Fast, inexpensive, and reliable HPLC method to determine monomer fractions in poly(3-hydroxybutyrate-co-3-hydroxyvalerate).

The determination of the monomer fractions in polyhydroxyalkanoates is of great importance for research on microbial-produced plastic material. The development of new process designs, the validation of mathematical models, and intelligent control strategies for production depend enormously on the correctness of the analyzed monomer fractions. Most of the available detection methods focus on the determination of the monomer fractions of the homopolymer poly(3-hydroxybutyrate). Only a few can analyze the monomer content in copolymers such as poly(3-hydroxybutyrate-co-3-hydroxyvalerate), which usually require expensive measuring devices, a high preparation time or the use of environmentally harmful halogenated solvents such as chloroform or dichloromethane. This work presents a fast, simple, and inexpensive method for the analysis of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with high-performance liquid chromatography. Samples from a bioreactor experiment for the production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with Cupriavidus necator H16 were examined regarding their monomer content using the new method and gas chromatography analysis, one of the most frequently used methods in literature. The results from our new method were validated using gas chromatography measurements and show excellent agreement.Key points∙ The presented HPLC method is an inexpensive, fast and environmentally friendly alternative to existing methods for quantification of monomeric composition of PHBV.∙ Validation with state of the art GC measurement exhibits excellent agreement over a broad range of PHBV monomer fractions.

Examining Sodium and Potassium Channel Conductances Involved in Hyperexcitability of Chemotherapy-Induced Peripheral Neuropathy: A Mathematical and Cell Culture-Based Study.

Chemotherapy-induced peripheral neuropathy (CIPN) is a prevalent, painful side effect which arises due to a number of chemotherapy agents. CIPN can have a prolonged effect on quality of life. Chemotherapy treatment is often reduced or stopped altogether because of the severe pain. Currently, there are no FDA-approved treatments for CIPN partially due to its complex pathogenesis in multiple pathways involving a variety of channels, specifically, voltage-gated ion channels. One aspect of neuropathic pain in vitro is hyperexcitability in dorsal root ganglia (DRG) peripheral sensory neurons. Our study employs bifurcation theory to investigate the role of voltage-gated ion channels in inducing hyperexcitability as a consequence of spontaneous firing due to the common chemotherapy agent paclitaxel. Our mathematical investigation of a reductionist DRG neuron model comprised of sodium channel Nav1.7, sodium channel Nav1.8, delayed rectifier potassium channel, A-type transient potassium channel, and a leak channel suggests that Nav1.8 and delayed rectifier potassium channel conductances are critical for hyperexcitability of small DRG neurons. Introducing paclitaxel into the model, our bifurcation analysis predicts that hyperexcitability is highest for a medium dose of paclitaxel, which is supported by multi-electrode array (MEA) recordings. Furthermore, our findings using MEA reveal that Nav1.8 blocker A-803467 and delayed rectifier potassium enhancer L-alpha-phosphatidyl-D-myo-inositol 4,5-diphosphate, dioctanoyl (PIP2) can reduce paclitaxel-induced hyperexcitability of DRG neurons. Our approach can be readily extended and used to investigate various other contributors of hyperexcitability in CIPN.

Computational analysis of a 9D model for a small DRG neuron.

Small dorsal root ganglion (DRG) neurons are primary nociceptors which are responsible for sensing pain. Elucidation of their dynamics is essential for understanding and controlling pain. To this end, we present a numerical bifurcation analysis of a small DRG neuron model in this paper. The model is of Hodgkin-Huxley type and has 9 state variables. It consists of a Nav1.7 and a Nav1.8 sodium channel, a leak channel, a delayed rectifier potassium, and an A-type transient potassium channel. The dynamics of this model strongly depend on the maximal conductances of the voltage-gated ion channels and the external current, which can be adjusted experimentally. We show that the neuron dynamics are most sensitive to the Nav1.8 channel maximal conductance ([Formula: see text]). Numerical bifurcation analysis shows that depending on [Formula: see text] and the external current, different parameter regions can be identified with stable steady states, periodic firing of action potentials, mixed-mode oscillations (MMOs), and bistability between stable steady states and stable periodic firing of action potentials. We illustrate and discuss the transitions between these different regimes. We further analyze the behavior of MMOs. As the external current is decreased, we find that MMOs appear after a cyclic limit point. Within this region, bifurcation analysis shows a sequence of isolated periodic solution branches with one large action potential and a number of small amplitude peaks per period. For decreasing external current, the number of small amplitude peaks is increasing and the distance between the large amplitude action potentials is growing, finally tending to infinity and thereby leading to a stable steady state. A closer inspection reveals more complex concatenated MMOs in between these periodic MMO branches, forming Farey sequences. Lastly, we also find small solution windows with aperiodic oscillations which seem to be chaotic. The dynamical patterns found here-as consequences of bifurcation points regulated by different parameters-have potential translational significance as repetitive firing of action potentials imply pain of some form and intensity; manipulating these patterns by regulating the different parameters could aid in investigating pain dynamics.

Model-based approach for predicting the impact of genetic modifications on product yield in biopharmaceutical manufacturing-Application to influenza vaccine production.

A large group of biopharmaceuticals is produced in cell lines. The yield of such products can be increased by genetic engineering of the corresponding cell lines. The prediction of promising genetic modifications by mathematical modeling is a valuable tool to facilitate experimental screening. Besides information on the intracellular kinetics and genetic modifications the mathematical model has to account for ubiquitous cell-to-cell variability. In this contribution, we establish a novel model-based methodology for influenza vaccine production in cell lines with overexpressed genes. The manipulation of the expression level of genes coding for host cell factors relevant for virus replication is achieved by lentiviral transduction. Since lentiviral transduction causes increased cell-to-cell variability due to different copy numbers and integration sites of the gene constructs we use a population balance modeling approach to account for this heterogeneity in terms of intracellular viral components and distributed kinetic parameters. The latter are estimated from experimental data of intracellular viral RNA levels and virus titers of infection experiments using cells overexpressing a single host cell gene. For experiments with cells overexpressing multiple host cell genes, only final virus titers were measured and thus, no direct estimation of the parameter distributions was possible. Instead, we evaluate four different computational strategies to infer these from single gene parameter sets. Finally, the best computational strategy is used to predict the most promising candidates for future modifications that show the highest potential for an increased virus yield in a combinatorial study. As expected, there is a trend to higher yields the more modifications are included.

Global optimization of distillation columns using surrogate models.

Surrogate-based optimization of distillation columns using an iterative Kriging approach is investigated. Focus is on deterministic global optimization to avoid suboptimal local minima. The determination of optimal setups and operating conditions for ideal and non-ideal distillation columns, leading to mixed-integer nonlinear programming problems, serve as case studies. It is found that the optimization using the adapted Kriging approach yields similar results compared to the direct global optimization of the original problem in the ideal case, while it leads to a huge improvement compared to a multistart local optimization approach in the non-ideal case.

Distributed modeling of human influenza A virus-host cell interactions during vaccine production.

This contribution is concerned with population balance modeling of virus-host cell interactions during vaccine production. Replication of human influenza A virus in cultures of adherent Madin-Darby canine kidney (MDCK) cells is considered as a model system. The progress of infection can be characterized by the intracellular amount of viral nucleoprotein (NP) which is measured via flow cytometry. This allows the differentiation of the host cell population and gives rise to a distributed modeling approach. For this purpose a degree of fluorescence is introduced as an internal coordinate which is linearly linked to the intracellular amount of NP. Experimental results for different human influenza A subtypes reveal characteristic dynamic phenomena of the cell distribution like transient multimodality and reversal of propagation direction. The presented population balance model provides a reasonable explanation for these dynamic phenomena by the explicit consideration of different states of infection of individual cells. Kinetic parameters are determined from experimental data. To translate the emerging infinite dimensional parameter estimation problem to a finite dimension the parameters are assumed to depend linearly on the internal coordinate. As a result, the model is able to reproduce all characteristic dynamic phenomena of the considered process for the two examined virus strains and allows deeper insight into the underlying kinetic processes. Thus, the model is an important contribution to the understanding of the intracellular virus replication and virus spreading in cell cultures and can serve as a stepping stone for optimization in vaccine production.

Experimental validation of a new integrated simulated moving bed process for the production of single enantiomers.

A new integrated 3-zone simulated moving bed (SMB) concept with internal racemization reaction was suggested recently for the production of single enantiomers from racemic mixtures [1,2]. The process utilizes an internal gradient to trigger the racemization within a single zone. It can deliver the pure enantiomer and outperforms conventional technologies. In this contribution, the concept is validated experimentally for the separation of a model system compound. The results demonstrate that the new concept is capable of producing a single enantiomer with purity, yield and conversion of 100%.

Design of simulated moving bed processes under reduced purity requirements.

The design of simulated moving bed chromatography under reduced purity requirements is investigated. A parametric study indicates that all internal flow rates should be considered as free parameters in process design. This is confirmed by systematic numerical optimisations of two different design scenarios. A restrictive scenario requires complete regeneration of liquid and solid phases. In contrast, in a non-restrictive design all flow rates are optimised. The latter leads to significantly improved process performance. On the basis of the obtained observations, a simple design method for simulated moving bed processes with desired outlet purity values is derived from equilibrium theory.

Optimal operation of simulated moving bed chromatographic processes by means of simple feedback control.

In this contribution, simple methods are presented for controlling a simulated moving bed (SMB) chromatographic process with standard PI (proportional integral) controllers. The first method represents a simple and model-free inferential control scheme which was motivated from common distillation column control. The SMB unit is equipped with UV detectors. The UV signals in the four separation zones of the unit are fixed by four corresponding PI controllers calculating the ratio of liquid and solid flow in the respective separation zone. In order to be able to adjust the product purity a second, model-based control scheme is proposed. It makes use of the nonlinear wave propagation phenomena in the apparatus. The controlled chromatographic unit is automatically working with minimum solvent consumption and maximum feed throughput--without any numerical optimization calculations. This control algorithm can therefore also be applied for fast optimization of SMB processes.

Simulated moving bed process with cyclic modulation of the feed concentration.

The improvement of the simulated moving bed (SMB) process based on the introduction of a cyclic modulation of the feed concentration is described. It is demonstrated that such a feed concentration gradient during the shifting cycle can improve the performance significantly. The productivity and the product concentrations can be increased while simultaneously the solvent consumption can be decreased compared to the conventional SMB process with constant feed parameters.