Critical Design Parameters of Tantalum-Based Comb Structures to Manipulate Mammalian Cell Morphology
Bibliographic record
Abstract
Mammalian tissues and cells often orient naturally in specific patterns to function effectively. This cellular alignment is influenced by the chemical nature and topographic features of the extracellular matrix. In implants, a range of different materials have been used in vivo. Of those, tantalum and its alloys are promising materials, especially in orthopedic implant applications. Previous studies have demonstrated that nano- and micro-scale surface features, such as symmetric comb structures, can significantly affect cell behavior and alignment. However, patterning need not be restricted to symmetric geometries, and there remains a gap in knowledge regarding how cells respond to asymmetric comb structures, where the widths of the trenches and lines in the comb differ. This study aims to address this gap by examining how Vero cells (cells derived from an African green monkey) respond when applied to tantalum and tantalum/silicon oxide asymmetric comb structures having fixed trench widths of 1 μm and line widths ranging from 3 μm to 50 μm. We also look at the cell responses on inverted patterns, where the line widths were fixed at 1 μm while trench widths varied. The orientation and morphology of the adherent cells were analyzed using fluorescence confocal microscopy and scanning electron microscopy. Our results indicate that the widths of the trenches and lines are important design parameters influencing cell behavior on asymmetric comb structures. Furthermore, the ability to manipulate cell morphology using these structures decreased when parts of the tantalum lines were replaced with silicon oxide.
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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) | 0.000 | 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".