Toxicity evaluation of high-fluorescent rare-earth metal nanoparticles for bioimaging applications
Bibliographic record
Abstract
Research on nanometer-sized luminescent semiconductors and their biological applications in detectors and contrasting agents is an emergent field in nanotechnology. When new nanosize technologies are developed for human health applications, their interaction with biological systems should be studied in depth. Rare-earth elements are used in medical and industrial applications, but their toxic effects are not known. In this work, the biological interaction between terbium-doped gadolinium oxysulfide nanoparticles (GOSNPs) with human peripheral blood mononuclear cells (PBMC), human-derived macrophages (THP-1), and human cervical carcinoma cell (HeLa) were evaluated. The GOSNPs were synthetized using a hydrothermal method to obtain monodisperse nanoparticles with an average size of 91 ± 9 nm. Characterization techniques showed the hexagonal phase of the Gd2O2S:Tb3+ free of impurities, and a strong green emission at λemi = 544 nm produced by Tb3+ was observed. Toxic effects of GOSNPs were evaluated using cell viability, apoptosis, cell-cycle progression, and immunological response techniques. In addition, an Artemia model was used to assess the toxicity in vivo. Results indicated cell apoptosis in both types of cells with less sensitivity for PBMC cells compared to HeLa cells. In addition, no toxic effects were observed in the in vivo model of Artemia. Moreover, GOSNPs significantly reduced the activation and cell-cycle progression of PBMC and HeLa cells, respectively. Interestingly, an increase in proinflammatory cytokines was not observed. Our data suggest that fluorescence applications of GOSNPs for biolabeling are not toxic in primary immune cells and they may have an immunomodulatory effect. © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 605–615, 2017.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".