Generation and Characterization of Murine Alternatively Activated Macrophages
Bibliographic record
Abstract
Macrophages play a key role in the innate immune response and help to direct the acquired immune response. Early in the innate immune response, they produce reactive oxygen species and pro-inflammatory cytokines and chemokines to drive inflammation and are referred to as "classically activated" or "killer" macrophages (M1). During the resolution phase of inflammation, they switch to what is known as an "alternatively activated" phenotype or "healer" macrophage (M2) and contribute to debris scavenging, angiogenesis, and wound healing. M1 macrophages are activated by treatment with IFNγ or LPS and M2 macrophages are activated by treatment with Th2 cytokines IL-4 or IL-13 and the M2 phenotype switch can be enhanced by IL-10. Macrophages can also be skewed during differentiation in vitro, and the resultant phenotype depends upon the cytokine provided to support their differentiation. In murine macrophages, MCSF promotes differentiation to an M1 phenotype, GM-CSF promotes differentiation to an M2 phenotype and IL-3 promotes differentiation into a profoundly M2 skewed phenotype. A defining feature of the phenotype of murine M1 versus M2 macrophages is how they metabolize L-arginine. In response to an inflammatory stimulus like LPS, M1 macrophages produce inducible nitric oxide synthase (iNOS) which uses L-arginine as a substrate to produce nitric oxide (NO). M2 macrophages constitutively produce the enzyme arginase I (argI), which sequesters L-arginine from iNOS and results in the production of ornithine and downstream polyamines and L-proline. M1 macrophages also produce relatively higher levels of pro-inflammatory IL-12 and lower levels of anti-inflammatory IL-10 relative to M2 macrophages. In this chapter, we describe in vitro derivation of polarized bone marrow macrophages and methods to analyze the resulting phenotype including Q-PCR, Western blotting, and enzyme assays to determine argI and iNOS expression and activity, as well as production of IL-12p40 and IL-10 and determination of IL-12/IL-10 ratios. Production of iNOS, NO, IL-12p40, and IL-10 are measured after treatment with LPS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".