Cell line-specific efficacy of thermoradiotherapy in human and canine cancer cells in vitro

Objective Aims were to investigate sensitivity of various human and canine cancer cell lines to hyperthermia and the influence of particular treatment conditions, and to analyze the DNA-damage response and mode of cell death in cell line radiosensitized by hyperthermia. Additionally, we were interested in the involvement of HSP70 in radiosensitization. Methods Radiosensitization by hyperthermia was determined in a panel of human and canine cancer cell lines using clonogenic cell survival assay, as well as levels of heat shock proteins (HSPs) using immunoblotting. The influence of the hyperthermia-radiotherapy time gap, different temperatures and the order of treatments on clonogenicity of hyperthermia-sensitive A549 cells was investigated. Additionally, DNA damage and cell death were assessed by Comet assay and an apoptosis/necrosis assay. Further we induced transient knockdown in A549 cells to test HSP70’s involvement in radiosensitization. Results Out of eight cell lines tested, only two (A549 and Abrams) showed significant decrease in clonogenic cell survival when pre-treated with hyperthermia at 42˚C. Strong induction of HSP70 upon thermoradiotherapy (HT-RT) treatment was found in all cell lines. Transient knockdown of HSP70 in A549 cells did not result in decrease of clonogenic cell survival in response to HT-RT. Conclusion Tumor cell-type, temperature and order of treatment play an important role in radiosensitization by hyperthermia. However, hyperthermia has limited potency to radiosensitize canine cancer cells grown in a 2D cell culture setting presented here. DNA damage and apoptosis/necrosis did not increase upon combined treatment and cytosolic levels of HSP70 appear not to play critical role in the radiosensitization of A549 cells

Time walkers and spatial dynamics of ageing information

The distribution of information is essential for living system's ability to coordinate and adapt. Random walkers are often used to model this distribution process and, in doing so, one effectively assumes that information maintains its relevance over time. But the value of information in social and biological systems often decay and must continuously be updated. To capture the spatial dynamics of ageing information, we introduce time walkers. A time walker moves like a random walker, but interacts with traces left by other walkers, some representing older information, some newer. The traces forms a navigable information landscape. We quantify the dynamical properties of time walkers moving on a two-dimensional lattice and the quality of the information landscape generated by their movements. We visualise the self-similar landscape as a river network, and show that searching in this landscape is superior to random searching and scales as the length of loop-erased random walks

Distributed Learning with Biogeography-Based Optimization

We present hardware testing of an evolutionary algorithm known as biogeography-based optimization (BBO) and extend it to distributed learning. BBO is an evolutionary algorithm based on the theory of biogeography, which describes how nature geographically distributes organisms. We introduce a new BBO algorithm that does not use a centralized computer, and which we call distributed BBO. BBO and distributed BBO have been developed by mimicking nature to obtain an algorithm that optimizes solutions for different situations and problems. We use fourteen common benchmark functions to obtain results from BBO and distributed BBO, and we also use both algorithms to optimize robot control algorithms. We present not only simulation results, but also experimental results using BBO to optimize the control algorithms of mobile robots. The results show that centralized BBO generally gives better optimization results and would generally be a better choice than any of the newly proposed forms of distributed BBO. However, distributed BBO allows the user to find a less optimal solution to a problem while avoiding the need for centralized, coordinated control

Coupled modelling of permafrost and groundwater : a case study approach

This report investigates the sensitivity of simulated permafrost thickness and dynamics to a variety of climatic, geological and hydrogeological conditions for two geological environments, basement under sedimentary cover and a low permeability succession of Mesozoic shales and siltstones (Case 1 and Case 2 respectively). A combination of one dimensional heat conduction modelling, including the effects of freeze-thaw, and two dimensional heat conduction-advection modelling, including freeze thaw, has been undertaken to simulate permafrost development in these two contrasting geological environments. This enables an assessment of the sensitivities to a range of possible geological parameters, advective heat flow, and the effect of glaciation with and without the influence of glacial loading. In this report, permafrost is defined as the sub-surface in which ice is present even in very small amounts, i.e. ice content is greater than 0%, and in the model, this is at the zero degree isotherm. The maximum permafrost thickness is strongly dependent on the mean annual surface temperature, the presence of ice that will insulate the system and the duration of the cold phase. By scaling the minimum temperature of 57 Pliocene-Pleistocene globally distributed benthic δ18O records to temperatures of 14°C, 18°C and 25 °C below the present day mean annual temperature, the maximum permafrost thickness for Case 1 is simulated to reach 171 m, 248 m, and 475 m, and for Case 2 80 m, 138 m, and 238 m respectively. The difference in permafrost thickness between the two Cases is attributed to the variation in subsurface rock properties. Deeper permafrost depths than for Case 1 and 2 can be expected where the thermal conductivity is higher than for Case 1 and 2. A sensitivity study of the geological parameters has shown that there is a strong, non-linear, relationship between thermal conductivity, latent heat and geothermal heat flow for a series of temperatures representative of the glacial cycles of the past one million years. This is in contrast to a steady state temperature profile, where permafrost thickness relates linearly to thermal conductivity, heat flow and ground surface temperature. Thickest permafrost under unchanged climatic conditions is to be expected where there is a low heat flow, a high thermal conductivity and a low porosity, such as for example in the north of Scotland. The results of the modelling show that when the temperature regime is dominated by heat conduction, such as for the low permeability Case 2, a heat conduction only model is sufficient to estimate the thickness and distribution of permafrost. However, when heat advection is likely to be important, such as in Case 1, the coupling of permafrost and groundwater flow is necessary to simulate the permafrost distribution during freeze and thaw, or during shallow permafrost events. This particularly holds true when permafrost is modelled to be relatively permeable, where modelling suggests that heat advection of cold water at recharge points (interfluves) results in cooling and thicker permafrost compared to discharge points where discharge of warmer water results in thinner permafrost. However, these variabilities in local permafrost thickness are of minor importance for the question of freezing of the repository. However, when assessing the broader influences of permafrost on a geological environment, local variations in permafrost extent of thickness can have consequences on the biosphere. Glaciation influences the thermal regime of the ground surface. If the glacier bed is undergoing pressure melting, as found in the ablation zone, a reduction in permafrost depth can be expected. If the glacier bed is cold based, as often found in the accumulation zone or at ice divides where strong vertical advection of cold ice has a cooling effect, then the maximum permafrost thickness can be expected to be similar to the scenario without glaciation. It may even increase if the temperatures at the glacier bed are colder than the ground surface temperatures, which may occur. when the temperature in the area where the ice is forming is colder than that prevailing downstream. Recharge and discharge decrease considerably during periods when permafrost is present. In the case of a model with an open model boundary to one side, representing the coast for example, and a high topographic gradient (Case 1), a large drop in hydraulic heads is observed beneath the permafrost. This results in lower groundwater flows at depth compared to unfrozen conditions. Where a modelled area is closed on all sides (Case 2), a decrease in flow at depth is also observed, however the hydraulic heads do not decrease to the same extent as the hydraulic gradient is less than for Case 1. During permafrost thaw, hydraulic heads rise, resulting in an uptake of groundwater into elastic storage from recharge over the top boundary of the model domain. When taliks underneath surface water bodies develop, the groundwater flow system remains more active than during continuous permafrost. Recharge and discharge are focused on the lakes and a regional groundwater flow system connecting the lakes can develop. Heat advection remains more important during thick permafrost when through taliks remain open. In the model, during periods of glaciation, hydraulic heads increase by ~1500 m at depth for Case 1 and Case 2 when ice loading is applied. When ice-sheet loading is not accounted for, the hydraulic head signal in low permeability layers is dampened. During glacial advance, groundwater recharge increases by up to two orders of magnitude, and during glacial retreat discharge increases. During ice advance, groundwater flow is in a downward direction but during ice retreat it is in an upward direction. Depending on the flow direction of the glacier, groundwater flow directions can be reversed during a glaciation. Modelling the Anglian Glaciation (middle Pleistocene glaciation, equivalent to the Elsterian or Mindel glaciation in Europe and the Alps, most extensive glaciation in the British Isles, MIS 12), the hydraulic head and groundwater flow magnitude are affected by the glaciation for tens of thousands of years, whereas after the Devensian glaciation (late Pleistocene glaciation, equivalent to the Weichselian/Vistulian or Würm glaciation in Europe and the Alps, MIS 5d to 2), the signal remains for thousands of years. High hydraulic heads that may be present during glaciation are likely to modify the groundwater flow around a GDF. The modelling presented here based on two settings and typical thermal and hydraulic properties for the rocks present, demonstrates that the depth of permafrost could extend up to a depth of 300m below the surface and, depending on specific characteristics (large thermal conductivity and low porosity) and an exceptionally long cold period, could extend to greater depths. Permafrost to these depths may affect the engineering properties of some rock types and could lead to the development of new fracture pathways in more brittle formations. Permafrost could also affect some of the engineered components of a GDF in similar ways, such as the properties of clay materials

Connectivity strategies to enhance the capacity of weight-bearing networks

The connectivity properties of a weight-bearing network are exploited to enhance it's capacity. We study a 2-d network of sites where the weight-bearing capacity of a given site depends on the capacities of the sites connected to it in the layers above. The network consists of clusters viz. a set of sites connected with each other with the largest such collection of sites being denoted as the maximal cluster. New connections are made between sites in successive layers using two distinct strategies. The key element of our strategies consists of adding as many disjoint clusters as possible to the sites on the trunk $T$ of the maximal cluster. The new networks can bear much higher weights than the original networks and have much lower failure rates. The first strategy leads to a greater enhancement of stability whereas the second leads to a greater enhancement of capacity compared to the original networks. The original network used here is a typical example of the branching hierarchical class. However the application of strategies similar to ours can yield useful results in other types of networks as well.Comment: 17 pages, 3 EPS files, 5 PS files, Phys. Rev. E (to appear

Breakdown of Kolmogorov scaling in models of cluster aggregation with deposition

The steady state of the model of cluster aggregation with deposition is characterized by a constant flux of mass directed from small masses towards large masses. It can therefore be studied using phenomenological theories of turbulence, such as Kolmogorov's 1941 theory. On the other hand, the large scale behavior of the aggregation model in dimensions lower than or equal to two is governed by a perturbative fixed point of the renormalization group flow, which enables an analytic study of the scaling properties of correlation functions in the steady state. In this paper, we show that the correlation functions have multifractal scaling, which violates linear Kolmogorov scaling. The analytical results are verified by Monte Carlo simulations.Comment: 5 pages 4 figure

Fellhanera gyrophorica, a new European species with conspicuous pycnidia

Fellhanera gyrophorica Sérus., Coppins, Diederich & Scheidegger is described as new from Europe Austria, Lithuania, Luxembourg, Poland, Switzerland and Ukraine. It is a sterile corticolous species with conspicuous and sometimes shortly stalked pycnidia whose outer walls produce gyrophoric acid. Its position in the genus Fellhanera (Pilocarpaceae) is tentative and further studies may necessitate its transfer to another genu

Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models

Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making

On D0-branes in Gepner models

We show why and when D0-branes at the Gepner point of Calabi-Yau manifolds given as Fermat hypersurfaces exist.Comment: 22 pages, substantial improvements in sections 2 and 3, references added, version to be publishe

Modeling temperature-dependent population dynamics in the excited state of the nitrogen-vacancy center in diamond

The nitrogen-vacancy (NV) center in diamond is well known in quantum metrology and quantum information for its favorable spin and optical properties, which span a wide temperature range from near zero to over 600 K. Despite its prominence, the NV center's photo-physics is incompletely understood, especially at intermediate temperatures between 10-100 K where phonons become activated. In this work, we present a rate model able to describe the cross-over from the low-temperature to the high-temperature regime. Key to the model is a phonon-driven hopping between the two orbital branches in the excited state (ES), which accelerates spin relaxation via an interplay with the ES spin precession. We extend our model to include magnetic and electric fields as well as crystal strain, allowing us to simulate the population dynamics over a wide range of experimental conditions. Our model recovers existing descriptions for the low- and high-temperature limits, and successfully explains various sets of literature data. Further, the model allows us to predict experimental observables, in particular the photoluminescence (PL) emission rate, spin contrast, and spin initialization fidelity relevant for quantum applications. Lastly, our model allows probing the electron-phonon interaction of the NV center and reveals a gap between the current understanding and recent experimental findings