Proteome analysis of the plasma protein layer adsorbed to a rough titanium surface
Bibliographic record
Abstract
In this study a label-free proteomic approach was used to investigate the composition of the layer of protein adsorbed to rough titanium (Ti) after exposure to human blood plasma. The influence of the protein layer on the surface free energy (SFE) of the Ti was evaluated by contact angle measurements. Ti discs were incubated with blood plasma for 180 min at 37 °C, and the proteins recovered were subjected to liquid chromatography coupled to tandem mass spectrometry analysis. A total of 129 different peptides were identified and assigned to 25 distinct plasma proteins. The most abundant proteins were fibronectin, serum albumin, apolipoprotein A-I, and fibrinogen, comprising 74.54% of the total spectral counts. Moreover, the protein layer increased the SFE of the Ti (p < 0.05). The layer adsorbed to the rough Ti surface was composed mainly of proteins related to cell adhesion, molecule transportation, and coagulation processes, creating a polar and hydrophilic interface for subsequent interactions with host cells.
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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".