Combined Effects of Masking and Distance on Aerosol Exposure Potential.

OBJECTIVE: To quantify the efficacy of masking and "social distancing" on the transmission of airborne particles from a phantom aerosol source (simulating an infected individual) to a nearby target (simulating a healthy bystander) in a well-controlled setting. METHODS: An aerosol was created using monodisperse polystyrene latex beads in place of infectious respiratory secretions. Detection was by aerodynamic particle spectrometry. Both reusable cloth masks and disposable paper masks were studied. Transmission was simulated indoors during a 3-minute interval to eliminate the effect of variable ventilation rate on aerosol exposure. The study commenced on September 16, 2020, and concluded on December 15, 2020. RESULTS: Compared with a baseline of 1-foot separation with no masks employed, particle count was reduced by 84% at 3 feet of separation and 97% at 6 feet. A modest decrease in particle count was observed when only the receiver was masked. The most substantial exposure reduction occurred when the aerosol source was masked (or both parties were masked). When both the source and target were masked, particle count was reduced by more than 99.5% of baseline, regardless of separation distance or which type of mask was employed. CONCLUSION: These results support the principle of layered protection to mitigate transmission of SARS-CoV-2, the virus causing COVID-19, and other respiratory viruses and emphasize the importance of controlling the spread of aerosol at its source. The combination of masking and distancing reduced the exposure to exhaled particulates more than any individual measure. Combined measures remain the most effective way to combat the spread of respiratory infection.

Novel repurposing of a Laerdal Airway trainer to simulate aerosolisation.

COVID-19 has claimed over 200 000 lives in the USA and put healthcare workers at risk. Healthcare workers have an increased exposure risk from aerosol-generating procedures such as endotracheal intubation. New barrier designs such as the acrylic box and horizontal plastic drape have emerged to reduce exposure to airborne particles. Particle generating models are needed to test aerosol generating procedure (AGP) barrier designs. To achieve this, an aerosol model that generates a visible and measurable increase in particles which SARS-CoV-2 could travel on and that can also be intubated was created. The model was created using a Laerdal Airway Management Trainer (Laerdal Medical, Stavanger, Norway) combined with a nebuliser and Ambu bag-valve resuscitator (Ambu, Columbia, Maryland, USA). Nebulised Glo Germ (Glo Germ, Moab, Utah, USA) dissolved in saline solution was moved through the tubing and out of the mannequin's mouth with compression of the Ambu bag. This nebulisation was visualised under ultraviolet light and the quantity of particles between 0.3 and 10.0 µm was measured with a particle counter. Nebulisation was visible exiting the mouth of the mannequin. Nebulised Glo Germ was visualised under ultraviolet light moving in the ambient air. Particles in the size range of 0.3-0.5 µm increased by 20-fold and 1-10 µm increased by 10 252%. SARS-CoV-2 can travel on aerosol and droplet particles and particle generating models are needed to visualise and measure exposure areas and the path particles take during AGPs. We used existing medical and simulation supplies to create a particle simulator.

Analysis of Carbon-Based Microelectrodes for Neurochemical Sensing.

The comprehensive microscopic, spectroscopic, and in vitro voltammetric analysis presented in this work, which builds on the well-studied properties of carbon-based materials, facilitates potential ways for improvement of carbon fiber microelectrodes (CFMs) for neuroscience applications. Investigations by both, scanning electron microscopy (SEM) and confocal Raman spectroscopy, confirm a higher degree of structural ordering for the fibers exposed to carbonization temperatures. An evident correlation is also identified between the extent of structural defects observed from SEM and Raman results with the CFM electrochemical performance for dopamine detection. To improve CFM physico-chemical surface stability and increase its mechanical resistance to the induced compressive stress during anticipated in vivo tissue penetration, successful coating of the carbon fiber with boron-doped diamond (BDD) is also performed and microspectroscopically analyzed here. The absence of spectral shifts of the diamond Raman vibrational signature verifies that the growth of an unstrained BDD thin film was achieved. Although more work needs to be done to identify optimal parameter values for improved BDD deposition, this study serves as a demonstration of foundational technology for the development of more sensitive electrochemical sensors, that may have been impractical previously for clinical applications, due to limitations in either safety or performance.

Instrumentation for electrochemical performance characterization of neural electrodes.

In an effort to determine the chronic stability, sensitivity, and thus the potential viability of various neurochemical recording electrode designs and compositions, we have developed a custom device called the Voltammetry Instrument for Neurochemical Applications (VINA). Here, we describe the design of the VINA and initial testing of its functionality for prototype neurochemical sensing electrodes. The VINA consists of multiple electrode fixtures, a flowing electrolyte bath, associated reservoirs, peristaltic pump, voltage waveform generator, data acquisition hardware, and system software written in National Instrument's LabVIEW. The operation of VINA was demonstrated on a set of boron-doped diamond neurochemical recording electrodes, which were subjected to an applied waveform for a period of eighteen days. Each electrode's cyclic voltammograms (CVs) were recorded, and sensitivity calibration to dopamine (DA) was performed. Results showed an initial decline with subsequent stabilization in the CV current measured during the voltammetric sweep, corresponding closely with changes in electrode sensitivity to DA. The VINA has demonstrated itself as a useful tool for the characterization of electrode stability and chronic electrochemical performance.

A Diamond-Based Electrode for Detection of Neurochemicals in the Human Brain.

Deep brain stimulation (DBS), a surgical technique to treat certain neurologic and psychiatric conditions, relies on pre-determined stimulation parameters in an open-loop configuration. The major advancement in DBS devices is a closed-loop system that uses neurophysiologic feedback to dynamically adjust stimulation frequency and amplitude. Stimulation-driven neurochemical release can be measured by fast-scan cyclic voltammetry (FSCV), but existing FSCV electrodes rely on carbon fiber, which degrades quickly during use and is therefore unsuitable for chronic neurochemical recording. To address this issue, we developed durable, synthetic boron-doped diamond-based electrodes capable of measuring neurochemical release in humans. Compared to carbon fiber electrodes, they were more than two orders-of-magnitude more physically-robust and demonstrated longevity in vitro without deterioration. Applied for the first time in humans, diamond electrode recordings from thalamic targets in patients (n = 4) undergoing DBS for tremor produced signals consistent with adenosine release at a sensitivity comparable to carbon fiber electrodes. (Clinical trials # NCT01705301).

SynBioSS: the synthetic biology modeling suite.

UNLABELLED: SynBioSS (Synthetic Biology Software Suite) is a suite of software for the modeling and simulation of synthetic genetic constructs. SynBioSS utilizes the registry of standard biological parts, a database of kinetic parameters, and both graphical and command-line interfaces to multiscale simulation algorithms. AVAILABILITY: SynBioSS is available under the GNU General Public License at http://synbioss.sourceforge.net.

Optimization of a stochastically simulated gene network model via simulated annealing.

By rearranging naturally occurring genetic components, gene networks can be created that display novel functions. When designing these networks, the kinetic parameters describing DNA/protein binding are of great importance, as these parameters strongly influence the behavior of the resulting gene network. This article presents an optimization method based on simulated annealing to locate combinations of kinetic parameters that produce a desired behavior in a genetic network. Since gene expression is an inherently stochastic process, the simulation component of simulated annealing optimization is conducted using an accurate multiscale simulation algorithm to calculate an ensemble of network trajectories at each iteration of the simulated annealing algorithm. Using the three-gene repressilator of Elowitz and Leibler as an example, we show that gene network optimizations can be conducted using a mechanistically realistic model integrated stochastically. The repressilator is optimized to give oscillations of an arbitrary specified period. These optimized designs may then provide a starting-point for the selection of genetic components needed to realize an in vivo system.

Model-driven designs of an oscillating gene network.

The current rapid expansion of biological knowledge offers a great opportunity to rationally engineer biological systems that respond to signals such as light and chemical inducers by producing specific proteins. Turning on and off the production of proteins on demand holds great promise for creating significant biotechnological and biomedical applications. With successful stories already registered, the challenge still lies with rationally engineering gene regulatory networks which, like electronic circuits, sense inputs and generate desired outputs. From the literature, we have found kinetic and thermodynamic information describing the molecular components and interactions of the transcriptionally repressing lac, tet, and ara operons. Connecting these components in a model gene network, we determine how to change the kinetic parameters to make this normally nonperiodic system one which has well-defined oscillations. Simulating the designed lac-tet-ara gene network using a hybrid stochastic-discrete and stochastic-continuous algorithm, we seek to elucidate the relationship between the strength and type of specific connections in the gene network and the oscillatory nature of the protein product. Modeling the molecular components of the gene network allows the simulation to capture the dynamics of the real biological system. Analyzing the effect of modifications at this level provides the ability to predict how changes to experimental systems will alter the network behavior, while saving the time and expense of trial and error experimental modifications.