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Optical coherence tomography : a potential tool to predict premature rupture of fetal membranes
(2013)
In this work, a multi-sensor chip for the investigation of the sensing properties of different types of metal oxides towards hydrogen peroxide in the ppm range is presented. The fabrication process and physical characterization of the multi-sensor chip are described. Pure SnO2 and WO3 as well as Pd- and Pt-doped SnO2 films are characterized in terms of their sensitivity to H2O2. The sensing films have been prepared by drop-coating of water-dispensed nano-powders. A physical characterization, including scanning electron microscopy and X-ray diffraction analysis of the deposited metal-oxide films, was done. From the measurements in hydrogen peroxide atmosphere, it could be shown, that all of the tested metal oxide films are suitable for the detection of H2O2 in the ppm range. The highest sensitivity and reproducibility was achieved using Pt-doped SnO2.
Calibration plot of a SnO2, WO3, Pt-, and Pd-doped SnO2 gas sensor for H2O2 concentrations in the ppm range.
In the present work, a novel method for monitoring sterilisation processes with gaseous H2O2 in combination with heat activation by means of a specially designed calorimetric gas sensor was evaluated. Therefore, the sterilisation process was extensively studied by using test specimens inoculated with Bacillus atrophaeus spores in order to identify the most influencing process factors on its microbicidal effectiveness. Besides the contact time of the test specimens with gaseous H2O2 varied between 0.2 and 0.5 s, the present H2O2 concentration in a range from 0 to 8% v/v (volume percent) had a strong influence on the microbicidal effectiveness, whereas the change of the vaporiser temperature, gas flow and humidity were almost negligible. Furthermore, a calorimetric H2O2 gas sensor was characterised in the sterilisation process with gaseous H2O2 in a wide range of parameter settings, wherein the measurement signal has shown a linear response against the H2O2 concentration with a sensitivity of 4.75 °C/(% v/v). In a final step, a correlation model by matching the measurement signal of the gas sensor with the microbial inactivation kinetics was established that demonstrates its suitability as an efficient method for validating the microbicidal effectiveness of sterilisation processes with gaseous H2O2.
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.