Macrophages, Foreign Body Giant Cells and Their Response to Implantable Biomaterials
Bibliographic record
Abstract
, elicit cellular and tissue responses. These responses include the inflammatory and wound healing responses, foreign body reactions, and fibrous encapsulation of the implanted materials. Macrophages are myeloid immune cells that are tactically situated throughout the tissues, where they ingest and degrade dead cells and foreign materials in addition to orchestrating inflammatory processes. Macrophages and their fused morphologic variants, the multinucleated giant cells, which include the foreign body giant cells (FBGCs) are the dominant early responders to biomaterial implantation and remain at biomaterial-tissue interfaces for the lifetime of the device. An essential aspect of macrophage function in the body is to mediate degradation of bio-resorbable materials including bone through extracellular degradation and phagocytosis. Biomaterial surface properties play a crucial role in modulating the foreign body reaction in the first couple of weeks following implantation. The foreign body reaction may impact biocompatibility of implantation devices and may considerably impact short- and long-term success in tissue engineering and regenerative medicine, necessitating a clear understanding of the foreign body reaction to different implantation materials. The focus of this review article is on the interactions of macrophages and foreign body giant cells with biomaterial surfaces, and the physical, chemical and morphological characteristics of biomaterial surfaces that play a role in regulating the foreign body response. Events in the foreign body response include protein adsorption, adhesion of monocytes/macrophages, fusion to form FBGCs, and the consequent modification of the biomaterial surface. The effect of physico-chemical cues on macrophages is not well known and there is a complex interplay between biomaterial properties and those that result from interactions with the local environment. By having a better understanding of the role of macrophages in the tissue healing processes, especially in events that follow biomaterial implantation, we can design novel biomaterials-based tissue-engineered constructs that elicit a favorable immune response upon implantation and perform for their intended applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".