Recent Developments in the Biological Consequences of Certain Chalcone Derivatives
Bibliographic record
Abstract
Abstract Chalcones include many naturally occurring and synthetic compounds which have attracted considerable scientific interest due to their diverse biological activities. Their basic structures are comprised of two aromatic rings connected by an α,β ‐unsaturated carbonyl system, which underpins some of their versatile pharmacological potential. Demonstrating robust antioxidant properties due to their phenolic groups, chalcones effectively scavenge free radicals, showing promise in combating oxidative stress‐related ailments. Additionally, their anti‐inflammatory effects modulate various pathways, highlighting their potential in treating inflammatory conditions. Chalcones also display antimicrobial activities against a range of pathogens and exhibit promising anticancer properties by impeding tumor proliferation and prompting apoptosis. Furthermore, their role as enzyme inhibitors extends to various targets, broadening their therapeutic potential. Despite these promising attributes, challenges related to limited bioavailability and metabolic stability necessitate ongoing research to optimize their efficacy. This review, which encompasses literature from 2010–2025, provides insights into biological applications and affords ideas for designing new chalcone‐based molecules.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".