Change in Rheologic Properties of Facial Soft-Tissue Fillers across the Physiologic Angular Frequency Spectrum
Bibliographic record
Abstract
BACKGROUND: The number of soft-tissue filler injections performed in the United States is constantly increasing and reflects the high demand for enhanced facial and body attractiveness. The objective of the present study was to measure the viscoelastic properties of soft-tissue fillers when subjected to different testing frequencies. The range of tested frequencies represents clinically different facial areas with more [lips (high frequency)] or less [zygomatic arch (low frequency)] soft-tissue movement. METHODS: A total of 35 randomly selected hyaluronic acid-based dermal filler products were tested in an independent laboratory for their values of G', G″, tan δ, and G* at angular frequencies between 0.1 and 100 radian/second. RESULTS: The results of the objective analyses revealed that the viscoelastic properties of all tested products changed between 0.1 and 100 radian/second angular frequency. Changes in G' ranged from 48.5 to 3116 percent, representing an increase in their initial elastic modulus, whereas changes in G″ ranged from -53.3 percent (i.e., decrease in G″) to 7741 percent (i.e., increase in G″), indicating both an increase and a decrease in their fluidity, respectively. CONCLUSIONS: The increase in G' would indicate the transition from a "softer" to a "harder" filler, and the observed decrease in G″ would indicate an increase in the filler's "fluidity." Changes in the frequency of applied shear forces such as those occurring in the medial versus the lateral face will influence the aesthetic outcome of soft-tissue filler injections.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".