Transfusion of antibody‐opsonized red blood cells results in a shift in the immune response from the red blood cell to the antibody in a murine model
Bibliographic record
Abstract
BACKGROUND: It is well known that infusion of immunoglobulin (Ig)G-coated cells results in an inhibited antigen-specific humoral immune response compared to the cells themselves, a phenomenon termed antibody-mediated immune suppression (AMIS). Although this AMIS effect has been well described with many different types of cells as well as vaccines and insoluble antigens, the mechanisms behind this effect remain unresolved. STUDY DESIGN AND METHODS: To study AMIS in a broad context, three different models of AMIS were studied. In the first, mice were transfused with sheep red blood cells (SRBCs) versus IgG-coated SRBCs. In the second, SRBCs expressing the antigen hen egg white lysozyme (HEL) were studied, and the third model consisted of the diphtheria/tetanus vaccine in the absence versus presence of anti-tetanus IgG. The antibody responses to the SRBCs and HEL-SRBCs, as well as the vaccine, were analyzed for up to 4 weeks after challenge. RESULTS: In these mouse models of immunization, the IgG-coated RBCs or HEL-RBCs induced an antibody response against the IgG, rather than against the RBCs. The decreased response to the RBCs was directly related to the increase of the response against the IgG. The inhibitory AMIS effect using the vaccine strategy again showed an immune response against the IgG, concurrent with a decrease in the immune response against the specific vaccine component targeted. CONCLUSIONS: This work demonstrates that, under AMIS conditions, the IgG itself becomes the focus of B cells in the immune system, suggesting a potential mechanism of B-cell regulation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".