A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

Dynamics and kinematics of eruptive activity at Fuego volcano, Guatemala 2005-2009

Volcanoes are the surficial expressions of complex pathways that vent magma and gasses generated deep in the Earth. Geophysical data record at least the partial history of magma and gas movement in the conduit and venting to the atmosphere. This work focuses on developing a more comprehensive understanding of explosive degassing at Fuego volcano, Guatemala through observations and analysis of geophysical data collected in 2005 – 2009. A pattern of eruptive activity was observed during 2005 – 2007 and quantified with seismic and infrasound, satellite thermal and gas measurements, and lava flow lengths. Eruptive styles are related to variable magma flux and accumulation of gas. Explosive degassing was recorded on broadband seismic and infrasound sensors in 2008 and 2009. Explosion energy partitioning between the ground and the atmosphere shows an increase in acoustic energy from 2008 to 2009, indicating a shift toward increased gas pressure in the conduit. Very-long-period (VLP) seismic signals are associated with the strongest explosions recorded in 2009 and waveform modeling in the 10 – 30 s band produces a best-fit source location 300 m west and 300 m below the summit crater. The calculated moment tensor indicates a volumetric source, which is modeled as a dike feeding a SW-dipping (35°) sill. The sill is the dominant component and its projection to the surface nearly intersects the summit crater. The deformation history of the sill is interpreted as: 1) an initial inflation due to pressurization, followed by 2) a rapid deflation as overpressure is explosively release, and finally 3) a reinflation as fresh magma flows into the sill and degasses. Tilt signals are derived from the horizontal components of the seismometer and show repetitive inflation deflation cycles with a 20 minute period coincident with strong explosions. These cycles represent the pressurization of the shallow conduit and explosive venting of overpressure that develops beneath a partially crystallized plug of magma. The energy released during the strong explosions has allowed for imaging of Fuego’s shallow conduit, which appears to have migrated west of the summit crater. In summary, Fuego is becoming more gas charged and its summit centered vent is shifting to the west - serious hazard consequences are likely.

Structural response and dynamics of fluid-structure-control interaction in wind turbine blades

Reducing the uncertainties related to blade dynamics by the improvement of the quality of numerical simulations of the fluid structure interaction process is a key for a breakthrough in wind-turbine technology. A fundamental step in that direction is the implementation of aeroelastic models capable of capturing the complex features of innovative prototype blades, so they can be tested at realistic full-scale conditions with a reasonable computational cost. We make use of a code based on a combination of two advanced numerical models implemented in a parallel HPC supercomputer platform: First, a model of the structural response of heterogeneous composite blades, based on a variation of the dimensional reduction technique proposed by Hodges and Yu. This technique has the capacity of reducing the geometrical complexity of the blade section into a stiffness matrix for an equivalent beam. The reduced 1-D strain energy is equivalent to the actual 3-D strain energy in an asymptotic sense, allowing accurate modeling of the blade structure as a 1-D finite-element problem. This substantially reduces the computational effort required to model the structural dynamics at each time step. Second, a novel aerodynamic model based on an advanced implementation of the BEM(Blade ElementMomentum) Theory; where all velocities and forces are re-projected through orthogonal matrices into the instantaneous deformed configuration to fully include the effects of large displacements and rotation of the airfoil sections into the computation of aerodynamic forces. This allows the aerodynamic model to take into account the effects of the complex flexo-torsional deformation that can be captured by the more sophisticated structural model mentioned above. In this thesis we have successfully developed a powerful computational tool for the aeroelastic analysis of wind-turbine blades. Due to the particular features mentioned above in terms of a full representation of the combined modes of deformation of the blade as a complex structural part and their effects on the aerodynamic loads, it constitutes a substantial advancement ahead the state-of-the-art aeroelastic models currently available, like the FAST-Aerodyn suite. In this thesis, we also include the results of several experiments on the NREL-5MW blade, which is widely accepted today as a benchmark blade, together with some modifications intended to explore the capacities of the new code in terms of capturing features on blade-dynamic behavior, which are normally overlooked by the existing aeroelastic models.

Predicting the Mechanical Properties of Carbon-Based Materials Using Molecular Dynamics

The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although molecular modeling has been used extensively to predict elastic properties of materials, modeling of more complex phenomenon such as fracture has only recently been possible with the development of new force fields such as ReaxFF, which is used in this work. It is not fully understood what molecular modeling parameters such as thermostat type, thermostat coupling, time step, system size, and strain rate are required for accurate modeling of fracture. Selection of modeling parameters to model fracture can be difficult and non-intuitive compared to modeling elastic properties using traditional force fields, and the errors generated by incorrect parameters may be non-obvious. These molecular modeling parameters are systematically investigated and their effects on the fracture of well-known carbon materials are analyzed. It is determined that for coupling coefficients of 250 fs and greater do not result in substantial differences in the stress-strain response of the materials using any thermostat type. A time step of 0.5 fs of smaller is required for accurate results. Strain rates greater than 2.2 ns-1 are sufficient to obtain repeatable results with slower strain rates for the materials studied. The results of this study indicate that further refinement of the Chenoweth parameter set is required to accurately predict the mechanical response of carbon-based systems. The ReaxFF has been used extensively to model systems in which bond breaking and formation occur. In particular ReaxFF has been used to model reactions of small molecules. Some elastic and fracture properties have been successfully modeled using ReaxFF in materials such as silicon and some metals. However, it is not clear if current parameterizations for ReaxFF are able to accurately reproduce the elastic and fracture properties of carbon materials. The stress-strain response of a new ReaxFF parameterization is compared to the previous parameterization and density functional theory results for well-known carbon materials. The new ReaxFF parameterization makes xv substantial improvements to the predicted mechanical response of carbon materials, and is found to be suitable for modeling the mechanical response of carbon materials. Finally, a new material composed of carbon nanotubes within an amorphous carbon (AC) matrix is modeled using the ReaxFF. Various parameters that may be experimentally controlled are investigated such as nanotube bundling, comparing multi-walled nanotube with single-walled nanotubes, and degree of functionalization of the nanotubes. Elastic and fracture properties are investigated for the composite systems and compared to results of pure-nanotube and pure-AC models. It is found that the arrangement of the nanotubes and degree of crosslinking may substantially affect the properties of the systems, particularly in the transverse directions.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.

EXPLORING CHANGES IN DETRITAL FLOCCULENT LAYER DYNAMICS DUE TO SHIFTS IN MACROPHYTE COMMUNITIES IN THE NORTHERN EVERGLADES

A shift in plant communities of the Water Conservation Areas (WCAs) within the Everglades has been linked to changes in hydrology and high levels of nutrient loading from surrounding agicultural areas. This has resulted in the encroachment of dense cattail stands (Typha domingensis) into areas that had previously been a ridge and slough landscape populated primarily by native sawgrass (Cladium jamaicense). In order to study ecological management solutions in this area, WCA-2A was broken into study plots; several of which became open water areas through the application of herbicide and burning regimens. The open water areas allowed for Chara spp (a submersed algal species) to replace Typha domingensis as the dominant macrophyte. This study investigated the polymer and ionic profiles of Chara spp, Typha domingensis and Cladium jamaicense and their contributions to detrital flocculent (floc) in the study plots where they are the dominant macrophytes. Floc is not only an important food source for aquatic species; it also supports many algal, fungal and bacterial communities. Data gathered in this study indicated that the floc sample from a phosphorus enriched open water study plot (EO1) where Chara spp was the dominant macrophyte may contain cell wall polymers from sources other than Chara spp (most likely Typha domingensis), while the chemical and polymeric profile of the floc of the study plot where Typha domingensis is the dominant macrophyte (EC1) suggests that the floc layer has contributions from algal sources as well as Typha domingensis. Additionally, monoclonal antibodies to Arabinoglalactan protein (AGP) and (1,4)-β-D galactan were identified as possible biomarkers for distinguishing algal dominated floc layers from layers dominated by emergent vegetation. Calcium labeling could be a useful tool for this as well because of the high amount of Ca2+ associated with Chara spp cell walls. When looking into the soluble phosphorus content of the macrophytes and paired floc samples of WCA-2A, it was found that Chara spp may be contributing a greater amount of Ca-bound phosphorus to floc layers where it is the dominant macrophyte when compared to floc layers from study plots dominated by emergent macrophytes. Floc layers also appear to be acting as a nutrient sink for soluble phosphorus. The findings of this study support the overall hypothesis that the shift from native emergent macrophyte communities to submersed macrophyte communities in study sites of the northern Everglades is affecting the polymeric/chemical profile and ionic content of detrital floc layers. The effects of this shift may contribute to changes in complex flocculent community dynamics.

Diversification in the South American Pampas: the genetic and morphological variation of the widespread Petunia axillaris complex (Solanaceae)

Understanding the spatiotemporal distribution of genetic variation and the ways in which this distribution is connected to the ecological context of natural populations is fundamental for understanding the nature and mode of intraspecific and, ultimately, interspecific differentiation. The Petunia axillaris complex is endemic to the grasslands of southern South America and includes three subspecies: P.a.axillaris, P.a.parodii and P.a.subandina. These subspecies are traditionally delimited based on both geography and floral morphology, although the latter is highly variable. Here, we determined the patterns of genetic (nuclear and cpDNA), morphological and ecological (bioclimatic) variation of a large number of P.axillaris populations and found that they are mostly coincident with subspecies delimitation. The nuclear data suggest that the subspecies are likely independent evolutionary units, and their morphological differences may be associated with local adaptations to diverse climatic and/or edaphic conditions and population isolation. The demographic dynamics over time estimated by skyline plot analyses showed different patterns for each subspecies in the last 100000years, which is compatible with a divergence time between 35000 and 107000years ago between P.a.axillaris and P.a.parodii, as estimated with the IMa program. Coalescent simulation tests using Approximate Bayesian Computation do not support previous suggestions of extensive gene flow between P.a.axillaris and P.a.parodii in their contact zone.

Recruitment of EB1, a master regulator of microtubule dynamics, to the surface of the Theileria annulata schizont

The apicomplexan parasite Theileria annulata transforms infected host cells, inducing uncontrolled proliferation and clonal expansion of the parasitized cell population. Shortly after sporozoite entry into the target cell, the surrounding host cell membrane is dissolved and an array of host cell microtubules (MTs) surrounds the parasite, which develops into the transforming schizont. The latter does not egress to invade and transform other cells. Instead, it remains tethered to host cell MTs and, during mitosis and cytokinesis, engages the cell's astral and central spindle MTs to secure its distribution between the two daughter cells. The molecular mechanism by which the schizont recruits and stabilizes host cell MTs is not known. MT minus ends are mostly anchored in the MT organizing center, while the plus ends explore the cellular space, switching constantly between phases of growth and shrinkage (called dynamic instability). Assuming the plus ends of growing MTs provide the first point of contact with the parasite, we focused on the complex protein machinery associated with these structures. We now report how the schizont recruits end-binding protein 1 (EB1), a central component of the MT plus end protein interaction network and key regulator of host cell MT dynamics. Using a range of in vitro experiments, we demonstrate that T. annulata p104, a polymorphic antigen expressed on the schizont surface, functions as a genuine EB1-binding protein and can recruit EB1 in the absence of any other parasite proteins. Binding strictly depends on a consensus SxIP motif located in a highly disordered C-terminal region of p104. We further show that parasite interaction with host cell EB1 is cell cycle regulated. This is the first description of a pathogen-encoded protein to interact with EB1 via a bona-fide SxIP motif. Our findings provide important new insight into the mode of interaction between Theileria and the host cell cytoskeleton.

The role of zinc dynamics in growth hormone secretion

Human growth hormone (GH) causes a variety of physiological and metabolic effects in humans and plays a pivotal role in postnatal growth. In somatotroph cells of the anterior pituitary, GH is stored in concentrated forms in secretory granules to be rapidly released upon GH-releasing hormone stimulation. During the process of secretory granule biogenesis, self-association of GH occurs in the compartments of the early secretory pathway (endoplasmic reticulum and Golgi complex). Since this process is greatly facilitated by the presence of zinc ions, it is of importance to understand the potential role of zinc transporters that participate in the fine-tuning of zinc homeostasis and dynamics, particularly in the early secretory pathway. Thus, the role of zinc transporters in supplying the secretory pathway with the sufficient amount of zinc required for the biogenesis of GH-containing secretory granules is essential for normal secretion. This report, illustrated by a clinical case report on transient neonatal zinc deficiency, focuses on the role of zinc in GH storage in the secretory granules and highlights the role of specific zinc transporters in the early secretory pathway.

Sediment dynamics in the subaquatic channel of the Rhone delta (Lake Geneva, France/Switzerland)

bstract With its smaller size, well-known boundary conditions, and the availability of detailed bathymetric data, Lake Geneva’s subaquatic canyon in the Rhone Delta is an excellent analogue to understand sedimentary pro- cesses in deep-water submarine channels. A multidisciplinary research effort was undertaken to unravel the sediment dynamics in the active canyon. This approach included innovative coring using the Russian MIR sub- mersibles, in situ geotechnical tests, and geophysical, sedimentological, geochemical and radiometric analysis techniques. The canyon floor/levee complex is character- ized by a classic turbiditic system with frequent spillover events. Sedimentary evolution in the active canyon is controlled by a complex interplay between erosion and sedimentation processes. In situ profiling of sediment strength in the upper layer was tested using a dynamic penetrometer and suggests that erosion is the governing mechanism in the proximal canyon floor while sedimen- tation dominates in the levee structure. Sedimentation rates progressively decrease down-channel along the levee structure, with accumulation exceeding 2.6 cm/year in the proximal levee. A decrease in the frequency of turbidites upwards along the canyon wall suggests a progressive confinement of the flow through time. The multi-proxy methodology has also enabled a qualitative slope-stability assessment in the levee structure. The rapid sediment loading, slope undercutting and over-steepening, and increased pore pressure due to high methane concentrations hint at a potential instability of the proximal levees. Fur- thermore, discrete sandy intervals show very high methane concentrations and low shear strength and thus could cor- respond to potentially weak layers prone to scarp failures.

Inverse modelling of the 14C bomb pulse in stalagmites to constrain the dynamics of soil carbon cycling at selected European cave sites

The decomposition of soil organic matter (SOM) is temperature dependent, but its response to a future warmer climate remains equivocal. Enhanced rates of decomposition of SOM under increased global temperatures might cause higher CO2 emissions to the atmosphere, and could therefore constitute a strong positive feedback. The magnitude of this feedback however remains poorly understood, primarily because of the difficulty in quantifying the temperature sensitivity of stored, recalcitrant carbon that comprises the bulk (>90%) of SOM in most soils. In this study we investigated the effects of climatic conditions on soil carbon dynamics using the attenuation of the 14C ‘bomb’ pulse as recorded in selected modern European speleothems. These new data were combined with published results to further examine soil carbon dynamics, and to explore the sensitivity of labile and recalcitrant organic matter decomposition to different climatic conditions. Temporal changes in 14C activity inferred from each speleothem was modelled using a three pool soil carbon inverse model (applying a Monte Carlo method) to constrain soil carbon turnover rates at each site. Speleothems from sites that are characterised by semi-arid conditions, sparse vegetation, thin soil cover and high mean annual air temperatures (MAATs), exhibit weak attenuation of atmospheric 14C ‘bomb’ peak (a low damping effect, D in the range: 55–77%) and low modelled mean respired carbon ages (MRCA), indicating that decomposition is dominated by young, recently fixed soil carbon. By contrast, humid and high MAAT sites that are characterised by a thick soil cover and dense, well developed vegetation, display the highest damping effect (D = c. 90%), and the highest MRCA values (in the range from 350 ± 126 years to 571 ± 128 years). This suggests that carbon incorporated into these stalagmites originates predominantly from decomposition of old, recalcitrant organic matter. SOM turnover rates cannot be ascribed to a single climate variable, e.g. (MAAT) but instead reflect a complex interplay of climate (e.g. MAAT and moisture budget) and vegetation development.

Dynamics of the last four glacial terminations recorded in Lake Van, Turkey

A well-dated suite of Lake Van climate-proxy data covering the last 360 ka documents environmental changes over 4 glacial/interglacial cycles in Eastern Anatolia, Turkey. The picture of cold and dry glacials and warm and wet interglacials emerging from pollen, organic carbon, authigenic carbonate content, elemental profiling by XRF and lithological analyses is inconsistent with classical interpretation of ox- ygen isotopic composition of carbonates pointing to a more complex pattern in Lake Van region. Detailed analysis of glacial terminations allows for the constraining of a depositional model explaining different patterns observed in all the proxies. We hypothesize that variations in relative contribution of rainfall, snowmelt and glacier meltwater recharging the basin have a very important role for all sedimentary processes in Lake Van. Lake level of glacial Lake Van, predominantly fed by snowmelt, was low, the water column was oxic, and carbonates precipitating in the epilimnion recorded the light isotopic signature of inflow. During terminations, increasing rainfall and significant supply of mountain glaciers' meltwater contributed to lake level rise. Increased rainfall enhanced density gradients in the water column, and hindered mixing leading to development of bottom-water anoxia. Carbonates precipitating during terminations show large fluctuations in their isotopic composition. Full interglacial conditions in Lake Van are characterized by high or slowly falling lake level. Rainfall and snowmelt feed the lake but due to re-established mixing, the isotopic composition of authigenic carbonates is heavier and closer to that of evaporation-influenced lake water than that of runoff representing snowmelt and atmospheric precipitation.

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.