Simultaneous knockdown of p18<sup>INK4C</sup>, p27<sup>Kip1</sup> and MAD1 via RNA interference results in the expansion of long-term culture-initiating cells of murine bone marrow cells <italic>in vitro</italic>
Bibliographic record
Abstract
A combination of extrinsic hematopoietic growth regulators, such as stem cell factor (SCF), interleukin (IL)-3 and IL-6, can induce division of quiescent hematopoietic stem cells (HSCs), but it usually impairs HSCs' self-renewal ability. However, intrinsic negative cell cycle regulators, such as p18INK4C (p18), p27Kip1 (p27) and MAD1, can regulate the self-renewal of HSCs. It is unknown whether the removal of some extrinsic regulators and the knockdown of intrinsic negative cell cycle regulators via RNA interference (RNAi) induce ex vivo expansion of the HSCs. To address this question, a lentiviral vector-based RNAi tool was developed to produce two copies of small RNA that target multiple genes to knockdown the intrinsic negative cell cycle regulators p18, p27 and MAD1. Colony-forming cells, long-term culture-initiating cells (LTC-IC) and engraftment assays were used to evaluate the effects of extrinsic and intrinsic regulators. Results showed that the medium with only SCF, but without IL-3 and IL-6, could maintain the sca-1+c-kit+ bone marrow cells with high LTC-IC frequency and low cell division. However, when the sca-1+c-kit+ bone marrow cells were cultured in a medium with only SCF and simultaneously knocked down the expression of p18, p27 and MAD1 via the lentiviral vector-based RNAi, the cells exhibited both high LTC-IC frequency and high cell division, though engraftment failed. Thus, the simultaneous knockdown of p18, p27 and MAD1 with a medium of only SCF can induce LTC-IC expansion despite the loss of engraftment ability.
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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 | 0.001 |
| 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".