Prognostic utility of sestamibi lung uptake does not require adjustment for stress-related variables: A retrospective cohort study

BACKGROUND: Increased (99m)Tc-sestamibi stress lung-to-heart ratio (sLHR) has been shown to predict cardiac outcomes similar to pulmonary uptake of thallium. Peak heart rate and use of pharmacologic stress affect the interpretation of lung thallium uptake. The current study was performed to determine whether (99m)Tc-sestamibi sLHR measurements are affected by stress-related variables, and whether this in turn affects prognostic utility. METHODS: sLHR was determined in 718 patients undergoing (99m)Tc-sestamibi SPECT stress imaging. sLHR was assessed in relation to demographics, hemodynamic variables and outcomes (mean follow up 5.6 ± 1.1 years). RESULTS: Mean sLHR was slightly greater in males than in females (P < 0.01) and also showed a weak negative correlation with age (P < 0.01) and systolic blood pressure (P < 0.01), but was unrelated to stress method or heart rate at the time of injection. In patients undergoing treadmill exercise, sLHR was also positively correlated with peak workload (P < 0.05) but inversely with double product (P < 0.05). The combined explanatory effect of sex, age and hemodynamic variables on sLHR was less than 10%. The risk of acute myocardial infarction (AMI) or death increased by a factor of 1.7–1.8 for each SD increase in unadjusted sLHR, and was unaffected by adjustment for sex, age and hemodynamic variables (hazard ratios 1.6–1.7). The area under the ROC curve for the unadjusted sLHR was 0.65 (95% CI 0.59–0.71, P < 0.0001) and was unchanged for the adjusted sLHR (0.65, 95% CI 0.61–0.72, P < 0.0001). CONCLUSION: Stress-related variables have only a weak effect on measured sLHR. Unadjusted and adjusted sLHR provide equivalent prognostic information for prediction of AMI or death

Compromised BRCA1-PALB2 interaction is associated with breast cancer risk.

The major breast cancer suppressor proteins BRCA1 and BRCA2 play essential roles in homologous recombination (HR)-mediated DNA repair, which is thought to be critical for tumor suppression. The two BRCA proteins are linked by a third tumor suppressor, PALB2, in the HR pathway. While truncating mutations in these genes are generally pathogenic, interpretation of missense variants remains a challenge. To date, patient-derived missense variants that disrupt PALB2 binding have been identified in BRCA1 and BRCA2; however, there has not been sufficient evidence to prove their pathogenicity in humans, and no variants in PALB2 that disrupt either its BRCA1 or BRCA2 binding have been reported. Here we report on the identification of a novel PALB2 variant, c.104T>C (p.L35P), that segregates in a family with a strong history of breast cancer. Functional analyses showed that L35P abrogates the PALB2-BRCA1 interaction and completely disables its abilities to promote HR and confer resistance to platinum salts and PARP inhibitors. Whole-exome sequencing of a breast cancer from a c.104T>C carrier revealed a second, somatic, truncating mutation affecting PALB2, and the tumor displays hallmark genomic features of tumors with BRCA mutations and HR defects, cementing the pathogenicity of L35P. Parallel analyses of other germline variants in the PALB2 N-terminal BRCA1-binding domain identified multiple variants that affect HR function to varying degrees, suggesting their possible contribution to cancer development. Our findings establish L35P as the first pathogenic missense mutation in PALB2 and directly demonstrate the requirement of the PALB2-BRCA1 interaction for breast cancer suppression

Bianchi Type-II String Cosmological Models in Normal Gauge for Lyra's Manifold with Constant Deceleration Parameter

The present study deals with a spatially homogeneous and anisotropic Bianchi-II cosmological models representing massive strings in normal gauge for Lyra's manifold by applying the variation law for generalized Hubble's parameter that yields a constant value of deceleration parameter. The variation law for Hubble's parameter generates two types of solutions for the average scale factor, one is of power-law type and other is of the exponential form. Using these two forms, Einstein's modified field equations are solved separately that correspond to expanding singular and non-singular models of the universe respectively. The energy-momentum tensor for such string as formulated by Letelier (1983) is used to construct massive string cosmological models for which we assume that the expansion ($\theta$) in the model is proportional to the component $\sigma^{1}_{~1}$ of the shear tensor $\sigma^{j}_{i}$. This condition leads to $A = (BC)^{m}$, where A, B and C are the metric coefficients and m is proportionality constant. Our models are in accelerating phase which is consistent to the recent observations. It has been found that the displacement vector $\beta$ behaves like cosmological term $\Lambda$ in the normal gauge treatment and the solutions are consistent with recent observations of SNe Ia. It has been found that massive strings dominate in the decelerating universe whereas strings dominate in the accelerating universe. Some physical and geometric behaviour of these models are also discussed.Comment: 24 pages, 10 figure

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic

Modern classification of neoplasms: reconciling differences between morphologic and molecular approaches

BACKGROUND: For over 150 years, pathologists have relied on histomorphology to classify and diagnose neoplasms. Their success has been stunning, permitting the accurate diagnosis of thousands of different types of neoplasms using only a microscope and a trained eye. In the past two decades, cancer genomics has challenged the supremacy of histomorphology by identifying genetic alterations shared by morphologically diverse tumors and by finding genetic features that distinguish subgroups of morphologically homogeneous tumors. DISCUSSION: The Developmental Lineage Classification and Taxonomy of Neoplasms groups neoplasms by their embryologic origin. The putative value of this classification is based on the expectation that tumors of a common developmental lineage will share common metabolic pathways and common responses to drugs that target these pathways. The purpose of this manuscript is to show that grouping tumors according to their developmental lineage can reconcile certain fundamental discrepancies resulting from morphologic and molecular approaches to neoplasm classification. In this study, six issues in tumor classification are described that exemplify the growing rift between morphologic and molecular approaches to tumor classification: 1) the morphologic separation between epithelial and non-epithelial tumors; 2) the grouping of tumors based on shared cellular functions; 3) the distinction between germ cell tumors and pluripotent tumors of non-germ cell origin; 4) the distinction between tumors that have lost their differentiation and tumors that arise from uncommitted stem cells; 5) the molecular properties shared by morphologically disparate tumors that have a common developmental lineage, and 6) the problem of re-classifying morphologically identical but clinically distinct subsets of tumors. The discussion of these issues in the context of describing different methods of tumor classification is intended to underscore the clinical value of a robust tumor classification. SUMMARY: A classification of neoplasms should guide the rational design and selection of a new generation of cancer medications targeted to metabolic pathways. Without a scientifically sound neoplasm classification, biological measurements on individual tumor samples cannot be generalized to class-related tumors, and constitutive properties common to a class of tumors cannot be distinguished from uninformative data in complex and chaotic biological systems. This paper discusses the importance of biological classification and examines several different approaches to the specific problem of tumor classification

ElliPro: a new structure-based tool for the prediction of antibody epitopes

<p>Abstract</p> <p>Background</p> <p>Reliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.</p> <p>Results</p> <p>Here we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at <url>http://tools.immuneepitope.org/tools/ElliPro</url>.</p> <p>Conclusion</p> <p>The results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.</p

Preference of Small Molecules for Local Minimum Conformations when Binding to Proteins

It is well known that small molecules (ligands) do not necessarily adopt their lowest potential energy conformations when binding to proteins. Analyses of protein-bound ligand crystal structures have reportedly shown that many of them do not even adopt the conformations at local minima of their potential energy surfaces (local minimum conformations). The results of these analyses raise a concern regarding the validity of virtual screening methods that use ligands in local minimum conformations. Here we report a normal-mode-analysis (NMA) study of 100 crystal structures of protein-bound ligands. Our data show that the energy minimization of a ligand alone does not automatically stop at a local minimum conformation if the minimum of the potential energy surface is shallow, thus leading to the folding of the ligand. Furthermore, our data show that all 100 ligand conformations in their protein-bound ligand crystal structures are nearly identical to their local minimum conformations obtained from NMA-monitored energy minimization, suggesting that ligands prefer to adopt local minimum conformations when binding to proteins. These results both support virtual screening methods that use ligands in local minimum conformations and caution about possible adverse effect of excessive energy minimization when generating a database of ligand conformations for virtual screening

Identification of Continuous Human B-Cell Epitopes in the Envelope Glycoprotein of Dengue Virus Type 3 (DENV-3)

BACKGROUND:Dengue virus infection is a growing global public health concern in tropical and subtropical regions of the world. Dengue vaccine development has been hampered by concerns that cross-reactive immunological memory elicited by a candidate vaccine could increase the risk of development of more severe clinical forms. One possible strategy to reduce risks associated with a dengue vaccine is the development of a vaccine composed of selected critical epitopes of each of the serotypes. METHODOLOGY/PRINCIPAL FINDINGS:Synthetic peptides were used to identify B-cell epitopes in the envelope (E) glycoprotein of dengue virus type 3 (DENV-3). Eleven linear, immunodominant epitopes distributed in five regions at amino acid (aa) positions: 51-65, 71-90, 131-170, 196-210 and 246-260 were identified by employing an enzyme- linked immunosorbent assay (ELISA), using a pool of human sera from dengue type 3 infected individuals. Peptides 11 (aa51-65), 27 and 28 (aa131-150) also reacted with dengue 1 (DENV-1) and dengue 2 (DENV-2) patient sera as analyzed through the ROC curves generated for each peptide by ELISA and might have serotype specific diagnostic potential. Mice immunized against each one of the five immunogenic regions showed epitopes 51-65, 131-170, 196-210 and 246-260 elicited the highest antibody response and epitopes131-170, 196-210 and 246-260, elicited IFN-gamma production and T CD4+ cell response, as evaluated by ELISA and ELISPOT assays respectively. CONCLUSIONS/SIGNIFICANCE:Our study identified several useful immunodominant IgG-specific epitopes on the envelope of DENV-3. They are important tools for understanding the mechanisms involved in antibody dependent enhancement and immunity. If proven protective and safe, in conjunction with others well-documented epitopes, they might be included into a candidate epitope-based vaccine

Ashwagandha Derived Withanone Targets TPX2-Aurora A Complex: Computational and Experimental Evidence to its Anticancer Activity

Cancer is largely marked by genetic instability. Specific inhibition of individual proteins or signalling pathways that regulate genetic stability during cell division thus hold a great potential for cancer therapy. The Aurora A kinase is a Ser/Thr kinase that plays a critical role during mitosis and cytokinesis and is found upregulated in several cancer types. It is functionally regulated by its interactions with TPX2, a candidate oncogene. Aurora A inhibitors have been proposed as anticancer drugs that work by blocking its ATP binding site. This site is common to other kinases and hence these inhibitors lack specificity for Aurora A inhibition in particular, thus advocating the need of some alternative inhibition route. Previously, we identified TPX2 as a cellular target for withanone that selectively kill cancer cells. By computational approach, we found here that withanone binds to TPX2-Aurora A complex. In experiment, withanone treatment to cancer cells indeed resulted in dissociation of TPX2-Aurora A complex and disruption of mitotic spindle apparatus proposing this as a mechanism of the anticancer activity of withanone. From docking analysis, non-formation/disruption of the active TPX2-Aurora A association complex could be discerned. Our MD simulation results suggesting the thermodynamic and structural stability of TPX2-Aurora A in complex with withanone further substantiates the binding. We report a computational rationale of the ability of naturally occurring withanone to alter the kinase signalling pathway in an ATP-independent manner and experimental evidence in which withanone cause inactivation of the TPX2-Aurora A complex. The study demonstrated that TPX2-Aurora A complex is a target of withanone, a potential natural anticancer drug