Ultrasound‐Triggered Enzymatic Gelation
Bibliographic record
Abstract
Hydrogels are formed using various triggers, including light irradiation, pH adjustment, heating, cooling, or chemical addition. Here, a new method for forming hydrogels is introduced: ultrasound-triggered enzymatic gelation. Specifically, ultrasound is used as a stimulus to liberate liposomal calcium ions, which then trigger the enzymatic activity of transglutaminase. The activated enzyme catalyzes the formation of fibrinogen hydrogels through covalent intermolecular crosslinking. The catalysis and gelation processes are monitored in real time and both the enzyme kinetics and final hydrogel properties are controlled by varying the initial ultrasound exposure time. This technology is extended to microbubble-liposome conjugates, which exhibit a stronger response to the applied acoustic field and are also used for ultrasound-triggered enzymatic hydrogelation. To the best of the knowledge, these results are the first instance in which ultrasound is used as a trigger for either enzyme catalysis or enzymatic hydrogelation. This approach is highly versatile and can be readily applied to different ion-dependent enzymes or gelation systems. Moreover, this work paves the way for the use of ultrasound as a remote trigger for in vivo hydrogelation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".