Recording from an Identified Neuron Efficiently Reveals Hazard for Brain Function in Risk Assessment.

Modern societies use a continuously growing number of chemicals. Because these are released into the environment and are taken up by humans, rigorous (but practicable) risk assessment must precede the approval of new substances for commerce. A number of tests is applicable, but it has been very difficult to efficiently assay the effect of chemicals on communication and information processing in vivo in the adult vertebrate brain. Here, we suggest a straightforward way to rapidly and accurately detect effects of chemical exposure on action potential generation, synaptic transmission, central information processing, and even processing in sensory systems in vivo by recording from a single neuron. The approach is possible in an identified neuron in the hindbrain of fish that integrates various sources of information and whose properties are ideal for rapid analysis of the various effects chemicals can have on the nervous system. The analysis uses fish but, as we discuss here, key neuronal functions are conserved and differences can only be due to differences in metabolism or passage into the brain, factors that can easily be determined. Speed and efficiency of the method, therefore, make it suitable to provide information in risk assessment, as we illustrate here with the effects of bisphenols on adult brain function.

Accuracy Bounds and Measurements of a Contactless Permittivity Sensor for Gases Using Synchronized Low-Cost mm-Wave Frequency Modulated Continuous Wave Radar Transceivers.

A primary concern in a multitude of industrial processes is the precise monitoring of gaseous substances to ensure proper operating conditions. However, many traditional technologies are not suitable for operation under harsh environmental conditions. Radar-based time-of-flight permittivity measurements have been proposed as alternative but suffer from high cost and limited accuracy in highly cluttered industrial plants. This paper examines the performance limits of low-cost frequency-modulated continuous-wave (FMCW) radar sensors for permittivity measurements. First, the accuracy limits are investigated theoretically and the Cramér-Rao lower bounds for time-of-flight based permittivity and concentration measurements are derived. In addition, Monte-Carlo simulations are carried out to validate the analytical solutions. The capabilities of the measurement concept are then demonstrated with different binary gas mixtures of Helium and Carbon Dioxide in air. A low-cost time-of-flight sensor based on two synchronized fully-integrated millimeter-wave (MMW) radar transceivers is developed and evaluated. A method to compensate systematic deviations caused by the measurement setup is proposed and implemented. The theoretical discussion underlines the necessity of exploiting the information contained in the signal phase to achieve the desired accuracy. Results of various permittivity and gas concentration measurements are in good accordance to reference sensors and measurements with a commercial vector network analyzer (VNA). In conclusion, the proposed radar-based low-cost sensor solution shows promising performance for the intended use in demanding industrial applications.

Metabolic costs of amino acid and protein production in Escherichia coli.

Escherichia coli is the most popular microorganism for the production of recombinant proteins and is gaining increasing importance for the production of low-molecular weight compounds such as amino acids. The metabolic cost associated with the production of amino acids and (recombinant) proteins from glucose, glycerol and acetate was determined using three different computational techniques to identify those amino acids that put the highest burden on the biosynthetic machinery of E. coli. Comparing the costs of individual amino acids, we find that methionine is the most expensive amino acid in terms of consumed mol of ATP per molecule produced, while leucine is the most expensive amino acid when taking into account the cellular abundances of amino acids. Moreover, we show that the biosynthesis of a large number of amino acids from glucose and particularly from glycerol provides a surplus of energy, which can be used to balance the high energetic cost of amino acid polymerization.

Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs.

While previous studies have shed light on the link between the structure of metabolism and its transcriptional regulation, the extent to which transcriptional regulation controls metabolism has not yet been fully explored. In this work, we address this problem by integrating a large number of experimental data sets with a model of the metabolism of Escherichia coli. Using a combination of computational tools including the concept of elementary flux patterns, methods from network inference and dynamic optimization, we find that transcriptional regulation of pathways reflects the protein investment into these pathways. While pathways that are associated to a high protein cost are controlled by fine-tuned transcriptional programs, pathways that only require a small protein cost are transcriptionally controlled in a few key reactions. As a reason for the occurrence of these different regulatory strategies, we identify an evolutionary trade-off between the conflicting requirements to reduce protein investment and the requirement to be able to respond rapidly to changes in environmental conditions.

Equality of average and steady-state levels in some nonlinear models of biological oscillations.

Nonlinear oscillatory systems, playing a major role in biology, do not exhibit harmonic oscillations. Therefore, one might assume that the average value of any of their oscillating variables is unequal to the steady-state value. For a number of mathematical models of calcium oscillations (e.g. the Somogyi-Stucki model and several models developed by Goldbeter and co-workers), the average value of the cytosolic calcium concentration (not, however, of the concentration in the intracellular store) does equal its value at the corresponding unstable steady state at the same parameter values. The average value for parameter values in the unstable region is even equal to the level at the stable steady state for other parameter values, which allow stability. This holds for all parameters except those involved in the net flux across the cell membrane. We compare these properties with a similar property of the Higgins-Selkov model of glycolytic oscillations and two-dimensional Lotka-Volterra equations. Here, we show that this equality property is critically dependent on the following conditions: There must exist a net flux across the model boundaries that is linearly dependent on the concentration variable for which the equality property holds plus an additive constant, while being independent of all others. A number of models satisfy these conditions or can be transformed such that they do so. We discuss our results in view of the question which advantages oscillations may have in biology. For example, the implications of the findings for the decoding of calcium oscillations are outlined. Moreover, we elucidate interrelations with metabolic control analysis.