Melatonin and the time window for the expression of the alpha 8 nicotinic acetylcholine receptor in the membrane of chick retinal cells in culture

We have previously shown that melatonin influences the development of alpha 8 nicotinic acetylcholine receptor (nAChR) by measurement of the acetylcholine-induced increase in the extracellular acidification rate (ECAR) in chick retinal cell cultures. Cellular differentiation that takes place between DIV (days in vitro) 4 and DIV 5 yields cells expressing alpha 8 nAChR and results in a significant increase in the ECAR acetylcholine-induced. Blocking melatonin receptors with luzindole for 48 h suppresses the development of functional alpha 8 nAChR. Here we investigated the time window for the effect of melatonin on retinal cell development in culture, and whether this effect was dependent on an increase in the expression of alpha 8 nAChR. First, we confirmed that luzindole was inhibiting the effects of endogenous melatonin, since it increases 2-[(125)I] iodomelatonin (23 pM) binding sites density in a time-dependent manner. Then we observed that acute (15, 60 min, or 12 h) luzindole treatment did not impair acetylcholine-induced increase in the ECAR mediated by activation of alpha 8 nAChR at DIV 5, while chronic treatment (from DIV 3 or DIV 4 till DIV 5, or DIV 3.5 till DIV 4.5) led to a time-dependent reduction of the increase in the acetylcholine-induced ECAR. The binding parameters for [(125)I]-alpha-bungarotoxin (10 nM) sites in membrane were unaffected by melatonin suppression that started at DIV 3. Thus, melatonin surges in the time window that occurs at the final stages of chick retinal cell differentiation in culture is essential for development of the cells expressing alpha 8 nAChR subtype in full functional form. (C) 2010 ISDN. Published by Elsevier Ltd. All rights reserved.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Destructive weighted Poisson cure rate models

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

Combustion iron distribution and deposition

[1] Iron is hypothesized to be an important micronutrient for ocean biota, thus modulating carbon dioxide uptake by the ocean biological pump. Studies have assumed that atmospheric deposition of iron to the open ocean is predominantly from mineral aerosols. For the first time we model the source, transport, and deposition of iron from combustion sources. Iron is produced in small quantities during fossil fuel burning, incinerator use, and biomass burning. The sources of combustion iron are concentrated in the industrialized regions and biomass burning regions, largely in the tropics. Model results suggest that combustion iron can represent up to 50% of the total iron deposited, but over open ocean regions it is usually less than 5% of the total iron, with the highest values (< 30%) close to the East Asian continent in the North Pacific. For ocean biogeochemistry the bioavailability of the iron is important, and this is often estimated by the fraction which is soluble ( Fe(II)). Previous studies have argued that atmospheric processing of the relatively insoluble Fe(III) occurs to make it more soluble ( Fe( II)). Modeled estimates of soluble iron amounts based solely on atmospheric processing as simulated here cannot match the variability in daily averaged in situ concentration measurements in Korea, which is located close to both combustion and dust sources. The best match to the observations is that there are substantial direct emissions of soluble iron from combustion processes. If we assume observed soluble Fe/black carbon ratios in Korea are representative of the whole globe, we obtain the result that deposition of soluble iron from combustion contributes 20-100% of the soluble iron deposition over many ocean regions. This implies that more work should be done refining the emissions and deposition of combustion sources of soluble iron globally.

Unraveling Dynamical Heterogeneity in the Ionic Liquid 1-Butyl-3-methylimidazolium Chloride

Heterogeneous dynamics within a time range of nanoseconds was investigated by molecular dynamics (MD) simulations of 1 -butyl-3-methylimidazolium chloride ([bmim]Cl). After identifying groups of fast and slow ions, it was shown that the separation between the location of the center of mass and the center of charge of cations, d(CMCC), is a signature of such difference in ionic mobility. The distance d(CMCC) can be used as a signature because it relaxes in the time window of the dynamical heterogeneity. The relationship between the parameter dcmcc and conformations of the side alkyl chain in [bmim] is discussed. Since the relatively slow relaxation of dcmcc is a consequence of coexisting polar and nonpolar domains in the bulk, the MD simulations reveal a subtle interplay between structural and dynamical heterogeneity in ionic liquids.

Kinetics of autocatalytic acid hydrolysis of cellulose with crystalline and amorphous fractions

The acid hydrolysis of cellulose with crystalline and amorphous fractions is analyzed on the basis of autocatalytic model with a positive feedback of acid production from the degraded biopolymer. In the condition of low acid rate production compared with hydrolysis rate, both fraction of cellulose decrease exponentially with linear and cubic time dependence, and the normalized number of scissions per cellulose chain follows a sigmoid behavior with reaction time. The model predicts that self generated acidic compounds from cellulose accelerate the degradation of the biopolymer. However, if the acidic compounds produced are volatile species, then their release under low pressure will reduce the global rate of degradation of cellulose toward its intrinsic rate value determined by the residual acid catalyst present in the starting material.

SIMULATIONS OF WINDS OF WEAK-LINED T TAURI STARS. II. THE EFFECTS OF A TILTED MAGNETOSPHERE AND PLANETARY INTERACTIONS

Based on our previous work, we investigate here the effects on the wind and magnetospheric structures of weak-lined T Tauri stars due to a misalignment between the axis of rotation of the star and its magnetic dipole moment vector. In such a configuration, the system loses the axisymmetry presented in the aligned case, requiring a fully three-dimensional (3D) approach. We perform 3D numerical magnetohydrodynamic simulations of stellar winds and study the effects caused by different model parameters, namely the misalignment angle theta(t), the stellar period of rotation, the plasma-beta, and the heating index.. Our simulations take into account the interplay between the wind and the stellar magnetic field during the time evolution. The system reaches a periodic behavior with the same rotational period of the star. We show that the magnetic field lines present an oscillatory pattern. Furthermore, we obtain that by increasing theta(t), the wind velocity increases, especially in the case of strong magnetic field and relatively rapid stellar rotation. Our 3D, time-dependent wind models allow us to study the interaction of a magnetized wind with a magnetized extrasolar planet. Such interaction gives rise to reconnection, generating electrons that propagate along the planet`s magnetic field lines and produce electron cyclotron radiation at radio wavelengths. The power released in the interaction depends on the planet`s magnetic field intensity, its orbital radius, and on the stellar wind local characteristics. We find that a close-in Jupiter-like planet orbiting at 0.05 AU presents a radio power that is similar to 5 orders of magnitude larger than the one observed in Jupiter, which suggests that the stellar wind from a young star has the potential to generate strong planetary radio emission that could be detected in the near future with LOFAR. This radio power varies according to the phase of rotation of the star. For three selected simulations, we find a variation of the radio power of a factor 1.3-3.7, depending on theta(t). Moreover, we extend the investigation done in Vidotto et al. and analyze whether winds from misaligned stellar magnetospheres could cause a significant effect on planetary migration. Compared to the aligned case, we show that the timescale tau(w) for an appreciable radial motion of the planet is shorter for larger misalignment angles. While for the aligned case tau(w) similar or equal to 100 Myr, for a stellar magnetosphere tilted by theta(t) = 30 degrees, tau(w) ranges from similar to 40 to 70 Myr for a planet located at a radius of 0.05 AU. Further reduction on tau(w) might occur for even larger misalignment angles and/or different wind parameters.

A Time Efficient Optical Model for GATE Simulation of a LYSO Scintillation Matrix Used in PET Applications

A time efficient optical model is proposed for GATE simulation of a LYSO scintillation matrix coupled to a photomultiplier. The purpose is to avoid the excessively long computation time when activating the optical processes in GATE. The usefulness of the model is demonstrated by comparing the simulated and experimental energy spectra obtained with the dual planar head equipment for dosimetry with a positron emission tomograph ( DoPET). The procedure to apply the model is divided in two steps. Firstly, a simplified simulation of a single crystal element of DoPET is used to fit an analytic function that models the optical attenuation inside the crystal. In a second step, the model is employed to calculate the influence of this attenuation in the energy registered by the tomograph. The use of the proposed optical model is around three orders of magnitude faster than a GATE simulation with optical processes enabled. A good agreement was found between the experimental and simulated data using the optical model. The results indicate that optical interactions inside the crystal elements play an important role on the energy resolution and induce a considerable degradation of the spectra information acquired by DoPET. Finally, the same approach employed by the proposed optical model could be useful to simulate a scintillation matrix coupled to a photomultiplier using single or dual readout scheme.

Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents

We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account the market price and the perceived fundamental value of the asset. The resulting excess demand is coupled to the market price. Rigorous analysis reveals that this feedback may lead to price oscillations, a single bounce, or monotonic price behaviour. The model is a rare example of an analytically tractable interacting-agent model which allows LIS to deduce in detail the origin of these different collective patterns. For a natural choice of initial distribution, the results are independent of the graph structure that models the peer network of agents whose decisions influence each other. (C) 2009 Elsevier B.V. All rights reserved.