Transcriptional targeting of sphingosine-1- phosphate receptor S1P2 by epigallocatechin- 3-gallate prevents sphingosine-1-phosphate- mediated signaling in macrophage-differentiated HL-60 promyelomonocytic leukemia cells
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Bibliographic record
Abstract
BACKGROUND: Macrophage chemotaxis followed by blood-brain barrier transendothelial migration is believed to be associated with inflammation in the central nervous system. Antineuroinflammatory strategies have identified the dietary-derived epigallocatechin-3-gallate (EGCG) as an efficient agent to prevent neuroinflammation-associated neurodegenerative diseases by targeting proinflammatory mediator signaling. METHODS: Given that high levels of sphingosine kinase and its product, sphingosine-1-phosphate (S1P), are present in brain tumors, we used quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and immunoblotting to test whether EGCG may impact on S1P receptor gene expression and prevent S1P response in undifferentiated and in terminally differentiated macrophages. RESULTS: Promyelomonocytic human leukemia (HL)-60 cells were differentiated into macrophages, and S1P triggered phosphorylation in extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and P38 mitogen-activated protein kinase (MAPK) intracellular signaling, as shown by Western blot analysis. Pretreatment of cells with EGCG prior to differentiation inhibited the response to S1P in all three pathways, while EGCG abrogated P38 MAPK phosphorylation when present only during differentiation. Terminally-differentiated macrophages were, however, insensitive to EGCG treatment. Using qRT-PCR, gene expression of the S1P receptors S1P1, S1P2, and S1P5 was predominantly induced in terminally-differentiated macrophages, while the S1P2 was decreased by EGCG treatment. CONCLUSION: Our data suggest that diet-derived EGCG achieves efficient effects as a preventive agent, targeting signaling pathways prior to cell terminal differentiation. Such properties could impact on cell chemotaxis through the blood-brain barrier and prevent cancer-related neuroinflammation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it