Platelet interaction and performance of antibacterial bioinspired nanostructures passivated with human plasma
Bibliographic record
Abstract
The ever-increasing ageing of the world population is demanding superior orthopedic devices. Issues such as implant infection, poor osseointegration, or chronic inflammation remain problematic to the lifespan and long-term efficacy of implants. Fabrication of materials with bioinspired nanostructures is one emerging antibacterial strategy to prevent implant infection, however their interactions with blood components, and whether they retain their bactericidal properties in an environment displaying a complex protein corona, remains largely unexplored. In the present study, titanium alloy, commercially pure and plasma-sprayed titania were hydrothermally etched, passivated with human native plasma to develop a protein corona, and then incubated with either Staphylococcus aureus , Pseudomonas aeruginosa or human platelets. Surface analysis was first used to characterize the topography, chemical composition or crystallinity of each material. Fluorescence staining and SEM were performed to evaluate the nanostructure bactericidal properties, as well as to study platelet attachment and morphology. Composition of platelet supernatant was studied using ELISA and flow cytometry. Overall, our study showed that the bioinspired nanostructured surfaces displayed both impressive antibacterial properties in a complex environment, and a superior blood biocompatibility profile in terms of platelet activation (particularly for titanium alloy). Additionally, the amount of pro-inflammatory cytokines released by platelets was found to be no different to that found in native plasma (background levels) and, in some cases, presented a more pro-healing profile with an increased secretion of factors such as TGF-β, PDGF-BB or BMP-2. The nanostructured surfaces performed equally, or better, than hydroxyapatite-coated titanium which is one of the current gold standards in orthopedics. Although further in vivo studies are required to validate these results, such bioinspired nanostructured surfaces certainly show promise to be safely applied to medical device surfaces used in orthopedics and other areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".