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Living cells are complex biological systems transforming metabolites taken up from the surrounding medium. Monitoring the responses of such cells to certain substrate concentrations is a challenging task and offers possibilities to gain insight into the vitality of a community influenced by the growth environment. Cell-based sensors represent a promising platform for monitoring the metabolic activity and thus, the “welfare” of relevant organisms. In the present study, metabolic responses of the model bacterium Escherichia coli in suspension, layered onto a capacitive field-effect structure, were examined to pulses of glucose in the concentration range between 0.05 and 2 mM. It was found that acidification of the surrounding medium takes place immediately after glucose addition and follows Michaelis–Menten kinetic behavior as a function of the glucose concentration. In future, the presented setup can, therefore, be used to study substrate specificities on the enzymatic level and may as well be used to perform investigations of more complex metabolic responses. Conclusions and perspectives highlighting this system are discussed.
Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.
Impedance spectroscopy: A tool for real-time in situ monitoring of the degradation of biopolymers
(2013)
Investigation of the degradation kinetics of biodegradable polymers is essential for the development of implantable biomedical devices with predicted biodegradability. In this work, an impedimetric sensor has been applied for real-time and in situ monitoring of degradation processes of biopolymers. The sensor consists of two platinum thin-film electrodes covered by a polymer film to be studied. The benchmark biomedical polymer poly(D,L-lactic acid) (PDLLA) was used as a model system. PDLLA films were deposited on the sensor structure from a polymer solution by using the spin-coating method. The degradation kinetics of PDLLA films have been studied in alkaline solutions of pH 9 and 12 by means of an impedance spectroscopy (IS) method. Any changes in a polymer capacitance/resistance induced by water uptake and/or polymer degradation will modulate the global impedance of the polymer-covered sensor that can be used as an indicator of the polymer degradation. The degradation rate can be evaluated from the time-dependent impedance spectra. As expected, a faster degradation has been observed for PDLLA films exposed to pH 12 solution.