Decellularized Plant-Based Scaffolds for Guided Alignment of Myoblast Cells
Bibliographic record
Abstract
Abstract Alignment and orientation of cells in vivo plays a crucial role in the functionality of tissue. A challenged faced by traditional cell culture approaches is that the majority of two-dimensional substrates fail to induce a controlled alignment of cells in vitro . To address this challenge, approaches utilizing mechanical stresses, exposure to electrical fields, structurally aligned biomaterials and/or textured microfabricated substrates, have been developed to control the organization of cells through microenvironmental stimuli. In the field of muscle tissue engineering it is often desirable to control the alignment and fusion of muscle precursor cells as it more closely resembles in vivo conditions. In this study, we utilize plant-derived cellulose biomaterials to control the in vitro alignment of C2C12 murine myoblasts. We hereby report that cells display a clear sensitivity to the highly aligned vascular bundle architectures found in decellularized celery ( Apium graveolens) . Conveniently, the xylem and phloem channels lie within the 10-100μm diameter, which has been shown to be optimal diameter for myoblast alignment through contact guidance. Following 10 days in proliferation media, F-actin filaments were observed to be aligned parallel to the longitudinal axis of the vascular bundle. Subsequently, following 5 days in differentiation media, myoblast maintained an aligned morphology, which led to the formation of aligned myotubes. We therefore conclude that the microtopography of the vascular bundle guides muscle cell alignment. The results presented here highlight the potential of this plant-derived scaffold for in vitro studies of muscle myogenesis, where structural anisotropy is required to more closely resemble in vivo conditions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".