viscometer.In vivopulmonary activity was determined by measuring lung function (arterial oxygenation, dynamic lung compliance) in ventilated rats and rabbits with surfactant deficiency/dysfunction induced by saline lavage to lower arterial PO2to <100 mmHg, consistent with clinical acute respiratory distress syndrome (ARDS). Results Synthetic surfactants containing 5:3:2 DPPC:POPC:POPG or 9:1 DEPN-8:PG-1 combined with 3% (by wt) of S-MB DATK, 3% SP-Css ion-lock 1, or 1.5% each of both peptides all adsorbed rapidly to low equilibrium surface tensions and also reduced surface tension to ≤1 mN/m under dynamic compression at 37 °C. However, dual-peptide surfactants containing 1.5% S-MB DATK + 1.5% SP-Css ion-lock 1 combined with 9:1 DEPN-8:PG-1 or 5:3:2 DPPC:POPC:POPG had the greatestin vivoactivity in improving arterial oxygenation and dynamic lung compliance in ventilated animals with ARDS. Saline dispersions of these dual-peptide synthetic surfactants were also found to have shear viscosities comparable to or below those of current animal-derived surfactant drugs, supporting their potential ease of deliverability by instillation in future clinical applications. Discussion Our findings support the potential of dual-peptide synthetic lipid/peptide surfactants containing S-MB DATK + SP-Css ion-lock 1 for treating diseases of surfactant deficiency or dysfunction. Moreover, phospholipase-resistant dual-peptide surfactants containing DEPN-8/PG-1 may have particular applications in treating direct forms of ARDS where endogenous phospholipases are present in the lungs.

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 integrity0.0000.000
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 head0.056
GPT teacher head0.351
Teacher spread0.295 · 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
Published2016
Admission routes1
Has abstractyes

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