Mitochondrial and Chromosomal Damage Induced by Oxidative Stress in Zn2+ Ions, ZnO-Bulk and ZnO-NPs treated Allium cepa roots
Bibliographic record
Abstract
Abstract Large-scale synthesis and release of nanomaterials in environment is a growing concern for human health and ecosystem. Therefore, we have investigated the cytotoxic and genotoxic potential of zinc oxide nanoparticles (ZnO-NPs), zinc oxide bulk (ZnO-Bulk), and zinc ions (Zn2+) in treated roots of Allium cepa, under hydroponic conditions. ZnO-NPs were characterized by UV-visible, XRD, FT-IR spectroscopy and TEM analyses. Bulbs of A. cepa exposed to ZnO-NPs (25.5 nm) for 12 h exhibited significant decrease (23 ± 8.7%) in % mitotic index and increase in chromosomal aberrations (18 ± 7.6%), in a dose-dependent manner. Transmission electron microcopy and FT-IR data suggested surface attachment, internalization and biomolecular intervention of ZnO-NPs in root cells, respectively. The levels of TBARS and antioxidant enzymes were found to be significantly greater in treated root cells vis-à-vis untreated control. Furthermore, dose-dependent increase in ROS production and alterations in ΔΨm were observed in treated roots. FT-IR analysis of root tissues demonstrated symmetric and asymmetric P=O stretching of >PO2− at 1240 cm−1 and stretching of C-O ribose at 1060 cm−1, suggestive of nuclear damage. Overall, the results elucidated A. cepa, as a good model for assessment of cytotoxicity and oxidative DNA damage with ZnO-NPs and Zn2+ in plants.
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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".