Trihydroxyflavones with antioxidant and anti‐inflammatory efficacy
Bibliographic record
Abstract
The classical anti-inflammatory therapies are frequently ineffective and present numerous and severe side effects, especially in long term use, which requires the development of anti-inflammatory drugs with different scaffolds and mechanisms of action. Owing to the high antioxidant potential and anti-inflammatory activities already inferred for hydroxyflavones, we found it would be relevant to evaluate the anti-inflammatory potential of a series of trihydroxyflavones by testing their ability to scavenge reactive oxygen species (ROS) and reactive nitrogen species (RNS) in cells and cell-free systems and to inhibit the proinflammatory pathways mediated by the enzymes cyclooxygenase (COX) and 5-lipoxygenase (5-LOX), in which reactive species have a proven involvement. The tested trihydroxyflavones proved to be effective inhibitors of neutrophils' oxidative burst and were shown to scavenge different ROS and RNS in cell-free systems. The most active compound in the majority of the assays was 3,3',4'-trihydroxyflavone, which was somehow expected due to the presence of the ortho-dihydroxy in the B-ring, an important structural feature in terms of free radical scavenging activity. Additionally, the studied compounds were able to inhibit the production of leukotriene B(4) by 5-LOX in activated neutrophils. 3,5,7-Trihydroxyflavone was able to inhibit both COX-1 and COX-2, which makes it a dual inhibitor of COX and 5-LOX pathways and, therefore, a promising candidate for a new therapeutic option in the treatment of inflammatory processes.
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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 | 0.001 | 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) | 0.005 | 0.001 |
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".