Differential ability of proinflammatory and anti-inflammatory macrophages to perform macropinocytosis
Bibliographic record
Abstract
Macropinocytosis mediates the uptake of antigens and of nutrients that dictate the regulation of cell growth by mechanistic target of rapamycin complex 1 (mTORC1). Because these functions differ in proinflammatory and anti-inflammatory macrophages, we compared the macropinocytic ability of two extreme polarization states. We found that anti-inflammatory macrophages perform vigorous macropinocytosis constitutively, while proinflammatory cells are virtually inactive. The total cellular content of Rho-family GTPases was higher in anti-inflammatory cells, but this disparity failed to account for the differential macropinocytic activity. Instead, reduced activity of Rac/RhoG was responsible for the deficient macropinocytosis of proinflammatory macrophages, as suggested by the stimulatory effects of heterologously expressed guanine nucleotide-exchange factors or of constitutively active (but not wild-type) forms of these GTPases. Similarly, differences in the activation state of phosphatidylinositol 3-kinase (PtdIns3K) correlated with the macropinocytic activity of pro- and anti-inflammatory macrophages. Differences in PtdIns3K and Rho-GTPase activity were attributable to the activity of calcium-sensing receptors (CaSRs), which appear to be functional only in anti-inflammatory cells. However, agonists of PtdIns3K, including cytokines, chemokines, and LPS, induced macropinocytosis in proinflammatory cells. Our findings revealed a striking difference in the macropinocytic ability of pro- and anti-inflammatory macrophages that correlates with their antigen-presenting and metabolic activity.
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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".