Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks.

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

Direct Transfer of Mesoporous Silica Nanoparticles between Macrophages and Cancer Cells.

Macrophages line the walls of microvasculature, extending processes into the blood flow to capture foreign invaders, including nano-scale materials. Using mesoporous silica nanoparticles (MSNs) as a model nano-scale system, we show the interplay between macrophages and MSNs from initial uptake to intercellular trafficking to neighboring cells along microtubules. The nature of cytoplasmic bridges between cells and their role in the cell-to-cell transfer of nano-scale materials is examined, as is the ability of macrophages to function as carriers of nanomaterials to cancer cells. Both direct administration of nanoparticles and adoptive transfer of nanoparticle-loaded splenocytes in mice resulted in abundant localization of nanomaterials within macrophages 24 h post-injection, predominately in the liver. While heterotypic, trans-species nanomaterial transfer from murine macrophages to human HeLa cervical cancer cells or A549 lung cancer cells was robust, transfer to syngeneic 4T1 breast cancer cells was not detected in vitro or in vivo. Cellular connections and nanomaterial transfer in vivo were rich among immune cells, facilitating coordinated immune responses.