Force generation in small ensembles of Brownian motors

The motility of certain gram-negative bacteria is mediated by retraction of type IV pili surface filaments, which are essential for infectivity. The retraction is powered by a strong molecular motor protein, PilT, producing very high forces that can exceed 150 pN. The molecular details of the motor mechanism are still largely unknown, while other features have been identified, such as the ring-shaped protein structure of the PilT motor. The surprisingly high forces generated by the PilT system motivate a model investigation of the generation of large forces in molecular motors. We propose a simple model, involving a small ensemble of motor subunits interacting through the deformations on a circular backbone with finite stiffness. The model describes the motor subunits in terms of diffusing particles in an asymmetric, time-dependent binding potential (flashing ratchet potential), roughly corresponding to the ATP hydrolysis cycle. We compute force-velocity relations in a subset of the parameter space and explore how the maximum force (stall force) is determined by stiffness, binding strength, ensemble size, and degree of asymmetry. We identify two qualitatively different regimes of operation depending on the relation between ensemble size and asymmetry. In the transition between these two regimes, the stall force depends nonlinearly on the number of motor subunits. Compared to its constituents without interactions, we find higher efficiency and qualitatively different force-velocity relations. The model captures several of the qualitative features obtained in experiments on pilus retraction forces, such as roughly constant velocity at low applied forces and insensitivity in the stall force to changes in the ATP concentration.Comment: RevTex 9 pages, 4 figures. Revised version, new subsections in Sec. III, removed typo

Input estimation for drug discovery using optimal control and Markov chain Monte Carlo approaches

Input estimation is employed in cases where it is desirable to recover the form of an input function which cannot be directly observed and for which there is no model for the generating process. In pharmacokinetic and pharmacodynamic modelling, input estimation in linear systems (deconvolution) is well established, while the nonlinear case is largely unexplored. In this paper, a rigorous definition of the input-estimation problem is given, and the choices involved in terms of modelling assumptions and estimation algorithms are discussed. In particular, the paper covers Maximum a Posteriori estimates using techniques from optimal control theory, and full Bayesian estimation using Markov Chain Monte Carlo (MCMC) approaches. These techniques are implemented using the optimisation software CasADi, and applied to two example problems: one where the oral absorption rate and bioavailability of the drug eflornithine are estimated using pharmacokinetic data from rats, and one where energy intake is estimated from body-mass measurements of mice exposed to monoclonal antibodies targeting the fibroblast growth factor receptor (FGFR) 1c. The results from the analysis are used to highlight the strengths and weaknesses of the methods used when applied to sparsely sampled data. The presented methods for optimal control are fast and robust, and can be recommended for use in drug discovery. The MCMC-based methods can have long running times and require more expertise from the user. The rigorous definition together with the illustrative examples and suggestions for software serve as a highly promising starting point for application of input-estimation methods to problems in drug discovery

A Prototype Decision Support Tool for Ballast Water Risk Management using a Combination of Hydrodynamic Models and Agent-Based Modelling

We report the development of a prototype Decision Support Tool (DST) for modelling the risks of spreading of non-indegenous invasive species via ballast water. The DST constitutes of two types of models: A 3D hydrodynamical model calculates the currents in the North Sea and Danish Straits, and an agent-based model estimates the dispersal of selected model organisms with the prevailing currents calculated by the 3D hydrodynamical model. The analysis is concluded by a post processing activity, where scenarios of dispersal are combined into an interim estimate of connectivity within the study area. The latter can be used as a tool for assessment of potential risk associated with intentional or unintentional discharges of ballast water. We discuss how this prototype DST can be used for ballast water risk management and outline other functions and uses, e.g. in regard to ecosystem-based management and the implementation of the EU Marine Strategy Framework Directive.https://commons.wmu.se/nsbwo/1001/thumbnail.jp

Electronic and Magnetic Structures of Sr2FeMoO6

We have investigated the electronic and magnetic structures of Sr2FeMoO6 employing site-specific direct probes, namely x-ray absorption spectroscopy with linearly and circularly polarized photons. In contrast to some previous suggestions, the results clearly establish that Fe is in the formal trivalent state in this compound. With the help of circularly polarized light, it is unambiguously shown that the moment at the Mo sites is below the limit of detection (< 0.25mu_B), resolving a previous controversy. We also show that the decrease of the observed moment in magnetization measurements from the theoretically expected value is driven by the presence of mis-site disorder between Fe and Mo sites.Comment: To appear in Physical Review Letter

Microscopic Origin of Quantum Chaos in Rotational Damping

The rotational spectrum of $^{168}$Yb is calculated diagonalizing different effective interactions within the basis of unperturbed rotational bands provided by the cranked shell model. A transition between order and chaos taking place in the energy region between 1 and 2 MeV above the yrast line is observed, associated with the onset of rotational damping. It can be related to the higher multipole components of the force acting among the unperturbed rotational bands.Comment: 7 pages, plain TEX, YITP/K-99

Transcriptional profiling of rat white adipose tissue response to 2,3,7,8-tetrachlorodibenzo-p-dioxin

Polychlorinated dibenzodioxins are environmental contaminants commonly produced as a by-product of industrial processes. The most potent of these, 2,3,7,8-tetrachlorodibenzo-rho-dioxin (TCDD), is highly lipophilic, leading to bioaccumulation. White adipose tissue (WAT) is a major site for energy storage, and is one of the organs in which TCDD accumulates. In laboratory animals, exposure to TCDD causes numerous metabolic abnormalities, including a wasting syndrome. We therefore investigated the molecular effects of TCDD exposure on WAT by profiling the transcriptomic response of WAT to 100 mu g/kg of TCDD at 1 or 4 days in TCDD-sensitive Long-Evans (Turku/AB; L-E) rats. A comparative analysis was conducted simultaneously in identically treated TCDD-resistant Han/Wistar (Kuopio; H/W) rats one day after exposure to the same dose. We sought to identify transcriptomic changes coinciding with the onset of toxicity, while gaining additional insight into later responses. More transcriptional responses to TCDD were observed at 4 days than at I day post-exposure, suggesting WAT shows mostly secondary responses. Two classic AHR-regulated genes, Cyp1a1 and Nqo1, were significantly induced by TCDD in both strains, while several genes involved in the immune response, including Ms4a7 and Fl1a1 were altered in L-E rats alone. We compared genes affected by TCDD in rat WAT and human adipose cells, and observed little overlap. Interestingly, very few genes involved in lipid metabolism exhibited altered expression levels despite the pronounced lipid mobilization from peripheral fat pads by TCDD in L-E rats. Of these genes, the lipolysis-associated Lpin1 was induced slightly over 2-fold in L-E rat WAT on day 4. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.Peer reviewe

Antimatter and Matter Production in Heavy Ion Collisions at CERN (The NEWMASS Experiment NA52)

Besides the dedicated search for strangelets NA52 measures light (anti)particle and (anti)nuclei production over a wide range of rapidity. Compared to previous runs the statistics has been increased in the 1998 run by more than one order of magnitude for negatively charged objects at different spectrometer rigidities. Together with previous data taking at a rigidity of -20 GeV/c we obtained 10^6 antiprotons 10^3 antideuterons and two antihelium3 without centrality requirements. We measured nuclei and antinuclei (p,d,antiprotons, antideuterons) near midrapidity covering an impact parameter range of b=2-12 fm. Our results strongly indicate that nuclei and antinuclei are mainly produced via the coalescence mechanism. However the centrality dependence of the antibaryon to baryon ratios show that antibaryons are diminished due to annihilation and breakup reactions in the hadron dense environment. The volume of the particle source extracted from coalescence models agrees with results from pion interferometry for an expanding source. The chemical and thermal freeze-out of nuclei and antinuclei appear to coincide with each other and with the thermal freeze-out of hadrons.Comment: 12 pages, 8 figures, to appear in the proceedings of the conference on 'Fundamental Issues in Elementary Matter' Bad Honnef, Germany, Sept. 25-29, 200

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

In this study, the ability to predict N-uptake in winter wheat crops using NIR-spectroscopy on soil samples was evaluated. Soil samples were taken in unfertilized plots in one winter wheat field during three years (1997-1999) and in another winter wheat field nearby in one year (2000). Soil samples were analyzed for organic C content and their NIR-spectra. N-uptake was measured as total N-content in aboveground plant materials at harvest. Models calibrated to predict N-uptake were internally cross validated and validated across years and across fields. Cross-validated calibrations predicted N-uptake with an average error of 12.1 to 15.4 kg N ha-1. The standard deviation divided by this error (RPD) ranged between 1.9 and 2.5. In comparison, the corresponding calibrations based on organic C alone had an error from 11.7 to 28.2 kg N ha-1 and RPDs from 1.3 to 2.5. In three of four annual calibrations within a field, the NIR-based calibrations worked better than the organic C based calibrations. The prediction of N-uptake across years, but within a field, worked slightly better with an organic C based calibration than with a NIR based one, RPD = 1.9 and 1.7 respectively. Across fields, the corresponding difference was large in favour of the NIR-calibration, RPD = 2.5 for the NIR-calibration and 1.5 for the organic C calibration. It was concluded that NIR-spectroscopy integrates information about organic C with other relevant soil components and therefore has a good potential to predict complex functions of soils such as N-mineralization. A relatively good agreement of spectral relationships to parameters related to the N-mineralization of datasets across the world suggests that more general models can be calibrated

IDOL regulates systemic energy balance through control of neuronal VLDLR expression.

Liver X receptors limit cellular lipid uptake by stimulating the transcription of Inducible Degrader of the LDL Receptor (IDOL), an E3 ubiquitin ligase that targets lipoprotein receptors for degradation. The function of IDOL in systemic metabolism is incompletely understood. Here we show that loss of IDOL in mice protects against the development of diet-induced obesity and metabolic dysfunction by altering food intake and thermogenesis. Unexpectedly, analysis of tissue-specific knockout mice revealed that IDOL affects energy balance, not through its actions in peripheral metabolic tissues (liver, adipose, endothelium, intestine, skeletal muscle), but by controlling lipoprotein receptor abundance in neurons. Single-cell RNA sequencing of the hypothalamus demonstrated that IDOL deletion altered gene expression linked to control of metabolism. Finally, we identify VLDLR rather than LDLR as the primary mediator of IDOL effects on energy balance. These studies identify a role for the neuronal IDOL-VLDLR pathway in metabolic homeostasis and diet-induced obesity