Suppression of the Cell-Mediated Immune Response by a Fas-Immunoglobulin Fusion Protein
Bibliographic record
Abstract
INTRODUCTION: Immunosuppressive agents must not only be effective in impairing the host's allo-immune response, but should also be selective in targeting only those elements of the immune system activated by the allograft. The fact that allo-activated T cells express surface protein molecules that are not typically present on resting T cells can be exploited to specifically target this population. Fas ligand is one such molecule whose cell surface expression on T cells is dramatically up-regulated upon activation. METHODS: We constructed a murine fusion protein by linking the extracellular domain of Fas to the Fc region of IgG2a. The rationale being to selectively target activated T cells via binding of its Fas moiety to cell surface Fas ligand, and then to allow the Fc moiety to invoke its usual effector mechanisms resulting in the destruction of the allo-activated T cell. Here, we describe the design and expression of Fas-IgG2a and characterize several key in vitro and in vivo properties of this fusion protein including its ability to impact on both cell-mediated immune responses and cellular apoptotic activity using a murine model of delayed-type hypersensitivity. RESULTS: In vitro, our Fas-IgG2a construct bound activated T cells via FasL and invoked cytotoxicity. In vivo, it demonstrated a prolonged half-life characteristic of an immunoglobulin-like molecule. Most significantly, it suppressed the cell-mediated immune response and diminished cellular apoptotic activity in lymphoid tissue in our murine model. CONCLUSION: Fas-IgG2a is a novel agent for delivering target-specific immunosuppression with potential applicability in the transplant setting.
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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".