FLUKA Monte Carlo simulation for the Leksell Gamma Knife Perfexion radiosurgery system: Homogeneous media

The purpose of this work is to investigate the capability of the FLUKA Monte Carlo (MC) code to simulate the Elekta Leksell Gamma Knife Perfexion (LGK-PFX) and reproduce the Treatment Planning System (TPS) Leksell GammaPlan version 8.2 (LGP) dose calculations for the case of a water equivalent phantom target. Thanks to the collaboration with Elekta Instruments AB, the collimation system geometry, the source positions and all the involved material have been simulated in detail. The relative linear dose distribution along the three coordinate axes, for each collimator size, and the Relative Output Factors (ROF) have been investigated. The simulation has been validated comparing simulated linear dose profiles with measurements performed with EBT radiochromic films. The acceptance criterion between experimental data and FLUKA results is based on the gamma index (GI) method. The FLUKA MC calculation for the ROF provided the values of 0.920 for the 8 mm collimators and 0.800 for the 4 mm collimators. These values are in good agreement with the Elekta reference data of 0.924 and 0.805 respectively. The percentage difference between calculated and reference values for the ROF is under 1% and within the FLUKA uncertainty. Also the simulated relative dose profiles show a good agreement with the LGP calculation expressed by means of the gamma index method. This established accuracy proves that FLUKA is a suitable and powerful tool in order to reproduce successfully the LGP calculations for the homogeneous media.     

Beginning to understand the role of sugar carriers in Colletotrichum lindemuthianum: the function of the gene mfs1

Fungi of the Colletotrichum genus are among the most prominent phytopathogens that cause diseases with a considerable economic impact, such as anthracnose. The hemibiotrophic fungus Colletotrichum lindemuthianum (teleomorph Glomerella cingulata f. sp. phaseoli) is the causal agent of the anthracnose of the common bean; and similarly to other phytopathogens, it uses multiple strategies to gain access to different carbon sources from its host. In this study, we examine mfs1, a newly identified C. lindemuthianum hexose transporter. The mfs1 gene is expressed only during the necrotrophic phase of the fungus’ interaction within the plant and allows it to utilize the available sugars during this phase. The deletion of mfs1 gene resulted in differential growth of the fungus in a medium that contained glucose, mannose or fructose as the only carbon source. This study is the first to describe a hexose transporter in the hemibiotrophic pathogen C. lindemuthianum and to demonstrate the central role of this protein in capturing carbon sources during the necrotrophic development of the plant/pathogen interaction.     

Diet supplementation with beta-carotene improves the serum lipid profile in rats fed a cholesterol-enriched diet

The present study investigated the underlying mechanism associated with the hypocholesterolemic activity of beta-carotene by examining its effects on the serum lipid profile, fecal cholesterol excretion, and gene expression of the major receptors, enzymes, and transporters involved in cholesterol metabolism. Female Fischer rats were divided into three groups and were fed either a control or a hypercholesterolemic diet supplemented or not supplemented with 0.2 % beta-carotene. After 6 weeks of feeding, blood, livers, and feces were collected for analysis, and quantitative real-time polymerase chain reaction (qRT-PCR) was performed. Dietary supplementation with 0.2 % beta-carotene decreased serum total cholesterol, non-HDL cholesterol, the atherogenic index, and hepatic total lipid and cholesterol contents. These changes were accompanied by an increase in the total lipid and cholesterol contents excreted in the feces. The qRT-PCR analyses demonstrated that the hypercholesterolemic diet promoted a decrease in the gene expression of sterol regulatory element-binding protein 2, 3-hydroxy-3-methylglutaryl CoA reductase, and low-density lipoprotein receptor and an increase in the gene expression of peroxisome proliferator-activated receptor α and cholesterol-7a-hydroxylase. The expression of these genes and gene expression of ATP-binding cassette subfamily G transporters 5and 8 were unaffected by beta-carotene supplementation. In conclusion, the decrease in serum cholesterol and the elevation of fecal cholesterol obtained following beta-carotene administration indicate that this substance may decrease cholesterol absorption in the intestine and increase cholesterol excretion into the feces without a direct effect on the expression of cholesterol metabolism genes.     

A conservation and rigidity based method for detecting critical protein residues

Background

Certain amino acids in proteins play a critical role in determining their structural stability and function. Examples include flexible regions such as hinges which allow domain motion, and highly conserved residues on functional interfaces which allow interactions with other proteins. Detecting these regions can aid in the analysis and simulation of protein rigidity and conformational changes, and helps characterizing protein binding and docking. We present an analysis of critical residues in proteins using a combination of two complementary techniques. One method performs in-silico mutations and analyzes the protein's rigidity to infer the role of a point substitution to Glycine or Alanine. The other method uses evolutionary conservation to find functional interfaces in proteins.

Results

We applied the two methods to a dataset of proteins, including biomolecules with experimentally known critical residues as determined by the free energy of unfolding. Our results show that the combination of the two methods can detect the vast majority of critical residues in tested proteins.

Conclusions

Our results show that the combination of the two methods has the potential to detect more information than each method separately. Future work will provide a confidence level for the criticalness of a residue to improve the accuracy of our method and eliminate false positives. Once the combined methods are integrated into one scoring function, it can be applied to other domains such as estimating functional interfaces.

     

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

Background

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units.

Results

Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures.

Conclusions

Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

     

Statins in cardiometabolic disease: what makes pitavastatin different?

The term cardiometabolic disease encompasses a range of lifestyle-related conditions, including Metabolic syndrome (MetS) and type 2 diabetes (T2D), that are characterized by different combinations of cardiovascular (CV) risk factors, including dyslipidemia, abdominal obesity, hypertension, hyperglycemia/insulin resistance, and vascular inflammation. These risk factors individually and interdependently increase the risk of CV and cerebrovascular events, and represent one of the biggest health challenges worldwide today. CV diseases account for almost 50% of all deaths in Europe and around 30% of all deaths worldwide. Furthermore, the risk of CV death is increased twofold to fourfold in people with T2D. Whilst the clinical management of CV disease has improved in Western Europe, the pandemic of obesity and T2D reduces the impact of these gains. This, together with the growing, aging population, means the number of CV deaths is predicted to increase from 17.1 million worldwide in 2004 to 23.6 million in 2030. The recommended treatment for MetS is lifestyle change followed by treatment for the individual risk factors. Numerous studies have shown that lowering low-density lipoprotein-cholesterol (LDL-C) levels using statins can significantly reduce CV risk in people with and without T2D or MetS. However, the risk of major vascular events in those attaining the maximum levels of LDL-C-reduction is only reduced by around one-third, which leaves substantial residual risk. Recent studies suggest that low high-density lipoprotein-cholesterol (HDL-C) (<1 .0 mmol/l; 40 mg/dl) and high triglyceride levels (≥1.7 mmol/l; 150 mg/dl) are independent risk factors for CV disease and that the relationship between HDL-C and CV risk persists even when on-treatment LDL-C levels are low (<1.7 mmol/l; 70 mg/dl). European guidelines highlight the importance of reducing residual risk by targeting these risk factors in addition to LDL-C. This is particularly important in patients with T2D and MetS because obesity and high levels of glycated hemoglobin are directly related to low levels of HDL-C and high triglyceride. Although most statins have a similar low-density lipoprotein-lowering efficacy, differences in chemical structure and pharmacokinetic profile can lead to variations in pleiotropic effects (for example, high-density lipoprotein-elevating efficacy), adverse event profiles, and drug-drug interactions. The choice of statin should therefore depend on the needs of the individual patient. The following reviews will discuss the potential benefits of pitavastatin versus other statins in the treatment of patients with dyslipidemia and MetS or T2D, focusing on its effects on HDL-C quantity and quality, its potential impact on atherosclerosis and CV risk, and its metabolic characteristics that reduce the risk of drug interactions. Recent controversies surrounding the potentially diabetogenic effects of statins will also be discussed.     

Anti-leukemia Activity of 7-hydroxy-2-substituted-methyl-5 H -oxazolo[3,2- a] pyrimidin-5-one Derivatives

The synthesis of new 7-hydroxy-2-substituted-methyl-5 H -oxazolo[3,2- a] pyrimidin-5-ones derivatives, designed as structural bicyclic analogues of the iron chelator deferiprone, is described. They were tested for their ability to inhibit proliferation in human Bcr-Abl + leukemia cells.     

Prolonged lifespan with enhanced exploratory behavior in mice overexpressing the oxidized nucleoside triphosphatase hMTH1

The contribution that oxidative damage to DNA and/or RNA makes to the aging process remains undefined. In this study, we used the hMTH1‐Tg mouse model to investigate how oxidative damage to nucleic acids affects aging. hMTH1‐Tg mice express high levels of the hMTH1 hydrolase that degrades 8‐oxodGTP and 8‐oxoGTP and excludes 8‐oxoguanine from both DNA and RNA. Compared to wild‐type animals, hMTH1‐overexpressing mice have significantly lower steady‐state levels of 8‐oxoguanine in both nuclear and mitochondrial DNA of several organs, including the brain. hMTH1 overexpression prevents the age‐dependent accumulation of DNA 8‐oxoguanine that occurs in wild‐type mice. These lower levels of oxidized guanines are associated with increased longevity and hMTH1‐Tg animals live significantly longer than their wild‐type littermates. Neither lipid oxidation nor overall antioxidant status is significantly affected by hMTH1 overexpression. At the cellular level, neurospheres derived from adult hMTH1‐Tg neural progenitor cells display increased proliferative capacity and primary fibroblasts from hMTH1‐Tg embryos do not undergo overt senescence in vitro. The significantly lower levels of oxidized DNA/RNA in transgenic animals are associated with behavioral changes. These mice show reduced anxiety and enhanced investigation of environmental and social cues. Longevity conferred by overexpression of a single nucleotide hydrolase in hMTH1‐Tg animals is an example of lifespan extension associated with healthy aging. It provides a link between aging and oxidative damage to nucleic acids.     

Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design.

Results

We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features.

Conclusions

In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.