Bacterial populations housed in microfluidic environments can serve as transceivers for molecular communication, but the data-rates are extremely low (e.g., 10 −5 bits per second.). In this work, genetically engineered Escherichia coli bacteria were maintained in a microfluidic device where their response to a chemical stimulus was examined over time. The bacteria serve as a communication receiver where a simple modulation such as on-off keying (OOK) is achievable, although it suffers from very poor data-rates. We explore an alternative communication strategy called time-elapse communication (TEC) that uses the time period between signals to encode information. We identify the limitations of TEC under practical non-zero error conditions and propose an advanced communication strategy called smart time-elapse communication (TEC-SMART) that achieves over a 10x improvement in data-rate over OOK. We derive the capacity of TEC and provide a theoretical maximum data-rate that can be achieved.

Whole cell patch clamping in vivo is an important neuroscience technique that uniquely provides access to both supra-threshold spiking and sub-threshold synaptic events of single neurons in the brain. This article describes how to set up and use the autopatcher, a robot for automatically obtaining high yield and high quality whole cell patch clamp recordings in vivo. Following this protocol, a functional experimental rig for automated whole cell patch clamping can be set up in one week. High quality surgical preparation of mice takes approximately 1 hour, and each autopatching experiment can be carried out over periods lasting several hours. Autopatching should enable in vivo intracellular investigations to be accessible by a significant number of neuroscience labs, and enable labs already doing in vivo patch clamp to scale up their efforts by reducing training time for new lab members and increasing experimental durations by handling mentally intensive tasks automatically.

This paper explores the deflection and buckling of fixed-guided beams used in compliant mechanisms. The paper’s main contributions include the addition of an axial deflection model to existing beam bending models, the exploration of the deflection domain of a fixed-guided beam, and the demonstration that nonlinear finite element models typically incorrectly predict a beam’s buckling mode unless unrealistic constraints are placed on the beam. It uses an analytical model for predicting the reaction forces, moments, and buckling modes of a fixed-guided beam undergoing large deflections. The model for the bending behavior of the beam is found using elliptic integrals. A model for the axial deflection of the buckling beam is also developed. These two models are combined to predict the performance of a beam undergoing large deflections including higher order buckling modes. The force versus displacement predictions of the model are compared to the experimental force versus deflection data of a bistable mechanism and a thermomechanical in-plane microactuator (TIM). The combined models show good agreement with the force versus deflection data for each device.

The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or 'autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo.

In vivo studies of neurophysiology using the whole cell patch-clamp technique enable exquisite access to both intracellular dynamics and cytosol of cells in the living brain but are underrepresented in deep subcortical nuclei because of fouling of the sensitive electrode tip. We have developed an autonomous method to navigate electrodes around obstacles such as blood vessels after identifying them as a source of contamination during regional pipette localization (RPL) in vivo. In mice, robotic navigation prevented fouling of the electrode tip, increasing RPL success probability 3 mm below the pial surface to 82% ( = 72/88) over traditional, linear localization (25%, = 24/95), and resulted in high-quality thalamic whole cell recordings with average access resistance (32.0 MΩ) and resting membrane potential (-62.9 mV) similar to cortical recordings in isoflurane-anesthetized mice. Whole cell yield improved from 1% ( = 1/95) to 10% ( = 9/88) when robotic navigation was used during RPL. This method opens the door to whole cell studies in deep subcortical nuclei, including multimodal cell typing and studies of long-range circuits. This work represents an automated method for accessing subcortical neural tissue for intracellular electrophysiology in vivo. We have implemented a novel algorithm to detect obstructions during regional pipette localization and move around them while minimizing lateral displacement within brain tissue. This approach leverages computer control of pressure, manipulator position, and impedance measurements to create a closed-loop platform for pipette navigation in vivo. This technique enables whole cell patching studies to be performed throughout the living brain.

Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.

Amplification of multiple unique genetic targets using the polymerase chain reaction (PCR) is commonly required in molecular biology laboratories. Such reactions are typically performed either serially or by multiplex PCR. Serial reactions are time consuming, and multiplex PCR, while powerful and widely used, can be prone to amplification bias, PCR drift, and primer-primer interactions. We present a new thermocycling method, termed thermal multiplexing, in which a single heat source is uniformly distributed and selectively modulated for independent temperature control of an array of PCR reactions. Thermal multiplexing allows amplification of multiple targets simultaneously-each reaction segregated and performed at optimal conditions. We demonstrate the method using a microfluidic system consisting of an infrared laser thermocycler, a polymer microchip featuring 1 ll, oil-encapsulated reactions, and closed-loop pulsewidth modulation control. Heat transfer modeling is used to characterize thermal performance limitations of the system. We validate the model and perform two reactions simultaneously with widely varying annealing temperatures (48 C and 68 C), demonstrating excellent amplification. In addition, to demonstrate microfluidic infrared PCR using clinical specimens, we successfully amplified and detected both influenza A and B from human nasopharyngeal swabs. Thermal multiplexing is scalable and applicable to challenges such as pathogen detection where patients presenting non-specific symptoms need to be efficiently screened across a viral or bacterial panel. V C 2015 AIP Publishing LLC.

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