Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L⁻¹). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.     

DNA analysis in hepatoblastoma by flow and image cytometry

BACKGROUND: In several types of tumors, including hepatocellular carcinoma, prognosis could be correlated with DNA ploidy. Few studies have been performed on hepatoblastoma with contradictory results. METHODS: Twenty-nine cases of nonpretreated hepatoblastoma were studied with flow cytometry and image cytometry for DNA index and proliferation index using paraffin-embedded tissue. RESULTS: Twenty-three (79.9%) tumors were diploid, and 6 (20.7%) were aneuploid (hyperdiploid). Patients with diploid tumors were younger than those with aneuploid tumors. With regard to stage, diploid tumors were almost equally distributed among stages (tumor, lymph node metastases, distant metastases), whereas aneuploid tumors tended to occur in higher stages (tumor, lymph node metastases, distant metastases). Diploid tumors had clearly a better prognosis than aneuploid tumors, although the difference was not statistically significant (flow cytometry, P = 0.06; image cytometry, P = 0.16). A more favorable prognosis was also noted for hepatoblastomas with low-proliferation index (< or = 7%), but the difference from tumors with high-proliferation index (> 7%) again was not statistically significant (P = 0.16). CONCLUSIONS: Although no statistically significant differences in prognosis between hepatoblastomas with diploid and aneuploid DNA content, respectively, were found, there is a clear tendency that diploid hepatoblastomas behave more favorably. The same is true for hepatoblastomas with low-proliferation index.     

Polycyclic Aromatic Hydrocarbons Activate the Aryl Hydrocarbon Receptor and the Constitutive Androstane Receptor to Regulate Xenobiotic Metabolism in Human Liver Cells

Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants produced by incomplete combustion of organic matter. They induce their own metabolism by upregulating xenobiotic-metabolizing enzymes such as cytochrome P450 monooxygenase 1A1 (CYP1A1) by activating the aryl hydrocarbon receptor (AHR). However, previous studies showed that individual PAHs may also interact with the constitutive androstane receptor (CAR). Here, we studied ten PAHs, different in carcinogenicity classification, for their potential to activate AHR- and CAR-dependent luciferase reporter genes in human liver cells. The majority of investigated PAHs activated AHR, while non-carcinogenic PAHs tended to activate CAR. We further characterized gene expression, protein abundancies and activities of the AHR targets CYP1A1 and 1A2, and the CAR target CYP2B6 in human HepaRG hepatoma cells. Enzyme induction patterns strongly resembled the profiles obtained at the receptor level, with AHR-activating PAHs inducing CYP1A1/1A2 and CAR-activating PAHs inducing CYP2B6. In summary, this study provides evidence that beside well-known activation of AHR, some PAHs also activate CAR, followed by subsequent expression of respective target genes. Furthermore, we found that an increased PAH ring number is associated with AHR activation as well as the induction of DNA double-strand breaks, whereas smaller PAHs activated CAR but showed no DNA-damaging potential.     

Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis

Without non-linear basis functions many problems can not be solved by linear algorithms. This article proposes a method to automatically construct such basis functions with slow feature analysis (SFA). Non-linear optimization of this unsupervised learning method generates an orthogonal basis on the unknown latent space for a given time series. In contrast to methods like PCA, SFA is thus well suited for techniques that make direct use of the latent space. Real-world time series can be complex, and current SFA algorithms are either not powerful enough or tend to over-fit. We make use of the kernel trick in combination with sparsification to develop a kernelized SFA algorithm which provides a powerful function class for large data sets. Sparsity is achieved by a novel matching pursuit approach that can be applied to other tasks as well. For small data sets, however, the kernel SFA approach leads to over-fitting and numerical instabilities. To enforce a stable solution, we introduce regularization to the SFA objective. We hypothesize that our algorithm generates a feature space that resembles a Fourier basis in the unknown space of latent variables underlying a given real-world time series. We evaluate this hypothesis at the example of a vowel classification task in comparison to sparse kernel PCA. Our results show excellent classification accuracy and demonstrate the superiority of kernel SFA over kernel PCA in encoding latent variables.     

A viability theory for digital businesses: Exploring the evolutionary changes of revenue mechanisms to support managerial decisions

The ongoing integration of Information Technology (IT) into various areas of our lives has led to a plethora of digital products and services. To survive competition in the long run, these offerings not only have to keep up with constant technological developments, but also have to adapt from a business point of view. Managers of these digital businesses have to especially focus on the design and evolution of their business’ revenue mechanisms to ensure the viability of their offerings. The related decisions are not trivial, as managers have to be aware of the relevant contextual factors and have to react quickly to changes in the environment. This paper proposes a viability theory for digital businesses described by 17 propositions that may guide managers in the design of revenue mechanisms and thereby support the evolution as well as the viability of a digital business.     

Development and Validation of an Artificial Mechanical Skin Model for the Study of Interactions between Skin and Microneedles

Microneedles are small needle‐like structures that are almost invisible to the naked eye. They have an immense potential to serve as a valuable tool in many medical applications, such as painless vaccination. Microneedles work by breaking through the stratum corneum, the outermost barrier layer of the skin, and providing a direct path for drug delivery into the skin. A lot of research has been presented over the past two decades on the applications of microneedles, yet the fundamental mechanism of how they interact, pressure, and penetrate the skin in its native state is worth examining further. As such, a major difficulty with understanding the mechanism of microneedle–skin interaction is the lack of an artificial mechanical human skin model to use as a standardized substrate. In this research news, the development of an artificial mechanical skin model based on a thorough mechanical study of fresh human and porcine skin samples is presented. The artificial mechanical skin model can be used to study the mechanical interactions between microneedles and skin, but not diffusion of molecules across skin. This model can assist in improving the performance of microneedles by enhancing the reproducibility of microneedle depth insertions for optimal drug delivery and biosensing.

     

Polymer/bioactive glass nanocomposites for biomedical applications: A review

Nanoscale bioactive glasses have been gaining attention due to their reported superior osteoconductivity when compared to conventional (micron-sized) bioactive glass materials. The combination of bioactive glass nanoparticles or nanofibers with polymeric systems enables the production of nanocomposites with potential to be used in a series of orthopedic applications, including scaffolds for tissue engineering and regenerative medicine. This review presents the state of art of the preparation of nanoscale bioactive glasses and corresponding composites with biocompatible polymers. The recent developments in the preparation methods of nano-sized bioactive glasses are reviewed, covering sol–gel routes, microemulsion techniques, gas phase synthesis method (flame spray synthesis), laser spinning, and electro-spinning. Then, examples of the preparation and properties of nanocomposites based on such inorganic bionanomaterials are presented, obtained using various polymer matrices, including polyesters such as poly(hydroxybutyrate), poly(lactic acid) and poly(caprolactone), and natural-based polymers such as polysaccharides (starch, chitin, chitosan) or proteins (silk fibroin, collagen). The physico-chemical, mechanical, and biological advantages of incorporating nanoscale bioactive glasses in such biodegradable nanocomposites are discussed and the possibilities to expand the use of these materials in other nanotechnology concepts aimed to be used in different biomedical applications are also highlighted.     

Metal injection molding of titanium for medical and aerospace applications

Mixing of titanium powder and thermoplastic binders creates a feedstock that is injection molded similar to plastic, has a chemical and thermal debinding process, and then is sintered to form a net-shape or near-net shape part. TiJet Medizintechnik GmbH (TiJet) developed and uses its own feedstock and powder processing technology to achieve desired mechanical properties. This paper explains the theory of the process and the possibilities that result from the development of this new powder processing technology, such as new alloys, design possibilities, etc. Discussed will be the microstructure, chemical composition, and mechanical properties of the manufactured parts.