Surface nanocavitation of titanium modulates macrophage activity
Bibliographic record
Abstract
Background: Nanoscale surface modifications are widely touted to improve the biocompatibility of medically relevant materials. Immune cells, such as macrophages, play a critical role in the initial healing events following implantation. Methods: To understand the response of macrophages to nanotopography better, we exposed U937-derived macrophages to a distinctive mesoporous titanium surface (TiNano) produced by a process of simple chemical nanocavitation, and to mechanically polished titanium (TiPolished) and glass coverslip (Glass) surfaces as controls. Cell numbers and morphology were evaluated. Osteopontin expression and that of the proinflammatory SPARC protein and its stabilin 1 receptor were analyzed. Release of inflammation-associated cytokines and chemokines was also measured. Results: Compared to the two control surfaces, there were fewer U937 cells on TiNano, and these exhibited a more rounded morphology with long filopodia. The cells showed areas of punctate actin distribution, indicating formation of podosomes. Of the three proteins examined, only osteopontin's immunofluorescence signal was clearly reduced. Irrespective of the substrate, the cytokine assay revealed important variations in expression levels of the multiple molecules analyzed and downregulation in a number of chemokines by the TiNano surface. Conclusion: These results indicate that macrophages sense and respond to the physicochemical cueing generated by the nanocavitated surface, triggering cellular and molecular changes consistent with lesser inflammatory propensity. Given the previously reported beneficial outcome of this mesoporous surface on osteogenic activity, it could be presumed that modulation of the macrophagic response it elicits may also contribute to initial bone-integration events.
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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".