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Record W4407078708 · doi:10.1007/s10237-024-01920-9

Transient flow-induced deformation of cancer cells in microchannels: a general computational model and experiments

2025· article· en· W4407078708 on OpenAlexafffund
Ruixin Lu, Junning Li, Zhengxiao Guo, Zhen Wang, James J. Feng, Yi Sui

Bibliographic record

VenueBiomechanics and Modeling in Mechanobiology · 2025
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilQueen Mary University of London
KeywordsTransient (computer programming)Deformation (meteorology)Materials scienceFlow (mathematics)MechanicsComputational fluid dynamicsComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Recently, the present authors proposed a three-dimensional computational model for the transit of suspended cancer cells through a microchannel (Wang et al. in Biomech Model Mechanobiol 22: 1129-1143, 2023). The cell model takes into account the three major subcellular components: A viscoelastic membrane that represents the lipid bilayer supported by the underlying cell cortex, a viscous cytoplasm, and a nucleus modelled as a smaller microcapsule. The cell deformation and its interaction with the surrounding fluid were solved by an immersed boundary-lattice Boltzmann method. The computational model accurately recovered the transient flow-induced deformation of the human leukaemia HL-60 cells in a constricted channel. However, as a general modelling framework, its applicability to other cell types in different flow geometries remains unknown, due to the lack of quantitative experimental data. In this study, we conduct experiments of the transit of human prostate cancer (PC-3) and leukaemia (K-562) cells, which represent solid and liquid tumour cell lines, respectively, through two distinct microchannel geometries, each dominated by shear and extension flow. We find that the two cell lines have qualitatively similar flow-induced dynamics. Comparisons between experiments and numerical simulations suggest that our model can accurately predict the transient cell deformation in both geometries, and that it can serve as a general modelling framework for the dynamics of suspended cancer cells in microchannels.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.480

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 head0.037
GPT teacher head0.289
Teacher spread0.251 · 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 designSimulation or modeling
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

Citations4
Published2025
Admission routes2
Has abstractyes

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