Microelectrode array (MEA) approaches have been proposed as a tool for detecting functional changes in electrically excitable cells, including neurons, exposed to drugs, chemicals or particles. However, conventional single well-MEA systems lack the throughput necessary for screening large numbers of uncharacterized compounds. Recently, multi-well MEA (mwMEA) formats have become available to address the need for increased throughput. The current experiments examined the effects of a training set of 30 chemicals on spontaneous activity in networks of cortical neurons grown on mwMEA plates. Each plate contained 12 wells with 64 microelectrodes/well, for a total of 768 channels. Of the 30 chemicals evaluated, 23 were known to alter neuronal function in vivo (“positives”), including 6 GABAergic and 3 glutamatergic antagonists/agonists, 4 pyrethroids, 3 metals, 2 cholinesterase inhibitors, 2 nicotinic acetylcholine receptor agonists, valproic acid, verapamil, and fluoxetine. Seven compounds expected to have no effect on neuronal function were tested as “negatives” (glyphosate, acetaminophen, salicylic acid, paraquat, saccharin, d-sorbitol and amoxicillin). Following collection of 33 min of baseline activity, chemical effects (50 µM or highest soluble concentration) were recorded for 33 min. Twenty of the positives altered the mean network spike rate by more than the 14% threshold (two standard deviations from the mean for DMSO control). The three positives without effect were bifenthrin, nicotine and imidacloprid. None of the negative compounds caused a change in activity beyond the threshold. Based on these results, the mwMEA assay has both high sensitivity (87% identification of positive compounds) and specificity (100% identification of negative compounds). These experiments demonstrate the capacity of mwMEAs to screen compounds for neurotoxic effects mediated by a broad variety of mechanisms.

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We study theoretically the propagation of a step-modulated optical field as it passes through a dispersive dielectric made up of a dilute collection of oscillators characterized by a single narrowband resonance. The propagated field is given in terms of an integral of a Fourier type, which cannot be evaluated even for simple models of the dispersive dielectric. The fact that the oscillators have a low number density (dilute medium) and have a narrow-band resonance allows us to simplify the integrand. In this case, the integral can be evaluated exactly, although it is not possible using this method to separate out the transient part of the propagated field known as optical precursors. We also use an asymptotic method (saddle-point method) to evaluate the integral. The contributions to the integral related to the saddle-points of the integrand give rise to the optical precursors. We obtain analytic expressions for the precursor fields and the domain over which the asymptotic method is valid. When combined to obtain the total transient field, we find that the agreement between the solutions obtained by the asymptotic and the exact methods is excellent. Our results demonstrate that precursors can persist for many nanoseconds and the chirp in the instantaneous frequency of the precursors can manifest itself in beats in the transmitted intensity. Our work strongly suggests that precursors have been observed in many previous experiments.

Biofuel blends of 10% ethanol (EtOH) and gasoline are common in the USA, and higher EtOH concentrations are being considered (15-85%). Currently, no physiologically-based pharmacokinetic (PBPK) models are available to describe the kinetics of EtOH-based biofuels. PBPK models were developed to describe life-stage differences in the kinetics of EtOH alone in adult, pregnant, and neonatal rats for inhalation, oral, and intravenous routes of exposure, using data available in the open literature. Whereas ample data exist from gavage and intravenous routes of exposure, kinetic data from inhalation exposures are limited, particularly at concentrations producing blood and target tissue concentrations associated with developmental neurotoxicity. Compared to available data, the three models reported in this paper accurately predicted the kinetics of EtOH, including the absorption, peak concentration, and clearance across multiple datasets. In general, model predictions for adult and pregnant animals matched inhalation and intravenous datasets better than gavage data. The adult model was initially better able to predict the time-course of blood concentrations than was the neonatal model. However, after accounting for age-related changes in gastric uptake using the calibrated neonate model, simulations consistently reproduced the early kinetic behavior in blood. This work provides comprehensive multi-route life-stage models of EtOH pharmacokinetics and represents a first step in development of models for use with gasoline-EtOH blends, with additional potential applicability in investigation of the pharmacokinetics of EtOH abuse, addiction, and toxicity.