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Andre E. Nel

Researcher at University of California, Los Angeles

Publications -  423
Citations -  62202

Andre E. Nel is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Biology & Paleontology. The author has an hindex of 105, co-authored 325 publications receiving 56090 citations. Previous affiliations of Andre E. Nel include Stellenbosch University & University of California, Berkeley.

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Two-Wave Nanotherapy To Target the Stroma and Optimize Gemcitabine Delivery To a Human Pancreatic Cancer Model in Mice

TL;DR: A two-wave approach provided effective shrinkage of the tumor xenografts beyond 25 days, compared to the treatment with free drug or gemcitabine-loaded liposomes only, and introduces the concept of using a stepwise engineered approach to address a range of biological impediments that interfere in nanocancer therapy in a spectrum of cancers.
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Tumor-penetrating peptide enhances transcytosis of silicasome-based chemotherapy for pancreatic cancer

TL;DR: It is demonstrated that iRGD enhances the efficacy of irinotecan-loaded silicasome–based therapy and may be a suitable adjuvant in nanoparticle-based treatments for PDAC.
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Quantitative techniques for assessing and controlling the dispersion and biological effects of multiwalled carbon nanotubes in mammalian tissue culture cells.

TL;DR: It is found that hydrophobicity is the major factor determining AP- and PD-MWCNT agglomeration in tissue culture media but that the ionic strength is the main factor determining COOH- MWCNT suspendability.
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The Fate of ZnO Nanoparticles Administered to Human Bronchial Epithelial Cells

TL;DR: Results corroborate a model for ZnO nanoparticle toxicity that is based on nanoparticle uptake followed by intracellular dissolution and suggest cellular uptake of ZNO nanoparticles is a mechanism of zinc accumulation in cells.
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Classification NanoSAR Development for Cytotoxicity of Metal Oxide Nanoparticles

TL;DR: It is important to recognize that a significantly larger data set would be needed in order to expand the applicability domain and increase the confidence and reliability of data-driven nanoSARs.