Dynamic changes in human THP-1-derived M1-to-M2 macrophage polarization during Thelazia callipaeda MIF induction
Bibliographic record
Abstract
Macrophages are innate immune cells with essential roles in the immune response during helminth infection. Particularly, the direction of macrophage polarization could contribute to pathogen trapping and killing as well as tissue repair and the resolution of type 2 inflammation. This study establishes that the recombinant protein of Thelazia callipaeda macrophage migration inhibitory factor ( T.cp -MIF) induces THP-1-derived macrophages to undergo M1 to M2 type dynamic polarization, using the methods of flow cytometry, real-time quantitative PCR, differential transcriptomic analysis and western blot. Interestingly, there was an increase in protein and mRNA expression of M1-type proteins and cytokines after the use of PI3K inhibitors, suggesting that the polarization state tends to favor the M1 type after M2 type inhibition. In conclusion, the dynamic polarization mechanism of T.cp -MIF-induced human THP-1-derived macrophages from M1 to M2 type is related to the binding of TLR4. It can first affect the M1 type polarization of macrophages by activating its downstream NF-κB pathway. Activation of the PI3K/Akt pathway and inhibition of NF-κB phosphorylation affects the M2 type polarization of macrophages.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".