Antigen‐specific IgG subclass composition in recipient mice can indicate the degree of red blood cell alloimmunization as well as discern between primary and secondary immunization
Bibliographic record
Abstract
BACKGROUND: Despite the vast antigen disparity between donor and recipient red blood cells (RBCs), only 2%-6% of transfusion patients mount an alloantibody response. Recently, RBC antigen density has been proposed as one of the factors that can influence alloimmunization, however, there has been no characterization of the role of antigen density along with RBC dose in primary and secondary immunization. STUDY DESIGN AND METHODS: To generate RBCs that express distinct antigen copy numbers, different quantities of hen egg lysozyme (HEL) were coupled to murine RBCs. The HEL-RBCs were subsequently transfused into recipient mice at different RBC doses and their HEL-specific IgM, IgG, and IgG subclass response was evaluated. RESULTS: Productive immune responses could be generated through a high copy number antigen transfused at low RBC doses or a low copy number transfused at high RBC doses. Further, primary but submaximal humoral immunization predominantly induced the IgG2b and IgG3 subclasses. In contrast, a maximal primary immunization or a secondary immunization induced all four IgG subclasses. DISCUSSION: Our results confirm the existence of an antigen threshold for productive immune responses but indicate that a high antigen copy number alone might not be enough to induce a response, but rather a combination of both antigen copy number and cell dosage may determine the outcome of immunization. Further, this study provides a proof of concept that the IgG subclass composition can be an indicator of the level of RBC alloimmunization as well as discern between primary and secondary immunization at least in this murine model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".