The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

FTS and 2-DG induce pancreatic cancer cell death and tumor shrinkage in mice

The Ras inhibitor S-trans-trans farnesylthiosalicylic acid (FTS) inhibits active Ras, which controls cell proliferation, differentiation, survival, and metabolism. FTS also inhibits HIF1α expression in cancer cells, leading to an energy crisis. The synthetic glucose analog 2-deoxy-D-glucose (2-DG), which inhibits glycolysis, is selectively directed to tumor cells that exhibit increased glucose consumption. The 2-DG enters tumor cells, where it competes with glucose for glycolytic enzymes. In cancer models, as well as in human phase 1 trials, 2-DG inhibits tumor growth without toxicity. We postulated that under normoxic conditions, tumor cells treated with FTS would be more sensitive than normal cells to 2-DG. We show here that combined treatment with FTS and 2-DG inhibited cancer cell proliferation additively, yet induced apoptotic cell death synergistically both in vitro and in vivo. The induced apoptosis was inferred from QVD-OPH inhibition, an increase in cleaved caspase 3, and loss of survivin. FTS and 2-DG when combined, but not separately, also induced an increase in fibrosis of the tumor tissue, chronic inflammation, and tumor shrinkage. Overall, these results suggest a possible new treatment of pancreatic tumors by the combined administration of FTS and 2-DG, which together induce pancreatic tumor cell death and tumor shrinkage under non-toxic conditions

Some approximate analytical methods in the study of the self-avoiding loop model with variable bending rigidity and the critical behaviour of the strong coupling lattice Schwinger model with Wilson fermions

Some time ago Salmhofer demonstrated the equivalence of the strong coupling lattice Schwinger model with Wilson fermions to a certain 8-vertex model which can be understood as a self-avoiding loop model on the square lattice with bending rigidity $\eta = 1/2$ and monomer weight $z = (2\kappa)^{-2}$. The present paper applies two approximate analytical methods to the investigation of critical properties of the self-avoiding loop model with variable bending rigidity, discusses their validity and makes comparison with known MC results. One method is based on the independent loop approximation used in the literature for studying phase transitions in polymers, liquid helium and cosmic strings. The second method relies on the known exact solution of the self-avoiding loop model with bending rigidity $\eta = 1/\sqrt{2}$. The present investigation confirms recent findings that the strong coupling lattice Schwinger model becomes critical for $\kappa_{cr} \simeq 0.38-0.39$. The phase transition is of second order and lies in the Ising model universality class. Finally, the central charge of the strong coupling Schwinger model at criticality is discussed and predicted to be $c = 1/2$.Comment: 22 pages LaTeX, 6 Postscript figure

Quantum dynamics in strong fluctuating fields

A large number of multifaceted quantum transport processes in molecular systems and physical nanosystems can be treated in terms of quantum relaxation processes which couple to one or several fluctuating environments. A thermal equilibrium environment can conveniently be modelled by a thermal bath of harmonic oscillators. An archetype situation provides a two-state dissipative quantum dynamics, commonly known under the label of a spin-boson dynamics. An interesting and nontrivial physical situation emerges, however, when the quantum dynamics evolves far away from thermal equilibrium. This occurs, for example, when a charge transferring medium possesses nonequilibrium degrees of freedom, or when a strong time-dependent control field is applied externally. Accordingly, certain parameters of underlying quantum subsystem acquire stochastic character. Herein, we review the general theoretical framework which is based on the method of projector operators, yielding the quantum master equations for systems that are exposed to strong external fields. This allows one to investigate on a common basis the influence of nonequilibrium fluctuations and periodic electrical fields on quantum transport processes. Most importantly, such strong fluctuating fields induce a whole variety of nonlinear and nonequilibrium phenomena. A characteristic feature of such dynamics is the absence of thermal (quantum) detailed balance.Comment: review article, Advances in Physics (2005), in pres

Feature selection using Haar wavelet power spectrum

BACKGROUND: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. RESULTS: Haar wavelet power spectra of genes were analysed and it was observed to be different in different diagnostic categories. This difference in trend and magnitude of the spectrum may be utilized in gene selection. Most of the genes selected by earlier complex methods were selected by the very simple present method. Each earlier works proved only few genes are quite enough to approach the classification problem [1]. Hence the present method may be tried in conjunction with other classification methods. The technique was applied without removing the noise in data to validate the robustness of the method against the noise or outliers in the data. No special softwares or complex implementation is needed. The qualities of the genes selected by the present method were analysed through their gene expression data. Most of them were observed to be related to solve the classification issue since they were dominant in the diagnostic category of the dataset for which they were selected as features. CONCLUSION: In the present paper, the problem of feature selection of microarray gene expression data was considered. We analyzed the wavelet power spectrum of genes and proposed a clustering and feature selection method useful for classification based on Haar wavelet power spectrum. Application of this technique in this area is novel, simple, and faster than other methods, fit for a wide range of data types. The results are encouraging and throw light into the possibility of using this technique for problem domains like disease classification, gene network identification and personalized drug design

Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

Do diagnostic delays in cancer matter?

background: The United Kingdom has poorer cancer outcomes than many other countries due partly to delays in diagnosing symptomatic cancer, leading to more advanced stage at diagnosis. Delays can occur at the level of patients, primary care, systems and secondary care. There is considerable potential for interventions to minimise delays and lead to earlier-stage diagnosis. methods: Scoping review of the published studies, with a focus on methodological issues. results: Trial data in this area are lacking and observational studies often show no association or negative ones. This review offers methodological explanations for these counter-intuitive findings. conclusion: While diagnostic delays do matter, their importance is uncertain and must be determined through more sophisticated methods

Cost-Effectiveness of Magnetic Resonance Imaging with a New Contrast Agent for the Early Diagnosis of Alzheimer's Disease

Background: Used as contrast agents for brain magnetic resonance imaging (MRI), markers for beta-amyloid deposits might allow early diagnosis of Alzheimer’s disease (AD). We evaluated the cost-effectiveness of such a diagnostic test, MRI+CLP (contrastophore-linker-pharmacophore), should it become clinically available. Methodology/Principal Findings: We compared the cost-effectiveness of MRI+CLP to that of standard diagnosis using currently available cognition tests and of standard MRI, and investigated the impact of a hypothetical treatment efficient in early AD. The primary analysis was based on the current French context for 70-year-old patients with Mild Cognitive Impairment (MCI). In alternative ‘‘screen and treat’ ’ scenarios, we analyzed the consequences of systematic screenings of over-60 individuals (either population-wide or restricted to the ApoE4 genotype population). We used a Markov model of AD progression; model parameters, as well as incurred costs and quality-of-life weights in France were taken from the literature. We performed univariate and probabilistic multivariate sensitivity analyses. The base-case preferred strategy was the standard MRI diagnosis strategy. In the primary analysis however, MRI+CLP could become the preferred strategy under a wide array of scenarios involving lower cost and/or higher sensitivity or specificity. By contrast, in the ‘‘screen and treat’’ analyses, the probability of MRI+CLP becoming the preferred strategy remained lower than 5%. Conclusions/Significance: It is thought that anti-beta-amyloid compounds might halt the development of dementia i