Cytotoxicity mitigated silica entrapped copper doped Zinc Sulfide Quantum dots as luminescent nanoprobes for biolabeling
Abstract
Quantum dots (QDs) are luminescent semiconductor nanoparticles with unique optical properties that facilitate their use in sensing, biological labeling, optical imaging, and diagnostics. Wider band gap materials, such as Zinc sulfide, are extensively employed as QD nanoprobes since they offer higher photostability, higher quantum yield, larger molar extinction coefficients, and longer fluorescence lifetimes than conventional organic fluorescent dyes used in bioassays. Tunable multiphoton emission in QDs is accomplished by doping with transition metals, of which, copper is the most beneficial owing to its comparable ionic radius, intense emission, and composition-variable spectral broadening. However, an overdose of Cu is toxic to the cells, leading to apoptosis. This cytotoxicity impedes the utilization of Cu-doped ZnS QDs for biolabeling. The present work deals with the diminution of copper cytotoxicity in Cu-doped ZnS Q-dots by means of silica entrapment, equipping them for in vitro and in vivo bioassays in the future. Cu-doped ZnS Q-dots were synthesized by chemical precipitation method and overlaid with silica by sol–gel method. Cytotoxicity investigation was performed on L929 Mouse fibroblast cells. X-ray diffraction studies confirmed that the prepared Q-dots were approximately 2 nm in size and were in the cubic phase. High resolution transmission electron microscopy revealed the spherical morphology of Q-dots. Micro-Raman Analysis was used to determine the Raman modes…
How strong is the evidence?
Evidence Hub reads this as a experimental / empirical study, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.