Computational analysis of mechanical behaviour of stem cell in micropipette aspiration technique
Bibliographic record
Abstract
Mechanical properties of living cells play an important role in helping to understand cell physiology and pathology. However, to ensure reliability, it is important to precisely define the experimental conditions of these mechanical test. In this study, viscoelastic properties of the outer layer (cytoplasm and membrane) were extracted using standard linear solid model. Finite element modeling of the two-layer cell was performed and the model was validated by experimental data. In the two-layer model, the effect of the radius of the nucleus and the location of the nucleus on the whole cell behavior were investigated. By increasing nucleus size, the whole cell properties follow the nucleus properties and the role of the nucleus becomes more dominant. By dislocating nucleus inside the cytoplasm, the cell behavior changes significantly and becomes more similar to that of nucleus properties. Similarly, changing the aspiration pressure and rate, impacts the observed behavior drastically. The results demonstrate that the location of the nucleus and the ratio of the radius of the cytoplasm to the radius of the nucleus can effectively influence the viscoelastic properties and mechanical behavior of the cell.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".