DEVELOPMENT OF MECHANICAL CHARACTERIZATION METHOD OF HYDROGEL SCAFFOLDS USING SYNCHROTRON PROPAGATION-BASED IMAGING
Bibliographic record
Abstract
Hydrogel-based scaffolds have been widely used in soft tissue regeneration due to their biocompatible and tissue-like environment for maintaining cellular functions and tissue regeneration. Understanding the mechanical properties and internal microstructure of hydrogel-based scaffold, once implanted, is imperative in many tissue engineering applications and longitude studies. Notably, this has been challenging to date as various conventional characterization methods by, for example, mechanical testing (for mechanical properties) and microscope (for internal microstructure) are destructive as they require removing scaffolds from the implantation site and processing samples for characterization. Synchrotron propagation-based imaging – computed tomography (PBI-CT) is feasible and promising for non-destructive monitoring of hydrogel scaffolds. As inspired, this study aimed to perform a study on the characterization of mechanical properties and microstructure of hydrogel scaffolds based on the PBI-CT.\nThe hydrogel solutions were prepared from 3% w/v alginate + 1% w/v gelatin and then printed by using the needle with a diameter of 200 μm, to form scaffolds with a dimension of 10×10×5 mm3. After successfully crosslinking of scaffolds, some of the scaffolds were degraded in a 37 °C media of phosphate buffered saline over 3 days, for the subsequent examination, along with those without degradation. The scaffolds both with and without degradation were subject to compressive testing, where the compression speed was set at 0.1 mm/s to reach the strain of 10%, 20%, 30%, 40%, and 50%, respectively. Once reached, the strain was held for 5 minutes for measuring the force and thus the stress within scaffolds, yielding the stress–strain curves. After that, the scaffolds were imaged and examined by SR-PBI-CT at the BMIT-ID beamline at Canadian Light Source (CLS). During the imaging process, the scaffolds were mechanically loaded, respectively, with the strains same as the ones in the aforementioned compressive testing, and at each strain, the scaffold was imaged and scanned with a pixel size of 13 µm for analysis.\nFrom the stress-strain curves obtained in the compression testing, the Young’s modulus was evaluated to characterize the elastic behavior of scaffolds: with the range between around 5-25 kPa; from the images captured by SR-PBI-CT, the scaffolds microstructures were examined in terms of the strand cross-section area, pore size, and hydrogel volume. Further, from the SR-PBI-CT images, the stress within hydrogel of scaffolds were evaluated, showing the agreement with those obtained from compression testing. These results have illustrated that the mechanical properties and microstructures of scaffolds, ether being degraded or not, can be examined and characterized by the SR-PBI-CT imaging, in a non-destructive manner. This would represent a significant advance for facilitating longitude studies on the scaffolds once implanted in-vivo.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".