One-Step Liquid Phase Polymerization of HEMA by Atmospheric-Pressure Plasma Discharges for Ti Dental Implants
Bibliographic record
Abstract
Dental implants can fail due to various factors, in which bad tissue integration is believed to have a significant role. Specific properties of the implant surface, such as its chemistry and roughness, are of paramount importance to address specific cell responses, such as the adsorption of proteins, as well as the adhesion and differentiation of cells, which are suitable for biomaterial and tissue engineering. In this study, an acrylate-containing coating was produced on titanium surfaces through the atmospheric pressure plasma treatment of a liquid precursor, 2-hydroxyethyl methacrylate. A hydrophilic coating was obtained, showing retention of the monomer chemistry as assessed by FTIR analysis and XPS. Enhanced fibroblast adhesion and decreased Staphylococcus aureus and Escherichia coli adhesion were recorded, showing that this is a suitable method to produce biocompatible coatings with a reduced bacterial adhesion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".