A Macrophage Reporter Cell Assay to Examine Toll-Like Receptor-Mediated NF-kB/AP-1 Signaling on Adsorbed Protein Layers on Polymeric Surfaces
Bibliographic record
Abstract
The persistent inflammatory host response to an implanted biomaterial, known as the foreign body reaction, is a significant challenge in the development and implementation of biomedical devices and tissue engineering constructs. Macrophages, an innate immune cell, are key players in the foreign body reaction because they remain at the implant site for the lifetime of the device, and are commonly studied to gain an understanding of this detrimental host response. Many biomaterials researchers have shown that adsorbed protein layers on implanted materials influence macrophage behavior, and subsequently impact the host response. The methods in this paper describe an in vitro model using adsorbed protein layers containing cellular damage molecules on polymer biomaterial surfaces to assess macrophage responses. An NF-кB/AP-1 reporter macrophage cell line and the associated colorimetric alkaline phosphatase assay were used as a rapid method to indirectly examine NF-кB/AP-1 transcription factor activity in response to complex adsorbed protein layers containing blood proteins and damage-associated molecular patterns, as a model of the complex adsorbed protein layers formed on biomaterial surfaces in vivo.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".