Exact Interactions Research Articles

Abstract 5075: The composition and interactions in the microenvironment of human prostate cancer

Abstract Background: Prostate cancer is a heterogeneous disease both genetically and in its clinical behavior. It is widely accepted that a tumor does not only consist of cancer cells but also contains many other non-malignant cells, including immune cells and cancer associated fibroblasts. These non-malignant cells create the tumor microenvironment. It is previously suggested that the tumor microenvironment modulates the behavior of various cancers, including prostate cancer. Little is known about the exact interactions between prostate cancer cells and its micro environment. In this study we aim to gain insight into the composition of the microenvironment and the interaction between malignant and non-malignant cells. Moreover, these interactions might hold a predictive signature for disease progression and metastatic disease. Methods: Biopsies were obtained from Formalin Fixed Paraffin Embedded (FFPE) human prostate cancers from 10 patients with pelvic lymph node metastases and 10 gleason score (7-8-9) matched patients with non-metastatic disease. RNA was isolated from the FFPE samples and sequenced. A tissue micro array was constructed from the same prostate cancers. Fresh prostate cancer biopsies were taken right after radical prostatectomy, and fibroblast cells were isolated for short term culture. Results: The RNA sequencing of FFPE prostate biopsies revealed an increased expression of cancer related stroma genes in tumor tissue compared to non-tumorous tissue. Presence of various cell types was confirmed by immunohistochemistry (IHC). The subtypes of various immune cell populations could be identified, including regulatory T cells and pro-tumorous M2-like macrophages. The percentage of M2-like macrophages identified by the CD163 marker showed a significant increase in tumor tissue compared to non-tumorous tissue, which was unique for patients with metastatic disease. Furthermore we could confirm that decreased stromal Androgen Receptor (AR) expression correlated with disease progression and also correlated with metastatic disease. To investigate which stromal cells were AR positive we performed double stainings of PDGFR beta and AR. Costaining of both markers confirmed AR expression in fibroblasts. The stromal cells cultured from the fresh prostate cancer biopsies were morphologically fibroblasts and expressed AR, Smooth Muscle Actin and PDGFR beta, suggesting a cancer associated phenotype. Testosterone stimulation of these fibroblasts showed increased chromatin binding of the AR. This suggests that the AR is functional in these cancer associated fibroblasts. Conclusions: This study gained insight into the composition of the prostate cancer microenvironment. The increased expression of CD163 and the decreased expression of stromal AR was related to pelvic lymph node metastases. Citation Format: Monique Melis, Bianca Cioni, Ekaterina Nevedomskaya, Johan van Burgsteden, Emma Hodel, Annegien Broeks, Henk van der Poel, Jeroen de Jong, Andre Bergman. The composition and interactions in the microenvironment of human prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5075. doi:10.1158/1538-7445.AM2015-5075

Nonlinear normal mode interactions in the SF(6) molecule studied with the aid of density functional theory.

Some exact interactions between vibrational modes in systems with discrete symmetry can be described by the theory of the bushes of nonlinear normal modes (NNMs) [G. M. Chechin and V. P. Sakhnenko, Phys. D (Amsterdam, Neth.) 117, 43 (1998)]. Each bush represents a dynamical object conserving the energy of the initial excitation. The existence of bushes of NNMs is ensured by some group-theoretical selection rules. In G. M. Chechin et al. [Int. J. Nonlinear Mech. 38, 1451 (2003)], existence and stability of the bushes of vibrational modes in the simple octahedral model of mass points interacting via Lennard-Jones potential were investigated. In the present paper, we study these dynamical objects by the density functional theory in the SF(6) molecule, which possesses the same symmetry and structure. We have fully confirmed the results previously obtained in the framework of the group-theoretical approach and have found some properties of the bushes of NNMs.

Low Fouling Electrospun Scaffolds with Clicked Bioactive Peptides for Specific Cell Attachment.

While electrospun fibers are of interest as scaffolds for tissue engineering applications, nonspecific surface interactions such as protein adsorption often prevent researchers from controlling the exact interactions between cells and the underlying material. In this study we prepared electrospun fibers from a polystyrene-based macroinitiator, which were then grafted with polymer brushes using surface-initiated atom transfer radical polymerization (SI-ATRP). These brush coatings incorporated a trimethylsilyl-protected PEG-alkyne monomer, allowing azide functional molecules to be covalently attached, while simultaneously reducing nonspecific protein adsorption on the fibers. Cells were able to attach and spread on fibrous substrates functionalized with a pendant RGD-containing peptide, while spreading was significantly reduced on nonfunctionalized fibers and those with the equivalent RGE control peptide. This effect was observed both in the presence and absence of serum in the culture media, indicating that protein adsorption on the fibers was minimal and cell adhesion within the fibrous scaffold was mediated almost entirely through the cell-adhesive RGD-containing peptide.

Bone geometry of the hip is associated with obesity and early structural damage – A 3.0T MRI study of community-based adults

Bone geometry of the hip is associated with obesity and early structural damage – A 3.0T MRI study of community-based adults

How Structure Defines Affinity in Protein-Protein Interactions

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins.

The individual and collective effects of exact exchange and dispersion interactions on the ab initio structure of liquid water.

In this work, we report the results of a series of density functional theory (DFT) based ab initio molecular dynamics (AIMD) simulations of ambient liquid water using a hierarchy of exchange-correlation (XC) functionals to investigate the individual and collective effects of exact exchange (Exx), via the PBE0 hybrid functional, non-local van der Waals/dispersion (vdW) interactions, via a fully self-consistent density-dependent dispersion correction, and an approximate treatment of nuclear quantum effects, via a 30 K increase in the simulation temperature, on the microscopic structure of liquid water. Based on these AIMD simulations, we found that the collective inclusion of Exx and vdW as resulting from a large-scale AIMD simulation of (H2O)128 significantly softens the structure of ambient liquid water and yields an oxygen-oxygen structure factor, SOO(Q), and corresponding oxygen-oxygen radial distribution function, gOO(r), that are now in quantitative agreement with the best available experimental data. This level of agreement between simulation and experiment demonstrated herein originates from an increase in the relative population of water molecules in the interstitial region between the first and second coordination shells, a collective reorganization in the liquid phase which is facilitated by a weakening of the hydrogen bond strength by the use of a hybrid XC functional, coupled with a relative stabilization of the resultant disordered liquid water configurations by the inclusion of non-local vdW/dispersion interactions. This increasingly more accurate description of the underlying hydrogen bond network in liquid water also yields higher-order correlation functions, such as the oxygen-oxygen-oxygen triplet angular distribution, POOO(θ), and therefore the degree of local tetrahedrality, as well as electrostatic properties, such as the effective molecular dipole moment, that are in much better agreement with experiment.

Exact operator Hamiltonians and interactions in the droplet bosonization method

We derive the exact form of the bosonized Hamiltonian for a many-body fermion system in one spatial dimension with arbitrary dispersion relations, using the droplet bosonization method. For a single-particle Hamiltonian polynomial in the momentum, the bosonized Hamiltonian is a polynomial of one degree higher in the bosonic ``boundary'' field and includes subleading lower-order and derivative terms. This generalizes the known results for massless relativistic and nonrelativistic fermions (quadratic and cubic bosonic Hamiltonians, respectively). We also consider two-body interactions and demonstrate that they lead to interesting collective behavior and phase transitions in the Fermi sea.

Integration of Artificial Neural Networks into Operational Ocean Wave Prediction Models for Fast and Accurate Emulation of Exact Nonlinear Interactions

In this paper, an implementation study was undertaken to employ Artificial Neural Networks (ANN) in third-generation ocean wave models for direct mapping of wind-wave spectra into exact nonlinear interactions. While the investigation expands on previously reported feasibility studies of Neural Network Interaction Approximations (NNIA), it focuses on a new robust neural network that is implemented in Wavewatch III (WW3) model. Several idealistic and real test scenarios were carried out. The obtained results confirm the feasibility of NNIA in terms of speeding-up model calculations and is fully capable of providing operationally acceptable model integrations. The ANN is able to emulate the exact nonlinear interaction for single-and multi-modal wave spectra with a much higher accuracy then Discrete Interaction Approximation (DIA). NNIA performs at least twice as fast as DIA and at least two hundred times faster than exact method (Web-Resio-Tracy, WRT) for a well trained dataset. The accuracy of NNIA is network configuration dependent. For most optimal network configurations, the NNIA results and scatter statistics show good agreement with exact results by means of growth curves and integral parameters. Practical possibilities for further improvements in achieving fast and highly accurate emulations using ANN for emulating time consuming exact nonlinear interactions are also suggested and discussed.

Luftschadstoffe und Asthma im Kindesalter

Exposure to outdoor air pollutants and passive tobacco smoke are common but avoidable worldwide risk factors for morbidity and mortality of individuals. In addition to well-known effects of pollutants on the cardiovascular system and the development of cancer, in recent years the association between air pollution and respiratory morbidity has become increasingly apparent. Not only in adults, but also in children with asthma and in healthy children a clear harmful effect of exposure towards air pollutants has been demonstrated in many studies. Among others increased pollution has been shown to result in more frequent and more severe respiratory symptoms, more frequent exacerbations, higher need for asthma medication, poorer lung function and increased visits to the emergency department and more frequent hospitalisations. While these associations are well established, the available data on the role of air pollution in the development of asthma seems less clear. Some studies have shown that increased exposure towards tobacco smoke and air pollution leads to an increase in asthma incidence and prevalence; others were not able to confirm those findings. Possible reasons for this discrepancy are different definitions of the outcome asthma, different methods for exposure estimation and differences in the populations studied with differing underlying genetic backgrounds. Regardless of this inconsistency, several mechanisms have already been identified linking air pollution with asthma development. Among these are impaired lung growth and development, immunological changes, genetic or epigenetic effects or increased predisposition for allergic sensitisation. What the exact interactions are and which asthmatic phenotypes will be influenced most by pollutants will be shown by future studies. This knowledge will then be helpful in exploring possible preventive measures for the individual and to help policy makers in deciding upon most appropriate regulations on a population level.

Nanoscale interactions of polyethylene glycol with thermo‐mechanically pre‐treated Pinus radiata biofuel substrate

Non-productive adsorption of cellulose degrading enzymes on lignin is a likely reason for reduced rate and extent of enzymatic conversion of lignocellulosic substrate to sugars. Additives such as polyethyleneglycol (PEG) may act as blocking agents in this non-productive interaction. However, the exact molecular level interactions of PEG with lignin in pre-treated lignocellulosic substrates are not known. We have used confocal fluorescence microscopy combined with Förster resonance energy transfer (FRET) to reveal molecular level interactions between lignin present in thermo-mechanically pre-treated Pinus radiata substrate, and fluorescently labeled PEG. It is demonstrated that PEG interaction with lignin is mainly associated with particles derived from secondary walls, with little or no penetration into fragments derived from the middle lamella. This nanoscale information on the PEG-substrate interaction will assist in rationalizing pre-treatment methods to reduce the recalcitrance of softwood biofuel substrates.

Efficient Algorithms for Electrostatic Interactions Including Dielectric Contrasts

Coarse-grained models of soft matter are usually combined with implicit solvent models that take the electrostatic polarizability into account via a dielectric background. In biophysical or nanoscale simulations that include water, this constant can vary greatly within the system. Performing molecular dynamics or other simulations that need to compute exact electrostatic interactions between charges in those systems is computationally demanding. We review here several algorithms developed by us that perform exactly this task. For planar dielectric surfaces in partial periodic boundary conditions, the arising image charges can be either treated with the MMM2D algorithm in a very efficient and accurate way or with the electrostatic layer correction term, which enables the user to use his favorite 3D periodic Coulomb solver. Arbitrarily-shaped interfaces can be dealt with using induced surface charges with the induced charge calculation (ICC*) algorithm. Finally, the local electrostatics algorithm, MEMD(Maxwell Equations Molecular Dynamics), even allows one to employ a smoothly varying dielectric constant in the systems. We introduce the concepts of these three algorithms and an extension for the inclusion of boundaries that are to be held fixed at a constant potential (metal conditions). For each method, we present a showcase application to highlight the importance of dielectric interfaces.

Diversity of intestinal microbiota in infancy and the risk of allergic disease in childhood

Numerous studies have attempted to describe specific microbiota deviations that may precede atopic sensitization and atopic disease in childhood. This has given rise to a hypothesis suggesting that a reduced intestinal microbial diversity in infancy increases the risk of allergic manifestations. This review intends to sum up the main findings and discuss relevant exposures that regulate intestinal microbial diversity. Taken together the three studies in this review lend support to the diversity hypothesis, but reported differences related to atopic sensitization and clinical expression are discussed. A summary on analytic methods and functional aspect of the microbiota in allergic disease is presented to ameliorate a presentation of recent articles on environmental and host-factors regulating microbiota composition and diversity. The current evidence indicates that intestinal microbiota diversity can be associated with allergic diseases, but the exact mechanisms and interactions contributing to this effect are far from understood and need further investigation.

Serum prostate-specific antigen as a predictor of prostate volume and lower urinary tract symptoms in a community-based cohort: a large-scale Korean screening study

The aim of this study is to assess the ability of serum prostate-specific antigen (PSA) to predict prostate volume (PV) and lower urinary tract symptoms (LUTS) represented by the international prostate symptom score (IPSS). From January 2001 to December 2011, data were collected from men who first enrolled in the Korean Prostate Health Council Screening Program. Patients with a serum PSA level of >10ng ml(-1) or age <40 years were excluded. Accordingly, a total of 34857 men were included in our study, and serum PSA, PV and the IPSS were estimated in all patients. Linear and age-adjusted multivariate logistic analyses were used to assess the potential association between PSA and PV or IPSS. The predictive value of PSA for estimating PV and IPSS was assessed based on the receiver operating characteristics-derived area under the curve (AUC). The mean PV was 29.9ml, mean PSA level was 1.49ng ml(-1) and mean IPSS was 15.4. A significant relationship was shown between PSA and PV, and the IPSS and PSA were also significantly correlated after adjusting by age. The AUCs of PSA for predicting PV >20ml, >25ml and >35ml were 0.722, 0.728 and 0.779, respectively. The AUCs of PSA for predicting IPSS >7, >13 and >19 were 0.548, 0.536 and 0.537, respectively. Serum PSA was a strong predictor of PV in a community-based cohort in a large-scale screening study. Although PSA was also significantly correlated with IPSS, predictive values of PSA for IPSS above the cutoff levels were not excellent. Further investigations are required to elucidate the exact interactions between PSA and LUTS and between PSA and PV in prospective controlled studies. Such studies may suggest how PSA can be used to clinically predict PV and the IPSS.

Holistic genetic optimization of a Generalized Multiple Discrete Interaction Approximation for wind waves

A key element of wind wave models is the parameterization of the resonant nonlinear interactions between spectral wave components. In a companion paper a new Generalized Multiple Discrete Interaction Approximation (GMD) has been developed. The present paper addresses the optimization of the free parameters of the GMD. A holistic optimization approach is used where full model integration results are optimized. Fifteen objective metrics are used, defined to measure the accuracy of a model using the GMD relative to a model using the full (exact) interactions. Due to the large number of free parameters to be optimized, and due to the existence of many local error minima in parameter space, traditional error mapping or steepest descent search algorithms are not suitable to optimize the GMD. The focus of the present study is on establishing genetic optimization techniques as a feasible and economical way to optimize the free parameters in the GMD. The behavior of the GMD with optimized parameters is outside the scope of this study, and is discussed in detail in the companion paper.

Recent Advances in Health Promoting Effect of Dietary Polyphenols

Association between intake of polyphenols and reduction in the risk of disease has been reported in cohort studies. Extensive researches which started after World War II have proposed many mechanisms to explain the biology behind this association. The exact molecular interactions of polyphenols at cellular level in the biological system remains speculative. Besides, doses for effective response and bioavailability are other important issues which remain unanswered. In 2009, we reviewed dietary polyphenols including their occurrence, synthesis and properties (Curr Nutr Food Sci 2009; 5: 249-63). Much progress has recently been made in the field of polyphenol research. Tools have improved significantly over the past few years and new databases have been created. The present article provides an update on the current understanding of polyphenols. Keywords: Polyphenols, bioavailability, molecular targets, human diseases, health, biological system, cellular level, research, effects, sources

Type 1 Diabetes: Current Concepts in Epidemiology, Pathophysiology, Clinical Care, and Research

Type 1 diabetes (T1D) is an autoimmune disease mediated by a combination of genetic and environmental triggers resulting in lymphocytic infiltration of pancreatic islets, destruction of beta cells, and lifelong dependency on exogenous insulin. Although T1D is prevalent (1 in 300) and its incidence is steadily increasing worldwide (3% per year), the exact gene-environment interactions precipitating the disease remain unknown. Living with T1D is challenging for patients, families, and caregivers. Because of the relative paucity of pediatric endocrinologists, general pediatricians and other subspecialists may occasionally be faced with the task of managing diabetes-related complaints. Herein, we provide a comprehensive review of the natural history, pathophysiology, and contemporary management of T1D. In addition, recent advances in T1D research are discussed.

PAMELA: An open-source software package for calculating nonlocal exact exchange effects on electron gases in core-shell nanowires

We present a new pseudospectral approach for incorporating many-body, nonlocal exact exchange interactions to understand the formation of electron gases in core-shell nanowires. Our approach is efficiently implemented in the open-source software package PAMELA (Pseudospectral Analysis Method with Exchange &amp; Local Approximations) that can calculate electronic energies, densities, wavefunctions, and band-bending diagrams within a self-consistent Schrödinger-Poisson formalism. The implementation of both local and nonlocal electronic effects using pseudospectral methods is key to PAMELA's efficiency, resulting in significantly reduced computational effort compared to finite-element methods. In contrast to the new nonlocal exchange formalism implemented in this work, we find that the simple, conventional Schrödinger-Poisson approaches commonly used in the literature (1) considerably overestimate the number of occupied electron levels, (2) overdelocalize electrons in nanowires, and (3) significantly underestimate the relative energy separation between electronic subbands. In addition, we perform several calculations in the high-doping regime that show a critical tunneling depth exists in these nanosystems where tunneling from the core-shell interface to the nanowire edge becomes the dominant mechanism of electron gas formation. Finally, in order to present a general-purpose set of tools that both experimentalists and theorists can easily use to predict electron gas formation in core-shell nanowires, we document and provide our efficient and user-friendly PAMELA source code that is freely available at http://alum.mit.edu/www/usagi.

Molecular characterization of Mtb-OMP decarboxylase by modeling, docking and dynamic studies

Tuberculosis (TB), the second most deadly disease in the world is caused by Mycobacterium tuberculosis (Mtb). In the present work a unique enzyme of Mtb orotidine 5' monophosphate decarboxylase (Mtb-OMP Decase) is selected as drug target due to its indispensible role in biosynthesis of pyrimidines. The present work is focused on understanding the structural and functional aspects of Mtb-OMP Decase at molecular level. Due to absence of crystal structure, the 3D structure of Mtb-OMP Decase was predicted by MODELLER9V7 using a known structural template 3L52. Energy minimization and refinement of the developed 3D model was carried out with Gromacs 3.2.1 and the optimized homology model was validated by PROCHECK,WHAT-IF and PROSA2003. Further, the surface active site amino acids were quantified by WHAT-IF pocket. The exact binding interactions of the ligands, 6-idiouridine 5' monophosphate and its designed analogues with the receptor Mtb-OMP Decase were predicted by docking analysis with AUTODOCK 4.0. This would be helpful in understanding the blockade mechanism of OMP Decase and provide a candidate lead for the discovery of Mtb-OMP Decase inhibitors, which may bring insights into outcome new therapy to treat drug resistant Mtb.

The dynamics of cortico-thalamo-cortical interactions at the transition from pre-ictal to ictal LFPs in absence epilepsy

PurposeGeneralized spike and wave discharges (SWD) are generated within the cortico-thalamo-cortical system. However the exact interactions between cortex and different thalamic nuclei needed for the generation and maintenance of SWD are still to be elucidated. This study aims to shed more light on these interactions via multisite cortical and thalamic local-field-potential recordings. MethodsWAG/Rij rats were equipped with multiple electrodes targeting layers 4 to 6 of the somatosensory-cortex, rostral and caudal RTN, VPM, anterior (ATN)- and posterior (Po) thalamic nucleus. The maximal-association-strength between signals was calculated for pre-ictal→ictal transition periods and in control periods using non-linear-association-analysis. Dynamics of changes in coupling-direction and time-delays between channels were analyzed. ResultsEarliest and strongest increases in coupling-strength were seen between cortical layers 5/6 and Po. Other thalamic nuclei became later involved in SWD activity. During the first 500ms of SWDs the cortex guided most thalamic nuclei while cortex and Po kept a bidirectional crosstalk. Most thalamic nuclei started to guide the Po until the end of the SWD. While the rostral RTN showed increased coupling with Po, the caudal RTN decoupled. Instead, it directed its activity to the rostral RTN. ConclusionsNext to the focal cortical instigator zone of SWDs, the Po seems crucial for their occurrence. This nucleus shows early increases in coupling and is the only nucleus which keeps a bidirectional crosstalk to the cortex within the first 500ms of SWDs. Other thalamic nuclei seem to have only a function in SWD maintenance. Rostral and caudal-RTN have opposite roles in SWD occurrence.

Antiangiogenic Therapy for Ischemic Retinopathies

Neovascularization is a common pathological process in various retinal vascular disorders including diabetic retinopathy (DR), age-related macular degeneration (AMD) and retinal vein occlusion (RVO). The development of neovascular vessels may lead to complications such as vitreous hemorrhage, fibrovascular tissue formation, and traction retinal detachments. Ultimately, irreversible vision loss may result. Various proangiogenic factors are involved in these complex processes. Different antiangiogenic drugs have been formulated in an attempt treat these vascular disorders. One factor that plays a major role in the development of retinal neovascularization is vascular endothelial growth factor (VEGF). Anti-VEGF agents are currently FDA approved for the treatment of AMD and RVO. They are also extensively used as an off-label treatment for diabetic macular edema (DME), proliferative DR, and neovascular glaucoma. However, at this time, the long-term safety of chronic VEGF inhibition has not been extensively evaluated. A large and rapidly expanding body of research on angiogenesis is being conducted at multiple centers across the globe to determine the exact contributions and interactions among a variety of angiogenic factors in an effort to determine the therapeutic potential of antiangiogenic agent in the treatment of a variety of retinal diseases.