Isolation of Murine Peritoneal Macrophages to Carry Out Gene Expression Analysis Upon Toll-like Receptors Stimulation
Bibliographic record
Abstract
During infection and inflammation, circulating monocytes leave the bloodstream and migrate into tissues, where they differentiate into macrophages. Macrophages express surface Toll-like receptors (TLRs), which recognize molecular patterns conserved through evolution in a wide range of microorganisms. TLRs play a central role in macrophage activation which is usually associated with gene expression alteration. Macrophages are critical in many diseases and have emerged as attractive targets for therapy. In the following protocol, we describe a procedure to isolate murine peritoneal macrophages using Brewer's thioglycollate medium. The latter will boost monocyte migration into the peritoneum, accordingly this will raise macrophage yield by 10-fold. Several studies have been carried out using bone marrow, spleen or peritoneal derived macrophages. However, peritoneal macrophages were shown to be more mature upon isolation and are more stable in their functionality and phenotype. Thus, macrophages isolated from murine peritoneal cavity present an important cell population that can serve in different immunological and metabolic studies. Once isolated, macrophages were stimulated with different TLR ligands and consequently gene expression was evaluated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".