Endotoxin Tolerance Represents a Distinctive State of Alternative Polarization (M2) in Human Mononuclear Cells
Bibliographic record
Abstract
Classical (M1) and alternative (M2) polarization of mononuclear cells (MNCs) such as monocyte and macrophages is known to occur in response to challenges within a microenvironment, like the encounter of a pathogen. LPS, also known as endotoxin, is a potent inducer of inflammation and M1 polarization. LPS can also generate an effect in MNCs known as endotoxin tolerance, defined as the reduced capacity of a cell to respond to LPS activation after an initial exposure to this stimulus. Using systems biology approaches in PBMCs, monocytes, and monocyte-derived macrophages involving microarrays and advanced bioinformatic analysis, we determined that gene responses during endotoxin tolerance were similar to those found during M2 polarization, featuring gene and protein expression critical for the development of key M2 MNC functions, including reduced production of proinflammatory mediators, expression of genes involved in phagocytosis, as well as tissue remodeling. Moreover, expression of different metallothionein gene isoforms, known for their role in the control of oxidative stress and in immunomodulation, were also found to be consistently upregulated during endotoxin tolerance. These results demonstrate that after an initial inflammatory stimulus, human MNCs undergo an M2 polarization probably to control hyperinflammation and heal the affected tissue.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".