Ex-Vivo Expansion of Megakaryocyte Progenitors.
Bibliographic record
Abstract
Abstract Following Bone Marrow Transplant, thrombocytopenia and neutropenia always occur and patients require additional post transplant support in the form of platelet transfusions. Megakaryocytes (Mk), the precursors of platelets, are contained in hematopoietic progenitor cell products but their number is variable and relatively low. The infusion of ex vivo expanded Mk precursors could be beneficial by shortening the time to platelet engraftment and therefore reducing the amount of platelet transfusion support required by bone marrow transplant patients. The objective of this project was to investigate the expansion of Mk progenitors from peripheral blood stem cell (PBSC) harvests from patients with haematological malignancies. Briefly, CD34+ cells were isolated and cultured in serum free media supplemented with thrombopoietin (TPO) and Interleukin 1 (IL-1) then incubated at 37°C /5% CO2 for 8 – 12 days. Megakaryocyte progenitor analysis was accomplished using flow cytometry analysis (CD34+/41+, CD41+, CD61+) and Mk culture analysis (CFU-Mk) (Stem Cell Technologies). Mk progenitor expansion efficiency was determined as “fold expansion” of Mk progenitors produced over input levels. After 8 days of culture, a mean expansion of 46 fold (range 1.2 – 327.0, n=10) in megakaryocytic cells (CD61+) and a 15 fold expansion (1.2 – 41.7, n=10) in megakaryocyte progenitor cells (CD34+/41+) was observed. After 12 days, a 116 fold expansion (1.5 – 286, n=7) in megakaryocytic cells (CD61+) and a 19 fold expansion (2.4 – 40, n=7) in Mk progenitors (CD34+/CD41+) was observed. This study demonstrates that CD34+ cells can be used to effectively expand megakaryocytic cells using just two cytokines for an incubation period of 8 – 12 days. This data could be used to develop future protocols for use in clinical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".