Application of the RBBP9 Serine Hydrolase Inhibitor, ML114, Decouples Human Pluripotent Stem Cell Proliferation and Differentiation
Bibliographic record
Abstract
Retinoblastoma binding protein 9 (RBBP9) is required for maintaining the expression of both pluripotency and cell cycle genes in human pluripotent stem cells (hPSCs). An siRNA-based study from our group showed it does so by influencing cell cycle progression through the RB/E2F pathway. In non-pluripotent cells, RBBP9 is also known to have serine hydrolase (SH) activity, acting on currently undefined target proteins. The role of RBBP9 SH activity in hPSCs, and during normal development, is currently unknown. To begin assessing whether RBBP9 SH activity might contribute to hPSC maintenance, hPSCs were treated with ML114-a selective chemical inhibitor of RBBP9 SH activity. Stem cells treated with ML114 showed significantly reduced population growth rate, colony size and progression through the cell cycle, with no observable change in cell morphology or decrease in pluripotency antigen expression-suggesting no initiation of hPSC differentiation. Consistent with this, hPSCs treated with ML114 retained the capacity for tri-lineage differentiation, as seen through teratoma formation. Subsequent microarray and Western blot analyses of ML114-treated hPSCs suggest the nuclear transcription factor Y subunit A (NFYA) may be a candidate effector of RBBP9 SH activity in hPSCs. These data support a role for RBBP9 in regulating hPSC proliferation independent of differentiation, whereby inhibition of RBBP9 SH activity de-couples decreased hPSC proliferation from initiation of differentiation.
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 | 0.001 |
| 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".