Multilayered lipid membrane stacks for biocatalysis using membrane enzymes

Multilayered or stacked lipid membranes are a common principle in biology and have various functional advantages compared to single lipid membranes, such as their ability to spatially organize processes, compartmentalize molecules and greatly increase surface area and hence membrane protein concentration. Here we report on a supramolecular assembly of a multilayered lipid membrane system in which poly-L-lysine electrostatically links negatively charged lipid membranes. When suitable membrane enzymes are incorporated, either an ubiquinol oxidase (cytochrome bo3 from Escherichia coli) or an oxygen tolerant hydrogenase (the membrane-bound hydrogenase from Ralstonia eutropha), cyclic voltammetry (CV) reveals a linear increase in biocatalytic activity with each additional membrane layer. Electron transfer between the enzymes and the electrode is mediated by the quinone pool that is present in the lipid phase. We deduce by atomic force microscopy, CV and fluorescence microscopy that quinones are able to diffuse between the stacked lipid membrane layers via defect sites where the lipid membranes are interconnected. This assembly is akin to that of interconnected thylakoid membranes or the folded lamella of mitochondria and have significant potential for mimicry in biotechnology applications such as energy production or biosensing

Current Profiles of Molecular Nanowires; DFT Green Function Representation

The Liouville-space Green function formalism is used to compute the current density profile across a single molecule attached to electrodes. Time ordering is maintained in real, physical, time, avoiding the use of artificial time loops and backward propagations. Closed expressions for molecular currents, which only require DFT calculations for the isolated molecule, are derived to fourth order in the molecule/electrode coupling.Comment: 21 page

Knot Theory: from Fox 3-colorings of links to Yang-Baxter homology and Khovanov homology

This paper is an extended account of my "Introductory Plenary talk at Knots in Hellas 2016" conference We start from the short introduction to Knot Theory from the historical perspective, starting from Heraclas text (the first century AD), mentioning R.Llull (1232-1315), A.Kircher (1602-1680), Leibniz idea of Geometria Situs (1679), and J.B.Listing (student of Gauss) work of 1847. We spend some space on Ralph H. Fox (1913-1973) elementary introduction to diagram colorings (1956). In the second section we describe how Fox work was generalized to distributive colorings (racks and quandles) and eventually in the work of Jones and Turaev to link invariants via Yang-Baxter operators, here the importance of statistical mechanics to topology will be mentioned. Finally we describe recent developments which started with Mikhail Khovanov work on categorification of the Jones polynomial. By analogy to Khovanov homology we build homology of distributive structures (including homology of Fox colorings) and generalize it to homology of Yang-Baxter operators. We speculate, with supporting evidence, on co-cycle invariants of knots coming from Yang-Baxter homology. Here the work of Fenn-Rourke-Sanderson (geometric realization of pre-cubic sets of link diagrams) and Carter-Kamada-Saito (co-cycle invariants of links) will be discussed and expanded. Dedicated to Lou Kauffman for his 70th birthday.Comment: 35 pages, 31 figures, for Knots in Hellas II Proceedings, Springer, part of the series Proceedings in Mathematics & Statistics (PROMS

Power Spectra for Cold Dark Matter and its Variants

The bulk of recent cosmological research has focused on the adiabatic cold dark matter model and its simple extensions. Here we present an accurate fitting formula that describes the matter transfer functions of all common variants, including mixed dark matter models. The result is a function of wavenumber, time, and six cosmological parameters: the massive neutrino density, number of neutrino species degenerate in mass, baryon density, Hubble constant, cosmological constant, and spatial curvature. We show how observational constraints---e.g. the shape of the power spectrum, the abundance of clusters and damped Lyman-alpha systems, and the properties of the Lyman-alpha forest--- can be extended to a wide range of cosmologies, including variations in the neutrino and baryon fractions in both high-density and low-density universes.Comment: 20 pages, LaTeX, 4 figures. Submitted to ApJ. Electronic versions of the fitting formula, as well as simple codes to output cosmological quantities (e.g. sigma_8) as a function of parameters and illustrative animations of parameter dependence, are available at http://www.sns.ias.edu/~whu/transfer/transfer.htm

Syntactic Markovian Bisimulation for Chemical Reaction Networks

In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially large state spaces. This makes the analysis very difficult in practice and represents the major bottleneck for the applicability of minimization techniques based, for instance, on lumpability. In this paper we present syntactic Markovian bisimulation (SMB), a notion of bisimulation developed in the Larsen-Skou style of probabilistic bisimulation, defined over the structure of a CRN rather than over its underlying CTMC. SMB identifies a lumpable partition of the CTMC state space a priori, in the sense that it is an equivalence relation over species implying that two CTMC states are lumpable when they are invariant with respect to the total population of species within the same equivalence class. We develop an efficient partition-refinement algorithm which computes the largest SMB of a CRN in polynomial time in the number of species and reactions. We also provide an algorithm for obtaining a quotient network from an SMB that induces the lumped CTMC directly, thus avoiding the generation of the state space of the original CRN altogether. In practice, we show that SMB allows significant reductions in a number of models from the literature. Finally, we study SMB with respect to the deterministic semantics of CRNs based on ordinary differential equations (ODEs), where each equation gives the time-course evolution of the concentration of a species. SMB implies forward CRN bisimulation, a recently developed behavioral notion of equivalence for the ODE semantics, in an analogous sense: it yields a smaller ODE system that keeps track of the sums of the solutions for equivalent species.Comment: Extended version (with proofs), of the corresponding paper published at KimFest 2017 (http://kimfest.cs.aau.dk/

Bio-inspired Attentive Segmentation of Retinal OCT Imaging

Albeit optical coherence imaging (OCT) is widely used to assess ophthalmic pathologies, localization of intra-retinal boundaries suffers from erroneous segmentations due to image artifacts or topological abnormalities. Although deep learning-based methods have been effectively applied in OCT imaging, accurate automated layer segmentation remains a challenging task, with the flexibility and precision of most methods being highly constrained. In this paper, we propose a novel method to segment all retinal layers, tailored to the bio-topological OCT geometry. In addition to traditional learning of shift-invariant features, our method learns in selected pixels horizontally and vertically, exploiting the orientation of the extracted features. In this way, the most discriminative retinal features are generated in a robust manner, while long-range pixel dependencies across spatial locations are efficiently captured. To validate the effectiveness and generalisation of our method, we implement three sets of networks based on different backbone models. Results on three independent studies show that our methodology consistently produces more accurate segmentations than state-of-the-art networks, and shows better precision and agreement with ground truth. Thus, our method not only improves segmentation, but also enhances the statistical power of clinical trials with layer thickness change outcomes

Prospects for K+→π+ννˉK^+ \to \pi^+ \nu \bar{ \nu } at CERN in NA62

The NA62 experiment will begin taking data in 2015. Its primary purpose is a 10% measurement of the branching ratio of the ultrarare kaon decay $K^+ \to \pi^+ \nu \bar{ \nu }$, using the decay in flight of kaons in an unseparated beam with momentum 75 GeV/c.The detector and analysis technique are described here.Comment: 8 pages for proceedings of 50 Years of CP

Variable pulmonary manifestations in Chitayat syndrome: Six additional affected individuals

Hand hyperphalangism leading to shortened index fingers with ulnar deviation, hallux valgus, mild facial dysmorphism and respiratory compromise requiring assisted ventilation are the key features of Chitayat syndrome. This condition results from the recurrent heterozygous missense variant NM_006494.2:c.266A>G; p.(Tyr89Cys) in ERF on chromosome 19q13.2, encoding the ETS2 repressor factor (ERF) protein. The pathomechanism of Chitayat syndrome is unknown. To date, seven individuals with Chitayat syndrome and the recurrent pathogenic ERF variant have been reported in the literature. Here, we describe six additional individuals, among them only one presenting with a history of assisted ventilation, and the remaining presenting with variable pulmonary phenotypes, including one individual without any obvious pulmonary manifestations. Our findings widen the phenotype spectrum caused by the recurrent pathogenic variant in ERF, underline Chitayat syndrome as a cause of isolated skeletal malformations and therefore contribute to the improvement of diagnostic strategies in individuals with hand hyperphalangism

Action Without Awareness: Reaching to an Object You Do Not Remember Seeing

BACKGROUND: Previous work by our group has shown that the scaling of reach trajectories to target size is independent of obligatory awareness of that target property and that "action without awareness" can persist for up to 2000 ms of visual delay. In the present investigation we sought to determine if the ability to scale reaching trajectories to target size following a delay is related to the pre-computing of movement parameters during initial stimulus presentation or the maintenance of a sensory (i.e., visual) representation for on-demand response parameterization. METHODOLOGY/PRINCIPAL FINDINGS: Participants completed immediate or delayed (i.e., 2000 ms) perceptual reports and reaching responses to different sized targets under non-masked and masked target conditions. For the reaching task, the limb associated with a trial (i.e., left or right) was not specified until the time of response cuing: a manipulation that prevented participants from pre-computing the effector-related parameters of their response. In terms of the immediate and delayed perceptual tasks, target size was accurately reported during non-masked trials; however, for masked trials only a chance level of accuracy was observed. For the immediate and delayed reaching tasks, movement time as well as other temporal kinematic measures (e.g., times to peak acceleration, velocity and deceleration) increased in relation to decreasing target size across non-masked and masked trials. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that speed-accuracy relations were observed regardless of whether participants were aware (i.e., non-masked trials) or unaware (i.e., masked trials) of target size. Moreover, the equivalent scaling of immediate and delayed reaches during masked trials indicates that a persistent sensory-based representation supports the unconscious and metrical scaling of memory-guided reaching

Correction: Zika virus-derived e-diii protein displayed on immunologically optimized vlps induces neutralizing antibodies without causing enhancement of dengue virus infection. vaccines 2019, 7, 72

The authors wish to make the following correction to their paper [1]. The same image was mistakenly selected for Figures 2 and 3. The image became replaced as you see in Figure 3 below