Wave propagation methods for the experimental characterization of soft biomaterials and tissues
Bibliographic record
Abstract
A good understanding of the viscoelasticity of soft biomaterials and tissue is needed to predict their mechanical response under loads in biological conditions. For example, the viscoelastic properties of hydrogels used in cell culturing and tissue engineering should approximately match those of the tissue they replace. These properties are strongly dependent on the excitation frequency. This has important implication for voice production. The human vocal folds oscillate at a fundamental frequency around 125, 200, 300 and 500 Hz in normal phonation for male, female, children and infants, respectively. Vibration frequencies can reach up to a few kHz, specially in singing. Vocal fold oscillations, essential to voice production, are significantly affected by the mechanical (viscoelastic) properties of the vocal fold mucosa. A novel characterization method based on Rayleigh wave propagation was developed for the quantification of frequency-dependent viscoelastic properties of soft biomaterials over a broad frequency range; i.e., up to 4 kHz. Synthetic silicone rubber and gelatin samples were fabricated and tested to evaluate the proposed method. The shear and elastic moduli and the loss factor obtained from the Rayleigh wave propagation method were compared with results from two other methods, as well as results from an independent study. The proposed method was found to be accurate and cost effective for the measurement of viscoelastic properties of soft biomaterials, such as phonosurgical biomaterials and hydrogels, over a wide frequency range. A non-invasive method was developed to measure the shear modulus of human vocal fold tissue in vivo during phonation. This is needed for the development of injectable biomaterials for vocal fold augmentation and repair, and to evaluate voice treatment procedures. The mucosal wave propagation speed was measured for four human subjects at different phonation frequencies using high speed endoscopic images of the larynx and image processing methods. The transverse shear modulus of the vocal fold mucosa was then calculated from a surface wave propagation dispersion equation using the measured wave speeds. The results were found to be in good agreement with those from other studies obtained via in vitro measurements, thereby supporting the validity of the proposed measurement method. Hyaluronic acid-gelatin hydrogels with varying concentrations of cross-linker are other constituents were fabricated. These biomaterials are for use as synthetic extracellular matrix in vocal fold tissue engineering. The Rayleigh wave propagation method was used to quantify the frequency-dependent viscoelastic properties of these hydrogels, including shear and viscous moduli, over a broad frequency range; i.e., from 40 to 4000 Hz. The viscoelastic properties of the designed hydrogels were similar to those of human vocal fold tissue obtained from in vivo and in vitro measurements. It was shown that the cross-linker concentration is the most common parameter to tune the viscoelastic properties of designed hyaluronan-based hydrogels. The hyaluronic acid and gelatin contents of these hydrogels are the main parameters to adjust their biochemical and biological properties, considering the changes in the viscoelastic properties of the hydrogels.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".