Microfluidic Formation of Ultrathin, Handleable Collagen Sheets Exhibiting Toe-heel Tensile Behavior
Bibliographic record
Abstract
Abstract The extracellular matrix (ECM) of cardiovascular tissues displays a non-linear, strain-dependent elastic modulus, attributed to the hierarchical organization of collagen. At low loads, these tissues exhibit compliance, permitting contraction or dilation, while at high loads, they stiffen considerably, increasing their mechanical strength by at least tenfold. Although collagen gels are widely used in 3D cell culture, tissue engineering, and biofabrication, current engineering techniques fail to replicate this hierarchical organization at the microscale. As a result, they lack both the non-linear tensile behavior and the physiologically relevant strength of native tissues. To address this limitation, we present templated collagen sheets that are 1.8 microns thin and 10 mm wide that demonstrate non-linear tensile behavior. Collagen sheets are obtained from an acidic collagen solution via a microfluidic flow focusing process, incorporating and subsequently removing emulsified oil droplets (mean diameters 2.1 microns and 5.0 microns, volume concentration 2.25%). Templated collagen sheets exhibit a two-fold increase in fibril alignment dispersion compared with non-templated ones. When assessed along their length, the Young’s modulus of templated sheets increases 62-fold at 90% failure strain, closely matching the properties of native load-bearing tissues. We anticipate that these ultrathin templated collagen sheets will have broad applications as a substrate material for the bottom-up fabrication of load-bearing biomaterials and tissue structures for in vitro applications and implantation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".