Pro-inflammatory activation of primary microglia and macrophages increases 18 kDa translocator protein expression in rodents but not humans
Bibliographic record
Abstract
The 18kDa Translocator Protein (TSPO) is the most commonly used tissue-specific marker of inflammation in positron emission tomography (PET) studies. It is expressed in myeloid cells such as microglia and macrophages, and in rodent myeloid cells expression increases with cellular activation. We assessed the effect of myeloid cell activation on TSPO gene expression in both primary human and rodent microglia and macrophages in vitro, and also measured TSPO radioligand binding with 3 H-PBR28 in primary human macrophages. As observed previously, we found that TSPO expression increases (∼9-fold) in rodent-derived macrophages and microglia upon pro-inflammatory stimulation. However, TSPO expression does not increase with classical pro-inflammatory activation in primary human microglia (fold change 0.85 [95% CI 0.58–1.12], p = 0.47). In contrast, pro-inflammatory activation of human monocyte-derived macrophages is associated with a reduction of both TSPO gene expression (fold change 0.60 [95% CI 0.45–0.74], p = 0.02) and TSPO binding site abundance (fold change 0.61 [95% CI 0.49–0.73], p < 0.0001). These findings have important implications for understanding the biology of TSPO in activated macrophages and microglia in humans. They are also clinically relevant for the interpretation of PET studies using TSPO targeting radioligands, as they suggest changes in TSPO expression may reflect microglial and macrophage density rather than activation phenotype.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".