Inflammatory Immune Responses Trigger Rejection of Allogeneic Fibroblasts Transplanted into Mouse Skin
Bibliographic record
Abstract
Fibroblasts, or their homolog stromal cells, are present in most tissues and play an essential role in tissue homeostasis and regeneration. As a result, fibroblast-based strategies have been widely employed in tissue engineering. However, while considered to have immunosuppressive properties, the survival and functionality of allogeneic fibroblasts after transplantation remain controversial. Here, we evaluated innate and adaptive immune responses against allogeneic fibroblasts following intradermal injection into different immune-deficient mouse strains. While allogeneic fibroblasts were rejected 1 week after transplantation in immunocompetent mice, rejection did not occur in immunodeficient γ chain–deficient NOD-SCID (NSG) mice. T-cell- and B-cell-deficient RAG1 knockout mice showed greater loss of fibroblasts by day 5 after transplantation compared with NSG mice ( P ≤ 0.05) but prolonged persistence compared with wild-type recipient ( P ≤ 0.005). Loss of fibroblasts correlated with the expression of proinflammatory chemokine genes and infiltration of myeloid cells in the transplantation site. Depletion of macrophages and neutrophils delayed rejection, revealing the role of innate immune cells in an early elimination of fibroblasts that is followed by T-cell-mediated rejection in the second week. These findings indicate that the application of allogeneic fibroblasts in tissue engineering products requires further improvements to overcome cell rejection by innate and adaptive immune 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) | 0.001 | 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 | 0.001 |
| 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".