Multiorgan engraftment and differentiation of human cord blood CD34 <sup>+</sup> Lin <sup>−</sup> cells in goats assessed by gene expression profiling
Bibliographic record
Abstract
To investigate multitissue engraftment of human primitive hematopoietic cells and their differentiation in goats, human CD34+ Lin- cord blood cells transduced with a GFP vector were transplanted into fetal goats at 45-55 days of gestation. GFP+ cells were detected in hematopoietic and nonhematopoietic organs including blood, bone marrow, spleen, liver, kidney, muscle, lung, and heart of the recipient goats (1.2-36% of all cells examined). We identified human beta2 microglobulin-positive cells in multiple tissues. GFP+ cells sorted from the perfused liver of a transplant goat showed human insulin-like growth factor 1 gene sequences, indicating that the engrafted GFP+ cells were of human origin. A substantial fraction of cells engrafted in goat livers expressed the human hepatocyte-specific antigen, proliferating cell nuclear antigen, albumin, hepatocyte nuclear factor, and GFP. DNA content analysis showed no evidence for cellular fusion. Long-term engraftment of GFP+ cells could be detected in the blood of goats for up to 2 yr. Microarray analysis indicated that human genes from a variety of functional categories were expressed in chimeric livers and blood. The human/goat xenotransplant model provides a unique system to study the kinetics of hematopoietic stem cell engraftment, gene expression, and possible stem cell plasticity under noninjured conditions.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".