Anti-inflammatory and immunosuppressive activation of human monocytes by a bioactive dendrimer
Bibliographic record
Abstract
The monocyte-macrophage (MPhi) lineage can undergo different pathways of activation. The classical priming by IFN-gamma, then triggering by LPS, conducts MPhi toward proinflammatory responses, whereas the alternative activation by IL-4, IL-10, IL-13, or glucocorticoids directs them toward an anti-inflammatory, immunosuppressive phenotype. Recently, we have shown that synthetic phosphorus-containing dendrimers activate human monocytes. Here, we analyzed the gene expression of monocytes activated by an acid azabisphosphonic-capped, phosphorus-containing dendrimer by comparison with untreated monocytes. We found that 78 genes were up-regulated, whereas 62 genes were down-regulated. Analysis of these genes directed the hypothesis of an alternative-like, anti-inflammatory activation of human monocytes. This was confirmed by quantitative RT-PCR and analysis of the surface expression of specific markers by flow cytometry. Functional experiments of inhibition of CD4(+) T-lymphocyte proliferation in MLR indicated that dendrimer-activated monocytes (da-monocytes) have an immune-suppressive phenotype similar to the one induced by IL-4. Moreover, da-monocytes preferentially enhanced amplification of CD4(+) T cells, producing IL-10, an immunosuppressive cytokine. Therefore, phosphorus-containing dendrimers appear as new nanobiotools promoting an anti-inflammatory and immunosuppressive activation of human monocytes and thus, prove to be good candidates for innovative, anti-inflammatory immunotherapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".