Integrative biochemical and computational analysis of leflunomide-induced redox alterations in Nauphoeta cinerea
Bibliographic record
Abstract
Leflunomide (LF) is an immunomodulator classified as a disease-modifying anti-rheumatic agent. Its mechanisms of action include inhibition of dihydroorotate dehydrogenase in lymphocytes, resulting in immunosuppressive effects, and blocking tyrosine kinase activation, generating anti-inflammatory effects. This study aimed to study biochemical parameters 24 h after leflunomide administration to Nauphoeta cinerea (Cockroach) model, focusing on toxicity assessment. Biochemical analyses were performed, and molecular docking studies were conducted with the proteins 6VCD, 2B3X, and 2B3Y. Leflunomide altered biochemical parameters by increasing markers such as PSH, NPSH, TBARS, and iron levels, suggesting that LF may induce oxidative stress. This was supported by a dose-dependent increase in PSH, indicating an adaptive defense response. Furthermore, a significant increase in NPSH was observed at 128 µg/mL coupled with increased lipid peroxidation and elevated iron levels at 256 µg/mL. Additionally, LF exhibited high molecular activity by interacting with the target proteins, presenting major alkyl-type bonds, in addition to the interaction of fluorine with 2 proteins (6VCD and 2B3Y). In conclusion, leflunomide appears to induce oxidative stress in a dose-dependent manner, triggering adaptive defense responses and altering key biochemical markers.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".