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Abstract A048: Development and validation of a microfluidic cell culture model for examining cerebral microvascular barrier responses to the tumor microenvironment

2024· article· en· W4392370377 on OpenAlexaff
Stacey Line, Magimairajan Vanan, Donald W. Miller

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsCancerCare ManitobaUniversity of Manitoba
Fundersnot available
KeywordsTumor microenvironmentNeuroscienceBlood–brain barrierMicrofluidicsMedicineBiologyCancer researchTumor cellsNanotechnologyMaterials scienceCentral nervous system

Abstract

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Abstract Introduction: The blood-brain barrier (BBB) is composed of specialized endothelial cells that limit the passage of solutes from the blood to the brain. Microfluidic technology that allows formation of 3D tubular microvessels has been applied to in vitro BBB models, and having advantages of fluid flow, cell-cell contact, provide a more robust and predictive model for assessing vascular permeability. Use of the microfluidic model to examine the effects of the tumor microenvironment on brain endothelial cell permeability would provide mechanistic fundamental knowledge that could be used to more effectively deliver therapeutic agents to the treatment site. Methods: Human brain microvessel endothelial cells (hCMEC/d3) were seeded (10,000 cells/µL) into the vascular channel and following vascular capillary tube formation, various human brain tumor cell lines (SF8628, U87, and U251) were seeded in the adjacent brain channel of the Mimeta 3-channel microfluidic unit. Tumor-induced alterations in barrier function were examined over a 72-hour period using paracellular (fluorescein-labeled detran-FDX70kD; IRdye 800; sodium fluorescein - NaF) and transcellularly transported dyes (rhodamine 800-R800). Tumor induced changes in permeability of various marker molecules were correlated to changes in the expression of selected BBB specific genes and the tumor secretome. Results: The microfluidic BBB culture model showed reduced permeability to all the permeability markers examined compared to TranswellTM inserts with values similar to those previously reported in vivo. Compared to monoculture, no significant changes in permeability were observed with U251 co-culture model. However, SF8628 enhanced barrier properties, while U87 increased paracellular leakiness. Examination of the barrier enhancing microenvironment observed with the SF8628 co-culture model indicated a Sonic Hedgehog dependent process that stimulates the release of Angiopoietin 1 (Ang1) and Platelet derived growth factor (PDGF-BB) release from the SF8628 tumor cells as the likely factors driving the permeability effects observed. With regards to the increased permeability observed with the U87 co-culture, increased cytokines (ie. IL-6 and IL-8) and altered fatty acid secretion appear to play a significant role in the reduced barrier properties of brain endothelial cells. Conclusion: The brain tumor microenvironment can have either barrier enhancing (SF8628 co-culture) or barrier reducing (U87-co culture) effects based on tumor cell induced changes in secreted factors. The dynamic microfluidic blood-brain barrier - brain tumor co-culture model provides a robust system with which to mechanistically identify tumor-driven changes in brain endothelial cell permeability. Citation Format: Stacey Line, Magimairajan Issai Vanan, Donald W. Miller. Development and validation of a microfluidic cell culture model for examining cerebral microvascular barrier responses to the tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr A048.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.068
GPT teacher head0.342
Teacher spread0.274 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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