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Record W4409934731 · doi:10.1002/bit.29013

Establishing a 3D Vascularized Tri‐Culture Model of the Human Airways via a Digital Light Processing Bioprinter

2025· article· en· W4409934731 on OpenAlexafffund
Sakshi Phogat, Tony Ju Feng Guo, Fama Thiam, Emmanuel T. Osei

Bibliographic record

VenueBiotechnology and Bioengineering · 2025
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMitacsProvidence Health Care
KeywordsBiomedical engineeringIn vivoSelf-healing hydrogelsChemistryMaterials scienceFibronectinFibrinTissue engineeringBiophysicsExtracellular matrixBiochemistryImmunologyBiologyMedicinePolymer chemistry

Abstract

fetched live from OpenAlex

The rise in chronic lung diseases globally and the corresponding lag in drug discovery in this field highlights the need for In Vitro models closely mimicking In Vivo lung tissue. Efforts to date have largely focused on In Vitro coculture models, often neglecting the pulmonary vasculature's role in lung physiology and lacking perfusability. To address this gap, we utilized digital light processing bioprinting to establish a complex three-dimensional (3D) vascularized tri-culture airway model. Models were generated using a photopolymerizable bioink consisting of 80% polyethylene glycol diacrylate (PEGDA) and 20% gelatin methacrylate (GelMa) and printed using the LUMENX+ bioprinter. Stiffness, diffusivity, and gel expansion were characterized. Models were printed with MRC-5 lung fibroblasts embedded in hydrogels, while EA.hy926 endothelial cells and 1HAEo- epithelial cells were seeded on the luminal surface and on the apical domain, respectively. Endothelialization was achieved by coating lumens with matrix proteins, followed by perfusion-based endothelial cell seeding and uniform distribution via rotating the model. Structural characterization, including immunofluorescence imaging, lactate dehydrogenase (LDH) viability, interleukin-6 and interleukin-8 quantification was performed following cigarette smoke extract (CSE) exposure. PEGDA/GelMa 80:20 hydrogels had a Young's modulus of 10.7 kPa, expanded by 101.5% in volume and 107% in weight after 24 h in phosphate-buffered saline, and turned completely blue following 12 h of exposure to 0.1% methylene blue. Immunofluorescence staining revealed an intact apical epithelial and luminal endothelial layer demonstrated by E-cadherin expression. Lung fibroblasts retained their spindle shape with dendritic extensions as shown by F-actin staining. Propidium iodide staining demonstrated 80-90% cell viability. Cigarette smoke exposure significantly increased IL-6 and IL-8 release, but not LDH release. A multiplex assay revealed distinct immune mediator profiles and clustering between co-cultures and tri-cultures at baseline, underscoring differences in intercellular communication. This study successfully engineered and characterized a 3D bioprinted vascularized tri-culture model that mimics human airways. The model is adaptable to future studies by incorporating additional cell types, primary cells, or modified designs and protocols.

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 score0.002
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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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