A sex-specific reconstitution bias in the competitive CD45.1/CD45.2 congenic bone marrow transplant model
Bibliographic record
Abstract
Allelic variants of the pan-haematopoietic cell marker CD45, identified as CD45.1 and CD45.2, have been established as a marker system to track haematopoietic cells following congenic mouse bone marrow transplants. Despite the frequent use of this model for studying the impact of genetic modifications on relative differentiation potential, it is now evident that a bias exists in CD45.1 versus CD45.2 cell reconstitution. While this bias has been demonstrated by reduced reconstitution potential in B cells of CD45.1 origin, differences in the development of other lymphocytes, as well as the impact of sex on this bias, remain uncertain. We performed bone marrow transplants with wild-type CD45.1 and CD45.2 donor cells, and characterised haematopoietic cell reconstitution in dual-expressing CD45.1/2 host mice. We report an increase in CD45.2 reconstitution in the bone marrow that persists in the spleen, thymus and blood. Through the use of CD45.1/2 hosts, we demonstrate the intrinsic bias towards CD45.2 reconstitution is independent of an immunogenic response to the CD45.1 epitope. Furthermore, we identify a sex-specific difference in reconstitution efficiencies, with female mice exhibiting a greater bias towards CD45.2 reconstitution than males. This work sheds new light on the limitations of the CD45.1/CD45.2 congenic system for tracking lymphocyte development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".