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Record W2126750664 · doi:10.1039/c004590j

Droplet-based microfluidic system for multicellular tumor spheroid formation and anticancer drug testing

2010· article· en· W2126750664 on OpenAlexaff
Linfen Yu, Michael C. W. Chen, Karen C. Cheung

Bibliographic record

VenueLab on a Chip · 2010
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpheroidMulticellular organismCell cultureCellMicrofluidicsChemistryBiophysicsFlow cytometryBiomedical engineeringCell biologyIn vitroNanotechnologyBiologyMaterials scienceImmunologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Creating multicellular tumor spheroids is critical for characterizing anticancer treatments since it may provide a better model than monolayer culture of tumor cells. Moreover, continuous dynamic perfusion allows the establishment of long term cell culture and subsequent multicellular spheroid formation. A droplet-based microfluidic system was used to form alginate beads with entrapped breast tumor cells. After gelation, the alginate beads were trapped in microsieve structures for cell culture in a continuous perfusion system. The alginate environment permitted cell proliferation and the formation of multicellular spheroids was observed. The dose-dependent response of the tumor spheroids to doxorubicin, and anticancer drug, showed multicellular resistance compared to conventional monolayer culture. The microsieve structures maintain constant location of each bead in the same position throughout the device seeding process, cell proliferation and spheroid formation, treatment with drug, and imaging, permitting temporal and spatial tracking.

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: none
Teacher disagreement score0.001
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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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

Citations247
Published2010
Admission routes1
Has abstractyes

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