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This study presents a numerical investigation of the dimerization of polyglutamine homo‐peptides of varying length. It employs the PRIME20 intermediate resolution protein model and studies it with a flat‐histogram type Monte Carlo simulation that gives access to the thermodynamic equilibrium of this model over the complete control parameter range (for the simulations this is temperature). For densities comparable to typical in vitro experimental conditions, this study finds that the aggregation and folding of the polyglutamine chains occur concurrently. However, as a function of chain length the sequence of establishment of intra‐ and intermolecular hydrogen bonding contacts changes. Chains longer than about N = 24 polyglutamine repeat units fold first and then aggregate. This agrees well with the experimental finding that, beyond N = 24 the single polyglutamine chain is the critical nucleus for the aggregation of amyloid fibrils. A finite size scaling of the ordering temperatures reveals that for this chain length (and longer chains) folding occurs at physiological (respectively larger) temperatures, whereas shorter chains are disordered at physiological conditions. [ABSTRACT FROM AUTHOR]

Process intensification has been widely used for many years in the mammalian biomanufacturing industry to increase productivity, agility and flexibility while reducing production costs. The most commonly used intensified processes are operated using a perfusion or fed‐batch seed bioreactor enabling a higher than usual seeding density in the fed‐batch production bioreactor. Hence, as part of the growth phase is shifted to the seed bioreactor, there is a lower split ratio, which increases the criticality of the seed bioreactor and could impact production performance. Therefore, such intensified processes should be designed and characterized for robust process scale‐up. This research work is focused on intensified processes with high seeding density inoculated from seed bioreactor in fed‐batch mode. The impact of the feeding strategy and specific power input (P/V) in the seed bioreactor and on the production step with two different cell lines (CL1 and CL2) producing two different monoclonal antibodies was investigated. Cell culture performance in the production bioreactor has been improved due to more stressful conditions for the cells in the seed bioreactor and the impact of the production bioreactor P/V on the production performance was limited. This is the first reported study highlighting a positive impact of cellular stress in seed bioreactors on intensified production bioreactor with the introduction of the "organized stress" concept. [ABSTRACT FROM AUTHOR]

Recent developments concerned with elucidating the semicrystalline structure formation in bulk polymer melts, with a focus on possibly important factors that have received less systematic attention, are reviewed. This includes the presence or absence of chain motion through the crystallites, which has a strong impact on the final crystallite thickness, and the effects of entanglements, which limit crystal growth and lower the crystallinity. From the theoretical side, interest is shown in shedding light on the thermodynamic driving forces of polymer crystallization, thus providing a theoretical background against which the kinetic limitations determine the resulting structures in experiments. [ABSTRACT FROM AUTHOR]

The anomalous Zeeman effect made it clear that charged particles like the electron possess a magnetic dipole moment. Classically, this could be understood if the charged particle possesses an eigenrotation, that is, spin. Within Nelson's stochastic mechanics, it was shown that the model of a rotating charged ball is able to reproduce the well‐known spin expectation values. This classically motivated model of intrinsic rotation described in terms of a stochastic process is revisited here within the formalism of stochastic optimal control theory. Quantum Hamilton equations (QHE) for spinning particles are derived, which reduce to their classical counterpart in the zero quantum noise limit. These equations enable the calculation of the common spin expectation values without the use of the wave function. They also offer information on the orientation dynamics of the magnetic moment of charged particles beyond the behavior of the spin averages. [ABSTRACT FROM AUTHOR]

ABSTRACT In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic traits characteristic of high-performance clones and enables informed decisions on which clones provide a good match for a particular process platform. The proposed approach also provides a mechanistic link between observed clone phenotype, process setup, and feeding regimes, and thereby offers concrete starting points for subsequent process optimization. Biotechnol. Bioeng. 2016;113: 2005-2019. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

We present state-of-the-art time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging with Bi primary ion clusters. The latest technological step pushes the lateral resolution into a region which has previously not been attained even by bombardment with mono-atomic primary beams. We show high lateral resolution TOF-SIMS images of line structures on certified reference samples and of real world samples. Moreover, we analyzed buried objects by prior removal of the covering material with the Bi cluster beam. Subsequent SIMS analysis of the vertical crater wall achieves a lateral resolution in the sub 50-nm range at a depth of about 20 µm. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]