The phosphatase PPM1A controls monocyte-to-macrophage differentiation
Bibliographic record
Abstract
Abstract Differentiation of circulating monocytes into tissue-bound or tissue-resident macrophages is a critical regulatory process affecting host defense and inflammation. However, the regulatory signaling pathways that control the differentiation of monocytes into specific and distinct functional macrophage subsets are poorly understood. Herein, we demonstrate that monocyte-to-macrophage differentiation is controlled by the Protein Phosphatase, Mg2+/Mn2+-dependent 1A (PPM1A). Genetic manipulation experiments demonstrated that overexpression of PPM1A attenuated the macrophage differentiation program, while knockdown of PPM1A expression accelerated the ability of monocytes to differentiate into macrophages. We identify imiquimod and Pam3CSK4 as two Toll-like receptor agonists that induce PPM1A expression, and show that increased expression of PPM1A at the onset of differentiation impairs cellular adherence, reduces expression of inflammatory (M1) macrophage-specific markers, and inhibits the production of inflammatory cytokines. Our findings reveal PPM1A as a negative threshold regulator of M1-type monocyte-to-macrophage differentiation, establishing it as a key phosphatase that orchestrates this program.
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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 | 0.000 |
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".