The Conversion of Human Tissue‐Like Inflammatory Monocytes Into Macrophages
Bibliographic record
Abstract
Abstract Classical circulating LyC6high murine monocytes differentiate progressively from inflammatory tissue monocytes to mature macrophages (Mϕ) after entry into gut mucosa. This protocol provides a two‐step in vitro culture method that replicates the human monocyte maturation cascade. First, purified circulating CD14+CD16− monocytes exposed to granulocyte‐macrophage colony‐stimulating factor (GM‐CSF), interferon gamma (IFNγ), and interleukin 23 (IL‐23) differentiate into tissue‐like inflammatory monocytes. Next, addition of transforming growth factor beta (TGFβ) plus interleukin 10 (IL‐10) promotes their maturation into tissue‐like Mϕ. Methods to sort these cells after culture are also provided. The fine‐tuning of this system might open therapeutic avenues for chronic inflammatory disorders. © 2021 Wiley Periodicals LLC This article was corrected on 25 July 2022. See the end of the full text for details. Basic Protocol 1: Isolation of human monocytes from peripheral blood Basic Protocol 2: First step culture for generation of inflammatory monocyte‐like cells Basic Protocol 3: Second step culture for differentiation of inflammatory monocyte‐like cells into macrophages Alternate Protocol: Sorting and culturing of inflammatory monocyte‐like cells
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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 | 0.000 |
| 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) | 0.008 | 0.007 |
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".