Novel grooved substrata stimulate macrophage fusion, CCL2 and MMP‐9 secretion
Bibliographic record
Abstract
Rough surface topographies on implants attract macrophages but the influence of topography on macrophage fusion to produce multinucleated giant cells (MGC) and foreign body giant cells (FBGC) is unclear. Two rough novel grooved substrata, G1 and G2, fabricated by anisotropic etching of Silicon <110> crystals without the use of photolithographic patterning, and a control smooth surface (Pol) were produced and replicated in epoxy. The surfaces were compared for their effects on RAW264.7 macrophage morphology, gene expression, cyto/chemokine secretion, and fusion for one and five days. Macrophages on grooved surfaces exhibited an elongated morphology similar to M2 macrophages and increased cell alignment with surface directionality, roughness and cell culture time. Up-regulated expression of macrophage chemoattractants at gene and protein level was observed on both grooved surfaces relative to Pol. Grooved surfaces showed time-dependent increase in soluble mediators involved in cell fusion, CCL2 and MMP-9, and an increased proportion of multinucleated cells at Day 5. Collectively, this study demonstrated that a rough surface with surface directionality produced changes in macrophage shape and macrophage attractant chemokines and soluble mediators involved in cell fusion. These in vitro results suggest a possible explanation for the observed accumulation of macrophages and MGCs on rough surfaced implants in vivo. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2243-2254, 2016.
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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 | 0.003 | 0.001 |
| 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 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".