Nanoparticles with various properties and functions are of growing interest for biomedical research, such as in vivo and in vitro sensors, imaging agents and delivery vehicles of therapeutics. An effective method to deliver nanoparticles into the intracellular environment is still a major challenge and critical to many biological studies. Current techniques, such as intracellular uptake, electroporation and microinjection, have different benefits and limitations (e.g., aggregation and endosomal degradation of nanoparticles, high cell mortality and low throughput). We demonstrate application of the well-established microelectrophoresis technique for the first time to deliver nanoparticles into target cells using fine-tipped micropipettes, which overcomes some of these delivery difficulties. Semiconductive quantum dots were selected as the nanoparticles in this study as they are widely used for biomedical imaging and sensing due to having functionalized surfaces suitable for bioconjugation, adaptable photophysical properties for multiplexed detection, and superior stability for longer investigation times. We developed a method to prepare monodisperse suspensions of quantum dots with average hydrodynamic diameter of ~20nm, which demonstrated sufficient colloidal stability to prevent aggregation and blockages in the tip of micropipettes during ejection while enabling sufficient electrical conductivity for ejection and recording electrical activity of cells. Fine-tipped glass micropipettes with an average tip inner diameter of 206 nm for ejection but less than 500 nm to minimize the cell membrane damage and cell distortion were successfully fabricated. Finally, quantum dots were successfully delivered into living human embryonic kidney cells using small electrical currents through fine-tipped glass micropipettes. The delivered quantum dots were found to stay monodispersed within the cells for 2 hours. We believe that microelectrophoresis technique may serve as a simple and general strategy for delivering a variety of biocompatible nanoparticles intracellularly in various biological systems.
We have developed a numerical model of Small Target Motion Detector neurons, bio-inspired from electrophysiological experiments in the fly brain. These neurons respond selectively to small moving features within complex moving surrounds. Interestingly, these cells still respond robustly when the targets are embedded in the background, without relative motion cues. This model contains representations of neural elements along a proposed pathway to the target-detecting neuron and the resultant processing enhances target discrimination in moving scenes. The model encodes high dynamic range luminance values from natural images (via adaptive photoreceptor encoding) and then shapes the transient signals required for target discrimination (via adaptive spatiotemporal high-pass filtering). Following this, a model for Rectifying Transient Cells implements a nonlinear facilitation between rapidly adapting, and independent polarity contrast channels (an 'on' and an 'off' pathway) each with center-surround antagonism. The recombination of the channels results in increased discrimination of small targets, of approximately the size of a single pixel, without the need for relative motion cues. This method of feature discrimination contrasts with traditional target and background motion-field computations. We improve the target-detecting output with inhibition from correlation-type motion detectors, using a form of antagonism between our feature correlator and the more typical motion correlator. We also observe that a changing optimal threshold is highly correlated to the value of observer ego-motion. We present an elaborated target detection model that allows for implementation of a static optimal threshold, by scaling the target discrimination mechanism with a model-derived velocity estimation of ego-motion.