Customizable Composite Fibers for Engineering Skeletal Muscle Models
Bibliographic record
Abstract
Engineering tissue-like scaffolds that can mimic the microstructure, architecture, topology, and mechanical properties of native tissues while offering an excellent environment for cellular growth has remained an unmet need. To address these challenges, multicompartment composite fibers are fabricated. These fibers can be assembled through textile processes to tailor tissue-level mechanical and electrical properties independent of cellular level components. Textile technologies also allow control of the distribution of different cell types and the microstructure of fabricated constructs and the direction of cellular growth within the 3D microenvironment. Here, we engineered composite fibers from biocompatible cores and biologically relevant hydrogel sheaths. The fibers are mechanically robust to being assembled using textile processes and could support adhesion, proliferation, and maturation of cell populations important for the engineering of skeletal muscles. We also demonstrated that the changes in the coating of the multicompartment fibers could potentially enhance myogenesis in vitro .
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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 | 0.000 | 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) | 0.002 | 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 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".