Intracellular nickel accumulation induces apoptosis and cell cycle arrest in human astrocytic cells
Bibliographic record
Abstract
Nickel, a heavy metal found in electronic wastes and fume from electronic cigarettes, induces neuronal cell death and is associated with neurocognitive impairment. Astrocytes are the first line of defense against nickel after entering the brain; however, the effects of nickel on astrocytes remain unknown. Herein, we investigated the effect of nickel exposure on cell survival and proliferation and the underlying mechanisms in U-87 MG human astrocytoma cells and primary human astrocytes. Intracellular nickel levels were elevated in U-87 MG cells in a dose- and time-dependent manner after exposure to nickel chloride. The median toxic concentrations of nickel in astrocytoma cells and primary human astrocytes were 600.60 and >1000 µM at 48 h post-exposure, respectively. Nickel exposure triggered apoptosis in concomitant with the decreased expression of anti-apoptotic B-cell lymphoma protein (Bcl-2) and increased caspase-3/7 activity. Nickel induced reactive oxygen species formation. Additionally, nickel suppressed astrocyte proliferation in a dose- and time-dependent manner by delaying G2 to M phase transition through the upregulation of cyclin B1 and p27 protein expression. These results indicate that nickel-induced cytotoxicity of astrocytes is mediated by the activation of apoptotic pathway and disruption of cell cycle regulation.
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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".