Phenolic 1,3‐diketones attenuate lipopolysaccharide‐induced inflammatory response by an alternative magnesium‐mediated mechanism
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Toll-like receptor 4 (TLR4) plays a key role in the induction of inflammatory responses both in peripheral organs and the CNS. Curcumin exerts anti-inflammatory functions by interfering with LPS-induced dimerization of TLR4-myeloid differentiation protein-2 (MD-2) complex and suppressing pro-inflammatory mediator release. However, the inhibitory mechanism of curcumin remains to be defined. EXPERIMENTAL APPROACH: Binding of bis-demethoxycurcumin (GG6) and its cyclized pyrazole analogue (GG9), lacking the 1,3-dicarbonyl function, to TLR4-MD-2 was determined using molecular docking simulations. The effects of these compounds on cytokine release and NF-κB activation were examined by ELISA and fluorescence staining in LPS-stimulated primary microglia. Interference with TLR4 dimerization was assessed by immunoprecipitation in Ba/F3 cells. KEY RESULTS: Both curcumin analogues bound to the hydrophobic region of the MD-2 pocket. However, only curcumin and GG6, both possessing the 1,3-diketone moiety, inhibited LPS-induced TLR4 dimerization, activation of NF-κB and secretion of pro-inflammatory cytokines in primary microglia. Consistent with the ability of 1,3-diketones to coordinate divalent metal ions, LPS stimulation in a low magnesium environment decreased pro-inflammatory cytokine release and NF-κB p65 nuclear translocation in microglia and decreased TLR4-MD-2 dimerization in Ba/F3 cells. Curcumin and GG6 also significantly reduced cytokine output in contrast to the pyrazole analogue GG9. CONCLUSIONS AND IMPLICATIONS: These results indicate that phenolic 1,3-diketones, with a structural motif able to coordinate magnesium ions, can modulate LPS-mediated TLR4-MD-2 signalling. Taken together, these studies identify a previously uncharacterized mechanism involving magnesium, underlying the inflammatory responses to LPS.
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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) | 0.000 | 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 | 0.001 | 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