Megakaryocyte Colony Formation of Fetal Liver Cells
Bibliographic record
Abstract
Purpose : This study was undertaken to obtain basic data about the megakaryocyte colony formation of fetal liver cells by using immunocytochemical staining and ex vivo culture with growth factors. Methods : The mononuclear cells were isolated from fetal liver and bone marrow with idiopathic thrombocytopenic purpura(ITP) and pancytopenia. These mononuclear cells were cultured in MegaCult TM -C(Stem Cell Tech, Canada) media in the presence of growth factors and CFU-Megakaryocyte(CFU-Mk) colonies were counted on day 12. The expansion of CD34+ and CD41+ cell was analyzed by flow cytometry after 5 days incubation using flask culture. Results : The numbers of CFU-Mk colonies of mononuclear cells obtained from fetal liver in the 11th week gestational age were more than those in the 19th week specimens; growth factors could not enhance the colony expansion in all cases. Total numbers of CFU-Mk colony of fetal liver cells were higher than bone marrow from ITP or pancytopenia groups. The numbers of pure or large CFU-Mk colonies of fetal liver cells were also higher than bone marrow specimens. The rate of CD34+ cell expression of fetal liver was increased after flask culture and the enhancement effect of epression was seen only in cases which added thrombopoietin. The rate of CD41+ cell expression of fetal liver was increased after incubation, but the enhancement effect of growth factors was unclear. Conclusion : This study revealed good results about the megakaryocyte colony assay of fetal liver mononuclear cells using MegaCult TM -C media. This study suggests that the fetal liver could be a good source of megakaryocytic progenitor cells for clinical application in hematopoietic stem cell transplantation. (J Korean Pediatr Soc 2002;45:247-255)
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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) | 0.002 | 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".