Biodistribution and Systemic Effects in Mice Following Intravenous Administration of Cadmium Telluride Quantum Dot Nanoparticles
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Quantum dots (QDs) are engineered nanoparticles (NPs) of semiconductor structure that possess unique optical and electronic properties and are widely used in biomedical applications; however, their risks are not entirely understood. This study investigated the tissue distribution and toxic effects of cadmium telluride quantum dots (CdTe-QDs) in male BALB/c mice for up to 1 week after single-dose intravenous injections. CdTe-QDs were detected in the blood, lung, heart, liver, spleen, kidney, testis and brain. Most CdTe-QDs accumulated in the liver, followed by the spleen and kidney. At high doses, exposure to CdTe-QDs resulted in mild dehydration, lethargy, ruffled fur, hunched posture, and body weight loss. Histological analysis of the tissues, upon highest dose exposures, revealed hepatic hemorrhage and necrotic areas in the spleen. The sera of mice treated with high doses of CdTe-QDs showed significant increases in alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin levels, as well as a reduction in albumin. CdTe-QD exposure also led to a reduced number of platelets and elevated total white blood cell counts, including monocytes and neutrophils, serum amyloid A, and several pro-inflammatory cytokines. These results demonstrated that the liver is the main target of CdTe-QDs and that exposure to CdTe-QDs leads to hepatic and splenic injury, as well as systemic effects, in mice. By contrast, cadmium chloride (CdCl 2 ), at an equivalent concentration of cadmium, appeared to have a different pharmacokinetic pattern from that of CdTe-QDs, having minimal effects on the aforementioned parameters, suggesting that cadmium alone cannot fully explain the toxicity of CdTe-QDs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".