The Modeling of Global Epidemics: Stochastic Dynamics and Predictability

The global spread of emergent diseases is inevitably entangled with the structure of the population flows among different geographical regions. The airline transportation network in particular shrinks the geographical space by reducing travel time between the world's most populated areas and defines the main channels along which emergent diseases will spread. In this paper, we investigate the role of the large-scale properties of the airline transportation network in determining the global propagation pattern of emerging diseases. We put forward a stochastic computational framework for the modeling of the global spreading of infectious diseases that takes advantage of the complete International Air Transport Association 2002 database complemented with census population data. The model is analyzed by using for the first time an information theory approach that allows the quantitative characterization of the heterogeneity level and the predictability of the spreading pattern in presence of stochastic fluctuations. In particular we are able to assess the reliability of numerical forecast with respect to the intrinsic stochastic nature of the disease transmission and travel flows. The epidemic pattern predictability is quantitatively determined and traced back to the occurrence of epidemic pathways defining a backbone of dominant connections for the disease spreading. The presented results provide a general computational framework for the analysis of containment policies and risk forecast of global epidemic outbreaks. On leave from CEA-Centre d'Etudes de Bruyères-Le-Chatel, France.     

Population Dynamics of Soil and Vegetation Protozoa

Many fresh-water protozoa can be found in litters and soils,but the ubiquitous species are those which are able to copewith fluctuating moisture conditions. Terrestrial protozoa aremore characteristic of bryophyte-soil habitats than aquaticecosystems. Nutritionally, two groups have evolved in responseto the plant community: naked, predominantly bacterial feeders,whose abundance is determined by the decomposability of thelitter in which they live; and the slow growing, humusassociatedtestacea, which are more abundant in the litters of slow decomposability.Ubiquitous species comprise about 90% of the protozoa in soils.More continuous moisture conditions enhance the appearance ofadditional species. Hence species diversity indicates highermoisture content of a soil. Protozoa may contribute to the functioningof the soil ecosystem by inducing fiocculation of bacterialpopulations and recycling of minerals through ingestion of bacteriaand excretion of soluble products. The surface of vegetationappears to represent the most terrestrial habitat a protozoancan exploit, because in contrast to the litter-soil ecosystem,only one species, Colpoda cucullus, dominates the population.     

The Impact of Aminoglycosides on the Dynamics of Translation Elongation

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Highlights? Combined single-molecule, structural, and biochemical studies on aminoglycoside action ? Aminoglycosides disrupt translation through inhibiting the dynamics of elongation ? Apramycin blocks translocation in translation elongation ? Paromomycin and gentamicin disrupt ribosomal rotation and translocation     

Measuring Predictability of Autonomous Network Transitions into Bursting Dynamics

Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-temporal features of network activity, predict autonomous network transitions from asynchronous to synchronous dynamics under various conditions. These metrics quantify spike-timing distributions within a narrow time window as a function of the relative location of the active neurons. We applied these metrics to investigate the properties of these transitions in excitatory-only and excitatory-and-inhibitory networks and elucidate how network topology, noise level, and cellular heterogeneity affect both the reliability and the timeliness of the predictions. The developed measures can be calculated in real time and therefore potentially applied in clinical situations.     

The Effects of Differences in Vegetation on Calcium Dynamics in Headwater Streams

Although organisms can alter dynamics of elements in ecosystems via physiological results, the effects of tree species on ecosystem nutrient dynamics are highly uncertain. A four-fold variation in the calcium concentrations of streams, soils and leaf litters were caused by the planting of Cryptomeria japonica in south-central Japan. In this study, we examined how the calcium dynamics were affected by the planting of C. japonica through strontium isotope analysis. We predicted the planting of C. japonica would result in the calcium concentration increasing because of the significant dissolution of calcium from bedrock. In a forest ecosystem, calcium is usually derived from precipitation and bedrock weathering, and their relative contributions can be estimated using a strontium isotope mixing model. Therefore, we collected stream water, litter, soil, precipitation and bedrock samples from 17 sites in catchments dominated by C. japonica plantation or evergreen broad-leaved forest; after collection, we analyzed the sample chemical compositions and strontium isotope ratios. The calcium concentrations in the stream water and the water-soluble calcium in the soil were significantly higher at sites dominated by C. japonica than at broad-leaved forest sites. Strontium isotope analysis indicated that there was more calcium from the bedrock present in stream water at sites dominated by C. japonica than in stream water at broad-leaved forest sites. Our results showed that watershed-scale dynamics of calcium and other cations can be altered by the type of vegetation in a catchment due to the effects of vegetation on the supply of calcium from bedrock.     

The Impact of Macroscopic Epistasis on Long-Term Evolutionary Dynamics

Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of epistasis over 50,000 generations in a well-studied laboratory evolution experiment in Escherichia coli. The extensive duration of this experiment provides a unique window into the effects of epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with a “two-epoch” model of adaptation, in which an initial burst of diminishing-returns epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of epistasis that are compatible with all of the experimental data.     

Carbon Flux and Carbohydrate Gene Families in Pineapple

The recently sequenced pineapple genome was used to identify and analyze some of the key gene families involved in carbohydrate biosynthesis, breakdown and modification. Gene products were grouped into glycosyltransferases (GT), glycoside hydrolases (GH), carbohydrate esterases (CE), and polysaccharide lyases (PL) based upon predicted catalytic activity. Non-catalytic carbohydrate-binding modules (CBM) and enzymes involved in lignification were also identified. The pineapple genes were compared with those from two and five monocot and eudicots species, respectively. The complement of pineapple sugar and cell wall metabolism genes is similar to that found in rice and sorghum, though the numbers of GTs and GHs is often fewer. This applies to a lesser extent to the genes involved in nucleotide-sugar interconversion, with both pineapple and papaya having a minimum complement. Interestingly, pineapple does not appear to contain mixed linkage β-glucan in its walls while possessing cellulose synthase-like (Csl), J and H genes. Pineapple and papaya have less than half the number of GT1 genes involved in small molecule glycosylation compared to Arabidopsis and tomato, and fewer members in GH families than Arabidopsis. The ratio of rice and sorghum to pineapple genes in GH families was more variable than in the case of GTs and it is unclear why pineapple GH gene numbers are so low. Rice, sorghum and pineapple have far fewer CE8, PL1 and GH28 genes related to pectin metabolism than most eudicots. The general lower number of cell wall genes in pineapple possibly reflects the absence of a genome duplication event. The data also suggests that pineapple straddles the boundary between grasses (family Poaceae) and eudicots in terms of genes involved in carbohydrate metabolism, which is also reflected in its cell wall composition.     

Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos

The study of object manipulation has been largely confined to discrete tasks, where accuracy, mechanical effort, or smoothness were examined to explain subjects'' preferred movements. This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. The experiment was conducted in a virtual set-up, where subjects moved a cup with a ball inside, modeled by cart-and-pendulum dynamics. Inverse dynamics calculations of the system showed that performing the task with different amplitudes and relative phases required different force profiles and rendered the object''s dynamics with different degrees of predictability (quantified by Mutual Information between the applied force and the cup kinematics and its sensitivity). Subjects (n = 8) oscillated the virtual cup between two targets via a robotic manipulandum, paced by a metronome at 1 Hz for 50 trials, each lasting 45 s. They were free to choose their movement amplitude and relative phase between the ball and cup. Experimental results showed that subjects increased their movement amplitudes, which rendered the interactions with the object more predictable and with lower sensitivity to the execution variables. These solutions were associated with higher average exerted force and lower object smoothness, contradicting common expectations from studies on discrete object manipulation and unrestrained movements. Instead, the findings showed that humans selected strategies with higher predictability of interaction dynamics. This finding expressed that humans seek movement strategies where force and kinematics synchronize to repeatable patterns that may require less sensorimotor information processing.     

Impact of Atmospheric Nitrogen Deposition on Carbon Dynamics in Two Scots Pine Forest Soils of Northern Germany

The impact of atmospheric N deposition on the dynamics of various carbon fractions was investigated in two Scots pine forest soils (cambisol, podzol) of Northern Germany in microcosm experiments. Total organic carbon (TOC), CO₂ emission, microbial carbon (C_mic) as well as organic hot- and coldwater extractable carbon fractions (C_hwe, C_cwe) were analyzed before, during, and after soil incubation in microcosms, run in three treatments: 0, +45, and +90 kg N ha⁻¹a⁻¹. On both sites, the N treatment showed no response to total organic carbon (TOC) contents in most of the investigated soil layers. Microbial carbon (C_mic) was significantly increased in the organic layer of both soil types by the N application. Subsequent to the N application, the CO₂ emission increased in all mineral soil layers of the cambisol but remained almost unaffected in the podzol. After the N application, a remarkable increase of hotwater extractable C (C_hwe) was detected for the organic layer of the cambisol but not for the podzol, whereas coldwater extractable C (C_cwe) concentrations decreased at both sites. The N application did not have a significant impact on the leachate concentrations of total organic carbon (TOC), dissolved organic carbon (DOC), and particulate organic carbon (POC) in the podzol, whereas the concentrations of these C fractions were decreased in the organic layer and the 35–70~cm mineral soil layer of the cambisol. The N treatment changed the contents of most of the investigated C fractions in both soil types and resulted in a considerable C~mobilization. But the processes of the C~mobilization between the cambisol and the podzol were completely different. According to the presented data, the cambisol obtaining moderate atmospheric N loads is much more sensitive to additional N inputs than the podzol that already received high amounts of atmospheric N.     

Climate Change Effects on Vegetation Distribution and Carbon Budget in the United States

The Kyoto protocol has focused the attention of the public and policymarkers on the earth's carbon (C) budget. Previous estimates of the impacts of vegetation change have been limited to equilibrium “snapshots” that could not capture nonlinear or threshold effects along the trajectory of change. New models have been designed to complement equilibrium models and simulate vegetation succession through time while estimating variability in the C budget and responses to episodic events such as drought and fire. In addition, a plethora of future climate scenarios has been used to produce a bewildering variety of simulated ecological responses. Our objectives were to use an equilibrium model (Mapped Atmosphere–Plant–Soil system, or MAPSS) and a dynamic model (MC1) to (a) simulate changes in potential equilibrium vegetation distribution under historical conditions and across a wide gradient of future temperature changes to look for consistencies and trends among the many future scenarios, (b) simulate time-dependent changes in vegetation distribution and its associated C pools to illustrate the possible trajectories of vegetation change near the high and low ends of the temperature gradient, and (c) analyze the extent of the US area supporting a negative C balance. Both models agree that a moderate increase in temperature produces an increase in vegetation density and carbon sequestration across most of the US with small changes in vegetation types. Large increases in temperature cause losses of C with large shifts in vegetation types. In the western states, particularly southern California, precipitation and thus vegetation density increase and forests expand under all but the hottest scenarios. In the eastern US, particularly the Southeast, forests expand under the more moderate scenarios but decline under more severe climate scenarios, with catastrophic fires potentially causing rapid vegetation conversions from forest to savanna. Both models show that there is a potential for either positive or negative feedbacks to the atmosphere depending on the level of warming in the climate change scenarios. Received 12 May 2000; accepted 22 November 2000.     

Pristine C60 Fullerene Nanoparticles Ameliorate Hyperglycemia-Induced Disturbances via Modulation of Apoptosis and Autophagy Flux

Neurochemical Research - Diabetes mellitus is a prevalent metabolic disorder associated with multiple complications including neuropathy, memory loss and cognitive decline. Despite a long history...     

The Restoration Dynamics of Fallow Vegetation in the Steppe Zone of the Khakassia Republic Based on Terrain and Satellite Data

Biophysics - The dynamics and specific features of the restoration of forbs–grass–wormwood and wormwood–grass phytocoenoses on fallow lands in the Altai region, the Republic of...     

Fire Risk and Vegetation Structural Dynamics in Mediterranean Shrubland

Phytomass structural characteristics are highly related to vegetation flammability. In fire-prone species like Mediterranean gorse, which accumulate standing dead fuel, susceptibility to fire is a function of fuel load, vegetation composition and fuel cover, and these characteristics change with time. Thus, for effective fuel control management, knowledge of the vegetation structural dynamics related to fire risk is crucial for preventing future fires. This study analyses structural dynamics in the above-ground phytomass of Ulex parviflorus shrublands in relation to different stages of flammability, i.e., the amount of time elapsed since the last fire. For this, 152 plants were cut from shrublands at different stages of development (young, mature and senescent), and various dimensional measurements were taken on each. The phytomass was separated into living or dead fuel fractions as well as into twigs or branches depending on the stem diameter. Basal diameter is the variable that best predicted Ulex parviflorus total phytomass as well as that of the different fractions. Both dimensional and phytomass variables increased with plant development. In the young shrublands Ulex parviflorus constitutes 54% of total phytomass, and Ulex parviflorus's dead twigs fraction accounts for 5% of total phytomass. In the mature and senescent shrublands, this species represents 80% of total shrubland phytomass, and dead twigs reach values greater than 40%. Our results show that structural changes in the fuel over short periods of time (young and mature) reveal critical periods in shrub development. Identification of these stages is a necessary tool for planning fuel control programmes.     

The Impact of the Allee Effect in Dispersal and Patch-Occupancy Age on the Dynamics of Metapopulations

In this paper, we introduce a Levins-type metapopulation model with empty and occupied patches, and dispersing population. We structure the proportion of occupied patches according to the patch-occupancy age. We observe that patch-occupancy age may destabilize the metapopulation, leading to persistent oscillations. We also allow for the dispersal rate to vary with the proportion of empty patches in a monotone or unimodal way. The unimodal dependence leads to multiple non-trivial equilibria and bistability when the reproduction number of the metapopulation < 1 but greater than a lower critical value ^*. We show that the metapopulation will persist independently of its initial status if > 1.     

The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.     

Seasonal Dynamics of Soil Labile Organic Carbon and Enzyme Activities in Relation to Vegetation Types in Hangzhou Bay Tidal Flat Wetland

Soil labile organic carbon and soil enzymes play important roles in the carbon cycle of coastal wetlands that have high organic carbon accumulation rates. Soils under three vegetations (Phragmites australis, Spartina alterniflora, and Scirpusm mariqueter) as well as bare mudflat in Hangzhou Bay wetland of China were collected seasonally. Seasonal dynamics and correlations of soil labile organic carbon fractions and soil enzyme activities were analyzed. The results showed that there were significant differences among vegetation types in the contents of soil organic carbon (SOC) and dissolved organic carbon (DOC), excepting for that of microbial biomass carbon (MBC). The P. australis soil was with the highest content of both SOC (7.86 g kg^-1) and DOC (306 mg kg^-1), while the S. mariqueter soil was with the lowest content of SOC (6.83 g kg^-1), and the bare mudflat was with the lowest content of DOC (270 mg kg^-1). Soil enzyme activities were significantly different among vegetation types except for urease. The P. australis had the highest annual average activity of alkaline phosphomonoesterase (21.4 mg kg^-1 h^-1), and the S. alterniflora had the highest annual average activities of β-glycosidase (4.10 mg kg^-1 h^-1) and invertase (9.81mg g^-1 24h^-1); however, the bare mudflat had the lowest activities of alkaline phosphomonoesterase (16.2 mg kg^-1 h^-1), β-glycosidase (2.87 mg kg^-1 h^-1), and invertase (8.02 mg g^-1 24h^-1). Analysis also showed that the soil labile organic carbon fractions and soil enzyme activities had distinct seasonal dynamics. In addition, the soil MBC content was significantly correlated with the activities of urease and β-glucosidase. The DOC content was significantly correlated with the activities of urease, alkaline phosphomonoesterase, and invertase. The results indicated that vegetation type is an important factor influencing the spatial-temporal variation of soil enzyme activities and labile organic carbon in coastal wetlands.     

Climate Records,Isotopes, and C:N Stoichiometry Reveal Carbon and Nitrogen Flux Dynamics Differ Between Functional Groups of Ectomycorrhizal Fungi

Ecosystems - A major functional division in ectomycorrhizal fungi is between taxa with hydrophobic ectomycorrhizae (strong proteolytic capabilities, deep nitrogen (N) acquisition, and extensive...