Oxidized phospholipid inhibition of toll-like receptor (TLR) signaling is restricted to TLR2 and TLR4 roles for cd14, lps-binding protein, and md2 as targets for specificity of inhibition

The generation of reactive oxygen species is a central feature of inflammation that results in the oxidation of host phospholipids. Oxidized phospholipids, such as 1-palmitoyl-2-arachidonyl-sn-glycero-3-phosphorylcholine (OxPAPC), have been shown to inhibit signaling induced by bacterial lipopeptide or lipopolysac-charide (LPS), yet the mechanisms responsible for the inhibition of Toll-like receptor (TLR) signaling by OxPAPC remain incompletely understood. Here, we examined the mechanisms by which OxPAPC inhibits TLR signaling induced by diverse ligands in macrophages, smooth muscle cells, and epithelial cells. OxPAPC inhibited tumor necrosis factor- production, IB degradation, p38 MAPK phosphorylation, and NF-B-dependent reporter activation induced by stimulants of TLR2 and TLR4 (Pam3CSK4 and LPS) but not by stimulants of other TLRs (poly(I·C), flagellin, loxoribine, single-stranded RNA, or CpG DNA) in macrophages and HEK-293 cells transfected with respective TLRs and significantly reduced inflammatory responses in mice injected subcutaneously or intraperitoneally with Pam3CSK4. Serum proteins, including CD14 and LPS-binding protein, were identified as key targets for the specificity of TLR inhibition as supplementation with excess serum or recombinant CD14 or LBP reversed TLR2 inhibition by OxPAPC, whereas serum accessory proteins or expression of membrane CD14 potentiated signaling via TLR2 and TLR4 but not other TLRs. Binding experiments and functional assays identified MD2 as a novel additional target of OxPAPC inhibition of LPS signaling. Synthetic phospholipid oxidation products 1-palmitoyl-2-(5-oxovaleryl)-sn-glycero-3-phosphocholine and 1-palmitoyl-2-glutaryl-sn-glycero-3-phosphocholine inhibited TLR2 signaling from 30 µM. Taken together, these results suggest that oxidized phospholipid-mediated inhibition of TLR signaling occurs mainly by competitive interaction with accessory proteins that interact directly with bacterial lipids to promote signaling via TLR2 or TLR4.

From 'perfect mix' to 'potion magique':regulatory T cells and anti-inflammatory cytokines as adjuvant targets

The efficacy of vaccines can be greatly improved by the addition of adjuvants, which enhance and modify immune responses. Historically, adjuvants have been discovered empirically by using experimental models.

Three-dimensional calibration targets for optical coherence tomography

The recent expansion of clinical applications for optical coherence tomography (OCT) is driving the development of approaches for consistent image acquisition. There is a simultaneous need for time-stable, easy-to-use imaging targets for calibration and standardization of OCT devices. We present calibration targets consisting of three-dimensional structures etched into nanoparticle-embedded resin. Spherical iron oxide nanoparticles with a predominant particle diameter of 400 nm were homogeneously dispersed in a two part polyurethane resin and allowed to harden overnight. These samples were then etched using a precision micromachining femtosecond laser with a center wavelength of 1026 nm, 100kHz repetition rate and 450 fs pulse duration. A series of lines in depth were etched, varying the percentage of inscription energy and speed of the translation stage moving the target with respect to the laser. Samples were imaged with a dual wavelength spectral-domain OCT system and point-spread function of nanoparticles within the target was measured.

Individualized glycaemic targets and pharmacotherapy in type 2 diabetes

The Global Partnership for Effective Diabetes Management, established to provide practical guidance to improve patient outcomes in diabetes, has developed and modified recommendations to improve glycaemic control in type 2 diabetes. The Global Partnership advocates an individualized therapeutic approach and, as part of the process to customize therapy, has previously identified specific type 2 diabetes patient subgroups that require special consideration. This article builds on earlier publications, expanding the scope of practical guidance to include newly diagnosed individuals with complications and women with diabetes in pregnancy. Good glycaemic control remains the cornerstone of managing type 2 diabetes, and plays a vital role in preventing or delaying the onset and progression of diabetic complications. Individualizing therapeutic goals and treatments to meet glycaemic targets safely and without delay remains paramount, in addition to a wider programme of care to reduce cardiovascular risk factors and improve patient outcomes. © The Author(s) 2013.

Three-dimensional calibration targets for optical coherence tomography

The recent expansion of clinical applications for optical coherence tomography (OCT) is driving the development of approaches for consistent image acquisition. There is a simultaneous need for time-stable, easy-to-use imaging targets for calibration and standardization of OCT devices. We present calibration targets consisting of three-dimensional structures etched into nanoparticle-embedded resin. Spherical iron oxide nanoparticles with a predominant particle diameter of 400 nm were homogeneously dispersed in a two part polyurethane resin and allowed to harden overnight. These samples were then etched using a precision micromachining femtosecond laser with a center wavelength of 1026 nm, 100kHz repetition rate and 450 fs pulse duration. A series of lines in depth were etched, varying the percentage of inscription energy and speed of the translation stage moving the target with respect to the laser. Samples were imaged with a dual wavelength spectral-domain OCT system and point-spread function of nanoparticles within the target was measured.

The design of high-power accelerator targets

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Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

The Inflation Index Prognosis Based on the Method of Decision-Marking “Tree”

The description of the support system for marking decision in terms of prognosing the inflation level based on the multifactor dependence represented by the decision – marking “tree” is given in the paper. The interrelation of factors affecting the inflation level – economic, financial, political, socio-demographic ones, is considered. The perspectives for developing the method of decision – marking “tree”, and pointing out the so- called “narrow” spaces and further analysis of possible scenarios for inflation level prognosing in particular, are defined.

Meeting 2050 CO2 emissions reduction targets:The potential for electric vehicles

This chapter explores the potential for electric vehicles to contribute to decarbonising surface transport. Decarbonising transport is a major global challenge-meeting CO2 emissions reduction targets for 2050, with a rapidly growing, and urbanising global population.

Inflation convergence in Europe

Convergence has been a popular theme in applied economics since the seminal papers of Barro (1991) and Barro and Sala-i-Martin (1992). The very notion of convergence quickly becomes problematic from an academic viewpoint however when we try and formalise a framework to think about these issues. In the light of the abundance of available convergence concepts, it would be useful to have a more universal framework that encompassed existing concepts as special cases. Moreover, much of the convergence literature has treated the issue as a zero-one outcome. We argue that it is more sensible and useful for policy decision makers and academic researchers to consider also ongoing convergence over time. Assessing the progress of ongoing convergence is one interesting and important means of evaluating whether the Eastern European New Member Countries (NMC) of the European Union (EU) are getting closer to being deemed “ready” to join the European Monetary Union (EMU), that is, fulfilling the Maastricht convergence criteria.

Inflation forecasting, relative price variability and skewness

This article presents out-of-sample inflation forecasting results based on relative price variability and skewness. It is demonstrated that forecasts on long horizons of 1.5-2 years are significantly improved if the forecast equation is augmented with skewness. © 2010 Taylor & Francis.

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regressiontechniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a nave random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists' long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies. © 2010 Elsevier B.V. All rights reserved.

Inflation, currency substitution and dollarization: The case of Argentina

This dissertation discusses the relationship between inflation, currency substitution and dollarization that has taken place in Argentina for the past several decades.^ First, it is shown that when consumers are able to hold only domestic monetary balances (without capital mobility) an increase in the rate of inflation will produce a balance of payments deficit. We then look at the same issue but with heterogeneous consumers, this heterogeneity being generated by non-proportional lump-sum transfers.^ Second, we discussed some necessary assumptions related to currency substitution models and concluded that there was no a-priori conclusion on whether currencies should be assumed to be "cooperant" or "non-cooperant" in utility. That is to say, whether individuals held different currencies together or one instead of the other.^ Third, we went into discussing the issue of currency substitution as being a constraint on governments' inflationary objectives rather than a choice of those governments to avoid hyperinflations. We showed that imperfect substitutability between currencies does not "reduce the scope for rational (hyper)inflationary processes" as it had been previously argued. It will ultimately depend on the parametrization used and not on the intrinsic characteristics of imperfect substitutability between currencies.^ We further showed that in Argentina, individuals have been able to endogenize the money supply by holding foreign monetary balances. We argued that the decision to hold foreign monetary balances by individuals is always a second best due to the trade-off between holding foreign monetary balances and consumption. For some levels of income, consumption, and foreign inflation, individuals would prefer to hold domestic monetary balances rather than foreign ones.^ We then modeled the distinction between dollarization and currency substitution. We concluded that although dollarization is necessary for currency substitution to take place, the decision to use foreign monetary balances for transactions purposes is largely independent from the dollarization process.^ Finally, we concluded that Argentina should not fully dollarize its economy because dollarization is always a second best to using a domestic currency. Further, we argued that a fixed exchange system would be better than a flexible exchange rate or a "crawling-peg" system because of the characteristics of the political system and the possibilities of "mass praetorianism" to develop, which is intricately linked to "populist" solutions. ^

Aquatic fauna as indicators for Everglades restoration: Applying dynamic targets in assessments

A major goal of the Comprehensive Everglades Restoration Plan (CERP) is to recover historical (pre-drainage) wading bird rookeries and reverse marked decreases in wading bird nesting success in Everglades National Park. To assess efforts to restore wading birds, a trophic hypothesis was developed that proposes seasonal concentrations of small-fish and crustaceans (i.e., wading bird prey) were a key factor to historical wading bird success. Drainage of the Everglades has diminished these seasonal concentrations, leading to a decline in wading bird nesting and displacing them from their historical nesting locations. The trophic hypothesis predicts that restoring historical hydrological patterns to pre-drainage conditions will recover the timing and location of seasonally concentrated prey, ultimately restoring wading bird nesting and foraging to the southern Everglades. We identified a set of indicators using small-fish and crustaceans that can be predicted from hydrological targets and used to assess management success in regaining suitable wading bird foraging habitat. Small-fish and crustaceans are key components of the Everglades food web and are sensitive to hydrological management, track hydrological history with little time lag, and can be studied at the landscape scale. The seasonal hydrological variation of the Everglades that creates prey concentrations presents a challenge to interpreting monitoring data. To account for the variable hydrology of the Everglades in our assessment, we developed dynamic hydrological targets that respond to changes in prevailing regional rainfall. We also derived statistical relationships between density and hydrological drivers for species representing four different life-history responses to drought. Finally, we use these statistical relationships and hydrological targets to set restoration targets for prey density. We also describe a report-card methodology to communicate the results of model-based assessments for communication to a broad audience.