Functional Coupling of Slack Channels and P2X3 Receptors Contributes to Neuropathic Pain Processing

The sodium-activated potassium channel Slack (K_Na1.1, Slo2.2, or Kcnt1) is highly expressed in populations of sensory neurons, where it mediates the sodium-activated potassium current (I_KNa) and modulates neuronal activity. Previous studies suggest that Slack is involved in the processing of neuropathic pain. However, mechanisms underlying the regulation of Slack activity in this context are poorly understood. Using whole-cell patch-clamp recordings we found that Slack-mediated I_KNa in sensory neurons of mice is reduced after peripheral nerve injury, thereby contributing to neuropathic pain hypersensitivity. Interestingly, Slack is closely associated with ATP-sensitive P2X3 receptors in a population of sensory neurons. In vitro experiments revealed that Slack-mediated I_KNa may be bidirectionally modulated in response to P2X3 activation. Moreover, mice lacking Slack show altered nocifensive responses to P2X3 stimulation. Our study identifies P2X3/Slack signaling as a mechanism contributing to hypersensitivity after peripheral nerve injury and proposes a potential novel strategy for treatment of neuropathic pain.     

Droplet Entrainment Analysis in a Flash Evaporator with an Image-Based Measurement Technique

Local droplet sizes and volumes of entrained liquid are captured with an image-based measurement technique for comparison with a conventional, integral method for entrainment analysis. Experiments in a forced circulation flash evaporation were performed for different operating conditions and with two different chemical systems. Droplet size and frequency rise with an increase in thermal energy input. The local readings confirm the trends found by the integral measurement method. The modification of the image-based probe enables the detection of small (≈ 10 µm) and at the same time fast droplets under challenging operating conditions, such as vacuum and superheated feed similar to industrial process conditions.     

Thermoset IM-LSI-based C/C-SiC: Influence of flow direction and weld lines on microstructure and mechanical properties

The production of ceramic matrix composites (CMC) based on C/C-SiC is still very cost-intensive and therefore only economical for a few applications. The fabrication of the preforms involves many costs that need to be reduced. In this work, the shaping of the CFRP-preforms is realized by thermoset injection molding, which enables large-scale production. The polymeric matrix used is a multi-component matrix consisting of novolak resin, curing agent and lubricant. Six millimeter chopped carbon fiber with a proportion of 50 wt.% were used as a reinforcement. These ingredients are processed by an industrial equipment for compounding and injection molding in order to manufacture a CFRP demonstrator representing a brake disc. Test specimens are cut out of the demonstrator in different directions in order to investigate influences of flow direction and weld lines on microstructural and mechanical properties. Afterward, the CFRP samples were converted to C/C-SiC composites by the liquid silicon infiltration process. The article addresses the flow behavior of the compound during the injection molding and the building of the weld lines in the demonstrator. In addition, results of the directional dependence of the microstructural and mechanical properties within the fabricated disc in the different production steps are presented.     

Chemoenzymatic Total Synthesis of Sorbicatechol Structural Analogues and Evaluation of Their Antiviral Potential

Sorbicillinoids are fungal polyketides characterized by highly complex and diverse molecular structures, with considerable stereochemical intricacy combined with a high degree of oxygenation. Many sorbicillinoids possess promising biological activities. An interesting member of this natural product family is sorbicatechol A, which is reported to have antiviral activity, particularly against influenza A virus (H1N1). Through a straightforward, one-pot chemoenzymatic approach with recently developed oxidoreductase SorbC, the characteristic bicyclo[2.2.2]octane core of sorbicatechol is structurally diversified by variation of its natural 2-methoxyphenol substituent. This facilitates the preparation of a focused library of structural analogues bearing substituted aromatic systems, alkanes, heterocycles, and ethers. Fast access to this structural diversity provides an opportunity to explore the antiviral potential of the sorbicatechol family.     

Detection and analysis of triterpenic compounds in apple extracts

A new technique for the rapid detection and analysis of triterpenic compounds in apple extracts using HPLC was developed and validated. The main advantage of this technique is the short duration of the analysis – this makes this technique superior to others currently applied for the routine HPLC analysis of triterpenic compounds. The developed, optimized, and validated technique was used for the evaluation of triterpenic compounds in samples of different cultivars of apples, their peels, and flesh. In total, four triterpenic compounds were isolated and identified. Ursolic acid was the dominant compound in all the tested apple samples. The highest amounts of triterpenic compounds were detected in the peels of the ‘Lodel’ apple cultivar, and thus apples of this cultivar may be potentially useful for the isolation of individual compounds and the production of functional food and dietary supplements.     

Failed Neuroprotection of Combined Inhibition of L-Type and ASIC1a Calcium Channels with Nimodipine and Amiloride

Effective pharmacological neuroprotection is one of the most desired aims in modern medicine. We postulated that a combination of two clinically used drugs—nimodipine (L-Type voltage-gated calcium channel blocker) and amiloride (acid-sensing ion channel inhibitor)—might act synergistically in an experimental model of ischaemia, targeting the intracellular rise in calcium as a pathway in neuronal cell death. We used organotypic hippocampal slices of mice pups and a well-established regimen of oxygen-glucose deprivation (OGD) to assess a possible neuroprotective effect. Neither nimodipine (at 10 or 20 µM) alone or in combination with amiloride (at 100 µM) showed any amelioration. Dissolved at 2.0 Vol.% dimethyl-sulfoxide (DMSO), the combination of both components even increased cell damage (p = 0.0001), an effect not observed with amiloride alone. We conclude that neither amiloride nor nimodipine do offer neuroprotection in an in vitro ischaemia model. On a technical note, the use of DMSO should be carefully evaluated in neuroprotective experiments, since it possibly alters cell damage.     

Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows

Automatic synthesis of realistic gestures promises to transform the fields of animation, avatars and communicative agents. In off-line applications, novel tools can alter the role of an animator to that of a director, who provides only high-level input for the desired animation; a learned network then translates these instructions into an appropriate sequence of body poses. In interactive scenarios, systems for generating natural animations on the fly are key to achieving believable and relatable characters. In this paper we address some of the core issues towards these ends. By adapting a deep learning-based motion synthesis method called MoGlow, we propose a new generative model for generating state-of-the-art realistic speech-driven gesticulation. Owing to the probabilistic nature of the approach, our model can produce a battery of different, yet plausible, gestures given the same input speech signal. Just like humans, this gives a rich natural variation of motion. We additionally demonstrate the ability to exert directorial control over the output style, such as gesture level, speed, symmetry and spacial extent. Such control can be leveraged to convey a desired character personality or mood. We achieve all this without any manual annotation of the data. User studies evaluating upper-body gesticulation confirm that the generated motions are natural and well match the input speech. Our method scores above all prior systems and baselines on these measures, and comes close to the ratings of the original recorded motions. We furthermore find that we can accurately control gesticulation styles without unnecessarily compromising perceived naturalness. Finally, we also demonstrate an application of the same method to full-body gesticulation, including the synthesis of stepping motion and stance.     

Predicting the damage development in epoxy resins using an anisotropic damage model

For fiber-reinforced plastics, the strain-rate dependent response is governed by the matrix behavior. In this work, the Goldberg model is considered for the epoxy matrix constitutive material model. Moreover, the strain-rate dependency is achieved by direct influence on the elastic modulus, the inelastic strain, and the material strain to failure. In addition, an anisotropic damage response is implemented and extended through a strain-rate dependent definition. Since the constitutive model relies on nonphysical parameters, a parameter study is further performed. Additional numerical investigations using a micro-mechanical model are performed. Tension and shear loading conditions are evaluated and the influence of different strain rates is explored. Furthermore, the implemented anisotropic damage model is compared and discussed against an isotropic damage model.     

Technologies for Single-Cell Isolation

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.