MétaCan
Menu
Back to cohort
Record W2083064863 · doi:10.1002/adhm.201300099

A Miniaturized Multipurpose Platform for Rapid, Label‐Free, and Simultaneous Separation, Patterning, and In Vitro Culture of Primary and Rare Cells

2013· article· en· W2083064863 on OpenAlexaff
Tohid F. Didar, Kristen Bowey, Guillermina Almazán, Maryam Tabrizian

Bibliographic record

VenueAdvanced Healthcare Materials · 2013
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPrimary cellMicrocontact printingCellCell cultureCell sortingMaterials scienceCell typeIn vitroCell adhesionNanotechnologyProgenitor cellBiomedical engineeringChemistryCell biologyStem cellBiologyBiochemistry

Abstract

fetched live from OpenAlex

Given that current cell isolation techniques are expensive, time consuming, yield low isolation purities, and/or alter target cell properties, a versatile, cost effective, and easy-to-operate microchip with the capability to simultaneously separate, capture, pattern, and culture rare and primary cells in vitro is developed. The platform is based on target cell adhesion onto the micro-fabricated interfaces produced by microcontact printing of cell-specific antibodies. Results show over 95% separation efficiency in less than 10 min for the separation of oligodendrocyte progenitor cells (OPCs) and cardiomyocytes from rat brain and heart mixtures, respectively. Target cell attachment and single cell spreading can be precisely controlled on the basis of the designed patterns. Both cell types can maintain their biofunctionality. Indeed, isolated OPCs can proliferate and differentiate into mature oligodendrocytes, while isolated cardiomyocytes retain their contractile properties on the separation platform. Successful separation of two dissimilar cell types present in varying concentrations in their respective cell mixtures and the demonstration of their integrity after separation open new avenues for time and cost-effective sorting of various cell types using the developed miniaturized platform.

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)0.000
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 score0.056
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.015
GPT teacher head0.291
Teacher spread0.275 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Healthcare MaterialsSame topic3D Printing in Biomedical ResearchFrench-language works237,207