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Keywords
Primäre Ziele der Hydrolyse pflanzlicher nachwachsender Rohstoffe sind möglichst hohe Zuckerkonzentrationen für nachfolgende Fermentationen und eine Maximierung der Produktivität. Zur Optimierung dieser Prozesse wird Organosolv-aufgeschlossene Buchenholz-Cellulose verwendet. Die Hydrolyse des Faserstoffes erfolgt mithilfe von Novozymes CTec2-Enzymen. Die Hydrolysen konnten durch neue Rührerelemente auf einen Maßstab von 1000 L übertragen werden. Dabei konnten maximale Ausbeuten (g Glucose g –1 Glucose im Faserstoff) bis 81 g g – 1 und Konzentrationen von 152 g L –1 erreicht werden. Zurzeit können unter Einsatz eines Feststoffreaktors Cellulosefasern in einer Konzentration bis 400 g L –1 enzymatisch hydrolysiert werden. Die cellulolytischen Enzyme stoßen bei hohen Feststoffkonzentrationen an ihre Grenzen. Mit steigendem Feststoffgehalt nimmt die Hydrolyseausbeute ab. Ein Ansatz zur Steigerung der Effizienz ist der Einsatz ligninolytischer Enzyme, die Ligninreste an der Organosolv-Cellulose aufschließen können. Eine solche Verbesserung der Zugänglichkeit für cellulolytische Enzyme an ihr Substrat wurde durch Kulturüberstände verschiedener ligninolytischer Pilze erreicht. Mit Kulturüberständen von Stereum sp. sind Steigerungen der Glucoseausbeuten um bis zu 30 % möglich.
High gradient magnetic separation (HGMS) has been established since the early 1970s. A more recent application of these systems is the use in bioprocesses. To integrate the HGMS in a fermentation process, it is necessary to optimize the separation matrix with regard to the magnetic separation characteristics and permeability of the non-magnetizable components of the fermentation broth. As part of the work presented here, a combined fluidic and magnetic force finite element model simulation was created using the software COMSOL Multiphysics and compared with separation experiments. Finally, as optimal lattice orientation of the separation matrix, a transversal rhombohedral arrangement was defined. The high suitability of the new filter matrix has been verified by separation experiments.
Organisation
(2014)
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(2014)
The constitutive androstane receptor (CAR) and the pregnane X receptor (PXR) are closely related nuclear receptors involved in drug metabolism and play important roles in the mechanism of phenobarbital (PB)-induced rodent nongenotoxic hepatocarcinogenesis. Here, we have used a humanized CAR/PXR mouse model to examine potential species differences in receptor-dependent mechanisms underlying liver tissue molecular responses to PB. Early and late transcriptomic responses to sustained PB exposure were investigated in liver tissue from double knock-out CAR and PXR (CARᴷᴼ-PXRᴷᴼ), double humanized CAR and PXR (CARʰ-PXRʰ), and wild-type C57BL/6 mice. Wild-type and CARʰ-PXRʰ mouse livers exhibited temporally and quantitatively similar transcriptional responses during 91 days of PB exposure including the sustained induction of the xenobiotic response gene Cyp2b10, the Wnt signaling inhibitor Wisp1, and noncoding RNA biomarkers from the Dlk1-Dio3 locus. Transient induction of DNA replication (Hells, Mcm6, and Esco2) and mitotic genes (Ccnb2, Cdc20, and Cdk1) and the proliferation-related nuclear antigen Mki67 were observed with peak expression occurring between 1 and 7 days PB exposure. All these transcriptional responses were absent in CARᴷᴼ-PXRᴷᴼ mouse livers and largely reversible in wild-type and CARʰ-PXRʰ mouse livers following 91 days of PB exposure and a subsequent 4-week recovery period. Furthermore, PB-mediated upregulation of the noncoding RNA Meg3, which has recently been associated with cellular pluripotency, exhibited a similar dose response and perivenous hepatocyte-specific localization in both wild-type and CARʰ-PXRʰ mice. Thus, mouse livers coexpressing human CAR and PXR support both the xenobiotic metabolizing and the proliferative transcriptional responses following exposure to PB.
Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).
Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.
Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.