A multi-laboratory evaluation of microelectrode array-based measurements of neural network activity for acute neurotoxicity testing

There is a need for methods to screen and prioritize chemicals for potential hazard, including neurotoxicity. Microelectrode array (MEA) systems enable simultaneous extracellular recordings from multiple sites in neural networks in real time and thereby provide a robust measure of network activity. In this study, spontaneous activity measurements from primary neuronal cultures treated with three neurotoxic or three non-neurotoxic compounds was evaluated across four different laboratories. All four individual laboratories correctly identifed the neurotoxic compounds chlorpyrifos oxon (an organophosphate insecticide), deltamethrin (a pyrethroid insecticide) and domoic acid (an excitotoxicant). By contrast, the other three compounds (glyphosate, dimethyl phthalate and acetaminophen) considered to be non-neurotoxic ("negative controls"), produced only sporadic changes of the measured parameters. The results were consistent across the different laboratories, as all three neurotoxic compounds caused concentration-dependent inhibition of mean firing rate (MFR). Further, MFR appeared to be the most sensitive parameter for effects of neurotoxic compounds, as changes in electrical activity measured by mean frequency intra burst (MFIB), and mean burst duration (MBD) did not result in concentration-response relationships for some of the positive compounds, or required higher concentrations for an effect to be observed. However, greater numbers of compounds need to be tested to confirm this. The results obtained indicate that measurement of spontaneous electrical activity using MEAs provides a robust assessment of compound effects on neural network function.

Investigation of nonlinear pupil dynamics by recurrence quantification analysis

Pupil is controlled by the autonomous nervous system (ANS). It shows complex movements and changes of size even in conditions of constant stimulation. The possibility of extracting information on ANS by processing data recorded during a short experiment using a low cost system for pupil investigation is studied. Moreover, the significance of nonlinear information contained in the pupillogram is investigated. We examined 13 healthy subjects in different stationary conditions, considering habitual dental occlusion (HDO) as a weak stimulation of the ANS with respect to the maintenance of the rest position (RP) of the jaw. Images of pupil captured by infrared cameras were processed to estimate position and size on each frame. From such time series, we extracted linear indexes (e.g., average size, average displacement, and spectral parameters) and nonlinear information using recurrence quantification analysis (RQA). Data were classified using multilayer perceptrons and support vector machines trained using different sets of input indexes: the best performance in classification was obtained including nonlinear indexes in the input features. These results indicate that RQA nonlinear indexes provide additional information on pupil dynamics with respect to linear descriptors, allowing the discrimination of even a slight stimulation of the ANS. Their use in the investigation of pathology is suggested.

Determining chemical reactivity driving biological activity from SMILES transformations: the bonding mechanism of anti-HIV pyrimidines

Assessing the molecular mechanism of a chemical-biological interaction and bonding stands as the ultimate goal of any modern quantitative structure-activity relationship (QSAR) study. To this end the present work employs the main chemical reactivity structural descriptors (electronegativity, chemical hardness, chemical power, electrophilicity) to unfold the variational QSAR though their min-max correspondence principles as applied to the Simplified Molecular Input Line Entry System (SMILES) transformation of selected uracil derivatives with anti-HIV potential with the aim of establishing the main stages whereby the given compounds may inhibit HIV infection. The bonding can be completely described by explicitly considering by means of basic indices and chemical reactivity principles two forms of SMILES structures of the pyrimidines, the Longest SMILES Molecular Chain (LoSMoC) and the Branching SMILES (BraS), respectively, as the effective forms involved in the anti-HIV activity mechanism and according to the present work, also necessary intermediates in molecular pathways targeting/docking biological sites of interest.

Altered network communication following a neuroprotective drug treatment

Preconditioning is defined as a range of stimuli that allow cells to withstand subsequent anaerobic and other deleterious conditions. While cell protection under preconditioning is well established, this paper investigates the influence of neuroprotective preconditioning drugs, 4-aminopyridine and bicuculline (4-AP/bic), on synaptic communication across a broad network of in vitro rat cortical neurons. Using a permutation test, we evaluated cross-correlations of extracellular spiking activity across all pairs of recording electrodes on a 64-channel multielectrode array. The resulting functional connectivity maps were analyzed in terms of their graph-theoretic properties. A small-world effect was found, characterized by a functional network with high clustering coefficient and short average path length. Twenty-four hours after exposure to 4-AP/bic, small-world properties were comparable to control cultures that were not treated with the drug. Four hours following drug washout, however, the density of functional connections increased, while path length decreased and clustering coefficient increased. These alterations in functional connectivity were maintained at four days post-washout, suggesting that 4-AP/bic preconditioning leads to long-term effects on functional networks of cortical neurons. Because of their influence on communication efficiency in neuronal networks, alterations in small-world properties hold implications for information processing in brain systems. The observed relationship between density, path length, and clustering coefficient is captured by a phenomenological model where connections are added randomly within a spatially-embedded network. Taken together, results provide information regarding functional consequences of drug therapies that are overlooked in traditional viability studies and present the first investigation of functional networks under neuroprotective preconditioning.