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Exogenous Surfactant as a Pulmonary Drug Delivery Vehicle for Budesonide in the Treatment of ARDS

2020· article· en· W3016858740 on OpenAlexaffabout
Brandon Baer, Lynda McCaig, Thebika Sivasri, Eric Sun, Cory Yamashita, Ruud A. W. Veldhuizen

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsWestern University
Fundersnot available
KeywordsBudesonideARDSMedicineLungPulmonary surfactantIn vivoInflammationSalineDrug deliveryPharmacologyImmunologyAsthmaAnesthesiaInternal medicineBiologyChemistry

Abstract

fetched live from OpenAlex

Background Inflammation associated with diseases like Acute Respiratory Distress Syndrome (ARDS) and Bacterial Pneumonia, often occurs in the deeper, alveolar, areas of the lung. In these circumstances the complex branching structure of the lung, its large surface area, and associated areas of airway collapse provide substantial hurdles for adequate delivery of anti‐inflammatory drugs to remote regions of inflammation. To address this, our lab has utilized a bovine derived exogenous surfactant (BLES) as a pulmonary vehicle to facilitate the transport of a glucocorticoid (budesonide). Budesonide is a strong anti‐inflammatory drug currently used in the lung to treat asthma, while BLES can open collapsed airways and spread to distal sites within the lung. Hypothesis Combining budesonide with a bovine derived exogenous surfactant will enhance its delivery and efficacy for treating pulmonary inflammation. Methods Our hypothesis was tested using both in vitro and in vivo methodology. For in vitro studies the wet bridge transfer system was utilized to assess spreading and efficacy of budesonide alone or in combination with BLES across an air‐liquid interface. In this system, macrophages were seeded to a remote site and stimulated with heat‐killed bacteria (HKB). Treatments were then administered to a delivery site and IL‐6 concentrations were measured at the remote site. An in vivo model of pulmonary inflammation was created by instilling either saline (control) or HKB into the lungs of male and female rats. This first instillation was followed 30 minutes later by a second instillation of either saline, budesonide or BLES/budesonide. Rats were then monitored for six hours before being euthanized. A bronchoalveolar lavage (BAL) was performed, followed by cell counts and differentials. Results The in vitro data showed that administering BLES or budesonide alone had no effect on IL‐6 concentrations at the remote site, across the air‐liquid interface. However, the administration of BLES/budesonide significantly reduced IL‐6 content at the remote site. Data collected from the in vivo experiment indicates that instillation of HKB significantly increased the number of inflammatory cells and neutrophils in the BAL compared to the control. Budesonide alone was able to show a reduction in the number of neutrophils in the BAL. However, BLES/budesonide showed significant reductions in both the number of inflammatory cells and neutrophils in the BAL compared to budesonide and HKB groups. Discussion The in vitro data indicates that BLES/budesonide is more effective at reaching and eliciting an anti‐inflammatory effect at a distal site than budesonide alone. Moreover, administering budesonide with BLES in vivo resulted in significant improvements in drug delivery and efficacy. Further measurements of pulmonary inflammation will include myeloperoxidase assays as well as quantifying pro‐inflammatory cytokine mRNA and protein through qPCR and ELISA assays respectively. This novel strategy of utilizing a spreading agent to delivery budesonide represents a new therapy for pulmonary inflammation and a novel approach for directly delivering drugs to distal regions in the lung of ARDS patients. Support or Funding Information Ontario Graduate Scholarship ‐ Doctoral

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 head0.076
GPT teacher head0.353
Teacher spread0.277 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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