Oxidative stress in the brain of nicotine-induced toxicity: protective role of<i>Andrographis paniculata</i>Nees and vitamin E
Bibliographic record
Abstract
Mitochondria are the crossroads of several crucial cellular activities; they produce considerable quantities of superoxide radical and hydrogen peroxide, which can damage important macromolecules. Nicotine affects a variety of cellular processes, from induction of gene expression to modulation of enzymatic activities. The aim of this study was to elucidate the protective effects of andrographolide (ANDRO) aqueous extract (AE-Ap) of Andrographis paniculata, and vitamin E on nicotine-induced brain mitochondria. In this investigation, nicotine (1 mg.kg body mass-1.day-1) was treated, for the period of 7 days, simultaneously with 2 A. paniculata products, ANDRO and AE-Ap (250 mg.kg body mass-1.day-1); and vitamin E (50 mg.kg body mass-1.day-1) was supplemented in different group of male Wistar rats. The activities of mitochondrial electron transport chain (Mito-ETC) complexes (I, II, III), nitric oxide production, superoxide anion, catalase, glutathione reductase, glutathione peroxidase, glutathione-S-transferase, and concentrations of reduced glutathione and oxidized glutathione were measured in discrete regions of brain (the cerebral hemisphere, cerebellum, diencephalons, and brain stem). The study revealed that nicotine inhibits the Mito-ETC complexes and produces nitric oxide, which suppressed the mitochondrial oxidative stress scavenger system in different brain regions. In these circumstances, lipid peroxidation and protein oxidation were noted in different discrete regions of brain mitochondria. ANDRO, AE-Ap, and vitamin E showed the protective potentiality against nicotine toxicity. The analysis of such alterations is important in determining the basis of normal dysfunction in the brain associated with nicotine toxicity, which could be ameliorated by A. paniculata and vitamin E, and may help to develop therapeutic means against nicotine-induced 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".