Due to interest in cell population heterogeneity, the development of new technology and methodologies for studying single cells has dramatically increased in recent years. The ideal single cell measurement system would be high throughput for statistical relevance, would measure the most important cellular parameters, and minimize disruption of normal cell function. We have developed a microwell array device capable of measuring single cell oxygen consumption rates (OCR). This OCR device is able to diffusionally isolate single cells and enables the quantitative measurement of oxygen consumed by a single cell with fmol/min resolution in a non-invasive and relatively high throughput manner. A glass microwell array format containing fixed luminescent sensors allows for future incorporation of additional cellular parameter sensing capabilities. To demonstrate the utility of the OCR device, we determined the oxygen consumption rates of a small group of single cells (12 to 18) for three different cells lines: murine macrophage cell line RAW264.7, human epithelial lung cancer cell line A549, and human Barrett's esophagus cell line CP-D.

A novel system that has enabled the measurement of single-cell oxygen consumption rates is presented. The experimental apparatus includes a temperature controlled environmental chamber, an array of microwells etched in glass, and a lid actuator used to seal cells in the microwells. Each microwell contains an oxygen sensitive platinum phosphor sensor used to monitor the cellular metabolic rates. Custom automation software controls the digital image data collection for oxygen sensor measurements, which are analyzed using an image-processing program to yield the oxygen concentration within each microwell versus time. Two proof-of-concept experiments produced oxygen consumption rate measurements for A549 human epithelial lung cancer cells of 5.39 and 5.27 fmol/min/cell, closely matching published oxygen consumption rates for bulk A549 populations.

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.

The development of a cellular isolation system (CIS) that enables the monitoring of singlecell oxygen consumption rates in real time is presented. The CIS was developed through a multidisciplinary effort within the Microscale Life Sciences Center (MLSC) at the University of Washington. The system comprises arrays of microwells containing Pt-porphyrinembedded polystyrene microspheres as the reporter chemistry, a lid actuator system and a gated intensified imaging camera, all mounted on a temperature-stabilized confocal microscope platform. Oxygen consumption determination experiments were performed on RAW264.7 mouse macrophage cells as proof of principle. Repeatable and consistent measurements indicate that the oxygen measurements did not adversely affect the physiological state of the cells measured. The observation of physiological rates in real time allows studies of cell-to-cell heterogeneity in oxygen consumption rate to be performed. Such studies have implications in understanding the role of mitochondrial function in the progression of inflammatory-based diseases, and in diagnosing and treating such diseases.

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