Engineering Highly Cellularized Living Materials via Mechanical Agitation
Bibliographic record
Abstract
Abstract Engineered living materials with high cell density are important in various applications such as hemostasis, tissue engineering, organoids, and biofabrication. However, it remains challenging to modulate the structure and mechanics of these highly cellularized living materials, while preserving cell viability and functionality. Here a mechanical strategy is reported to engineer living materials with cell densities as high as 1 billion cells per milliliter, without altering chemical and cellular compositions. Using blood clots as a clinically relevant model, mechanical agitation is shown to enables precise tuning a wide range of clot properties, including stiffness, toughness, contraction, and lysis. Notably, agitation can enhance the elastic modulus and fracture toughness of clots by up to fourfold compared to those degraded by agitation. Combined experimental and computational studies demonstrate that agitation‐induced 3D cell organization governs the macroscopic mechanical responses. In vitro cell culture and in vivo animal experiments further validate the safety and efficacy of this strategy. Furthermore, the strategy is applicable to various hydrogels and cellular inclusions such as red blood cells, fibroblasts, and microgels. This work offers new avenues for engineering living materials, with technological implications for biofabrication, tissue engineering, and treatments for blood clot‐related diseases.
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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 | 0.001 |
| 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) | 0.002 | 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".