The role of ATM in the cell cycle control of V(D)J recombination

Lymphocyte development requires the assembly of diversified antigen receptor complexes generated by the genetically programmed V(D)J recombination event. Because germline DNA is cut, introducing potentially dangerous double-stranded breaks (DSBs) and rearranged prior to repair, its activity is limited to the non-cycling stages of the cell cycle, G0/G1. The potential involvement of a key mediator, Ataxia Telangiectasia Mutated or ATM, in the DNA damage response (DDR) and cell cycle checkpoints has been implicated in recombination, but its role is not fully understood. Thymic lymphomas from ATM deficient mice contain clonal chromosomal translocations involving the T-cell antigen receptor (TCR). A previous report found ATM and its downstream target p53 associated with V(D)J intermediates, suggesting the DDR senses recombination. In this study, we sought to understand the role of ATM in V(D)J recombination. Developing thymocytes from ATM deficient mice were analyzed according to the cell cycle to detect V(D)J intermediates. Examination of all TCR loci in the non-cycling (G0/G1) and cycling (S/G2/M) fractions revealed the persistence of intermediates in ATM deficient thymocytes, contrary to the wild-type in which intermediates are found only during G0/G1. Further analysis found no defect in end-joining of intermediates, nor were they detected in developed T-cells. Based upon the presence of persisting intermediates, the recombination initiating nuclease Rag-2 was examined; strict regulation limits it to G 0/G1. Rag-2 regulation was not affected by an ATM deficiency as Rag-2 expression remained contained within G0/G 1, indicating recombination is not continuous. To determine if an ATM deficiency affects recognition of V(D)J breaks, sites of recombination identified by a TCR locus or Rag expression were analyzed according to co-localization with a DDR factor phosphorylated immediately after DNA damage, phosphorylated H2AX (γH2AX). No differences in co-localization were found between the wild-type and ATM deficiency, demonstrating ATM deficient lymphocytes retain the ability to recognize DSBs. Together, these results suggest ATM is necessary in the cell cycle regulation of recombination but not essential for the identification of V(D)J breaks. ATM ensures the containment of intermediates within G0/G1 and maintains genomic stability of developing lymphocytes, emphasizing its fundamental role in preventing tumorigenesis.^

Assessment of the effect on statistical power of regression model misspecification by using techniques of mathematical statistics and simulation study

Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

SYSTEMIC TOXICITY IN RODENTS FOLLOWING ACUTE AND SUBCHRONIC INHALATION OF FORMALDEHYDE (FLOW CYTOMETRY, CELL CYCLE KINETICS, ALKALINE ELUTION)

Systemic toxicity was evaluated in Sprague-Dawley (SD) rats and A-strain mice exposed to HCHO inhalation at 0, 0.5, 3, or 15 ppm for six hours/day, five days/week for up to 24 weeks. Toxicity was measured by flow cytometry to detect changes in cell cycle RNA and DNA content and by alkaline elution to detect DNA protein cross-link (DPC) formation.^ A G(,2)M block was detected in SD rat marrow following one week of exposure to 0.5, 3, or 15 ppm HCHO, but this block did not persist. No effect was noticed in mouse marrow. Only a minimal increase in RNA content was detected in rat or mouse marrow while exfoliated lung cells showed a significant increase in RNA activity after one week of exposure.^ Acute exposure in SD rats for four hours/day for one or three days at 150 ppm showed an increase in RNA activity in exfoliated lung cells but not in the marrow after one day. On the third day, dead cells were detected in exfoliated lung cells.^ In alkaline elution studies, no DPC were detected in marrow of SD rats after 24 weeks exposure up to 15 ppm. During acute exposures, a dose response relationship was detected in SD rat exfoliated lung cells which yielded cross-linking factors of 0.954, 1.237, and 1.417 following a four hour exposure to 15, 50, or 150 ppm, respectively. No DPC were detected in the marrow at 150 ppm. In vitro exposures to HCHO of CHO and SHE cells and rat marrow cells revealed the production of DPC and DNA-DNA cross-links.^ Cytoxan treatment of SD rats was used to provide positive controls for flow cytometry and alkaline elution. A drastic reduction in RNA content and cycling cells occurred one day following treatment. After four days, RNA content was greatly increased; and on day eleven the marrow had regenerated. DPCs were detected in both the marrow and the exfoliated lung cells.^ The lack of significant responses in SD rats and A-strain mice below 15 ppm HCHO is explainable by host defense mechanisms. Apparently, the mucociliary apparatus and enzymatic detoxification are sufficient to reduce systemic toxicity to low level concentrations of formaldehyde. ^

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Carbon cycle change in the Eocene

The transition from the extreme global warmth of the early Eocene 'greenhouse' climate ~55 million years ago to the present glaciated state is one of the most prominent changes in Earth's climatic evolution. It is widely accepted that large ice sheets first appeared on Antarctica ~34 million years ago, coincident with decreasing atmospheric carbon dioxide concentrations and a deepening of the calcite compensation depth in the world's oceans, and that glaciation in the Northern Hemisphere began much later, between 10 and 6 million years ago. Here we present records of sediment and foraminiferal geochemistry covering the greenhouse-icehouse climate transition. We report evidence for synchronous deepening and subsequent oscillations in the calcite compensation depth in the tropical Pacific and South Atlantic oceans from ~42 million years ago, with a permanent deepening 34 million years ago. The most prominent variations in the calcite compensation depth coincide with changes in seawater oxygen isotope ratios of up to 1.5 per mil, suggesting a lowering of global sea level through significant storage of ice in both hemispheres by at least 100 to 125 metres. Variations in benthic carbon isotope ratios of up to ~1.4 per mil occurred at the same time, indicating large changes in carbon cycling. We suggest that the greenhouse-icehouse transition was closely coupled to the evolution of atmospheric carbon dioxide, and that negative carbon cycle feedbacks may have prevented the permanent establishment of large ice sheets earlier than 34 million years ago.

Model results of sensitivity experiments for marine nitrogen cycle in four NetCDF files

The marine nitrogen (N) inventory is thought to be stabilized by negative feedback mechanisms that reduce N inventory excursions relative to the more slowly overturning phosphorus inventory. Using a global biogeochemical ocean circulation model we show that negative feedbacks stabilizing the N inventory cannot persist if a close spatial association of N2 fixation and denitrification occurs. In our idealized model experiments, nitrogen deficient waters, generated by denitrification, stimulate local N2 fixation activity. But, because of stoichiometric constraints, the denitrification of newly fixed nitrogen leads to a net loss of N. This can enhance the N deficit, thereby triggering additional fixation in a vicious cycle, ultimately leading to a runaway N loss. To break this vicious cycle, and allow for stabilizing negative feedbacks to occur, inputs of new N need to be spatially decoupled from denitrification. Our idealized model experiments suggest that factors such as iron limitation or dissolved organic matter cycling can promote such decoupling and allow for negative feedbacks that stabilize the N inventory. Conversely, close spatial co-location of N2 fixation and denitrification could lead to net N loss.

Phytoplankton responses and associated carbon cycling during shipboard carbonate chemistry manipulation experiments conducted around Northwest European shelf seas

The ongoing oceanic uptake of anthropogenic carbon dioxide (CO2) is significantly altering the carbonate chemistry of seawater, a phenomenon referred to as ocean acidification. Experimental manipulations have been increasingly used to gauge how continued ocean acidification will potentially impact marine ecosystems and their associated biogeochemical cycles in the future; however, results amongst studies, particularly when performed on natural communities, are highly variable, which may reflect community/environment-specific responses or inconsistencies in experimental approach. To investigate the potential for identification of more generic responses and greater experimentally reproducibility, we devised and implemented a series (n = 8) of short-term (2-4 days) multi-level (>=4 conditions) carbonate chemistry/nutrient manipulation experiments on a range of natural microbial communities sampled in Northwest European shelf seas. Carbonate chemistry manipulations and resulting biological responses were found to be highly reproducible within individual experiments and to a lesser extent between geographically separated experiments. Statistically robust reproducible physiological responses of phytoplankton to increasing pCO2, characterised by a suppression of net growth for small-sized cells (<10 µm), were observed in the majority of the experiments, irrespective of natural or manipulated nutrient status. Remaining between-experiment variability was potentially linked to initial community structure and/or other site-specific environmental factors. Analysis of carbon cycling within the experiments revealed the expected increased sensitivity of carbonate chemistry to biological processes at higher pCO2 and hence lower buffer capacity. The results thus emphasise how biogeochemical feedbacks may be altered in the future ocean.

Ocean Acidification Affects Redox-Balance and Ion-Homeostasis in the Life-Cycle Stages of Emiliania huxleyi

Ocean Acidification (OA) has been shown to affect photosynthesis and calcification in the coccolithophore Emiliania huxleyi, a cosmopolitan calcifier that significantly contributes to the regulation of the biological carbon pumps. Its non-calcifying, haploid life-cycle stage was found to be relatively unaffected by OA with respect to biomass production. Deeper insights into physiological key processes and their dependence on environmental factors are lacking, but are required to understand and possibly estimate the dynamics of carbon cycling in present and future oceans. Therefore, calcifying diploid and non-calcifying haploid cells were acclimated to present and future CO2 partial pressures (pCO2; 38.5 Pa vs. 101.3 Pa CO2) under low and high light (50 vs. 300 µmol photons/m**2 /s). Comparative microarray-based transcriptome profiling was used to screen for the underlying cellular processes and allowed to follow up interpretations derived from physiological data. In the diplont, the observed increases in biomass production under OA are likely caused by stimulated production of glycoconjugates and lipids. The observed lowered calcification under OA can be attributed to impaired signal-transduction and ion-transport. The haplont utilizes distinct genes and metabolic pathways, reflecting the stage-specific usage of certain portions of the genome. With respect to functionality and energy-dependence, however, the transcriptomic OA-responses resemble those of the diplont. In both life-cycle stages, OA affects the cellular redox-state as a master regulator and thereby causes a metabolic shift from oxidative towards reductive pathways, which involves a reconstellation of carbon flux networks within and across compartments. Whereas signal transduction and ion-homeostasis appear equally OA-sensitive under both light intensities, the effects on carbon metabolism and light physiology are clearly modulated by light availability. These interactive effects can be attributed to the influence of OA and light on the redox equilibria of NAD and NADP, which function as major sensors for energization and stress. This generic mode of action of OA may therefore provoke similar cell-physiological responses in other protists.

Stochastic homogenization of the laser intensity to improve the irradiation uniformity of capsules directly driven by thousands laser beams

Illumination uniformity of a spherical capsule directly driven by laser beams has been assessed numerically. Laser facilities characterized by ND = 12, 20, 24, 32, 48 and 60 directions of irradiation with associated a single laser beam or a bundle of NB laser beams have been considered. The laser beam intensity profile is assumed super-Gaussian and the calculations take into account beam imperfections as power imbalance and pointing errors. The optimum laser intensity profile, which minimizes the root-mean-square deviation of the capsule illumination, depends on the values of the beam imperfections. Assuming that the NB beams are statistically independents is found that they provide a stochastic homogenization of the laser intensity associated to the whole bundle, reducing the errors associated to the whole bundle by the factor  , which in turn improves the illumination uniformity of the capsule. Moreover, it is found that the uniformity of the irradiation is almost the same for all facilities and only depends on the total number of laser beams Ntot = ND × NB.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

Analysis of the Behaviour of Biofuel-Fired Gas Turbine Power Plants

The utilisation of biofuels in gas turbines is a promising alternative to fossil fuels for power generation. It would lead to significant reduction of CO2 emissions using an existing combustion technology, although significant changes seem to be needed and further technological development is necessary. The goal of this work is to perform energy and exergy analyses of the behaviour of gas turbines fired with biogas, ethanol and synthesis gas (bio-syngas), compared with natural gas. The global energy transformation process (i.e. from biomass to electricity) has also been studied. Furthermore, the potential reduction of CO2 emissions attained by the use of biofuels has been determined, considering the restrictions regarding biomass availability. Two different simulation tools have been used to accomplish the aims of this work. The results suggest a high interest and the technical viability of the use of Biomass Integrated Gasification Combined Cycle (BIGCC) systems for large scale power generation.

Digital Control Implementation to Reduce the Cost and Improve the Performance of the Control Stage of an Industrial Switched-Mode Power Supply

The main objective of this work is the design and implementation of the digital control stage of a 280W AC/DC industrial power supply in a single low-cost microcontroller to replace the analog control stage. The switch-mode power supply (SMPS) consists of a PFC boost converter with fixed frequency operation and a variable frequency LLC series resonant DC/DC converter. Input voltage range is 85VRMS-550VRMS and the output voltage range is 24V-28V. A digital controller is especially suitable for this kind of SMPS to implement its multiple functionalities and to keep the efficiency and the performance high over the wide range of input voltages. Additional advantages of the digital control are reliability and size. The optimized design and implementation of the digital control stage it is presented. Experimental results show the stable operation of the controlled system and an estimation of the cost reduction achieved with the digital control stage.

Run-time Scalable Architecture for Deblocking Filtering in H.264/AVC-SVC Video Codecs

Systems relying on fixed hardware components with a static level of parallelism can suffer from an underuse of logical resources, since they have to be designed for the worst-case scenario. This problem is especially important in video applications due to the emergence of new flexible standards, like Scalable Video Coding (SVC), which offer several levels of scalability. In this paper, Dynamic and Partial Reconfiguration (DPR) of modern FPGAs is used to achieve run-time variable parallelism, by using scalable architectures where the size can be adapted at run-time. Based on this proposal, a scalable Deblocking Filter core (DF), compliant with the H.264/AVC and SVC standards has been designed. This scalable DF allows run-time addition or removal of computational units working in parallel. Scalability is offered together with a scalable parallelization strategy at the macroblock (MB) level, such that when the size of the architecture changes, MB filtering order is modified accordingly

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.