Storage protein profiles in Spanish and runner market type peanuts and potential markers

BACKGROUND: Proteomic analysis has proven to be the most powerful method for describing plant species and lines, and for identification of proteins in complex mixtures. The strength of this method resides in high resolving power of two-dimensional electrophoresis (2-DE), coupled with highly sensitive mass spectrometry (MS), and sequence homology search. By using this method, we might find polymorphic markers to differentiate peanut subspecies. RESULTS: Total proteins extracted from seeds of 12 different genotypes of cultivated peanut (Arachis hypogaea L.), comprised of runner market (A. hypogaea ssp. hypogaea) and Spanish-bunch market type (A. hypogaea ssp. fastigiata), were separated by electrophoresis on both one- and two-dimensional SDS-PAGE gels. The protein profiles were similar on one-dimensional gels for all tested peanut genotypes. However, peanut genotype A13 lacked one major band with a molecular weight of about 35 kDa. There was one minor band with a molecular weight of 27 kDa that was present in all runner peanut genotypes and the Spanish-derivatives (GT-YY7, GT-YY20, and GT-YY79). The Spanish-derivatives have a runner-type peanut in their pedigrees. The 35 kDa protein in A13 and the 27 kDa protein in runner-type peanut genotypes were confirmed on the 2-D SDS-PAGE gels. Among more than 150 main protein spots on the 2-D gels, four protein spots that were individually marked as spots 1–4 showed polymorphic patterns between runner-type and Spanish-bunch peanuts. Spot 1 (ca. 22.5 kDa, pI 3.9) and spot 2 (ca. 23.5 kDa, pI 5.7) were observed in all Spanish-bunch genotypes, but were not found in runner types. In contrast, spot 3 (ca. 23 kDa, pI 6.6) and spot 4 (ca. 22 kDa, pI 6.8) were present in all runner peanut genotypes but not in Spanish-bunch genotypes. These four protein spots were sequenced. Based on the internal and N-terminal amino acid sequences, these proteins are isoforms (iso-Ara h3) of each other, are iso-allergens and may be modified by post-translational cleavage. CONCLUSION: These results suggest that there may be an association between these polymorphic storage protein isoforms and peanut subspecies fastigiata (Spanish type) and hypogaea (runner type). The polymorphic protein peptides distinguished by 2-D PAGE could be used as markers for identification of runner and Spanish peanuts

A randomized, double-blind, placebo-controlled trial to assess safety and tolerability during treatment of type 2 diabetes with usual diabetes therapy and either Cycloset™ or placebo

Background: Cycloset™ is a quick-release formulation of bromocriptine mesylate, a dopamine agonist, which in animal models of insulin resistance and type 2 diabetes acts centrally to reduce resistance to insulin- mediated suppression of hepatic glucose output and tissue glucose disposal. In such animals, bromocriptine also reduces hepatic triglyceride synthesis and free fatty acid mobilization, manifesting decreases in both plasma triglycerides and free fatty acids. In clinical trials, morning administration of Cycloset™ either as monotherapy or adjunctive therapy to sulfonylurea or insulin reduces HbA1c levels relative to placebo by 0.55–1.2. Cycloset™ therapy also reduces plasma triglycerides and free fatty acid by approximately 25% and 20%, respectively, among those also receiving sulfonylurea therapies. The effects of once-daily morning Cycloset™ therapy on glycemic control and plasma lipids are demonstrable throughout the diurnal portion of the day (7 a.m. to 7 p.m.) across postprandial time points. Methods/Design: 3,095 individuals were randomized in a 2:1 ratio into a one year trial aimed to assess the safety and efficacy of Cycloset™ compared to placebo among individuals receiving a variety of treatments for type 2 diabetes. Eligibility criteria for this randomized placebo controlled trial included: age 30–80, HbA1c ≤ 10%, diabetes therapeutic regimen consisting of diet or no more than two hypoglycemic agents or insulin with or without one additional oral agent (usual diabetes therapy; UDT). The primary safety endpoint will test the hypothesis that the rate of all-cause serious adverse events after one year of usual diabetes therapy (UDT) plus Cycloset™ is not greater than that for UDT plus placebo by more than an acceptable margin defined as a hazard ratio of 1.5 with a secondary endpoint analysis of the difference in the rate of serious cardiovascular events, (myocardial infarction, stroke, coronary revascularization or hospitalization for or angina or congestive heart failure). Efficacy analyses will evaluate effects of Cycloset™ versus placebo on change from baseline in HbA1c, fasting glucose, body weight, waist circumference, blood pressure and plasma lipids. Discussion: This study will extend the current data on Cycloset™ safety, tolerability and efficacy in individuals with type 2 diabetes to include its effects in combination with thiazolodinediones, insulin secretagogues, metformin, alpha-glucosidase inhibitors and exogenous insulin regimens. Trial registration: clinical trials.gov NCT0037767

The Outcome of Phagocytic Cell Division with Infectious Cargo Depends on Single Phagosome Formation

Given that macrophages can proliferate and that certain microbes survive inside phagocytic cells, the question arises as to the post-mitotic distribution of microbial cargo. Using macrophage-like cells we evaluated the post-mitotic distribution of intracellular Cryptococcus yeasts and polystyrene beads by comparing experimental data to a stochastic model. For beads, the post-mitotic distribution was that expected from chance alone. However, for yeast cells the post-mitotic distribution was unequal, implying preferential sorting to one daughter cell. This mechanism for unequal distribution was phagosomal fusion, which effectively reduced the intracellular particle number. Hence, post-mitotic intracellular particle distribution is stochastic, unless microbial and/or host factors promote unequal distribution into daughter cells. In our system unequal cargo distribution appeared to benefit the microbe by promoting host cell exocytosis. Post-mitotic infectious cargo distribution is a new parameter to consider in the study of intracellular pathogens since it could potentially define the outcome of phagocytic-microbial interactions

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Similar Genetic Mechanisms Underlie the Parallel Evolution of Floral Phenotypes

The repeated origin of similar phenotypes is invaluable for studying the underlying genetics of adaptive traits; molecular evidence, however, is lacking for most examples of such similarity. The floral morphology of neotropical Malpighiaceae is distinctive and highly conserved, especially with regard to symmetry, and is thought to result from specialization on oil-bee pollinators. We recently demonstrated that CYCLOIDEA2–like genes (CYC2A and CYC2B) are associated with the development of the stereotypical floral zygomorphy that is critical to this plant–pollinator mutualism. Here, we build on this developmental framework to characterize floral symmetry in three clades of Malpighiaceae that have independently lost their oil bee association and experienced parallel shifts in their floral morphology, especially in regard to symmetry. We show that in each case these species exhibit a loss of CYC2B function, and a strikingly similar shift in the expression of CYC2A that is coincident with their shift in floral symmetry. These results indicate that similar floral phenotypes in this large angiosperm clade have evolved via parallel genetic changes from an otherwise highly conserved developmental program

Turnip mosaic potyvirus probably first spread to Eurasian brassica crops from wild orchids about 1000 years ago

Turnip mosaic potyvirus (TuMV) is probably the most widespread and damaging virus that infects cultivated brassicas worldwide. Previous work has indicated that the virus originated in western Eurasia, with all of its closest relatives being viruses of monocotyledonous plants. Here we report that we have identified a sister lineage of TuMV-like potyviruses (TuMV-OM) from European orchids. The isolates of TuMV-OM form a monophyletic sister lineage to the brassica-infecting TuMVs (TuMV-BIs), and are nested within a clade of monocotyledon-infecting viruses. Extensive host-range tests showed that all of the TuMV-OMs are biologically similar to, but distinct from, TuMV-BIs and do not readily infect brassicas. We conclude that it is more likely that TuMV evolved from a TuMV-OM-like ancestor than the reverse. We did Bayesian coalescent analyses using a combination of novel and published sequence data from four TuMV genes [helper component-proteinase protein (HC-Pro), protein 3(P3), nuclear inclusion b protein (NIb), and coat protein (CP)]. Three genes (HC-Pro, P3, and NIb), but not the CP gene, gave results indicating that the TuMV-BI viruses diverged from TuMV-OMs around 1000 years ago. Only 150 years later, the four lineages of the present global population of TuMV-BIs diverged from one another. These dates are congruent with historical records of the spread of agriculture in Western Europe. From about 1200 years ago, there was a warming of the climate, and agriculture and the human population of the region greatly increased. Farming replaced woodlands, fostering viruses and aphid vectors that could invade the crops, which included several brassica cultivars and weeds. Later, starting 500 years ago, inter-continental maritime trade probably spread the TuMV-BIs to the remainder of the world

The sudden change phenomenon of quantum discord

Even if the parameters determining a system's state are varied smoothly, the behavior of quantum correlations alike to quantum discord, and of its classical counterparts, can be very peculiar, with the appearance of non-analyticities in its rate of change. Here we review this sudden change phenomenon (SCP) discussing some important points related to it: Its uncovering, interpretations, and experimental verifications, its use in the context of the emergence of the pointer basis in a quantum measurement process, its appearance and universality under Markovian and non-Markovian dynamics, its theoretical and experimental investigation in some other physical scenarios, and the related phenomenon of double sudden change of trace distance discord. Several open questions are identified, and we envisage that in answering them we will gain significant further insight about the relation between the SCP and the symmetry-geometric aspects of the quantum state space.Comment: Lectures on General Quantum Correlations and their Applications, F. F. Fanchini, D. O. Soares Pinto, and G. Adesso (Eds.), Springer (2017), pp 309-33