Induction of Oxidative Stress in SH-SY5Y Cells by Overexpression of hTau40 and Its Mitigation by Redox-Active Nanoparticles
Bibliographic record
Abstract
Abnormally phosphorylated tau protein is the principal component of neurofibrillary tangles, accumulating in the brain in many neurodegenerative diseases, including Alzheimer's disease. The aim of this study was to examine whether overexpression of tau protein leads to changes in the redox status of human neuroblastoma SH-SY5Y cells. The level of reactive oxygen species (ROS) was elevated in tau-overexpressing cells (TAU cells) as compared with cells transfected with the empty vector (EP cells). The level of glutathione was increased in TAU cells, apparently due to overproduction as an adaptation to oxidative stress. The TAU cells had elevated mitochondrial mass. They were more sensitive to 6-hydroxydopamine, delphinidin, 4-amino-TEMPO, and nitroxide-containing nanoparticles (NPs) compared to EP controls. These results indicate that overexpression of the tau protein imposes oxidative stress on the cells. The nitroxide 4-amino-TEMPO and nitroxide-containing nanoparticles (NPs) mitigated oxidative stress in TAU cells, decreasing the level of ROS. Nitroxide-containing nanoparticles lowered the level of lipid peroxidation in both TAU and EP cells, suggesting that nitroxides and NPs may mitigate tau-protein-induced oxidative stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".