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Record W3111279014 · doi:10.1183/23120541.00705-2020

Development and validation of an open-source, disposable, 3D-printed <i>in vitro</i> environmental exposure system for Transwell culture inserts

2020· article· en· W3111279014 on OpenAlexafffund
Abiram Chandiramohan, Mohammedhossein Dabaghi, Jennifer A. Aguiar, Nicholas Tiessen, Mary Lou Stewart, Quynh Cao, Jenny Nguyen, Nima Makhdami, Gerard Cox, Andrew C. Doxey, Jeremy A. Hirota

Bibliographic record

VenueERJ Open Research · 2020
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of British ColumbiaUniversity of WaterlooMcMaster University
FundersLung Health Foundation
KeywordsMedicineIn vitro3d printedOpen sourceBiomedical engineeringOperating systemComputer scienceBiochemistry

Abstract

fetched live from OpenAlex

Accessible in vitro models recapitulating the human airway that are amenable to study whole cannabis smoke exposure are needed for immunological and toxicological studies that inform public health policy and recreational cannabis use. In the present study, we developed and validated a novel three-dimensional (3D)-printed in vitro exposure system (IVES) that can be directly applied to study the effect of cannabis smoke exposure on primary human bronchial epithelial cells. Using commercially available design software and a 3D printer, we designed a four-chamber Transwell insert holder for exposures to whole smoke. COMSOL Multiphysics software was used to model gas distribution, concentration gradients, velocity profile and shear stress within IVES. Following simulations, primary human bronchial epithelial cells cultured at the air�liquid interface on Transwell inserts were exposed to whole cannabis smoke using a modified version of the Foltin puff procedure. Following 24 h, outcome measurements included cell morphology, epithelial barrier function, lactate dehydrogenase (LDH) levels, cytokine expression and gene expression. Whole smoke delivered through IVES possesses velocity profiles consistent with uniform gas distribution across the four chambers and complete mixing. Airflow velocity ranged between 1.0 and 1.5 �m�s -1 and generated low shear stresses (&lt;&lt;1 Pa). Human airway epithelial cells exposed to cannabis smoke using IVES showed changes in cell morphology and disruption of barrier function without significant cytotoxicity. Cannabis smoke elevated interleukin-1 family cytokines and elevated CYP1A1 and CYP1B1 expression relative to control, validating IVES smoke exposure impacts in human airway epithelial cells at a molecular level. The growing legalisation of cannabis on a global scale must be paired with research related to potential health impacts of lung exposures. IVES represents an accessible, open-source, exposure system that can be used to model varying types of cannabis smoke exposures with human airway epithelial cells grown under air�liquid interface culture conditions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.068
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.329
Teacher spread0.266 · 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 teacher head, 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

Citations10
Published2020
Admission routes2
Has abstractyes

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