Vesicle motion during sustained exocytosis in chromaffin cells

Chromaffin cells release catecholamines by exocytosis, a process that includes vesicle docking, priming and fusion. Although all these steps have been intensively studied, some aspects of their mechanisms, particularly those regarding vesicle transport to the active sites situated at the membrane, are still unclear. In this work, we show that it is possible to extract information on vesicle motion in Chromaffin cells from the combination of Langevin simulations and amperometric measurements. We developed a numerical model based on Langevin simulations of vesicle motion towards the cell membrane and on the statistical analysis of vesicle arrival times. We also performed amperometric experiments in bovine-adrenal Chromaffin cells under Ba2+ stimulation to capture neurotransmitter releases during sustained exocytosis. In the sustained phase, each amperometric peak can be related to a single release from a new vesicle arriving at the active site. The amperometric signal can then be mapped into a spike-series of release events. We normalized the spike-series resulting from the current peaks using a time-rescaling transformation, thus making signals coming from different cells comparable. We discuss why the obtained spike-series may contain information about the motion of all vesicles leading to release of catecholamines. We show that the release statistics in our experiments considerably deviate from Poisson processes. Moreover, the interspike-time probability is reasonably well described by two-parameter gamma distributions. In order to interpret this result we computed the vesicles’ arrival statistics from our Langevin simulations. As expected, assuming purely diffusive vesicle motion we obtain Poisson statistics. However, if we assume that all vesicles are guided toward the membrane by an attractive harmonic potential, simulations also lead to gamma distributions of the interspike-time probability, in remarkably good agreement with experiment. We also show that including the fusion-time statistics in our model does not produce any significant changes on the results. These findings indicate that the motion of the whole ensemble of vesicles towards the membrane is directed and reflected in the amperometric signals. Our results confirm the conclusions of previous imaging studies performed on single vesicles that vesicles’ motion underneath plasma membranes is not purely random, but biased towards the membrane.

The Surface Plasmon Resonance of Supported Noble Metal Nanoparticles: Characterization, Laser Tailoring, and SERS Application

This work deals with the optical properties of supported noble metal nanoparticles, which are dominated by the so-called Mie resonance and are strongly dependent on the particles’ morphology. For this reason, characterization and control of the dimension of these systems are desired in order to optimize their applications. Gold and silver nanoparticles have been produced on dielectric supports like quartz glass, sapphire and rutile, by the technique of vapor deposition under ultra-high vacuum conditions. During the preparation, coalescence is observed as an important mechanism of cluster growth. The particles have been studied in situ by optical transmission spectroscopy and ex situ by atomic force microscopy. It is shown that the morphology of the aggregates can be regarded as oblate spheroids. A theoretical treatment of their optical properties, based on the quasistatic approximation, and its combination with results obtained by atomic force microscopy give a detailed characterization of the nanoparticles. This method has been compared with transmission electron microscopy and the results are in excellent agreement. Tailoring of the clusters’ dimensions by irradiation with nanosecond-pulsed laser light has been investigated. Selected particles are heated within the ensemble by excitation of the Mie resonance under irradiation with a tunable laser source. Laser-induced coalescence prevents strongly tailoring of the particle size. Nevertheless, control of the particle shape is possible. Laser-tailored ensembles have been tested as substrates for surface-enhanced Raman spectroscopy (SERS), leading to an improvement of the results. Moreover, they constitute reproducible, robust and tunable SERS-substrates with a high potential for specific applications, in the present case focused on environmental protection. Thereby, these SERS-substrates are ideally suited for routine measurements.

Evolving Classifiers - Evolutionary Algorithms in Data Mining

Data mining means to summarize information from large amounts of raw data. It is one of the key technologies in many areas of economy, science, administration and the internet. In this report we introduce an approach for utilizing evolutionary algorithms to breed fuzzy classifier systems. This approach was exercised as part of a structured procedure by the students Achler, Göb and Voigtmann as contribution to the 2006 Data-Mining-Cup contest, yielding encouragingly positive results.