Reconstitution of immune cell in liver and lymph node of adult- and newborn-engrafted humanized mice
Bibliographic record
Abstract
BACKGROUND: Humanized mouse models are an increasingly popular preclinical model to study the human immune response in a biological system. There are a variety of protocols to generate these mice, each differing in the strain of the recipient, source of hematopoietic stem cells, and mode of transplantation. Though there is well-documented reconstitution information regarding the spleen, blood, and bone marrow, there is little information regarding reconstitution of the lymph node and liver. In this report, we sought to compare reconstitution levels in a variety of immunological tissues, including the lymph node and liver, between mice engrafted intravenously as adults and intrahepatically in newborns. RESULTS: CD34+ cells were enriched from cord blood and transplanted intravenously into irradiated adult NOD-Rag1(-/-)IL2rγ(-/-) (NRG) mice or intra-hepatically into irradiated newborn NRG mice. At 9-28 weeks post-engraftment, immunological tissues were processed and analyzed for human lymphoid and myeloid subsets. Adult and newborn engrafted humanized mice were comparable in long-term reconstitution of human CD45 cells and subsequent lymphoid and myeloid subsets in the spleen, bone marrow, thymus, lymph node, and liver. Mice engrafted as newborns had a higher level of T-cells and a lower level of B-cells compared to mice engrafted as adults. We observed significant levels of human immune cell engraftment in both the lymph node and the liver, with a predominant adaptive immune population in both compartments. CONCLUSIONS: Human immune cells repopulate liver and mesenteric lymph nodes of NRG mice and can be used to study the human immune system in the gastrointestinal tract.
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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 | 0.001 | 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) | 0.003 | 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".