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Record W4281609624 · doi:10.3390/ph15060695

A More Biomimetic Cell Migration Assay with High Reliability and Its Applications

2022· article· en· W4281609624 on OpenAlexaff
Di Yin, Hongbo Zhang, Chun Yang, Wenjun Zhang, Shih‐Mo Yang

Bibliographic record

VenuePharmaceuticals · 2022
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCell migrationHeLaCellAngiogenesisCancer cellNanotechnologyMaterials scienceBiomedical engineeringCell biologyChemistryCancer researchCancerBiologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Cell migration refers to the directional movement of cells to the surrounding cell-free zone in response to chemical and mechanical stimuli. A cell migration assay is an essential device for studying pharmaceutical and medical problems. In this paper, we present a novel approach to a cell migration assay on a chip with two merits, namely (i) simultaneous creation of many cell samples on the same condition and (ii) cells migrating while being stressed in a fluidic environment. The first merit has addressed the problem of poor reproducibility in experimental studies for medical problems such as wound healing, and the second merit has made the cell migration device, which is an in vitro environment, more biomimetic. The two merits are attributed to a novel mechanical method to simultaneously create many cell-free zones and to the design of a microfluidic process to create shear stress in cells uniformly. Two applications were studied on our device to explore its effectiveness. The first application is regarding the combination chemotherapy of cisplatin and doxorubicin (Adriamycin) on cervical cancer cells (HeLa). The second application is regarding inhibiting the migration of endothelial cells (HUVEC) in the process of anti-angiogenesis.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.025
GPT teacher head0.321
Teacher spread0.296 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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