Remote Determination of Time-Dependent Stiffness of Surface-Degrading-Polymer Scaffolds Via Synchrotron-Based Imaging
Bibliographic record
Abstract
Surface-degrading polymers have been widely used to fabricate scaffolds with the mechanical properties appropriate for tissue regeneration/repair. During their surface degradation, the material properties of polymers remain approximately unchanged, but the scaffold geometry and thus mechanical properties vary with time. This paper presents a novel method to determine the time-dependent mechanical properties, particularly stiffness, of scaffolds from the geometric changes captured by synchrotron-based imaging, with the help of finite element analysis (FEA). Three-dimensional (3D) tissue scaffolds were fabricated from surface-degrading polymers, and during their degradation, the tissue scaffolds were imaged via the synchrotron-based imaging to characterize their changing geometry. On this basis, the stiffness behavior of scaffolds was estimated from the FEA, and the results obtained were compared to the direct measurements of scaffold stiffness from the load-displacement material testing. The comparison illustrates that the Young's moduli estimated from the FEA and characterized geometry are in agreement with the ones of direct measurements. The developed method of estimating the mechanical behavior was also demonstrated effective with a nondegrading scaffold that displays the nonlinear stress-strain behavior. The in vivo monitoring of Young's modulus by morphology characterization also suggests the feasibility of characterizing experimentally the difference between in vivo and in vitro surface degradation of tissue engineering constructs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".