Lipopolysaccharide induces BV2 microglial cell migration via a decrease in SET8 expression
Bibliographic record
Abstract
Excessively activated microglia exhibit increased migration, resulting in tissue damage and chronic inflammation. Src was confirmed to play an important role in regulation of cell motility following lipopolysaccharide (LPS) treatment. SET8 plays an important part in multiple cellular signal pathways. In this study, we speculated that SET8 is involved in LPS-induced microglial migration via regulation of Src expression. Our study showed that LPS promoted cell migration via augmentation of Src expression in BV2 cells. Moreover, LPS treatment decreased SET8 expression and upregulated the expression of the transcription factor ETS proto-oncogene 1 (ETS1). Overexpression of both SET8 and small interfering ETS1 reversed LPS-induced Src expression and cell migration. The effects of short hairpin SET8 (shSET8) and ETS1 overexpression are the same as the effects of LPS treatment. Decrease of Src expression reversed the shSET8-induced and ETS1 overexpression-induced migration of BV2 cells. Furthermore, SET8 was observed to associate with ETS1. Chromatin immunoprecipitation assay indicated H4K20me1, a downstream target of SET8, in addition to ETS1, was enriched at the Src promoter region. Furthermore, shSET8 increased Src promoter activity and also increased the positive effect of ETS1 overexpression on Src promoter activity. This study shows that SET8 associates with ETS1 to regulate Src expression, which is involved in LPS-induced BV2 cell migration.
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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 | 0.001 |
| 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".