Generation of Mouse-Zebrafish Hematopoietic Tissue Chimeric Embryos for Hematopoiesis and Host-Pathogen Interaction Studies
Bibliographic record
Abstract
ABSTRACT Xenografts of the hematopoietic system are extremely useful as disease models and for translational research. Zebrafish xenografts have been widely used to monitor blood cancer cell dissemination and homing due to the optical clarity of embryos and larvae, which allow unrestricted in vivo visualization of migratory events. To broaden the scope of xenotransplantation studies in zebrafish, we have developed a technique that transiently generates hematopoietic tissue chimeras by transplanting murine bone marrow cells into zebrafish blastulae. This procedure leads to mammalian cell integration into the fish developmental hematopoietic program. Monitoring zebrafish chimeras at different time points post fertilization using in vivo time-lapse and confocal imaging showed murine cell co-localization with developing primitive and definitive hematopoietic tissues, intravasation into fish circulation, and dynamic hematopoietic cell-vascular endothelial and hematopoietic cell-niche interactions. Immunohistochemistry assays performed in chimeric animals showed that, after engraftment, murine cells expressed antigens related to i) hematopoietic stem and progenitor cells, ii) active cell proliferation, and iii) myeloid cell lineages. Lastly, xenografted zebrafish larvae infected with Klebsiella pneumoniae showed murine immune cells trafficking to bacterial foci and interacting with bacterial cells. Overall, these results show that mammalian bone marrow cells xenografted in zebrafish integrate into the host hematopoietic system revealing highly conserved molecular mechanisms of hematopoiesis between zebrafish and mammals. In addition, this procedure introduces a useful and simple method that improves and broadens the scope of hematopoietic tissue xenotransplantation studies in zebrafish.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".