Skin-derived precursor cells undergo substrate-dependent galvanotaxis that can be modified by neighbouring cells
Bibliographic record
Abstract
Many cell types respond to electric fields (EFs) through cell migration, a process termed galvanotaxis. The galvanotactic response is critical for development and wound healing. Here we investigate whether skin-derived precursor cells (SKPs), which have the potential to differentiate into mesodermal and peripheral neural cell types, undergo directed migration in the presence of an EF. We found that EF application promotes SKP migration towards the anode. The migratory response is substrate-dependent as SKPs undergo directed migration on laminin and Matrigel, but not collagen. The majority of SKPs express the undifferentiated cell markers nestin, fibronectin and Sox2, after both EF application and in sister cultures with no EF application, suggesting that EFs do not promote cell differentiation. Co-cultures of SKPs and brain-derived neural precursor cells (NPCs), a population of cells that undergo rapid, cathode-directed migration, reveal that in the presence of NPCs an increased percentage of SKPs undergo galvanotaxis, providing evidence that cells can provide cues to modify the galvanotactic response. We propose that a better understanding of SKP migration in the presence of EFs may provide insight into improved strategies for wound repair.
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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) | 0.000 | 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) | 0.000 | 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".