Chronic systemic therapy with low-dose morpholino oligomers ameliorates the pathology and normalizes locomotor behavior in mdx Mice

The administration of antisense oligonucleotides (AOs) to skip one or more exons in mutated forms of the DMD gene and so restore the reading frame of the transcript is one of the most promising approaches to treat Duchenne muscular dystrophy (DMD). At present, preclinical studies demonstrating the efficacy and safety of long-term AO administration have not been conducted. Furthermore, it is essential to determine the minimal effective dose and frequency of administration. In this study, two different low doses (LDs) of phosphorodiamidate morpholino oligomer (PMO) designed to skip the mutated exon 23 in the mdx dystrophic mouse were administered for up to 12 months. Mice treated for 50 weeks showed a substantial dose-related amelioration of the pathology, particularly in the diaphragm. Moreover, the generalized physical activity was profoundly enhanced compared to untreated mdx mice showing that widespread, albeit partial, dystrophin expression restores the normal activity in mdx mice. Our results show for the first time that a chronic long-term administration of LDs of unmodified PMO, equivalent to doses in use in DMD boys, is safe, significantly ameliorates the muscular dystrophic phenotype and improves the activity of dystrophin-deficient mice, thus encouraging the further clinical translation of this approach in humans.

Factors contributing to the development of extreme North Atlantic cyclones and their relationship with the NAO

The occurrence of extreme cyclones is analysed in terms of their relationship to the NAO phase and the dominating environmental variables controlling their intensification. These are latent energy (equivalent potential temperature 850 hPa is used as an indicator), upper-air baroclinicity, horizontal divergence and jet stream strength. Cyclones over the North Atlantic are identified and tracked using a numerical algorithm, permitting a detailed analysis of their life cycles. Extreme cyclones are selected as the 10% most severe in terms of intensity. Investigations focus on the main strengthening phase of each cyclone. The environmental factors are related to the NAO, which affects the location and orientation of the cyclone tracks, thus explaining why extreme cyclones occur more (less) frequently during strong positive (negative) NAO phases. The enhanced number of extreme cyclones in positive NAO phases can be explained by the larger area with suitable growth conditions, which is better aligned with the cyclone tracks and is associated with increased cyclone life time and intensity. Moreover, strong intensification of cyclones is frequently linked to the occurrence of extreme values of growth factors in the immediate vicinity of the cyclone centre. Similar results are found for ECHAM5/OM1 for present day conditions, demonstrating that relationships between the environment factors and cyclones are also valid in the GCM. For future climate conditions (following the SRES A1B scenario), the results are similar, but a small increase of the frequency of extreme values is detected near the cyclone cores. On the other hand, total cyclone numbers decrease by 10% over the North Atlantic. An exception is the region near the British Isles, which features increased track density and intensity of extreme cyclones irrespective of the NAO phase. These changes are associated with an intensified jet stream close to Europe. Moreover, an enhanced frequency of explosive developments over the British Isles is found, leading to more frequent windstorms affecting Europe.

Extreme wind storms over Europe in present and future climate: a cluster analysis approach

Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.

Whistler mode wave growth and propagation in the prenoon magnetosphere

Pitch-angle scattering of electrons can limit the stably trapped particle flux in the magnetosphere and precipitate energetic electrons into the ionosphere. Whistler-mode waves generated by a temperature anisotropy can mediate this pitch-angle scattering over a wide range of radial distances and latitudes, but in order to correctly predict the phase-space diffusion, it is important to characterise the whistler-mode wave distributions that result from the instability. We use previously-published observations of number density, pitch-angle anisotropy and phase space density to model the plasma in the quiet pre-noon magnetosphere (defined as periods when AE<100nT). We investigate the global propagation and growth of whistler-mode waves by studying millions of growing ray paths and demonstrate that the wave distribution at any one location is a superposition of many waves at different points along their trajectories and with different histories. We show that for observed electron plasma properties, very few raypaths undergo magnetospheric reflection, most rays grow and decay within 30 degrees of the magnetic equator. The frequency range of the wave distribution at large L can be adequately described by the solutions of the local dispersion relation, but the range of wavenormal angle is different. The wave distribution is asymmetric with respect to the wavenormal angle. The numerical results suggest that it is important to determine the variation of magnetospheric parameters as a function of latitude, as well as local time and L-shell.

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35–72°N and 15°W–43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and +200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small.

Agriculture and the life histories of Mauritius kestrels

Habitat modification for agriculture is one of the greatest current threats to global biodiversity. Studies show large-scale population declines and short-term demographic impacts, but knowledge of the long-term effects of agriculture on individuals remains poor. This thesis examines the short- and long-term impact of agriculture on a reintroduced population of the Mauritius kestrel Falco punctatus, a tropical forest-dwelling raptor endemic to the island of Mauritius, that also utilises agricultural habitats. This population is a particularly appropriate model system, because complete life history data exists for individuals over a 22-year period, alongside detailed habitat and climate data. Agriculture has a short-term detrimental effect on Mauritius kestrel breeding success by exacerbating the seasonal decline in fledgling production. This is partly driven by the habitat-specific composition of the prey community that kestrels exploit to feed their chicks. The fledglings from agricultural territories tend to recruit in agricultural territories. This is largely due to poor natal dispersal and fine-scale spatial autocorrelation in the habitat matrix. Breeders do not respond to agriculture in the breeding territory by dispersing, unless the pair bond is broken. Therefore, individuals originating in agricultural territories tend to recruit, and remain in, agricultural territories throughout their lives. In addition to this, females from agricultural natal territories have shorter lifespans, schedule their peak reproductive output earlier in life, and exhibit more rapid senescence than non-agricultural females. The combination of this long-term effect and the adult experience of agriculture imposed by life history and environmental constraints, leads to a lower mean lifetime reproductive rate compared to females originating in non-agricultural habitats. These results demonstrate that agriculture experienced in early life has a lifelong effect on individuals. The effects can persist in time and space, with potentially delayed effects on population dynamics. These findings are important for understanding species’ responses to agricultural expansion.

The 30-year TAMSAT African rainfall climatology and time-series (TARCAT) dataset

African societies are dependent on rainfall for agricultural and other water-dependent activities, yet rainfall is extremely variable in both space and time and reoccurring water shocks, such as drought, can have considerable social and economic impacts. To help improve our knowledge of the rainfall climate, we have constructed a 30-year (1983–2012), temporally consistent rainfall dataset for Africa known as TARCAT (TAMSAT African Rainfall Climatology And Time-series) using archived Meteosat thermal infra-red (TIR) imagery, calibrated against rain gauge records collated from numerous African agencies. TARCAT has been produced at 10-day (dekad) scale at a spatial resolution of 0.0375°. An intercomparison of TARCAT from 1983 to 2010 with six long-term precipitation datasets indicates that TARCAT replicates the spatial and seasonal rainfall patterns and interannual variability well, with correlation coefficients of 0.85 and 0.70 with the Climate Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) gridded-gauge analyses respectively in the interannual variability of the Africa-wide mean monthly rainfall. The design of the algorithm for drought monitoring leads to TARCAT underestimating the Africa-wide mean annual rainfall on average by −0.37 mm day−1 (21%) compared to other datasets. As the TARCAT rainfall estimates are historically calibrated across large climatically homogeneous regions, the data can provide users with robust estimates of climate related risk, even in regions where gauge records are inconsistent in time.

Rare variants in LRRK1 and Parkinson's disease

Approximately 20 % of individuals with Parkinson's disease (PD) report a positive family history. Yet, a large portion of causal and disease-modifying variants is still unknown. We used exome sequencing in two affected individuals from a family with late-onset PD to identify 15 potentially causal variants. Segregation analysis and frequency assessment in 862 PD cases and 1,014 ethnically matched controls highlighted variants in EEF1D and LRRK1 as the best candidates. Mutation screening of the coding regions of these genes in 862 cases and 1,014 controls revealed several novel non-synonymous variants in both genes in cases and controls. An in silico multi-model bioinformatics analysis was used to prioritize identified variants in LRRK1 for functional follow- up. However, protein expression, subcellular localization, and cell viability were not affected by the identified variants. Although it has yet to be proven conclusively that variants in LRRK1 are indeed causative of PD, our data strengthen a possible role for LRRK1 in addition to LRRK2 in the genetic underpinnings of PD but, at the same time, highlight the difficulties encountered in the study of rare variants identified by next-generation sequencing in diseases with autosomal dominant or complex patterns of inheritance.

Propagation of the Madden–Julian Oscillation and scale interaction with the diurnal cycle in a high-resolution GCM

The Madden–Julian Oscillation (MJO) is the chief source of tropical intra-seasonal variability, but is simulated poorly by most state-of-the-art GCMs. Common errors include a lack of eastward propagation at the correct frequency and zonal extent, and too small a ratio of eastward- to westward-propagating variability. Here it is shown that HiGEM, a high-resolution GCM, simulates a very realistic MJO with approximately the correct spatial and temporal scale. Many MJO studies in GCMs are limited to diagnostics which average over a latitude band around the equator, allowing an analysis of the MJO’s structure in time and longitude only. In this study a wider range of diagnostics is applied. It is argued that such an approach is necessary for a comprehensive analysis of a model’s MJO. The standard analysis of Wheeler and Hendon (Mon Wea Rev 132(8):1917–1932, 2004; WH04) is applied to produce composites, which show a realistic spatial structure in the MJO envelopes but for the timing of the peak precipitation in the inter-tropical convergence zone, which bifurcates the MJO signal. Further diagnostics are developed to analyse the MJO’s episodic nature and the “MJO inertia” (the tendency to remain in the same WH04 phase from one day to the next). HiGEM favours phases 2, 3, 6 and 7; has too much MJO inertia; and dies out too frequently in phase 3. Recent research has shown that a key feature of the MJO is its interaction with the diurnal cycle over the Maritime Continent. This interaction is present in HiGEM but is unrealistically weak.

Interactive effect of cowpea variety, dose and exposure time on bruchid tolerance to botanical pesticides

Callosobruchus maculatus has for years remained a serious menace in cowpea in Sub-Sahara Africa. The objective of this study was to investigate the effect of genotypic cowpea (Vigna unguiculata (L.) Walp) varieties, time and dose on C. maculatus exposed to powders of Piper guineense and Eugenia aromatica. Irrespective of duration and botanicals, bruchid reared on KDV showed the highest tolerance to both plant materials; while their counterparts from IAR48V were the most susceptible. Median lethal time (LT50) also varied according to the plant materials; with the highest in KDV reared bruchid [P. guineense: KDV (18.31), IAR48V (9.27), IFBV (13.17); E. aromatica: KDV (76.01), IAR48V (5.59), IFBV (6.49)]. There was a significant impact of cowpea variety (V), exposure time (T) and dose (D) on the tolerance of C. maculatus to both plant materials. The effect of all two-way (VxT, VxD, DxT) and three way interactions (V×T×D) on the tolerance of C. maculatus to both plant materials was also significant. Varietal effect was more pronounced in bruchids exposed to E. aromatica; while exposure time was more pronounced in bruchids exposed to P. guineense.

Mapping power law distributions in digital health social networks: methods, interpretations, and practical implications

BACKGROUND: Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. OBJECTIVES: The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. METHODS: Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. RESULTS: All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). CONCLUSIONS: This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.

High intake of fruits and vegetables predicts weight loss in Brazilian overweight adults

To determine whether changes in dietary intakes predict weight loss, we studied 80 overweight adults who attended a nutritional counseling program during 6 months of follow-up at a primary health care center in Brazil. Habitual diet was assessed using a validated food frequency questionnaire at baseline and after 6 months. The mean age (+/-SD) of the participants was 46.5 +/- 9.5 years, and their mean body mass index was 29 +/- 3 kg/m(2) at baseline. After 6 months, the differences in body weight and fruit/vegetable intake were -1.4 +/- 3 kg and 109 +/- 320 g daily, respectively. Using multiple linear regression models adjusted for age, sex, changes in walking time, and total energy intake, the increased intake of dietary fiber from fruits/vegetables was associated with a greater weight loss (beta 1 [95% confidence interval (CI)] = -0.180 [-0.269, -0.0911) after 6 months of follow-up. Similar results were observed for increased intake of vegetables (beta 1 [95% CI] = -0.00497 [-0.008, -0.0021) and fruits (beta 1 [95% CI] = -0.00290 [-0.005, -0.001]) as predictors of weight loss. The increase of 100 g/d of vegetables and fruits represented a body weight loss of 500 and 300 g after 6 months, respectively (P <.05). Our findings support the relevance of increased intakes of fruits and vegetables that may help avoid weight gain in overweight adults. (C) 2008 Elsevier Inc. All rights reserved.

Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Experimental characterization of nonlinear systems: a real-time evaluation of the analogous Chua`s circuit behavior

This paper presents an experimental characterization of the behavior of an analogous version of the Chua`s circuit. The electronic circuit signals are captured using a data acquisition board (DAQ) and processed using LabVIEW environment. The following aspects of the time series analysis are analyzed: time waveforms, phase portraits, frequency spectra, Poincar, sections, and bifurcation diagram. The circuit behavior is experimentally mapped with the parameter variations, where are identified equilibrium points, periodic and chaotic attractors, and bifurcations. These analysis techniques are performed in real-time and can be applied to characterize, with precision, several nonlinear systems.

Evaluation of Postpolymerization as a Function of the Storage Time of Triethylene Glycol Dimethacrylate/2,2-Bis[4-(2-Hydroxy-3-Methacryloxy-Prop-1-Oxy)-Phenyl]-propane Bisphenyl-alpha-Glycidyl Ether Dimethacrylate Copolymers Used in Dental Resins by Differential Scanning Calorimetry and Dynamic Mechanical Analysis

The aim of this work was to evaluate the effect of the storage time on the thermal properties of triethylene glycol dimethacrylate/2,2-bis[4-(2-hydroxy-3-methacryloxy-prop-1-oxy)-phenyl]propane bisphenyl-alpha-glycidyl ether dimethacrylate (TB) copolymers used in formulations of dental resins after photopolymerization. The TB copolymers were prepared by photopolymerization with an Ultrablue IS light-emitting diode, stored in the dark for 160 days at 37 degrees C, and characterized with differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and Fourier transform infrared spectroscopy with attenuated total reflection. DSC curves indicated the presence of an exothermic peak, confirming that the reaction was not completed during the photopolymerization process. This exothermic peak became smaller as a function of the storage time and was shifted at higher temperatures. In DMA studies, a plot of the loss tangent versus the temperature initially showed the presence of two well-defined peaks. The presence of both peaks confirmed the presence of residual monomers that were not converted during the photopolymerization process. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 112: 679-684, 2009