Quantum Dots-interactions at the nano-bio interface
Bibliographic record
Abstract
Nanotechnology is an area of research that lies at the interface of physics, chemistry, engineering and biotechnology. The last decade has seen nanotechnology become a household term, as nano-scale products, known as nanoparticles, have become diverse in nature and form. Despite their immense promise, the widespread application of nanoparticles is currently limited due to their questionable biocompatibility and unclear consequences on cells and other biological components. We have selected fluorescent nanocrystals, called quantum dots (QDs), to investigate the interactions between nanoparticles and the biological environment, due to their superior optical properties. In the present studies, the mechanisms underlying the adaptive cell response to QDs were examined in multiple model cell lines. We observed significant morphological and functional changes at the cellular and subcellular levels following long term exposure to uncapped QDs. We showed that QD-induced toxicity included the production of reactive oxygen and nitrogen species as well as disruption of mitochondrial function. In addition, we found a novel role for transcription factor EB (TFEB), a master regulator of lysosome biogenesis in the successful cellular adaptation process. We showed that modifications to the QD surface can significantly decrease its toxicity, and in some cases, render the QDs non-toxic. Understanding the mechanisms of cellular adaptation to QDs is a first step for the establishment of protocols to evaluate the safety of other nanomaterials. We then investigated the effects of QD surface properties and how they contribute to particle uptake by using QDs with the same core, but with different surface functionalization. We demonstrated that QD surface charge plays an important role in internalization in two different human cell lines. In addition, we provided evidence for the involvement of several overlapping modes of uptake and export from the cell. Finally, we systematically investigated the effects of QD surface properties on particle stability in biological media. We found that serum proteins were differently adsorbed to the particle surface, and this played a key role in determining the primary mode of internalization. Taken together, the results from this work contribute to the development of nano-scale materials in two main ways:1)by presenting in vitro measures as the first step in the evaluation of nanomaterial safety.2)by demonstrating how surface charge and ligand properties drive specific modes of internalization The findings presented herein promote understanding of the intricacies at the nano-bio interface and provide guiding principles for sensible nanoparticle design, with careful consideration for size, shape and surface charge.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; both teacher heads agree on what is shown here.
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".