Probing interactions of NMD factors in a distance-dependent manner by BioID

The understanding of molecular mechanisms requires the elucidation of protein-protein interaction in vivo. For large multi-factor complexes like those assembling on mRNA, co-immunoprecipitation assays often identify many peripheral interactors that complicate the interpretation of such results and that might conceal other insightful mechanistic connections. Here we address the protein-protein interaction network for key factors in the nonsense-mediated mRNA decay (NMD) pathway in a distant-dependent manner using BioID1,2. In this novel approach, the mutant E. coli biotin-protein ligase BirAR118G is fused to the bait protein and biotinylates proximal proteins promiscuously. Hence, interactors positioned close to the bait in vivo are enriched by streptavidin purification and identified by mass spectrometry or western blotting. We present a validation of the BioID assay and preliminary results for close interactors of UPF1 and other key players in NMD.

Probing interactions of NMD factors in a distance-dependent manner by BioID

The understanding of molecular mechanisms requires the elucidation of protein-protein interaction in vivo. For large multi-factor complexes like those assembling on mRNA, co-immunoprecipitation assays often identify many peripheral interactors that complicate the interpretation of such results and that might conceal other insightful mechanistic connections. Here we address the protein-protein interaction network for key factors in the nonsense-mediated mRNA decay (NMD) pathway in a distant-dependent manner using BioID1,2. In this novel approach, the mutant E. coli biotin-protein ligase BirAR118G is fused to the bait protein and biotinylates proximal proteins promiscuously. Hence, interactors positioned close to the bait in vivo are enriched by streptavidin purification and identified by mass spectrometry or western blotting. We present a validation of the BioID assay and preliminary results for close interactors of UPF1 and other key players in NMD.

Gas distribution in shallow large diameter packed beds

It is important to maintain a uniform distribution of gas and liquid in large diameter packed columns to maintain mass transfer efficiency on scaling up. This work presents measurements and methods of evaluating maldistributed gas flow in packed columns. Little or no previous work has been done in this field. A gas maldistribution number, F, was defined, based on point to point velocity variations in the gas emerging from the top of packed beds. f has a minimum value for a uniformly distributed flow and much larger values for maldistributed flows. A method of testing the quality of vapour distributors is proposed, based on "the variation of f with packed height. A good gas distributor requires a short packed depth to give a good gas distribution. Measurements of gas maldistribution have shown that the principle of dynamic similarity is satisfied if two geometrically similar beds are operated at the same Reynold's number. The validity of f as a good measure of gas maldistribution, and the principle of dynamic similarity are tested statistically by Multi-Factor Analysis of the variance, and visually by the response "surfaces technique. Pressure distribution has been measured in a model of a large diameter packed bed, and shown to be associated with the velocity of the gas in a tangential feed pipe. Two simplified theoretical models are proposed to describe the flow of gases through packed beds and to support the principle of dynamic similarity. These models explain why the packed bed itself causes the flow of gas to become more uniformly distributed. A 1.2m. diameter scaled-down model was constructed geometrically similar to a 7.3m. diameter vacuum crude distillation column. The previously known internal cylinder gas distributor was tested. Three new distributors suitable for use in a large diameter column were developed and tested, these are: Internal Cylinder with Slots and Cross Baffles, Internal Cylinder with Guides in the Annulus, Internal Cylinder with Internal Cross Baffles - It has been shown that this is an excellent distributor.

Relationships Between Hydrology and Soils Describe Vegetation Patterns in Seasonally Flooded Tree Islands of the Southern Everglades, Florida

Tree island ecosystems are important and distinct features of Florida Everglades wetlands. We described the inter-relationships among abiotic factors describing seasonally flooded tree islands and characterized plant–soil relationships in tree islands occurring in a relatively unimpacted area of the Everglades. We used Principal Components Analysis (PCA) to reduce our multi-factor dataset, quantified forest structure and vegetation nutrient dynamics, and related these vegetation parameters to PCA summary variables using linear regression analyses. We found that, of the 21 abiotic parameters used to characterize the ecosystem structure of seasonally flooded tree islands, 13 parameters were significantly correlated with four principal components, and they described 78% of the variance among the study islands. Most variation was described by factors related to soil oxidation and hydrology, exemplifying the sensitivity of tree island structure to hydrologic conditions. PCA summary variables describing tree island structure were related to variability in Chrysobalanus icaco (L.) canopy cover, Ilex cassine (L.) and Salix caroliniana (Michx.) canopy cover, Myrica cerifera (L.) plot frequency, litter turnover, % phosphorus resorption of co-dominant species, and nitrogen nutrient-use efficiency. This study supported findings that vegetation characteristics can be sensitive indicators of variability in tree island ecosystem structure. This study produced valuable, information which was used to recommend ecological targets (i.e. restoration performance measures) for seasonally flooded tree islands in more impacted regions of the Everglades landscape.

Energy efficiency in the Chinese provinces: a fixed effects stochastic frontier spatial Durbin error panel analysis

Energy efficiency improvement has been a key objective of China’s long-term energy policy. In this paper, we derive single-factor technical energy efficiency (abbreviated as energy efficiency) in China from multi-factor efficiency estimated by means of a translog production function and a stochastic frontier model on the basis of panel data on 29 Chinese provinces over the period 2003–2011. We find that average energy efficiency has been increasing over the research period and that the provinces with the highest energy efficiency are at the east coast and the ones with the lowest in the west, with an intermediate corridor in between. In the analysis of the determinants of energy efficiency by means of a spatial Durbin error model both factors in the own province and in first-order neighboring provinces are considered. Per capita income in the own province has a positive effect. Furthermore, foreign direct investment and population density in the own province and in neighboring provinces have positive effects, whereas the share of state-owned enterprises in Gross Provincial Product in the own province and in neighboring provinces has negative effects. From the analysis it follows that inflow of foreign direct investment and reform of state-owned enterprises are important policy handles.

Bond Fund Performance During Recessions and Expansions: Empirical Evidence from a Small Market

This paper provides the first investigation about bond mutual fund performance during recession and expansion periods separately. Based on multi-factor performance evaluation models, results show that bond funds significantly underperform the market during both phases of the business cycle. Nevertheless, unlike equity funds, bond funds exhibit considerably higher alphas during good economic states than during market downturns. These results, however, seem entirely driven by the global financial crisis subperiod. In contrast, during the recession associated to the Euro sovereign debt crisis, bond funds are able to accomplish neutral performance. This improved performance throughout the debt crisis seems to be related to more conservative investment strategies, which reflect an increase in managers’ risk aversion.

Pricing derivatives with stochastic volatility

This Ph.D. thesis contains 4 essays in mathematical finance with a focus on pricing Asian option (Chapter 4), pricing futures and futures option (Chapter 5 and Chapter 6) and time dependent volatility in futures option (Chapter 7). In Chapter 4, the applicability of the Albrecher et al.(2005)'s comonotonicity approach was investigated in the context of various benchmark models for equities and com- modities. Instead of classical Levy models as in Albrecher et al.(2005), the focus is the Heston stochastic volatility model, the constant elasticity of variance (CEV) model and the Schwartz (1997) two-factor model. It is shown that the method delivers rather tight upper bounds for the prices of Asian Options in these models and as a by-product delivers super-hedging strategies which can be easily implemented. In Chapter 5, two types of three-factor models were studied to give the value of com- modities futures contracts, which allow volatility to be stochastic. Both these two models have closed-form solutions for futures contracts price. However, it is shown that Model 2 is better than Model 1 theoretically and also performs very well empiri- cally. Moreover, Model 2 can easily be implemented in practice. In comparison to the Schwartz (1997) two-factor model, it is shown that Model 2 has its unique advantages; hence, it is also a good choice to price the value of commodity futures contracts. Fur- thermore, if these two models are used at the same time, a more accurate price for commodity futures contracts can be obtained in most situations. In Chapter 6, the applicability of the asymptotic approach developed in Fouque et al.(2000b) was investigated for pricing commodity futures options in a Schwartz (1997) multi-factor model, featuring both stochastic convenience yield and stochastic volatility. It is shown that the zero-order term in the expansion coincides with the Schwartz (1997) two-factor term, with averaged volatility, and an explicit expression for the first-order correction term is provided. With empirical data from the natural gas futures market, it is also demonstrated that a significantly better calibration can be achieved by using the correction term as compared to the standard Schwartz (1997) two-factor expression, at virtually no extra effort. In Chapter 7, a new pricing formula is derived for futures options in the Schwartz (1997) two-factor model with time dependent spot volatility. The pricing formula can also be used to find the result of the time dependent spot volatility with futures options prices in the market. Furthermore, the limitations of the method that is used to find the time dependent spot volatility will be explained, and it is also shown how to make sure of its accuracy.

The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

Over-expression and purification strategies for recombinant multi-protein oligomers: A case study of Mycobacterium tuberculosis sigma/anti-sigma factor protein complexes

The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the sigma factor/anti-sigma factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of sigma factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. (C) 2010 Elsevier Inc. All rights reserved.

Understanding multi-asset factor models: Factor exposure interpretation

Field lab: Business project

Automatic dimming multi-lamp fluorescent management system with active input power factor corrector stage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Risk Factor Analysis of Late Survival After Heart Transplantation According to Donor Profile: A Multi-Institutional Retrospective Study of 512 Transplants

Introduction. Patients with terminal heart failure have increased more than the available organs leading to a high mortality rate on the waiting list. Use of Marginal and expanded criteria donors has increased due to the heart shortage. Objective. We analyzed all heart transplantations (HTx) in Sao Paulo state over 8 years for donor profile and recipient risk factors. Method. This multi-institutional review collected HTx data from all institutions in the state of Sao Paulo, Brazil. From 2002 to 2008 (6 years), only 512 (28.8%) of 1777 available heart donors were accepted for transplantation. All medical records were analyzed retrospectively; none of the used donors was excluded, even those considered to be nonstandard. Results. The hospital mortality rate was 27.9% (n = 143) and the average follow-up time was 29.4 +/- 28.4 months. The survival rate was 55.5% (n = 285) at 6 years after HTx. Univariate analysis showed the following factors to impact survival: age (P = .0004), arterial hypertension (P = .4620), norepinephrine (P = .0450), cardiac arrest (P = .8500), diabetes mellitus (P = .5120), infection (P = .1470), CKMB (creatine kinase MB) (P = .8694), creatinine (P = .7225), and Na+ (P = .3273). On multivariate analysis, only age showed significance; logistic regression showed a significant cut-off at 40 years: organs from donors older than 40 years showed a lower late survival rates (P = .0032). Conclusions. Donor age older than 40 years represents an important risk factor for survival after HTx. Neither donor gender nor norepinephrine use negatively affected early survival.