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Objectives: The aim of the present study was to characterize the cellular reaction to a xenogeneic resorbable collagen membrane of porcine origin using a subcutaneous implantation model in Wistar rats over 30 days.
Materials and methods: Ex vivo, liquid platelet-rich fibrin (PRF), a leukocyte and platelet-rich cell suspension, was used to evaluate the blood cell membrane interaction. The material was implanted subcutaneously in rats. Sham-operated rats without biomaterial displayed physiological wound healing (control group). Histological, immunohistological, and histomorphometric analyses were focused on the inflammatory pattern, vascularization rate, and degradation pattern.
Results: The membrane induced a large number of mononuclear cells over the observation period, including lymphocytes, macrophages, and fibroblasts. After 15 days, multinucleated giant cells (MNGCs) were observed on the biomaterial surface. Their number increased significantly, and they proceeded to the center of the biomaterial on day 30. These cells highly expressed CD-68, calcitonin receptor, and MMP-9, but not TRAP or integrin-ß3. Thus, the membrane lost its integrity and underwent disintegration as a consequence of the induction of MNGCs. The significant increase in MNGC number correlated with a high rate of vascularization, which was significantly higher than the control group. Physiological wound healing in the control group did not induce any MNGCs at any time point. Ex vivo blood cells from liquid-PRF did not penetrate the membrane.
Conclusion: The present study suggests a potential role for MNGCs in biomaterial degradation and questions whether it is beneficial to accept them in clinically approved biomaterials or focus on biomaterials that induce only mononuclear cells. Thus, further studies are necessary to identify the function of biomaterial-induced MNGCs.
Clinical relevance: Understanding the cellular reaction to biomaterials is essential to assess their suitability for specific clinical indications and outline the potential benefit of specific group of biomaterials in the respective clinical indications.
Combining market data with a publicly available monthly snapshot of Deutsche Börse’s index ranking list, I create a model that predicts index changes in the DAX, MDAX, SDAX, and TecDAX from 2010 to 2019 before they are officially announced. Even though I empirically show that index changes are predictable, they still earn sizeable post-announcement 1-day abnormal returns up to 1.42% and − 1.54% for promotions and demotions, respectively. While abnormal returns are larger in smaller stocks, I find no evidence that they are related to funding constraints or additional risk for trading on wrong predictions. A trading strategy that trades according to my model yields an annualized Sharpe ratio of 0.83 while being invested for just 4 days a year.
Disordered proteins and nucleic acids can condense into droplets that resemble the membraneless organelles observed in living cells. MD simulations offer a unique tool to characterize the molecular interactions governing the formation of these biomolecular condensates, their physicochemical properties, and the factors controlling their composition and size. However, biopolymer condensation depends sensitively on the balance between different energetic and entropic contributions. Here, we develop a general strategy to fine-tune the potential energy function for molecular dynamics simulations of biopolymer phase separation. We rebalance protein–protein interactions against solvation and entropic contributions to match the excess free energy of transferring proteins between dilute solution and condensate. We illustrate this formalism by simulating liquid droplet formation of the FUS low-complexity domain (LCD) with a rebalanced MARTINI model. By scaling the strength of the nonbonded interactions in the coarse-grained MARTINI potential energy function, we map out a phase diagram in the plane of protein concentration and interaction strength. Above a critical scaling factor of αc ≈ 0.6, FUS-LCD condensation is observed, where α = 1 and 0 correspond to full and repulsive interactions in the MARTINI model. For a scaling factor α = 0.65, we recover experimental densities of the dilute and dense phases, and thus the excess protein transfer free energy into the droplet and the saturation concentration where FUS-LCD condenses. In the region of phase separation, we simulate FUS-LCD droplets of four different sizes in stable equilibrium with the dilute phase and slabs of condensed FUS-LCD for tens of microseconds, and over one millisecond in aggregate. We determine surface tensions in the range of 0.01–0.4 mN/m from the fluctuations of the droplet shape and from the capillary-wave-like broadening of the interface between the two phases. From the dynamics of the protein end-to-end distance, we estimate shear viscosities from 0.001 to 0.02 Pa s for the FUS-LCD droplets with scaling factors α in the range of 0.625–0.75, where we observe liquid droplets. Significant hydration of the interior of the droplets keeps the proteins mobile and the droplets fluid.
This paper defends The Transformation of Values into Prices on the Basis of Random Systems, published in EIER, by answering to the Comments made in the same journal by Professors Mori, Morioka and Yamazaki. The clarifications mainly concern the justification of the randomness assumptions, the conditions needed to obtain the equality of total profit with total surplus value in the simplified one-industry system and the invariance of the results to changes in the units of measurement.
Single-particle electron cryo-microscopy (cryoEM) has undergone a `resolution revolution' that makes it possible to characterize megadalton (MDa) complexes at atomic resolution without crystals. To fully exploit the new opportunities in molecular microscopy, new procedures for the cloning, expression and purification of macromolecular complexes need to be explored. Macromolecular assemblies are often unstable, and invasive construct design or inadequate purification conditions and sample-preparation methods can result in disassembly or denaturation. The structure of the 2.6 MDa yeast fatty acid synthase (FAS) has been studied by electron microscopy since the 1960s. Here, a new, streamlined protocol for the rapid production of purified yeast FAS for structure determination by high-resolution cryoEM is reported. Together with a companion protocol for preparing cryoEM specimens on a hydrophilized graphene layer, the new protocol yielded a 3.1 Å resolution map of yeast FAS from 15 000 automatically picked particles within a day. The high map quality enabled a complete atomic model of an intact fungal FAS to be built.
Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction
(2020)
Class I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in the Drosophila larval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive, in vivo time-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of stochastic growth and retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure–function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites.
The 𝒮-cone provides a common framework for cones of polynomials or exponen- tial sums which establish non-negativity upon the arithmetic-geometric inequality, in particular for sums of non-negative circuit polynomials (SONC) or sums of arithmetic- geometric exponentials (SAGE). In this paper, we study the S-cone and its dual from the viewpoint of second-order representability. Extending results of Averkov and of Wang and Magron on the primal SONC cone, we provide explicit generalized second- order descriptions for rational S-cones and their duals.
The aim of this study is to provide a systematic assessment of the influence of the position on the arterial input function (AIF) for perfusion quantification. In 39 patients with a wide range of left ventricular function the AIF was determined using a diluted contrast bolus of a cardiac magnetic resonance imaging in three left ventricular levels (basal, mid, apex) as well as aortic sinus (AoS). Time to peak signal intensities, baseline corrected peak signal intensity and upslopes were determined and compared to those obtained in the AoS. The error induced by sampling the AIF in a position different to the AoS was determined by Fermi deconvolution. The time to peak signal intensity was strongly correlated (r2 > 0.9) for all positions with a systematic earlier arrival in the basal (− 2153 ± 818 ms), the mid (− 1429 ± 928 ms) and the apical slice (− 450 ± 739 ms) relative to the AoS (all p < 0.001). Peak signal intensity as well as upslopes were strongly correlated (r2 > 0.9 for both) for all positions with a systematic overestimation in all positions relative to the AoS (all p < 0.001 and all p < 0.05). Differences between the positions were more pronounced for patients with reduced ejection fraction. The error of averaged MBF quantification was 8%, 13% and 27% for the base, mid and apex. The location of the AIF significantly influences core parameters for perfusion quantification with a systematic and ejection fraction dependent error. Full quantification should be based on obtaining the AIF as close as possible to the myocardium to minimize these errors.
We introduce a novel approach based on elas- tic and inelastic scattering rates to extract the hyper-surface of the chemical freeze-out from a hadronic transport model in the energy range from Elab = 1.23 AGeV to √sNN = 62.4 GeV. For this study, the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) model combined with a coarse-graining method is employed. The chemical freeze- out distribution is reconstructed from the pions through sev- eral decay and re-formation chains involving resonances and taking into account inelastic, pseudo-elastic and string excita- tion reactions. The extracted average temperature and baryon chemical potential are then compared to statistical model analysis. Finally we investigate various freeze-out criteria suggested in the literature. We confirm within this micro- scopic dynamical simulation, that the chemical freeze-out at all energies coincides with ⟨E⟩/⟨N⟩ ≈ 1 GeV, while other criteria, like s/T 3 = 7 and nB +nB ̄ ≈ 0.12 fm−3 are limited to higher collision energies.
The production of light (anti-)nuclei and (anti-)hypernuclei in ultra-relativistic heavy-ion collisions, but also in more elementary collisions as proton–proton and proton–nucleus collisions, became recently a focus of interest. In particular, the fact that these objects are all loosely bound compared to the temperature and energies, e.g. the kinetic energies involved, is often stressed out to be special for their production. The binding energies of these (anti-)nuclei is between 130 keV (Λ separation energy in the hypertriton) and about 8 MeV per nucleon. Whereas the connected temperatures are of the order of 100 to 160 MeV. This lead to some difficulties in the interpretation of the usually discussed production models, i.e. coalescence and statistical-thermal models, as will be discussed here. In this brief review we discuss selected highlights of the production of light (anti-)nuclei, such as (anti-)deuteron, (anti-)helium and (anti-)alpha nuclei. In addition, we will discuss the current status of the highly debated lifetime of the (anti-)hypertriton and connected measurements and model results.