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The improvement in the positioning accuracy of machine tools necessitates reliable friction models for compensation. Friction and damping are primarily caused by mechanical contacts, and they have a wide influence on the dynamics of machine tools. Particularly in the linear motor driven axis, linear bearings induce majority of the friction; contact is observed between the ball and raceway in linear bearings. Based on the Hertzian contact theory and a tangential force model, a model is developed for the friction behavior during the contact between the ball and raceway. This model determines the stick and slip areas, and the relative velocity at the contact surface. Hence, the calculation of the friction force, its hysteresis characteristics, and the stick and slip portions becomes possible.

A powerful approach for the optimization of industrial bioprocesses is to perform detailed simulations integrating large-scale computational fluid dynamics (CFD) and cellular reaction dynamics (CRD). However, complex metabolic kinetic models containing a large number of equations pose formidable challenges in CFD-CRD coupling and computation time afterward. This necessitates to formulate a relatively simple but yet representative model structure. Such a kinetic model should be able to reproduce metabolic responses for short-term (mixing time scale of tens of seconds) and long-term (fed-batch cultivation of hours/days) dynamics in industrial bioprocesses. In this paper, we used Penicillium chrysogenum as a model system and developed a metabolically structured kinetic model for growth and production. By lumping the most important intracellular metabolites in 5 pools and 4 intracellular enzyme pools, linked by 10 reactions, we succeeded in maintaining the model structure relatively simple, while providing informative insight into the state of the organism. The performance of this 9-pool model was validated with a periodic glucose feast-famine cycle experiment at the minute time scale. Comparison of this model and a reported black box model for this strain shows the necessity of employing a structured model under feast-famine conditions. This proposed model provides deeper insight into the in vivo kinetics and, most importantly, can be straightforwardly integrated into a computational fluid dynamic framework for simulating complete fermentation performance and cell population dynamics in large scale and small scale fermentors. Biotechnol. Bioeng. 2017;114: 1733-1743. © 2017 Wiley Periodicals, Inc.

The trajectories, referred to as lifelines, of individual microorganisms in an industrial scale fermentor under substrate limiting conditions were studied using an Euler-Lagrange computational fluid dynamics approach. The metabolic response to substrate concentration variations along these lifelines provides deep insight in the dynamic environment inside a large-scale fermentor, from the point of view of the microorganisms themselves. We present a novel methodology to evaluate this metabolic response, based on transitions between metabolic “regimes” that can provide a comprehensive statistical insight in the environmental fluctuations experienced by microorganisms inside an industrial bioreactor. These statistics provide the groundwork for the design of representative scale-down simulators, mimicking substrate variations experimentally. To focus on the methodology we use an industrial fermentation of Penicillium chrysogenum in a simplified representation, dealing with only glucose gradients, single-phase hydrodynamics, and assuming no limitation in oxygen supply, but reasonably capturing the relevant timescales. Nevertheless, the methodology provides useful insight in the relation between flow and component fluctuation timescales that are expected to hold in physically more thorough simulations. Microorganisms experience substrate fluctuations at timescales of seconds, in the order of magnitude of the global circulation time. Such rapid fluctuations should be replicated in truly industrially representative scale-down simulators.

A dedicated stimulated emission depletion (STED) microscope had been designed and implemented into the Göttingen Instrument for Nano-Imaging with X-rays (GINIX) at the synchrotron beamline P10 of the PETRA III storage ring (DESY, Hamburg). The microscope was installed on the same optical table used for X-ray holography and scanning small-angle X-ray scattering (SAXS). Scanning SAXS was implemented with the Kirkpatrick–Baez (KB) nano-focusing optics of GINIX, while X-ray holography used a combined KB and X-ray waveguide optical system for full-field projection recordings at a defocus position of the object. The STED optical axis was aligned (anti-)parallel to the focused synchrotron beam and was laterally displaced from the KB focus. This close proximity between the STED and the X-ray probe enabled in situ combined recordings on the same biological cell, tissue or any other biomolecular sample, using the same environment and mounting. Here, the instrumentation and experimental details of this correlative microscopy approach are described, as first published in our preceding work [Bernhardt et al. (2018), Nat. Commun. 9, 3641], and the capabilities of correlative STED microscopy, X-ray holography and scanning SAXS are illustrated by presenting additional datasets on cardiac tissue cells with labeled actin cytoskeleton.

Modern fluorescence superresolution microscopes are capable of imaging living cells on the nanometer scale. One of those techniques is stimulated emission depletion (STED) which increases the microscope’s resolution many times in the lateral and the axial directions. To achieve these high resolutions not only close to the coverslip but also at greater depths, the choice of objective becomes crucial. Oil immersion objectives have frequently been used for STED imaging since their high numerical aperture (NA) leads to high spatial resolutions. But during live-cell imaging, especially at great penetration depths, these objectives have a distinct disadvantage. The refractive index mismatch between the immersion oil and the usually aqueous embedding media of living specimens results in unwanted spherical aberrations. These aberrations distort the point spread functions (PSFs). Notably, during z- and 3D-STED imaging, the resolution increase along the optical axis is majorly hampered if at all possible. To overcome this limitation, we here use a water immersion objective in combination with a spatial light modulator for z-STED measurements of living samples at great depths. This compact design allows for switching between objectives without having to adapt the STED beam path and enables on the fly alterations of the STED PSF to correct for aberrations. Furthermore, we derive the influence of the NA on the axial STED resolution theoretically and experimentally. We show under live-cell imaging conditions that a water immersion objective leads to far superior results than an oil immersion objective at penetration depths of 5–180 μm.

The concepts called STED/RESOLFT superresolve features by a light-driven transfer of closely packed molecules between two different states, typically a nonfluorescent "off" state and a fluorescent "on" state at well-defined coordinates on subdiffraction scales. For this, the applied light intensity must be sufficient to guarantee the state difference for molecules spaced at the resolution sought. Relatively high intensities have therefore been applied throughout the imaging to obtain the highest resolutions. At regions where features are far enough apart that molecules could be separated with lower intensity, the excess intensity just adds to photobleaching. Here, we introduce DyMIN (standing for Dynamic Intensity Minimum) scanning, generalizing and expanding on earlier concepts of RESCue and MINFIELD to reduce sample exposure. The principle of DyMIN is that it only uses as much on/off-switching light as needed to image at the desired resolution. Fluorescence can be recorded at those positions where fluorophores are found within a subresolution neighborhood. By tuning the intensity (and thus resolution) during the acquisition of each pixel/voxel, we match the size of this neighborhood to the structures being imaged. DyMIN is shown to lower the dose of STED light on the scanned region up to ∼20-fold under common biological imaging conditions, and >100-fold for sparser 2D and 3D samples. The bleaching reduction can be converted into accordingly brighter images at

Friction in linear guideways has an influence on the motion accuracy of machine tool drives. As feedback control has a lag to the friction change in reverse motion, a feedforward compensation is generally used in friction models. However, it is difficult to estimate the friction of rolling balls in raceway grooves because it involves both stick and differential slip characteristics. In this paper, a measurement method is presented using an analytical procedure to clarify micro stick and slip factors in rolling friction. In the measurement test, four balls and two raceway grooves are used to measure the friction force under dry and lubricated conditions. The locomotive bristle model is then applied to identify the stick and slip parameters, which are then compared between the various conditions of lubrication.

The super-resolution microscopy called RESOLFT relying on fluorophore switching between longlived states, stands out by its coordinate-targeted sequential sample interrogation using low light levels. While RESOLFT has been shown to discern nanostructures in living cells, the reversibly photoswitchable green fluorescent protein (rsEGFP) employed in these experiments was switched rather slowly and recording lasted tens of minutes. We now report on the generation of rsEGFP2 providing faster switching and the use of this protein to demonstrate 25-250 times faster recordings.DOI:http://dx.doi.org/10.7554/eLife.00248.001. peerReviewed

Friction and damping have a wide influence on machine tools’ dynamics. The statistical spread of identical machine tools’ friction and components’ influence on it are marginally known. In order to reduce this lack of knowledge, measurements of friction in linear axes of identical machine tools were performed. In the course of this paper the variance of friction in a single axis is determined as well as the difference between several machine tools. Different types of feed drive systems, ball screw and linear motor driven, are measured and compared. The measured friction curves are used to estimate parameters of an extended Stribeck friction model. As a result, a method of measuring and analyzing friction in machine tools is developed and the evaluated parameters can be used for observing the assembly process, for condition monitoring, for on-board diagnostics and for scatter based parameterization of simulation models.

We investigate the cooperative effect of molecular tilt and defocus on fluorophore localization by centroid calculation in far-field superresolution microscopy based on stochastic single molecule switching. If tilt angle and defocus are unknown, the localization contains systematic errors up to about ±125 nm. When imaging rotation-impaired fluorophores of unknown random orientation, the average localization accuracy in three-dimensional samples is typically limited to about ±32 nm, restricting the attainable resolution accordingly.

The stirred-tank reactor (standard configuration) equipped with a Rushton turbine is theoretically investigated by solving continuity, momentum and turbulence quantity balance equations. Modelling approaches for the Rushton turbine and further important modelling aspects concerning the stirred tank are discussed. In this work the Rushton turbine is modelled with the aid of experimental data. In combination with this special modelling approach for the stirrer, the accuracy of three ad hoc applicable k – e turbulence models in predicting mean flow and turbulence quantities is tested with the aid of three-dimensional simulations. The differing simulation results are compared with experimental data. None of these k – e models performs satisfactorily without modification. However, in considering experimental observations and the general construction of k – e models it is possible to optimize one special k – e model. Good agreement can then be achieved between measured flow details and the simulation results for vessels and impellers of different geometry.

Approaches to mathematical modelling of anaerobic digestion and criteria for reactor design in anaerobic wastewater treatment are based on biological degradation kinetics. Whatever type of kinetics is used, the crucial problem always is reliable parameter estimation. For Monod-type kinetics a concept based on batch and fed-batch techniques is presented, which allows accurate estimation of kinetic parameters Vmax and KS in short-time experiments. Following the method of Optimal Experimental Design, sensitivity analysis is applied to design fed-batch experiments. The paper presents the methodology and results for the anaerobic degradation of acetic acid and discusses further implications of the experimental strategy.

The paper deals with a mathematical model for anaerobic treatment of waste water from sugar industry which has been developed for supporting the scale-up of a fluidized bed reactor. The dynamic model is based on material balance equations for substrates and products in gas and liquid phase. The effects taken into account are the biological degradation steps including chemical equilibria and mass transport between gas and liquid phase as well as convection and dispersion. Axial gradients of pH-values are calculated from a charge balance. Simulation results show reasonable agreement with measured gradients of substrates and pH in a 10 m3 fluidized bed reactor. For a new 500 m3 fluidized bed reactor simulations are performed to study the effects of increased hydrostatic pressure and increased ratio of feed to recirculation rate on the pH-values at the bottom of the reactor. The results indicate that for high COD-loading rates stationary pH-gradients may have significant influence upon the outcome of the process.

In this contribution some new aspects in the design of structured models for stirred tank bioreactors are discussed. Numerical solutions of the set of momentum equations for gas and liquid phase are presented The results of this computational fluiddynamic calculations (CFD) are then used for solving the material balances of a biological (oxygen sensitive culture of Bacillus subtilis ) and a physico-chemical (pH-calculation) model. In these models microbial and chemical reactions do not affect fluid dynamics, so that a strict separation of the solution of momentum and material balances is possible.

In this contribution new hardware and software concepts are presented for on-line supervision and control of fermentation processes. The concepts consist of components which are connected to instrumental network. With the aid of micro-robot systems the implementation of a high sophisticated analytic module is possible. Automation of sample preparation steps and the instrumental network of process control system, host computer lead to a better quality of control and state estimation. All components (software and hardware) are flexible and commercially available, so that their adaptation and transfer into industrial production processes is feasible.

We introduce a parallelized STED microscope featuring m = 4 pairs of scanning excitation and STED beams, providing m-fold increased imaging speed of a given sample area, while maintaining basically all of the advantages of single beam scanning. Requiring only a single laser source and fiber input, the setup is inherently aligned both spatially and temporally. Given enough laser power, the design is readily scalable to higher degrees of parallelization m.

Stimulated emission depletion (STED) microscopy usually employs a scanning excitation beam that is superimposed by a donut-shaped STED beam for keeping the fluorophores at the periphery of the excitation spot dark. Here, we introduce a simple birefringent device that produces a donut-shaped focal spot with suitable polarization for STED, while leaving the excitation spot virtually intact. The device instantly converts a scanning (confocal) microscope with a co-aligned STED beam into a full-blown STED microscope. The donut can be adapted to reveal, through the resulting fluorescence image, the orientation of fluorophores in the sample, thus directly providing subdiffraction resolution images of molecular orientation.

The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism. © 2010 Macmillan Publishers Limited. All rights reserved.

In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization techniques: first to handle the large data sets, second to support the human perception in the crowded environment, and third to provide an interactive exploration tool. To adjust the state of the cell to an external signal, a specific set of signaling molecules transports the information to the nucleus deep inside the cell. There, key molecules regulate gene expression. In contrast to continuous ODE models we model all signaling molecules individually in a more realistic crowded and disordered environment. Beyond spatiotemporal concentration profiles our data describes the process on a mesoscopic, molecular level, allowing a detailed view of intracellular events. In our proposed schematic visualization individual molecules, their tracks, or reactions can be selected and brought into focus to highlight the signal transduction pathway. Segmentation, depth cues and depth of field are applied to reduce the visual complexity. We also provide a virtual microscope to display images for comparison with wet lab experiments. The method is applied to distinguish different transport modes of MAPK (mitogen-activated protein kinase) signaling molecules in a cell. In addition, we simulate the diffusion of drug molecules through the extracellular space of a solid tumor and visualize the challenges in cancer related therapeutic drug delivery.

One of the most ambitious and challenging goals of systems biology is the identification oftargets for reshaping biological systems based on quantitative predictions with the aid of mathematicalmodels. Whereas the potential and promise of biological systems modelling is substantial, severalobstacles are still encountered when addressing the issue of predictive design based on dynamic models.This is particularly because of the well known difficulties in assessing enzyme kinetics under in vivo conditions as a prerequisite for a sound quantitative analysis ofthe network via dynamic modelling. The article will describe developments and applications of toolsaimed at achieving sustained improvements within this important field. Our experience in using metabolitedata for reconstruction of dynamic models led to a dual approach. At the core of the modular conceptis the decomposition of the networks into manageable subunits. Furthermore, a new top down approachis presented for estimating kinetic parameters for the individual reactions in whole cell metabolicnetworks from time series data.

The purpose of strategies for the integration of fluid dynamics and physiology is the development of more reliable simulation tools to accelerate the process of scale-up. The rigorous mathematical modeling of the richly interactive relationship between the dynamic response of biosystems and the physical environment changing in time and space must rest on the link between coupled momentum, energy and mass balances and structured modeling of the biophase. With the exponential increase in massive computer capabilities hard- and software tools became available for simulation strategies based on such holistic integration approaches. The review discusses fundamental aspects of application of computational fluid dynamics (CFD) to three-dimensional two-phase turbulence flow in stirred tank bioreactors. Examples of coupling momentum and material balance equations with simple unstructured kinetic models for the behavior of the biophase are used to illustrate the application of these strategies to the selection of suitable impeller configurations. The examples reviewed in this paper include distribution of carbon and energy source in fed batch cultures as well as dissolved oxygen fields during aerobic fermentations. A more precise forecasting of the impact of the multitude of interactions must, however, rest upon a rigorous understanding of the response of the cell factory to the complex dynamic stimulation due to space- and time-dependent concentration fields. The paper also introduces some ideas for fast and very fast experimental observations of intracellular pool concentrations based on stimulus response methods. These observations finally lead to a more complex integration approach based on the coupling of CFD and structured metabolic models.

The complete sequencing of about 20 genomes has opened a new era in biology. Amongst various other novel research opportunities due to this achievement there is now the possibility of delineating the metabolic maps for several organisms by “inverse genetics,” that is, by inferring the function of enzymes from the genes encoding them (cf. Bork et al., 1998). In the light of this development and promising biotechnological and medical aspects, there has recently been increasing interest in ways of understanding the architecture of cellular metabolism on a rational basis (cf. Heinrich & Schuster, 1996; Rohwer et al., 1996; Nuno et al., 1997; Stephanopoulos et al., 1998). The present contribution is a brief review of the state of the art in the structural (topological) analysis of metabolic networks, a field often referred to as pathway analysis. After a short account of various theoretical concepts, potential applications in biotechnology and medicine are outlined. Several situations where pathway analysis can tell us more about optimal metabolic routes than linear programming approaches are discussed.

The yeast S. cerevisiae has been used in the oldest biotechnical workshops and industries, baking, brewing, and wine making, from the earliest days of recorded histories. In our times it is in particular the application as bakers yeast which has resulted in production processes with very impressive scales of operation. With the advent of recombinant DNA technology, the yeast has also proved to be an excellent host for the production of a number of different proteins with exciting commercial applications. With increasing information on metabolic processes and physiology it can be expected that this organism becomes a very suitable cell factory for the production of high-added-value products.

The stirred and aerated tank fermentor is still the most important type of bioreactor for industrial production processes. The agitator or agitators are required to perform a wide range of functions: adequate momentum, heat and mass transfer, and mixing as well as gas-dispersion and homogenization of suspensions. As these various operations make different demands, optimization of the individual tasks would result in different design of the impellers. Therefore, agitators used in practice always reflect compromises. Conventional impellers used in fermentation are typically classified into axial and radial flow impellers. Examples of the two groups are illustrated in Fig. 7.1. Of the many impeller geometries, the six-blade disk impeller (Rushton turbine) with gas sparging below the impeller is most often used in standard configurations. However, an interest in using high-flow, low-power-number agitators such as Intermig (Fig. 7.2a), Lightnin A315 (Fig. 7.2b), Prochem Maxflow T (Fig. 7.2c), and Scaba 6SRGT (Fig. 7.2d) has been developed and improved performance of fermentation processes has been reported with such alternative designs [1-3].

The aim of this contribution is to discuss some new aspects in the design of structured models for stirred tank bioreactors. The modelling strategy starts from a simple multiphase compartment model, which is based on an aggregation of well-mixed multiphase compartiments including mass transfer between the phases. In order to incorporate the available information of intrinsic fluid dynamics it is necessary to put finite volume elements in the place of these compartments. The fluxes from and into those elements can be estimated from the real fluid dynamics. Numerical solutions of the set of momentum equations for gas and liquid phase are shown along with application examples for a biological model (oxygen sensitive culture of Bacillus subtilis) and a physico-chemical model for pH-calculation.

Although research on the development of on-line HPLC systems has been conducted for many years, there is still no satisfactory solution available in the area of fully automatic sampling and sample preparation during fermentation processes. Sample preparation, which is often complicated, is of great importance for a successful application. A particular problem, for example, is still the reliable and robust dilution of the sample. The proposed system fulfills the requirement of fully automatic sampling and sample preparation by use of the biofiltrator and an autosampler with microrobotic-system. In addition to applications for on-line-HPLC, the same configuration can be applied to on-line FIA (Flow Injection Analysis). This double function leads to a new name: High-Pressure-Injection Analysis (HPIA). The selection of the individual components was largely based on convenient use and industrial suitability. Because of the modular structure of the system, it is possible to include other components at any time. Furthermore, it is even possible to use this application in other areas such as environmental analysis and process chromatography.

In recent years considerable emphasis has been placed on the application of computer control to substrate feeding in baker's yeast production. Many investigators have studied the dynamics of different control loops and also first steps have already been taken to optimize the control algorithms. As far as the experimental verification of different strategies is concerned, the published work is, however, restricted to laboratory scale only. From current practice in baker's yeast industry which is most often based on open loop control with fixed schedule for carbon substrate addition, it is well known that mixing of substrate is playing an important role. The effects of the dynamics of mixing process in mechanicaly stirred tanks upon the performance of baker's yeast fermentation with fixed schedule have been investigated earlier by using a circulation model (Bajpai and Reuss, 1982). In the present contribution this framework is used in conjunction with a closed computer control of carbon substrate feeding based on exhaust air analysis. From experimental results for computer controlled fermentation in 10 and 2 000 l scale a decrease of productivity with increasing circulation times of liquid is observed. These results can be confirmed with the model calculations.

The major bottleneck for computer-coupling of fermentation processes is the lack of reliable, sterilisable and robust sensors for process key variables like biomass, substrate and product concentrations. Principally there are two ways to overcome this difficulty: a) construction of new sensors like product specific electrodes for in situ application or b) automatic coupling of powerful analyser systems like HPLC. This work is aimed to present a new system for coupling automatically an HPLC-System to fermentors. Furthermore this system is able to measure automatically filtration characteristies of the fermentation broth. The relationship between filtration characteristics, the height of the filter cake and its density was applied to the determination of morphology parameters of Penicillium by Nestaas and Wang (1981). Similar to other attempts for coupling autoanalyser systems, their concept was based on a filter unit with backflushed filter media. Problems in the use of such concepts for industrial media had been described several times in literature. Therefore in this work the concept of renewable filters.is chosen.The filter media is a band of filter paper or membrane filter (dependinq on the process), which lies between the media support and the'filter body.The sequence of the different operations : sterilisation, sampling, filtration, HPLC-analysis of the filtrate cleaning and finally transportation of the filter media is computer controlled. During filtration the computer registers the data for weight of the filtrate (load cell) filtration time and height of the filter cake from a couple of reflection light barriers. Using this information! the computer predicts filtration and morphology parameters. Examples for the application of this automatic system will be discussed with the aid of fermentations with a mycelial organism and yeasts. In all of these examples the emphasis of discussion is placed on both filtration parameters and HPLC-coupling.

The major bottleneck for computer-coupling of fermentation processes is the lack of reliable, sterilisable and robust sensors for process key variables like biomass, substrate and product concentrations. Principally there are two ways to overcome this difficulty: a) construction of new sensors like product specific electrodes for in situ application or b) automatic coupling of powerful analyser systems like HPLC. This work is aimed to present a new system for coupling automatically an HPLC-system to fermentors. Furthermore this system is able to measure automatically filtration characteristics of the fermentation broth. The relationship between filtration characteristics, the height of the filter cake and its density was applied to the determination of morphology parameters of Penicillium by Nestaas and Wang (1981). Similar to other attempts for coupling autoanalyser systems, their concept was based on a filter unit with backflushed filter media. Problems in the use of such concepts for industrial media had been described several times in literature. Therefore in this work the concept of renewable filters is chosen. The filter media is a band of filter paper or membrane filter (depending on the process), which lies between the media support and the filter body. The sequence of the different operations:sterilisation, sampling, filtration, HPLC-analysis of the filtrate cleaning and finally transportation of the filter media is computer controlled. During filtration the computer registers the data for weight of the filtrate (load cell) filtration time and height of the filter cake from a couple of reflection light barriers. Using this information the computer predicts filtration and morphology parameters. Examples for the application of this automatic system will be discussed with the aid of fermentations with a mycelial organism and yeasts. In all of these examples the emphasis of discussion is placed on both filtration parameters and HPLC-coupling.

In recent years considerable emphasis has been placed on the application of computer control to substrate feeding in baker's yeast production. Many investigators have studied the dynamics of different control loops and also first steps have already been taken to optimize the control algorithms. As far as the experimental verification of different strategies is concerned, the published work is, however, restricted to laboratory scale only. From current practice in baker's yeast industry which is most often based on open loop control with fixed schedule for carbon substrate addition, it is well known that mixing of substrate is playing an important role. The effects of the dynamics of mixing process in mechanicaly stirred tanks upon the performance of baker's yeast fermentation with fixed schedule have been investigated earlier by using a circulation model (Bajpai and Reuss, 1982). In the present contribution this framework is used in conjunction with a closed computer control of carbon substrate feeding based on exhaust air analysis. From experimental results for computer controlled fermentation in 10 and 20001 scale a decrease of productivity with increasing circulation times of liquid is observed. These results can be confirmed with the model calculations.