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The Effect of Cholesterol on the Biophysical Inhibition of Pulmonary Surfactant by Albumin

2016· article· en· W4389024206 on OpenAlexaffabout
Ruud A. W. Veldhuizen, Scott Milos, Jake Ruehlicke, Cory Yamashita

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPulmonary surfactantSurface tensionChemistryBovine serum albuminAlbuminARDSChromatographyPulmonary complianceCholesterolLungBiochemistryInternal medicineMedicine

Abstract

fetched live from OpenAlex

Pulmonary surfactant is a mixture of 85% phospholipids, 5–8% cholesterol and 5–8% surfactant proteins which forms a surface tension reducing lipid film at the air‐liquid interface of the alveoli. By reducing the surface tension to near 0mN/m values during compression (i.e. exhalation) surfactant maintains alveolar stability at low lung volumes and maintains proper lung compliance. The importance of surfactant is evident in Acute Respiratory Distress Syndrome (ARDS) in which the dysfunction of surfactant contributes to hypoxemia, regional areas of collapse and reduced lung compliance. Specifically, serum proteins, such as Albumin, leaking into the lung during ARDS have been shown to interfere with surfactant's ability to reach low surface tension. In addition, recent studies suggest that elevated cholesterol within surfactant also contribute to surfactant dysfunction in the setting of lung injury. Although the effects of cholesterol and serum proteins with surfactant have been studied independently, the interaction between the two has not previously been investigated. It was hypothesized that elevated levels of cholesterol within surfactant will make surfactant more susceptible to serum protein inhibition. Methods Bovine Lipid Extract Surfactant (BLES), a commercially available exogenous surfactant, was utilized and modified to generate samples with concentrations of 0, 2.5, 5 and 10% (w/w) cholesterol. Varying amounts of Bovine Serum Albumin (BSA) were subsequently added to each sample to attain concentrations of 0, 20, 30, 40 and 50 mg/ml. A constrained sessile drop surfactometer was used to determine the minimal achievable surface tensions during dynamic compression/expansion cycles. Results Samples with various levels of cholesterol, in the absence of BSA, reached minimum surface tension values of near 0mN/m during compression. At moderate levels of BSA (20 & 30mg/ml), minimum surface tensions were lower in surfactant samples containing cholesterol as compared to samples containing no cholesterol. Finally, at high BSA values, all surfactant samples had surface tension values that were higher than those at the lower BSA concentration but were not significantly different among the sample with different cholesterol concentrations. Discussion Contrary to the hypothesis, values of up to 10% cholesterol within surfactant do not appear to increase the susceptibility of surfactant to serum protein inhibition. In fact, the results suggest that cholesterol mitigates the effect of moderate levels of BSA on surfactant function. It is concluded that cholesterol within surfactant contributes to its resistance against inhibition by albumin. Support or Funding Information Canadian Institutes for Health Research.

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 score0.003
Threshold uncertainty score0.005

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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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
Published2016
Admission routes2
Has abstractyes

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