Human chronic myelogenous leukemia K562 cells undergo erythrocytic differentiation and cell cycle interruption in response to PMEA (9-(2-Phosphonyl-methoxyethyl)-adenine)
Bibliographic record
Abstract
Disruption during cellular differentiation can cause hematopoietic stem cells to proliferate uncontrollably, resulting in the development of cancer. Differentiation therapies are being investigated as a type of cancer treatment which involve inducing agents that promote the differentiation of cancer cells into those with similar properties to normal blood cells. These cells can then undergo apoptosis at an accelerated and controlled rate compared to cancer cells, making this a potential therapeutic technique. In this study, the ability of human chronic myelogenous leukemia K562 cells to undergo cellular differentiation in response to the inducing agent 9-(2-Phosphonyl-methoxy ethyl)-adenine (PMEA) is investigated. PMEA has previously been shown to disrupt cell replication, and promote erythrocytic differentiation in K562 cells. In order to further test the effectiveness of this inducer, cell proliferation was measured with a cell growth curve, hemoglobin presence was measured with benzidine staining, and gamma-globin expression (a protein subunit of fetal hemoglobin) was measured in both induced and uninduced K562 cell cultures via RT-qPCR and western blotting. The results indicate that PMEA slows cell replication, and promotes hemoglobin (and subsequently gamma-globin) expression in treated cells. In summary, the findings support the conclusion that PMEA is able to promote erythrocytic differentiation in K562 cells, and provides information that supports differentiation therapies as a method for cancer treatment. Department: Biology Faculty Mentors: Dr. Kim Harcombe and Dr. Nina Bernstein
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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 | 0.001 |
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".