Microbial Production of Short Chain Fatty Acids from Lignocellulosic Biomass:Current Processes and Market

Biological production of organic acids from conversion of biomass derivatives has received increased attention among scientists and engineers and in business because of the attractive properties such as renewability, sustainability, degradability, and versatility. The aim of the present review is to summarize recent research and development of short chain fatty acids production by anaerobic fermentation of nonfood biomass and to evaluate the status and outlook for a sustainable industrial production of such biochemicals. Volatile fatty acids (VFAs) such as acetic acid, propionic acid, and butyric acid have many industrial applications and are currently of global economic interest. The focus is mainly on the utilization of pretreated lignocellulosic plant biomass as substrate (the carbohydrate route) and development of the bacteria and processes that lead to a high and economically feasible production of VFA. The current and developing market for VFA is analyzed focusing on production, prices, and forecasts along with a presentation of the biotechnology companies operating in the market for sustainable biochemicals. Finally, perspectives on taking sustainable product of biochemicals from promise to market introduction are reviewed

Fundamental aspects of cardiovascular regulation in predisposition to atrial fibrillation

Background: Atrial fibrillation is the most common sustained arrhythmia in cardiology. The structural factors leading to atrial fibrillation are well known, but there should be also regarded the functional factors. In 2014, the Task Force published guidelines for atrial fibrillation describing the importance of the vegetative nervous system in creating predisposition to atrial fibrillation although it describes that the mechanism is not completely clear. Furthermore, it is important to understand this mechanism, regarding the increasing number of patients affected by atrial fibrillation without any structural heart diseases. The aim of this work is to understand the physiological background of the predisposition to the appearance and recurrence of atrial fibrillation regarding the role of neural regulatory systems of the heart, especially when no structural heart diseases are present. Therefore, the following is a fundamental analysis of the neural regulation of heart rhythm, including the vegetative nervous system at its medullar and central levels and also the cerebral cortex input in heart regulation. Conclusions: The predisposition to atrial fibrillation regarding the neural regulatory systems of the heart can be pinpointed to three key factors: 1. Central over-activity; 2. Sympathetic efferent overflow towards the heart in rest state; 3. Parasympathetic exhaustion and break-down of the parasymphatetic protective function

New approach to heart rate variability analysis based on cardiophysiological biomarkers

Background: The heart rate variability (HRV) analysis is a well-known method demonstrating its value over the years in different medical fields. However, it still has its known limitations. Material and methods: The new approach to HRV analysis is based on a complementary HRV standard analysis with new cardiophysiological biomarkers. The biomarkers are assessed on cardiorhythmograms obtained by a 5-minute ECG recording using a specialized hardware (Polyspectrum-HRV-device, Neurosoft). Results: A possible applicative value of the biomarkers is shown on examples of how a prognosis for recurrence of atrial fibrillation (AFib) could be made. When in a rest-state cardiorhythmogram are observed LF drops and are followed by a pathological counterregulation, prognostically, recurrence of atrial fibrillation is expected. When in a cardiorhythmogram LF drops are observed and are followed by a physiological counterregulation, prognostically, sinus rhythm is expected. Physiological background of the biomarkers: increased central modulation of the heart in rest state of a patient, a sympathetic overflow of the heart in calm state and insufficiency of compensatory parasymphatetic counteractivation. Limitations of the paper: this is a methodological paper without description of patients. This paper will be followed by a clinical paper in which we are going to describe the validation of these cardiophysiological biomarkers on patients with AFib. Conclusions: Complementary to the standard HRV analysis, cardiophysiological biomarkers should be assessed: LF drops and HF counterregulation could be used for prognosis construction in cardiology

Closed-loop auditory stimulation method to modulate sleep slow waves and motor learning performance in rats

Slow waves and cognitive output have been modulated in humans by phase-targeted auditory stimulation. However, to advance its technical development and further our understanding, implementation of the method in animal models is indispensable. Here, we report the successful employment of slow waves’ phase-targeted closed-loop auditory stimulation (CLAS) in rats. To validate this new tool both conceptually and functionally, we tested the effects of up- and down-phase CLAS on proportions and spectral characteristics of sleep, and on learning performance in the single-pellet reaching task, respectively. Without affecting 24 hr sleep-wake behavior, CLAS specifically altered delta (slow waves) and sigma (sleep spindles) power persistently over chronic periods of stimulation. While up-phase CLAS does not elicit a significant change in behavioral performance, down-phase CLAS exerted a detrimental effect on overall engagement and success rate in the behavioral test. Overall CLAS-dependent spectral changes were positively correlated with learning performance. Altogether, our results provide proof-of-principle evidence that phase-targeted CLAS of slow waves in rodents is efficient, safe, and stable over chronic experimental periods, enabling the use of this high-specificity tool for basic and preclinical translational sleep research.Fil: Moreira, Carlos G. Universitat Zurich; SuizaFil: Baumann, Christian R.. Universitat Zurich; Suiza. Neuroscience Center Zurich; SuizaFil: Scandella, Maurizio. Universitat Zurich; SuizaFil: Nemirovsky, Sergio Ivan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Leach, Sven. University Children's Hospital Zurich; SuizaFil: Huber, Reto. University Children's Hospital Zurich; Suiza. Universitat Zurich; SuizaFil: Noain, Daniela Maria Clara. University Hospital Zurich; Suiza. Universitat Zurich; Suiz

Unitary Positive-Energy Representations of Scalar Bilocal Quantum Fields

The superselection sectors of two classes of scalar bilocal quantum fields in D>=4 dimensions are explicitly determined by working out the constraints imposed by unitarity. The resulting classification in terms of the dual of the respective gauge groups U(N) and O(N) confirms the expectations based on general results obtained in the framework of local nets in algebraic quantum field theory, but the approach using standard Lie algebra methods rather than abstract duality theory is complementary. The result indicates that one does not lose interesting models if one postulates the absence of scalar fields of dimension D-2 in models with global conformal invariance. Another remarkable outcome is the observation that, with an appropriate choice of the Hamiltonian, a Lie algebra embedded into the associative algebra of observables completely fixes the representation theory.Comment: 27 pages, v3: result improved by eliminating redundant assumptio

Supervised Learning in SNN via Reward-Modulated Spike-Timing-Dependent Plasticity for a Target Reaching Vehicle

Spiking neural networks (SNNs) offer many advantages over traditional artificial neural networks (ANNs) such as biological plausibility, fast information processing, and energy efficiency. Although SNNs have been used to solve a variety of control tasks using the Spike-Timing-Dependent Plasticity (STDP) learning rule, existing solutions usually involve hard-coded network architectures solving specific tasks rather than solving different kinds of tasks generally. This results in neglecting one of the biggest advantages of ANNs, i.e., being general-purpose and easy-to-use due to their simple network architecture, which usually consists of an input layer, one or multiple hidden layers and an output layer. This paper addresses the problem by introducing an end-to-end learning approach of spiking neural networks constructed with one hidden layer and reward-modulated Spike-Timing-Dependent Plasticity (R-STDP) synapses in an all-to-all fashion. We use the supervised reward-modulated Spike-Timing-Dependent-Plasticity learning rule to train two different SNN-based sub-controllers to replicate a desired obstacle avoiding and goal approaching behavior, provided by pre-generated datasets. Together they make up a target-reaching controller, which is used to control a simulated mobile robot to reach a target area while avoiding obstacles in its path. We demonstrate the performance and effectiveness of our trained SNNs to achieve target reaching tasks in different unknown scenarios

Large non-Gaussian Halo Bias from Single Field Inflation

We calculate Large Scale Structure observables for non-Gaussianity arising from non-Bunch-Davies initial states in single field inflation. These scenarios can have substantial primordial non-Gaussianity from squeezed (but observable) momentum configurations. They generate a term in the halo bias that may be more strongly scale-dependent than the contribution from the local ansatz. We also discuss theoretical considerations required to generate an observable signature.Comment: 30 pages, 14 figures, typos corrected and minor changes to match published version JCAP09(2012)00

The Evolution of Fangs, Venom, and Mimicry Systems in Blenny Fishes

Venom systems have evolved on multiple occasions across the animal kingdom, and they can act as key adaptations to protect animals from predators. Consequently, venomous animals serve as models for a rich source of mimicry types, as non-venomous species benefit from reductions in predation risk by mimicking the coloration, body shape, and/or movement of toxic counterparts. The frequent evolution of such deceitful imitations provides notable examples of phenotypic convergence and are often invoked as classic exemplars of evolution by natural selection. Here, we investigate the evolution of fangs, venom, and mimetic relationships in reef fishes from the tribe Nemophini (fangblennies). Comparative morphological analyses reveal that enlarged canine teeth (fangs) originated at the base of the Nemophini radiation and have enabled a micropredatory feeding strategy in non-venomous Plagiotremus spp. Subsequently, the evolution of deep anterior grooves and their coupling to venom secretory tissue provide Meiacanthus spp. with toxic venom that they effectively employ for defense. We find that fangblenny venom contains a number of toxic components that have been independently recruited into other animal venoms, some of which cause toxicity via interactions with opioid receptors, and result in a multifunctional biochemical phenotype that exerts potent hypotensive effects. The evolution of fangblenny venom has seemingly led to phenotypic convergence via the formation of a diverse array of mimetic relationships that provide protective (Batesian mimicry) and predatory (aggressive mimicry) benefits to other fishes. Our results further our understanding of how novel morphological and biochemical adaptations stimulate ecological interactions in the natural world

Anisotropic flow of charged hadrons, pions and (anti-)protons measured at high transverse momentum in Pb-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}}=2.76 TeV

The elliptic, $v_2$, triangular, $v_3$, and quadrangular, $v_4$, azimuthal anisotropic flow coefficients are measured for unidentified charged particles, pions and (anti-)protons in Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV with the ALICE detector at the Large Hadron Collider. Results obtained with the event plane and four-particle cumulant methods are reported for the pseudo-rapidity range $|\eta|<0.8$ at different collision centralities and as a function of transverse momentum, $p_{\rm T}$, out to $p_{\rm T}=20$ GeV/$c$. The observed non-zero elliptic and triangular flow depends only weakly on transverse momentum for $p_{\rm T}>8$ GeV/$c$. The small $p_{\rm T}$ dependence of the difference between elliptic flow results obtained from the event plane and four-particle cumulant methods suggests a common origin of flow fluctuations up to $p_{\rm T}=8$ GeV/$c$. The magnitude of the (anti-)proton elliptic and triangular flow is larger than that of pions out to at least $p_{\rm T}=8$ GeV/$c$ indicating that the particle type dependence persists out to high $p_{\rm T}$.Comment: 16 pages, 5 captioned figures, authors from page 11, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/186