Single cells, despite being the base unit of living organisms, possess a high degree of hierarchical structure and functional compartmentalization. This complexity exists for good reason: cells must respond efficiently and effectively to its surrounding environment by differentiating, moving, interacting, and more in order to survive or inhabit its role in the larger biological system. At the core of these responses is cellular decision-making. Cells process cues internally and externally from the environment and effect intracellular asymmetry in biochemistry and structure in order to carry out the proper biological responses.

Functionalized magnetic particles have shown to be a powerful tool in interacting with biological matter, through either cell or biomolecule sorting, and the activation of biological processes. This dissertation reports on techniques utilizing manipulated magnetic nanoparticles (internalized by cells) to spatially and temporally localize intracellular cues, and examines the resulting asymmetry in biological processes generated by our methods. We first examine patterned micromagnetic elements as a simple strategy of rapidly manipulating magnetic nanoparticles throughout the intracellular space. Silicon or silicon dioxide substrates form the base for electroplated NiFe rods, which are repeated at varying size and pitch. A planarizing resin, initially SU-8, is used as the substrate layer for cellular adhesion. We demonstrate that through the manipulations of a simple external magnet, these micro–fabricated substrates can mediate rapid (under 2 s) and precise (submicron), reversible translation of magnetic nanoparticles through cellular space. Seeding cells on substrates composed of these elements allows simultaneous control of ensembles of nanoparticles over thousands of cells at a time. We believe such substrates could form the basis of magnetically based tools for the activation of biological matter.

We further utilize these strategies to generate user-controllable (time-varying and localizable), massively parallel forces on arrays of cells mediated by coalesced ensembles of magnetic nanoparticles. The above process is simplified and adapted for single cell analysis by precisely aligning fibronectin patterned cells to a single flanking micromagnet. The cells are loaded with magnetic-fluorescent nanoparticles, which are then localized to uniform positions at the internal edge of the cell membrane over huge arrays of cells using large external fields, allowing us to conduct composed studies on cellular response to force. By applying forces approaching the yield tension (5 nN / μ m) of single cells, we are able to generate highly coordinated responses in cellular behavior. We discover that increasing tension generates highly directed, PAK-dependent leading-edge type filopodia that increase in intensity with rising tension. In addition, we find that our generated forces can simulate cues created during cellular mitosis, as we are consistently able to generate significant (45 to 90 degree) biasing of the metaphase plate during cell division. Large sample size and rapid sample generation also allow us to analyze cells at an unprecedented rate — a single sample can simultaneously stimulate thousands of cells for high statistical accuracy in measurements.

We believe these approaches have potential not just as a tool to study single-cell response, but as a means of cell control, potentially through modifying cell movement, division, or differentiation. More generally, once approaches to release nanoparticles from endosomes are implemented, the technique provides a platform to dynamically apply a range of localized stimuli arbitrarily within cells. Through the bioconjugation of proteins, nucleic acids, small molecules, or whole organelles a broad range of questions should be accessible concerning molecular localization and its importance in cell function.

Development of brain-machine interfaces and treatment of neurological diseases can benefit from analysis of recorded data from implanted electrodes. Existing wireless neural recording systems are often bulky, dissipate too much heat to be implanted, or only have a small number of channels. Furthermore, advances in micro-machined electrodes provide the possibility of high-density recordings, but the companion electronics do not provide enough simultaneous channels with low enough power, wireless telemetry, or a small form-factor. A system level view of wireless recording-circuitry which could overcome these deficiencies is described in this work. The overall system comprises of an analog front end (AFE), digital signal processing (DSP), and transmitter (TX). Each block is analyzed, and system-level specifications are derived. Based on these specifications, each block can be optimized for low power and small area. The analog front-end uses open-loop amplifiers to support lower voltage operation than previously published work. A prototype amplifier was also fabricated to measure performance in a 65-nm CMOS process that is needed for low-power digital signal processing. The amplifier performance was comparable to other recently published amplifiers with 2.5 μV noise in 10 kHz bandwidth while dissipating 17.2 μV from a low 1 V supply. The use of programmable bias currents in the amplifier, to exploit the trade-off between noise and power, was proposed to set each individual amplifier's noise level (and power) to meet requirements for accurate spike detection. Literature reviews of digital-signal processors and transmitters are used to construct approximate models of power versus performance. These models are then used to investigate the overall system power with different levels of digital processing. With a target application of neural spike recording, four modes (raw data, spike detection, feature extraction, and clustering) were analyzed. A system that uses feature extraction yields the lowest overall power, supports 400 channels with a practical wireless link, and consumes approximately 8 mW.

A sensitive and miniaturized amperometric nitrate (NO3-) sensor for groundwater monitoring was designed, fabricated, and tested. The thin-film microelectrodes were patterned on the silicon substrate with microfabrication techniques. The sensor shows very promising performance, compared to commercial nitrate sensors. A low detection limit of 4 ?M and wide dynamic range of 10 mM with excellent linearity (r2=0.99) are achieved and yet sensor is in a small form factor (4×4×3 cm). Many efforts have been being made to improve the sensor reliability and to realize stand-alone field measurements. Reference electrode was treated with polyurethane coating. An automated sample-handling and sensor calibration system was studied. A miniaturized potentiostat with built-in pumps and valves controller have also been made. In order to overcome short life-time of the thin-film sensing electrode, a palm-sized sensor that consists of Plexiglass housing, macro-scale electrodes, and microfluidic channels have been newly developed. The interference from common ions in groundwater was characterized and major interferents are Sr+, Ca2+, and PO¬43-. An ion specific membrane is employed in the sensor to minimize interference, and selectivity of the sensor is currently being analyzed.

MEMS electromagnets occupy a unique niche in the design space of magnetic devices: they are small enough that length-scaling enables Tesla-scale field intensity and kTesla-scale field gradient, but large enough that power dissipation does not exceed practical power density limits for conductive cooling. This work demonstrates the first application of MEMS electromagnets to charged particle beam optics. Particle beam optics are an important component in beam transport systems for medical and scientific instruments such as Hadron therapy for cancer treatment and free electron lasers for high energy coherent light production. These MEMS devices promise smaller and higher performance instruments using the performance scaling that results from reducing the electromagnet gap. This work demonstrated a MEMS multi-pole Ni₈₀Fe₂₀-yoke electromagnet with a 600 &mum pole-pole gap producing a 24-mT dipole field at 3 A, steering a 34-keV electron beam in two dimensions without measurable hysteresis. The same multi-pole electromagnet producing a 220-T/m quadrupole field gradient at 4.7 A was used to focus a 34-keV electron beam. The spatial distribution of the quadrupole field was characterized using a novel electron beam-probe method. Simulations project that 4-pole electromagnets with 100 &mum pole-pole gap electromagnets and a 200 &mum thick Co ₅₇Ni$13Fe₃₀ yoke will produce 850 mT dipole fields and 20,000 T/m quadrupole field gradients, exceeding all published quadrupole optics by more than an order of magnitude.

Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. The system amplifies, digitally encodes, and transmits neural signals real-time at a rate of 9.6 kbps, while consuming less than 66 mW of power. The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.