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Three-dimensional cell cultures may better mimic avascular tumors. Yet, they still lack characterization and standardization. Therefore, this study aimed to (a) generate multicellular aggregates (MCAs) of four breast cell lines: MCF7, MDA-MB-231, and SKBR3 (tumoral) and MCF12A (non-tumoral) using ultra-low attachment (ULA) plates, (b) detail the methodology used for their formation and analysis, providing technical tips, and (c) characterize the MCAs using morphometry, qualitative cytology (at light and electron microscopy), and quantitative immunocytochemistry (ICC) analysis. Each cell line generated uniform MCAs with structural differences among cell lines: MCF7 and MDA-MB-231 MCAs showed an ellipsoid/discoid shape and compact structure, while MCF12A and SKBR3 MCAs were loose, more flattened, and presented bigger areas. MCF7 MCAs revealed glandular breast differentiation features. ICC showed a random distribution of the proliferating and apoptotic cells throughout the MCAs, not fitting in the traditional spheroid model. ICC for cytokeratin, vimentin, and E-cadherin showed different results according to the cell lines. Estrogen (ER) and progesterone (PR) receptors were positive only in MCF7 and human epidermal growth factor receptor 2 (HER-2) in SKBR3. The presented characterization of the MCAs in non-exposed conditions provided a good baseline to evaluate the cytotoxic effects of potential anticancer compounds.

Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CCH, Gerstner W. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. J Neurophysiol 107: 1756-1775, 2012. First published December 7, 2011; doi:10.1152/jn.00408.2011.-Cortical information processing originates from the exchange of action potentials between many cell types. To capture the essence of these interactions, it is of critical importance to build mathematical models that reflect the characteristic features of spike generation in individual neurons. We propose a framework to automatically extract such features from current-clamp experiments, in particular the passive properties of a neuron (i.e., membrane time constant, reversal potential, and capacitance), the spike-triggered adaptation currents, as well as the dynamics of the action potential threshold. The stochastic model that results from our maximum likelihood approach accurately predicts the spike times, the subthreshold voltage, the firing patterns, and the type of frequency-current curve. Extracting the model parameters for three cortical cell types revealed that cell types show highly significant differences in the time course of the spike-triggered currents and moving threshold, that is, in their adaptation and refractory properties but not in their passive properties. In particular, GABAergic fast-spiking neurons mediate weak adaptation through spike-triggered currents only, whereas regular spiking excitatory neurons mediate adaptation with both moving threshold and spike-triggered currents. GABAergic nonfast-spiking neurons combine the two distinct adaptation mechanisms with reduced strength. Differences between cell types are large enough to enable automatic classification of neurons into three different classes. Parameter extraction is performed for individual neurons so that we find not only the mean parameter values for each neuron type but also the spread of parameters within a group of neurons, which will be useful for future large-scale computer simulations.

The distributions obtained by left-truncating at k a mixed Poisson distribution, kT-MP, and those obtained by mixing previously left-truncated Poisson distributions, M-kTP, are characterized by means of their probability generating function. The main consequence is that every kT-MP distribution is a M-kTP distribution, but not the other way around.