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Biomedical subjects

B Sonnleitner

Publications and source records attributed to B Sonnleitner.

9 recordsLinked to original sources
PubMed1992

Biomass determination.

The reasons for and historical backgrounds of biomass determination are discussed under the aspects of theoretical and practical importance, usefulness and representativity. Off-line methods are evaluated and compared with on-line methods; constraints of applications and conclusiveness of results are rated. Special emphasis is given to the fact that mere knowledge of a bio-mass concentration is not sufficiently valuable to learn more about physiology nor to determine the effectiveness of a biotechnological process. A combination of several different alternative measuring principles in parallel as well as the exploitation of software sensors is proposed as a promising future solution.

Ecology↗
PubMed1992

On-line measurement in biotechnology: techniques.

Bioprocesses are generally ill controlled. This is due to the fact that the measurement of relevant variables is difficult. Therefore, fundamental knowledge of metabolic interrelations is, at least in vivo, limited. In this article, some of the most important measurement techniques are reviewed in order to provide an evaluation of their current state. Emphasis is given to the underlying principles and on-line capability which allow to judge their importance and potential for exploitation resulting in well (maybe entirely) controlled bioprocesses in the future.

Biosensing Techniques↗
PubMed1992

On-line measurement in biotechnology: exploitation, objectives and benefits.

Sound data biologically relevant are prerequisites when developing high-performance bioprocesses. Understanding of physiological regulation as well as sophisticated control strategies are highly dependent on the observability of the culture, i.e. the generation and exploitation of suited signals even under complex environmental measurement conditions. Against this background, the increasing number of analytical systems is very supportive and, accordingly, an appropriate handling of sensors and measured data is of decisive importance. This article reports on practical experience with routines for maintenance, service and calibration of hardware sensors which improve the quality of measurements significantly. Verification and validation of signals is outlined in order to make the value of data exploitation tools obvious. A method for the characterization of information is introduced by practical examples of Saccharomyces cerevisiae cultures when explaining the specific properties of extracting biological information from raw data. Finally, examples for advantageous exploitation of on-line data are given.

Biosensing Techniques↗
PubMed1992

The decisive role of the Saccharomyces cerevisiae cell cycle behaviour for dynamic growth characterization.

The dynamic behaviour of the cell cycle and the physiology of Saccharomyces cerevisiae was monitored in transient experiments. Frequent flow cytometric analyses of the DNA (nuclear phase state) and the cell size enabled us to characterize the proliferation properties of yeast cells under well controlled and undisturbed cultivation conditions. Preliminarily, the correlation between flow cytometric light scattering measurements and the cell size was attested for yeasts. These flow cytometric results are compared with the physiological behaviour of the culture that was detected by high resolution on-line analyses and off-line measurements. The presented results focus on the importance of the yeast cell cycle behaviour for the dynamic growth characterization. Any kind of transients in yeast cultures induced partial synchronization. The characteristics and the time course of the yeast cell cycle were found to be strongly dependent on the physiological environment.

Cell Cycle↗
PubMed1991

Automatic bioprocess control. 2. Implementations and practical experiences.

Our improved implementation for bioprocess control allows flexible responses to many process needs. It is based on computer equipment consisting of three hierarchically ordered levels. On the lowest level, a DDC slave computer handles setpoints and simple tasks generating the chemical and physical environment for the cells. It can be designed manually by the user or automatically by the supervisory computer on the second level. This provides for raw data organization, analysis and interpretation either to support personnel on line in decision making, to select predefined control strategies, or even to search for others. In the coordinating computer on the third level, common tasks of different supervisory computers (bioprocesses) are shared, saving money for the equipment. Tasks and concepts as well as experimental experiences are described to outline the capabilities of the configuration.

Biotechnology↗
PubMed1991

Automatic bioprocess control. 1. A general concept.

Automation of bioprocesses is presented and discussed. A general concept is applied to laboratory scale reactors as well as to large scale production facilities consisting of many unit operations with a hierarchical and highly modular structure. The implementation of non-dedicated and intelligent analytical subsystems is foreseen. Hard- and software requirements are discussed in view of the functional requirements of both scientific research and production engineering. Some practical experience is reported using several different components in parallel installations.

Biotechnology↗
PubMed1991

On-line determination of glucose in biotechnological processes: comparison between FIA and an in situ enzyme electrode.

Two different analysis techniques for on-line monitoring of glucose in biotechnological processes have been tested: an in situ enzyme electrode and a flow injection analysis system (FIA). The measuring ranges, detection limits, response times and the reliabilities of each system have been compared during monitoring of batch and continuous cultures of Saccharomyces cerevisiae.

Computers↗
PubMedDate not supplied

Quantitation of microbial metabolism.

Quantitation is a characteristic property of natural sciences and technologies and is the background for all kinetic and dynamic studies of microbial life. This presentation concentrates therefore on materials and methods as tools necessary to accomplish a sound, quantitative and mechanistic understanding of metabolism. Mathematical models are the software, bioreactors, actuators and analytical equipment are the hardware used. Experiments must be designed and performed in accordance with the relaxation times of the biosystem investigated; some of the respective consequences are discussed and commented in detail. Special emphasis is given to the required density, accuracy and reproducibility of data as well as their validation.

Bacteria↗