The Role of Fetuin-A on the Attachment and Proliferation of Osteoblast-like Cells on Model Gold Surfaces
Bibliographic record
Abstract
Fetuin-A is a plasma protein of interest for bone-interfacing applications because of its role in mineralization processes through calcium/phosphate ion-binding capabilities. However, the role of fetuin A in the initial stages of cellular interaction with biomaterials and the mechanisms involved are not fully clear. This work investigated the response of osteoblast-like Saos-2 cells to model gold substrates presenting preadsorbed fetuin-A as a surface modification to determine the role of the protein in cell attachment and proliferation. Correlative quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance, and radiolabeling confirmed that fetuin-A adsorbed on model surfaces in similar quantities compared to serum albumin but formed a less packed layer with increased water entrapment. Cells attached to gold surfaces presenting preadsorbed fetuin-A displayed morphological characteristics similar to those with preadsorbed albumin with lower average surface area and maximum axis compared to the fibronectin control. Over 3 days, fetuin-A exhibited lower cellular proliferation compared to the fibronectin control, likely correlated to the decrease in cellular metabolism observed at the same time point, and persisted over 7 days. These results provide insight into the role of adsorbed fetuin-A for bone-interfacing implant applications, suggesting that the preadsorption of the protein alone is not sufficient to promote early stages of osseointegration.
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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".