No abstract

The production of structurally well-defined unilamellar vesicles and the control of their stability are of utmost importance for many of their applications but still a largely unresolved practical issue. In the present work we show that by admixing small amounts of amphiphilic copolymer to the original components of a spontaneously vesicle-forming surfactant mixture we are able to control the self-assembly process in a systematic way. For this purpose we employed a zwitanionic model system of zwitterionic TMDAO and anionic LiPFOS. As the copolymer reduces the line tension of the intermediately formed disks, this translates directly into a longer disk growth phase and formation of correspondingly larger vesicles. By this approach we are able to vary their size over a large range and produce vesicles of extremely low polydispersity. Furthermore, the temporal stability of the formed vesicles is enhanced by orders of magnitude in proportion to the concentration of copolymer added. This is achieved by exerting kinetic control that allows engineering the vesicle structure via a detailed knowledge of the formation pathway as obtained by highly time-resolved SAXS experiments. Synthesis of such very well-defined vesicles by the method shown should in general be applicable to catanionic or zwitanionic amphiphiles and will have far reaching consequences for controlled nanostructure formation and application of these self-assembled systems.

This article presents a new program that allows highly automatized analyses of series of, especially, anisotropic two-dimensional neutron and X-ray small-angle scattering data as well as one-dimensional data series. The main aim of this work was to reduce the effort of the analysis of complex scattering systems, which remains an essential burden in the evaluation process of complex systems. The program is built in a modular manner to support a stepwise analysis of smallangle scattering data. For example, from a two-dimensional data series, features such as anisotropy or changes of the preferred scattering direction or intensities along the radial or azimuthal directions as well as along the series axis (e.g. time axis) can quickly be extracted. Different anisotropy measurement methods are available, which are described herein. In a second step, physical scattering models can be fitted to the extracted data. More complex models can be easily added. The fitting procedure can be applied with nearly every possible constraint and works automatically on whole scattering data series. Furthermore, simultaneous fitting can be used to analyze coupled series, and parallel working methods are implemented to speed up the code execution. Finally, results can be easily visualized. The name of the program is SASET, which is an acronym standing for small-angle scattering evaluation tool. SASET is based on MATLAB.

BackgroundThe morphology of yeast cells changes during budding, depending on the growth rate and cultivation conditions. A photo-optical microscope was adapted and used to observe such morphological changes of individual cells directly in the cell suspension. In order to obtain statistically representative samples of the population without the influence of sampling, in situ microscopy (ISM) was applied in the different phases of a Saccharomyces cerevisiae batch cultivation. The real-time measurement was performed by coupling a photo-optical probe to an automated image analysis based on a neural network approach.ResultsAutomatic cell recognition and classification of budding and non-budding cells was conducted successfully. Deviations between automated and manual counting were considerably low. A differentiation of growth activity across all process stages of a batch cultivation in complex media became feasible. An increased homogeneity among the population during the growth phase was well observable. At growth retardation, the portion of smaller cells increased due to a reduced bud formation. The maturation state of the cells was monitored by determining the budding index as a ratio between the number of cells, which were detected with buds and the total number of cells. A linear correlation between the budding index as monitored with ISM and the growth rate was found.ConclusionIt is shown that ISM is a meaningful analytical tool, as the budding index can provide valuable information about the growth activity of a yeast cell, e.g. in seed breeding or during any other cultivation process. The determination of the single-cell size and shape distributions provided information on the morphological heterogeneity among the populations. The ability to track changes in cell morphology directly on line enables new perspectives for monitoring and control, both in process development and on a production scale.Electronic supplementary materialThe online version of this article (10.1186/s12934-018-0922-y) contains supplementary material, which is available to authorized users.

Inferring structural information from the intensity of a small-angle scattering (SAS) experiment is an ill-posed inverse problem. Thus, the determination of a solution is in general non-trivial. In this work, the indirect Fourier transform (IFT), which determines the pair distance distribution function from the intensity and hence yields structural information, is discussed within two different statistical inference approaches, namely a frequentist one and a Bayesian one, in order to determine a solution objectively From the frequentist approach the cross-validation method is obtained as a good practical objective function for selecting an IFT solution. Moreover, modern machine learning methods are employed to suppress oscillatory behaviour of the solution, hence extracting only meaningful features of the solution. By comparing the results yielded by the different methods presented here, the reliability of the outcome can be improved and thus the approach should enable more reliable information to be deduced from SAS experiments.