MétaCan
Menu
Back to cohort
Record W2152538644 · doi:10.1039/b916669f

Chamber and microfluidic probe for microperfusion of organotypic brain slices

2009· article· en· W2152538644 on OpenAlexafffund
Arthur Queval, Nageswara R. Ghattamaneni, Cécile M. Perrault, Raminder Gill, Maryam Mirzaei, R. Anne McKinney, David Juncker

Bibliographic record

VenueLab on a Chip · 2009
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsMcGill University and Génome Québec Innovation CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsMicrofluidicsBiomedical engineeringFluorescence microscopeConfocalConfocal microscopyNanotechnologyPerfusionMicroscopeChemistryMaterials scienceFluorescenceBiophysicsPathologyBiologyOpticsMedicineCell biology

Abstract

fetched live from OpenAlex

Microfluidic systems are increasingly being used for the culture and study of dissociated cells because they require only minute amounts of materials while enabling drug screening and chemotaxis studies down to the single cell level. However, the culture of organized tissue, such as brain slices, has been more difficult to adapt to microfluidic devices. Here, we present a microfluidic system, comprising (i) a perfusion chamber for the culture of organotypic slices that is compatible with high resolution imaging on inverted microscopes, and (ii) a novel transparent microfluidic probe (MFP) for the localized microperfusion of the brain tissue. The MFP is made in poly(dimethylsiloxane), features six micrometre-scale apertures and can be assembled within a few hours in a standard laboratory. Each aperture can indiscriminately be used either for the injection or aspiration of solutions, giving rise to many possible combinations. The MFP was successfully used for the perfusion of a small number of cells in a brain slice with concurrent confocal fluorescence imaging of the perfused dye and sub-cellular structures within the tissue.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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
GenreMethods

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

Citations95
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueLab on a ChipSame topic3D Printing in Biomedical ResearchFrench-language works237,207