Investigating Viscoelastic Properties of Myofibrils Isolated From hiPSC-CMs Using Atomic Force Microscopy and Quasi-Linear Viscoelastic Model
Bibliographic record
Abstract
Abstract Knowing the mechanical properties of cardiac myofibrils isolated from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) can provide valuable insight into the structure and function of the heart muscle. Previous studies focused mostly on studying myofibrillar stiffness using simplified elastic models. In this study, the mechanical properties of myofibrils isolated from hiPSC-CMs were measured using atomic force microscopy (AFM). The quasi-linear viscoelastic (QLV) model was used to interpret the elastic and viscous properties of myofibrils. Since there have been no previous studies on the viscoelastic properties of myofibrils extracted from hiPSC-CMs, myofibrils extracted from porcine left-ventricular (LV) tissue were used to compare and verify experimental processes and QLV model parameters. The elastic modulus of myofibrils extracted from porcine LV tissue was determined to be 8.82 ± 6.09 kPa which is consistent with previous studies which reported that porcine LV tissue is less stiff on average than mouse and rat cardiac myofibrils. The elastic modulus of myofibrils extracted from hiPSC-CMs was found to be 9.78 ± 5.80 kPa, which is consistent with the range of 5–20 kPa reported for myofibrils extracted from the adult human heart. We found that myofibrils isolated from hiPSC-CMs relax slower than myofibrils extracted from porcine LV tissue, particularly in the first 0.25 s after the peak stress in the stress relaxation test. These findings provide important insights into the mechanical behavior of hiPSC-CMs and have implications for the development of treatments for heart diseases.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".