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Sequelae of prematurity triggered by oxidative stress and free radical-mediated tissue damage have coined the term “oxygen radical disease of prematurity”. Caffeine, a potent free radical scavenger and adenosine receptor antagonist, reduces rates of brain damage in preterm infants. In the present study, we investigated the effects of caffeine on oxidative stress markers, anti-oxidative response, inflammation, redox-sensitive transcription factors, apoptosis, and extracellular matrix following the induction of hyperoxia in neonatal rats. The brain of a rat pups at postnatal Day 6 (P6) corresponds to that of a human fetal brain at 28–32 weeks gestation and the neonatal rat is an ideal model in which to investigate effects of oxidative stress and neuroprotection of caffeine on the developing brain. Six-day-old Wistar rats were pre-treated with caffeine and exposed to 80% oxygen for 24 and 48 h. Caffeine reduced oxidative stress marker (heme oxygenase-1, lipid peroxidation, hydrogen peroxide, and glutamate-cysteine ligase catalytic subunit (GCLC)), promoted anti-oxidative response (superoxide dismutase, peroxiredoxin 1, and sulfiredoxin 1), down-regulated pro-inflammatory cytokines, modulated redox-sensitive transcription factor expression (Nrf2/Keap1, and NFκB), reduced pro-apoptotic effectors (poly (ADP-ribose) polymerase-1 (PARP-1), apoptosis inducing factor (AIF), and caspase-3), and diminished extracellular matrix degeneration (matrix metalloproteinases (MMP) 2, and inhibitor of metalloproteinase (TIMP) 1/2). Our study affirms that caffeine is a pleiotropic neuroprotective drug in the developing brain due to its anti-oxidant, anti-inflammatory, and anti-apoptotic properties.
Entre los mundos
(2017)
The paper deals with the increasing growth of embedded systems and their role within structures similar to the Internet (Internet of Things) as those that provide calculating power and are more or less appropriate for analytical tasks. Faced with the example of a cyber-physical manufacturing system, a common objective function is developed with the intention to measure efficient task processing within analytical infrastructures. A first validation is realized on base of an expert panel.
Despite high institutional hurdles for constitutional change, one observes surprisingly many EU treaty revisions. This article takes up the questions of what determines whether a treaty provision is successfully changed and why provisions are renegotiated at subsequent Intergovernmental Conferences. The article presents an institutionalist theory explaining success and renegotiation and tests the theory using all core institutional provisions by means of Qualitative Comparative Analysis. The causal analysis shows that low conflict potential of an issue is sufficient for successfully changing the treaties. Furthermore, high conflict potential of an issue and its fundamental change are sufficient for it to be renegotiated.
Winter precipitation forecast in the European and mediterranean regions using cluster analysis
(2017)
The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.
The past few years have witnessed the emergence of a plethora of transnational climate governance experiments. They have been developed by a broad range of actors, such as cities, non-profit organizations, and private corporations. Several scholars have lately devoted particular attention to voluntary global business initiatives in the policy domain of climate change. Their studies have provided considerable insights into the role and function of such new modes of climate governance. However, the precise nature of the relationship between the various climate governance experiments and the international climate negotiations has not been analyzed in enough detail. Against this backdrop, the present article explores the interplay of a business sector climate governance experiment, i.e. the Greenhouse Gas Protocol (GHG Protocol) with the international climate regime. On the one hand, the article underscores that the GHG Protocol has filled a regulatory gap in global climate policy-making by providing the means for the corporate sector to comprehensively account and report their GHGs. On the other hand, it reveals that the application of the GHG Protocol guidelines depends to a large extent on the existence of an overarching policy framework set up by nation-states at the intergovernmental level. Only if private companies receive a clear political signal that stringent mandatory GHG emission controls and a global market-based instrument are at least likely to be adopted will they put substantial efforts into the accurate measurement and management of their GHGs. Thus, this article points to the limits of climate governance experimentation and suggests that business sector climate governance experiments need to be embedded in a coherent international regulatory setting which generates a clear stimulus for corporate action.
The shape of trait distributions may inform about the selective forces that structure ecological communities. Here, we present a new moment-based approach to classify the shape of observed biomass-weighted trait distributions into normal, peaked, skewed, or bimodal that facilitates spatio-temporal and cross-system comparisons. Our observed phytoplankton trait distributions exhibited substantial variance and were mostly skewed or bimodal rather than normal. Additionally, mean, variance, skewness und kurtosis were strongly correlated. This is in conflict with trait-based aggregate models that often assume normally distributed trait values and small variances. Given these discrepancies between our data and general model assumptions we used the observed trait distributions to test how well different aggregate models with first- or second-order approximations and different types of moment closure predict the biomass, mean trait, and trait variance dynamics using weakly or moderately nonlinear fitness functions. For weakly non-linear fitness functions aggregate models with a second-order approximation and a data-based moment closure that relied on the observed correlations between skewness and mean, and kurtosis and variance predicted biomass and often also mean trait changes fairly well and better than models with first-order approximations or a normal-based moment closure. In contrast, none of the models reflected the changes of the trait variances reliably. Aggregate model performance was often also poor for moderately nonlinear fitness functions. This questions a general applicability of the normal-based approach, in particular for predicting variance dynamics determining the speed of trait changes and maintenance of biodiversity. We evaluate in detail how and why better approximations can be obtained.
Analytic Kantianism
(2017)
Wilfrid Sellars and John McDowell can both be read as proponents of Analytic Kantianism. However, their accounts differ in important detail. In particular, McDowell has criticized Sellars’s account of sensory consciousness in a number of papers (most notably in LFI and SC), both as a reading of Kant and on its systematic merits. The present paper offers a detailed analysis of this criticism and a defense of Sellars’s position against the background of a methodology of transcendental philosophy.
The review describes how morphological priming can be utilised to study the processing of morphologically complex words in bilinguals. The article starts with an overview of established experimental paradigms based on morphological priming, discusses a number of basic methodological pitfalls with regard to experimental design and materials, then reviews previous L2 morphological priming studies, and concludes with a brief discussion of recent developments in the field as well as possible future directions.