Sulfo-SMCC Prevents Annealing of Taxol-Stabilized Microtubules In Vitro

Microtubule structure and functions have been widely studied in vitro and in cells. Research has shown that cysteines on tubulin play a crucial role in the polymerization of microtubules. Here, we show that blocking sulfhydryl groups of cysteines in taxol-stabilized polymerized microtubules with a commonly used chemical crosslinker prevents temporal end-to-end annealing of microtubules in vitro. This can dramatically affect the length distribution of the microtubules. The crosslinker sulfosuccinimidyl 4-(N-maleimidomethyl)cyclohexane-1-carboxylate, sulfo-SMCC, consists of a maleimide and an N-hydroxysuccinimide ester group to bind to sulfhydryl groups and primary amines, respectively. Interestingly, addition of a maleimide dye alone does not show the same interference with annealing in stabilized microtubules. This study shows that the sulfhydryl groups of cysteines of tubulin that are vital for the polymerization are also important for the subsequent annealing of microtubules.Comment: 3 figure

Topology counts: force distributions in circular spring networks

Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network.Comment: 5 pages, 4 figures. Missing labels in Fig. 4 added. Reference fixe

PySCIPOpt: Mathematical Programming in Python with the SCIP Optimization Suite

This is the author accepted manuscript. The final version is available frpm Springer Verlag via the DOI in this record5th International Congress on Mathematical Software (ICMS 2016), 11-14 July 2016, Berlin, GermanySCIP is a solver for a wide variety of mathematical optimization problems. It is written in C and extendable due to its plug-in based design. However, dealing with all C specifics when extending SCIP can be detrimental to development and testing of new ideas. This paper attempts to provide a remedy by introducing PySCIPOpt, a Python interface to SCIP that enables users to write new SCIP code entirely in Python. We demonstrate how to intuitively model mixed-integer linear and quadratic optimization problems and moreover provide examples on how new Python plug-ins can be added to SCIP.German Federal Ministry of Education and Researc

FilamentSensor 2.0 : An open-source modular toolbox for 2D/3D cytoskeletal filament tracking

This is the software described in our article 'FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking' and the used datasets for image analysis. It is intended as a easy to use software for tracking of cytoskeletal fibers offering both source code and GUI-based executable. Datasets are sorted according to figures in the article with folders containing raw images, analysis results and resulting figure files. The source folder also includes a tutorial and installation notes. For a system running Ubuntu 21.04 there is a slightly modified command line needed: java --module-path /usr/share/openjfx/lib –add-modules=javafx.base,javafx.controls,javafx.fxml,javafx.graphics,javafx.media,javafx.swing,javafx.web -jar GUIFocalAdhesionOnly.ja

Topology determines force distributions in one-dimensional random spring networks

Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N,z). Despite the universal properties of such (N,z) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks

Topology Counts: Force Distributions in Circular Spring Networks

Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous, and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques, we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as the mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network. Our results for 1D linear spring networks readily generalize to arbitrary dimensions

A Gestational High Protein Diet Affects the Abundance of Muscle Transcripts Related to Cell Cycle Regulation throughout Development in Porcine Progeny

BACKGROUND: In various animal models pregnancy diets have been shown to affect offspring phenotype. Indeed, the underlying programming of development is associated with modulations in birth weight, body composition, and continual diet-dependent modifications of offspring metabolism until adulthood, producing the hypothesis that the offspring's transcriptome is permanently altered depending on maternal diet. METHODOLOGY/PRINCIPAL FINDINGS: To assess alterations of the offspring's transcriptome due to gestational protein supply, German Landrace sows were fed isoenergetic diets containing protein levels of either 30% (high protein--HP) or 12% (adequate protein--AP) throughout their pregnancy. Offspring muscle tissue (M. longissimus dorsi) was collected at 94 days post conception (dpc), and 1, 28, and 188 days post natum (dpn) for use with Affymetrix GeneChip Porcine Genome Arrays and subsequent statistical and Ingenuity pathway analyses. Numerous transcripts were found to have altered abundance at 94 dpc and 1 dpn; at 28 dpn no transcripts were altered, and at 188 dpn only a few transcripts showed a different abundance between diet groups. However, when assessing transcriptional changes across developmental time points, marked differences were obvious among the dietary groups. Depending on the gestational dietary exposure, short- and long-term effects were observed for mRNA expression of genes related to cell cycle regulation, energy metabolism, growth factor signaling pathways, and nucleic acid metabolism. In particular, the abundance of transcripts related to cell cycle remained divergent among the groups during development. CONCLUSION: Expression analysis indicates that maternal protein supply induced programming of the offspring's genome; early postnatal compensation of the slight growth retardation obvious at birth in HP piglets resulted, as did a permanently different developmental alteration and responsiveness to the common environment of the transcriptome. The transcriptome modulations are interpreted as the molecular equivalent of developmental plasticity of the offspring that necessitates adaptation and maintenance of the organismal phenotype

Integrated North Sea grids: The costs, the benefits and their distribution between countries

A large number of offshore wind farms and interconnectors are expected to be constructed in the North Sea region over the coming decades, creating substantial opportunities for the deployment of integrated network solutions. Creating interconnected offshore grids that combine cross-border links and connections of offshore plants to shore offers multiple economic and environmental advantages for Europe's energy system. However, despite evidence that integrated solutions can be more beneficial than traditional radial connection practices, no such projects have been deployed yet. In this paper we quantify costs and benefits of integrated projects and investigate to which extent the cost-benefit sharing mechanism between participating countries can impede or encourage the development of integrated projects. Three concrete interconnection case studies in the North Sea area are analysed in detail using a national-level power system model. Model outputs are used to compute the net benefit of all involved stakeholders under different allocation schemes. Given the asymmetric distribution of costs and benefits, we recommend to consistently apply the Positive Net Benefit Differential mechanism as a starting point for negotiations on the financial closure of investments in integrated offshore infrastructure

Intrauterine Growth Retarded Progeny of Pregnant Sows Fed High Protein:Low Carbohydrate Diet Is Related to Metabolic Energy Deficit

High and low protein diets fed to pregnant adolescent sows led to intrauterine growth retardation (IUGR). To explore underlying mechanisms, sow plasma metabolite and hormone concentrations were analyzed during different pregnancy stages and correlated with litter weight (LW) at birth, sow body weight and back fat thickness. Sows were fed diets with low (6.5%, LP), adequate (12.1%, AP), and high (30%, HP) protein levels, made isoenergetic by adjusted carbohydrate content. At −5, 24, 66, and 108 days post coitum (dpc) fasted blood was collected. At 92 dpc, diurnal metabolic profiles were determined. Fasted serum urea and plasma glucagon were higher due to the HP diet. High density lipoprotein cholesterol (HDLC), %HDLC and cortisol were reduced in HP compared with AP sows. Lowest concentrations were observed for serum urea and protein, plasma insulin-like growth factor-I, low density lipoprotein cholesterol, and progesterone in LP compared with AP and HP sows. Fasted plasma glucose, insulin and leptin concentrations were unchanged. Diurnal metabolic profiles showed lower glucose in HP sows whereas non-esterified fatty acids (NEFA) concentrations were higher in HP compared with AP and LP sows. In HP and LP sows, urea concentrations were 300% and 60% of AP sows, respectively. Plasma total cholesterol was higher in LP than in AP and HP sows. In AP sows, LW correlated positively with insulin and insulin/glucose and negatively with glucagon/insulin at 66 dpc, whereas in HP sows LW associated positively with NEFA. In conclusion, IUGR in sows fed high protein∶low carbohydrate diet was probably due to glucose and energy deficit whereas in sows with low protein∶high carbohydrate diet it was possibly a response to a deficit of indispensable amino acids which impaired lipoprotein metabolism and favored maternal lipid disposal