A Newly Designed Curcumin Analog Y20 Mitigates Cardiac Injury via Anti-Inflammatory and Anti-Oxidant Actions in Obese Rats
Bibliographic record
Abstract
Obesity is strongly associated with the cause of structural and functional changes of the heart in both human and animal models. Oxidative stress and inflammation play a critical role in the development of obesity-induced cardiac disorders. Curcumin is a natural product from Curcuma Longa with multiple bioactivities. In our previous study, in order to reach better anti-inflammatory and anti-oxidant dual activities, we designed a new mono-carbonyl curcumin analog, Y20, via the structural modification with both trifluoromethyl and bromine. This study was designed to investigate the protective effects of Y20 on obesity-induced cardiac injury and its underlying mechanisms. In high fat diet-fed rats, oral administration of Y20 at 20 mg/kg or curcumin at 50 mg/kg significantly decreased the cardiac inflammation and oxidative stress and eventually improved the cardiac remodeling by mitigating cardiac disorganization, hypertrophy, fibrosis and apoptosis. Y20 at 20 mg/kg showed comparable and even stronger bioactivities than curcumin at 50 mg/kg. The beneficial actions of Y20 are closely associated with its ability to increase Nrf2 expression and inhibit NF-κB activation. Taken together, these results suggest that Y20 may have a great therapeutic potential in the treatment of obesity-induced cardiac injury using Nrf2 and NF-κB as the therapeutic targets for treating obesity-related disorders.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".