Epigallocatechin gallate effectively ameliorates fluoride-induced oxidative stress and DNA damage in the liver of rats
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Environmental exposure to sodium fluoride (NaF) compounds is a worldwide health concern. Epigallocatechin gallate (EGCG) is a green tea catechin found in a variety of green tea preparations. The intention of this study was to investigate the hepatoprotective role of EGCG in NaF-intoxicated rats. Rats were orally treated with NaF alone (25 mg·(kg body mass)(-1)·day(-1)) or plus EGCG at different doses (20, 40, and 80 mg·(kg body mass)(-1)·day(-1)) for 4 weeks. Hepatotoxicity of NaF was determined by increased levels of serum hepatospecific markers and total bilirubin, along with increased levels of thiobarbituric acid reactive substances, lipid hydroperoxides, protein carbonyl content, and conjugated dienes. The hepatotoxic nature of NaF was further evidenced by the decreased activity of enzymatic and nonenzymatic antioxidant levels in liver. NaF-treated rats also showed increased DNA damage and fragmentation in hepatocytes. Administration of EGCG (40 mg·(kg body mass)(-1)) to NaF-intoxicated rats significantly recuperated the distorted biochemical indices, DNA damage, and pathological changes in the liver tissue. Thus, the results of the present study clearly demonstrate that EGCG has strong free radical scavenging, antioxidant, and antigenotoxic properties that protect against NaF-induced oxidative hepatic injury in rats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".