Hepatotoxicity of Cadmium Telluride Quantum Dots Induced by Mitochondrial Dysfunction
Bibliographic record
Abstract
The aim of this study was to investigate the detailed mechanisms of hepatotoxicity induced by cadmium telluride quantum dots (CdTe-QDs) in BALB/c mice after intravenous injection. The study investigated oxidative stress, apoptosis, and effects on mitochondria as potential mechanistic events to elucidate the observed hepatotoxicity. Oxidative stress in the liver, induced by CdTe-QD exposure, was demonstrated by depletion of total glutathione, an increase in superoxide dismutase activity, and changes in the gene expression of several oxidative stress-related biomarkers. Furthermore, CdTe-QD treatment led to apoptosis in the liver via both intrinsic and extrinsic apoptotic pathways. Effects on mitochondria were evidenced by the enlargement and increase in the number of mitochondria in hepatocytes of treated mice. CdTe-QDs also caused changes in the levels and gene expression of electron transport chain enzymes, depletion of ATP, and an increase in the level of the peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), a regulator of mitochondrial biogenesis. The findings from this study suggest that CdTe-QDs-induced hepatotoxicity might have originated from mitochondrial effects which resulted in oxidative stress and apoptosis in the liver cells. This study provides insight into the biological effects of CdT-QDs at the tissue level and the detailed mechanisms of their toxicity in animals. The study also provides important data for bridging the gap between in vitro and in vivo testing and risk assessment of these NPs.
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".