Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.     

LC-MS characterization and purity assessment of a prototype bispecific antibody

Bispecific IgG asymmetric (heterodimeric) antibodies offer enhanced therapeutic efficacy, but present unique challenges for drug development. These challenges are related to the proper assembly of heavy and light chains. Impurities such as symmetric (homodimeric) antibodies can arise with improper assembly. A new method to assess heterodimer purity of such bispecific antibody products is needed because traditional separation-based purity assays are unable to separate or quantify homodimer impurities. This paper presents a liquid chromatography-mass spectrometry (LC-MS)-based method for evaluating heterodimeric purity of a prototype asymmetric antibody containing two different heavy chains and two identical light chains. The heterodimer and independently expressed homodimeric standards were characterized by two complementary LC-MS techniques: Intact protein mass measurement of deglycosylated antibody and peptide map analyses. Intact protein mass analysis was used to check molecular integrity and composition. LC-MS^E peptide mapping of Lys-C digests was used to verify protein sequences and characterize post-translational modifications, including C-terminal truncation species. Guided by the characterization results, a heterodimer purity assay was demonstrated by intact protein mass analysis of pure deglycosylated heterodimer spiked with each deglycosylated homodimeric standard. The assay was capable of detecting low levels (2%) of spiked homodimers in conjunction with co-eluting half antibodies and multiple mass species present in the homodimer standards and providing relative purity differences between samples. Detection of minor homodimer and half-antibody C-terminal truncation species at levels as low as 0.6% demonstrates the sensitivity of the method. This method is suitable for purity assessment of heterodimer samples during process and purification development of bispecific antibodies, e.g., clone selection.     

Overcoming resistance to rapalogs in gliomas by combinatory therapies

Glioblastoma is the most common and aggressive brain tumor type, with a mean patient survival of approximately 1 year. Many previous analyses of the glioma kinome have identified key deregulated pathways that converge and activate mammalian target of rapamycin (mTOR). Following the identification and characterization of mTOR-promoting activity in gliomagenesis, data from preclinical studies suggested the targeting of mTOR by rapamycin or its analogs (rapalogs) as a promising therapeutic approach. However, clinical trials with rapalogs have shown very limited efficacy on glioma due to the development of resistance mechanisms. Analysis of rapalog-insensitive glioma cells has revealed increased activity of growth and survival pathways compensating for mTOR inhibition by rapalogs that are suitable for therapeutic intervention. In addition, recently developed mTOR inhibitors show high anti-glioma activity. In this review, we recapitulate the regulation of mTOR signaling and its involvement in gliomagenesis, discuss mechanisms resulting in resistance to rapalogs, and speculate on strategies to overcome resistance. This article is part of a Special Issue entitled: Inhibitors of Protein Kinases (2012).     

Identification of Pak1 inhibitors using water thermodynamic analysis

Abstract

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.     

Phlebotominae of epidemiological importance in cutaneous leishmaniasis in northwestern Argentina: risk maps and ecological niche models

In Argentina, 58.2% out of the 8126 Cutaneous Leishmaniasis (CL) incident cases accumulated from 1954 to 2006 were reported in the provinces of Salta and Jujuy. The aim of this study was to develop an exploratory risk map and a potential distribution map of the vector, in order to offer recommendations for CL prevention. A total of 12 079 Phlebotominae (Diptera: Psychodidae) belonging to the species Lutzomyia neivai (Pinto), Lu. migonei (França), Lu. cortelezzii (Brèthes), Lu. shannoni (Dyar), Lu. quinquefer (Dyar) and Brumptomyia spp. (França & Parrot) were captured. Potential distribution models were created for two species, Lu. neivai (incriminated vector of Leishmania braziliensis) and Lu. migonei, associated with domestic animals in Argentina and that in turn could be involved as a link between zoonotic transmission cycles and anthropozoonotic. The Maximum Entropy Modeling System (MaxEnt) was used. The Jackknife test was performed, and the ‘rainfall of the driest month’ was the variable that best generalized the models. Accuracy was evaluated by the area under the curve (AUC) and validated by the Cohen's kappa index. This approximation provides a new analytical resource of high potential for the prevention of the disease, in order to allocate resources properly and to develop the most suitable strategies for action.     

Molecular dynamics simulation on the effect of transition metal binding to the N-terminal fragment of amyloid-β

Abstract

We report molecular dynamics simulations of three possible adducts of Fe(II) to the N-terminal 1–16 fragments of the amyloid-β peptide, along with analogous simulations of Cu(II) and Zn(II) adducts. We find that multiple simulations from different starting points reach pseudo-equilibration within 100–300?ns, leading to over 900?ns of equilibrated trajectory data for each system. The specifics of the coordination modes for Fe(II) have only a weak effect on peptide secondary and tertiary structures, and we therefore compare one of these with analogous models of Cu(II) and Zn(II) complexes. All share broadly similar structural features, with mixture of coil, turn and bend in the N-terminal region and helical structure for residues 11–16. Within this overall pattern, subtle effects due to changes in metal are evident: Fe(II) complexes are more compact and are more likely to occupy bridge and ribbon regions of Ramachandran maps, while Cu(II) coordination leads to greater occupancy of the poly-proline region. Analysis of representative clusters in terms of molecular mechanics energy and atoms-in-molecules properties indicates similarity of four-coordinate Cu and Zn complexes, compared to five-coordinate Fe complex that exhibits lower stability and weaker metal–ligand bonding.

Communicated by Ramaswamy H. Sarma     

Some Effects of Ethanolic Extracts of Potatoes on Phosphorylase Activity

Effects of materials extracted from potatoes with hot 80% ethanol on the course of phosphorylase reactions were examined. These materials had no effect on phosphorylase activities as determined by the rate of liberation of inorganic phosphate from glucose-1-phosphate in the presence of a large amount of primer; however, in the presence of a small amount of primer or in its absence, these materials had significant effects on the liberation of inorganic phosphate and starch formation. These results suggested the presence of a small amount of primers in these materials. Evidence was presented against the participation of d-enzyme on the formation of starch when partially purified preparations of potato phosphorylase or crude extracts from potatoes were used as the enzyme.     

A multi-step directional generalized gradient vector flow snake for target tumor segmentation in US-guided high-intensity focused ultrasound ablation

Getting precise locations of target tumors can help to ensure ablation of cancerous tissues and avoid unwanted destruction of healthy tissues in high-intensity focused ultrasound (HIFU) treatment system. Because of speckle noise and spurious boundaries in ultrasound images, traditional image segmentation methods are not suitable for achieving the precise locations of target tumors in HIFU ablation. In this paper, a multi-step directional generalized gradient vector flow snake model is introduced for target tumor segmentation. In the first step, the traditional generalized gradient vector flow (GGVF) snake is used to obtain an approximate contour of the tumor. According to the approximate contour, a new distance map is generated. Subsequently, a new directional edge map is created by calculating a scalar product of the gradients of the distance map and the initial image. In this process, the gradient directional information and the magnitude information of the distance map are used to attenuate unwanted edges and highlight the real edges in the new directional edge map. Finally, a refined GGVF field is derived from a diffusion operation of the gradient vectors of the directional edge map. The GGVF field is used to refine the tumor's contour, by directing the approximate contour to edges with the desired gradient directionality. Based on the newly developed snake model, the influences of the spurious boundaries and the speckle noise are significantly reduced in the ultrasound image segmentation. Experimental results indicate that this technique is greatly useful for target tumor segmentation in HIFU treatment system     

Global marine bacterial diversity peaks at high latitudes in winter

Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world''s oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms.     

Computational tool for the early screening of monoclonal antibodies for their viscosities

Highly concentrated antibody solutions often exhibit high viscosities, which present a number of challenges for antibody-drug development, manufacturing and administration. The antibody sequence is a key determinant for high viscosity of highly concentrated solutions; therefore, a sequence- or structure-based tool that can identify highly viscous antibodies from their sequence would be effective in ensuring that only antibodies with low viscosity progress to the development phase. Here, we present a spatial charge map (SCM) tool that can accurately identify highly viscous antibodies from their sequence alone (using homology modeling to determine the 3-dimensional structures). The SCM tool has been extensively validated at 3 different organizations, and has proved successful in correctly identifying highly viscous antibodies. As a quantitative tool, SCM is amenable to high-throughput automated analysis, and can be effectively implemented during the antibody screening or engineering phase for the selection of low-viscosity antibodies.