Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks

Exact calculation of electronic properties of molecules is a fundamental step for intelligent and rational compounds and materials design. The intrinsically graph-like and non-vectorial nature of molecular data generates a unique and challenging machine learning problem. In this paper we embrace a learning from scratch approach where the quantum mechanical electronic properties of molecules are predicted directly from the raw molecular geometry, similar to some recent works. But, unlike these previous endeavors, our study suggests a benefit from combining molecular geometry embedded in the Coulomb matrix with the atomic composition of molecules. Using the new combined features in a Bayesian regularized neural networks, our results improve well-known results from the literature on the QM7 dataset from a mean absolute error of 3.51 kcal/mol down to 3.0 kcal/mol.Comment: Under review ICANN 201

Future oriented group training for suicidal patients: a randomized clinical trial

<p>Abstract</p> <p>Background</p> <p>In routine psychiatric treatment most clinicians inquire about indicators of suicide risk, but once the risk is assessed not many clinicians systematically focus on suicidal thoughts. This may reflect a commonly held opinion that once the depressive or anxious symptoms are effectively treated the suicidal symptoms will wane. Consequently, many clients with suicidal thoughts do not receive systematic treatment of their suicidal thinking. There are many indications that specific attention to suicidal thinking is necessary to effectively decrease the intensity and recurrence of suicidal thinking. We therefore developed a group training for patients with suicidal thoughts that is easy to apply in clinical settings as an addition to regular treatment and that explicitly focuses on suicidal thinking. We hypothesize that such an additional training will decrease the frequency and intensity of suicidal thinking.</p> <p>We based the training on cognitive behavioural approaches of hopelessness, worrying, and future perspectives, given the theories of Beck, McLeod and others, concerning the lack of positive expectations characteristic for many suicidal patients. In collaboration with each participant in the training individual positive future possibilities and goals were challenged.</p> <p>Methods/Design</p> <p>We evaluate the effects of our program on suicide ideation (primary outcome measure). The study is conducted in a regular treatment setting with regular inpatients and outpatients representative for Dutch psychiatric treatment settings. The design is a RCT with two arms: TAU (Treatment as Usual) versus TAU plus the training. Follow up measurements are taken 12 months after the first assessment.</p> <p>Discussion</p> <p>There is a need for research on the effectiveness of interventions in suicidology, especially RCT's. In our treatment program we combine aspects and interventions that have been proven to be useful in the treatment of suicidal thinking and behavior.</p> <p>Trial registration</p> <p>ISRCTN56421759</p

Establishment of a human cell-based in vitro battery to assess developmental neurotoxicity hazard of chemicals

Developmental neurotoxicity (DNT) is a major safety concern for all chemicals of the human exposome. However, DNT data from animal studies are available for only a small percentage of manufactured compounds. Test methods with a higher throughput than current regulatory guideline methods, and with improved human relevance are urgently needed. We therefore explored the feasibility of DNT hazard assessment based on new approach methods (NAMs). An in vitro battery (IVB) was assembled from ten individual NAMs that had been developed during the past years to probe effects of chemicals on various fundamental neurodevelopmental processes. All assays used human neural cells at different developmental stages. This allowed us to assess disturbances of: (i) proliferation of neural progenitor cells (NPC); (ii) migration of neural crest cells, radial glia cells, neurons and oligodendrocytes; (iii) differentiation of NPC into neurons and oligodendrocytes; and (iv) neurite outgrowth of peripheral and central neurons. In parallel, cytotoxicity measures were obtained. The feasibility of concentration-dependent screening and of a reliable biostatistical processing of the complex multi-dimensional data was explored with a set of 120 test compounds, containing subsets of pre-defined positive and negative DNT compounds. The battery provided alerts (hit or borderline) for 24 of 28 known toxicants (82% sensitivity), and for none of the 17 negative controls. Based on the results from this screen project, strategies were developed on how IVB data may be used in the context of risk assessment scenarios employing integrated approaches for testing and assessment (IATA).European Food Safety Authority (EFSA-Q-2018-00308), the Danish Environmental Protection Agency (EPA), Denmark, under the grant number MST-667-00205, the State Ministry of Baden-Wuerttemberg, Germany, for Economic Affairs, Labour and Tourism (NAM-Accept), the project CERST (Center for Alternatives to Animal Testing) of the Ministry for culture and science of the State of North-Rhine Westphalia, Germany (file number 233–1.08.03.03- 121972/131–1.08.03.03–121972), the European Chemical Industry Council Long-Range Research Initiative (Cefic LRI) under the project name AIMT11 and the BMBF (NeuroTool). It has also received funding from the European Union's Horizon 2020 research and innovation program under grant agreements No. 964537 (RISK-HUNT3R), No. 964518 (ToxFree), No. 101057014 (PARC) and No. 825759 (ENDpoiNTs)

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

Phosphoenolpyruvate carboxylase dentified as a key enzyme in erythrocytic Plasmodium falciparum carbon metabolism

Phospoenolpyruvate carboxylase (PEPC) is absent from humans but encoded in thePlasmodium falciparum genome, suggesting that PEPC has a parasite-specific function. To investigate its importance in P. falciparum, we generated a pepc null mutant (D10Δpepc), which was only achievable when malate, a reduction product of oxaloacetate, was added to the growth medium. D10Δpepc had a severe growth defect in vitro, which was partially reversed by addition of malate or fumarate, suggesting that pepc may be essential in vivo. Targeted metabolomics using 13C-U-D-glucose and 13C-bicarbonate showed that the conversion of glycolytically-derived PEP into malate, fumarate, aspartate and citrate was abolished in D10Δpepc and that pentose phosphate pathway metabolites and glycerol 3-phosphate were present at increased levels. In contrast, metabolism of the carbon skeleton of 13C,15N-U-glutamine was similar in both parasite lines, although the flux was lower in D10Δpepc; it also confirmed the operation of a complete forward TCA cycle in the wild type parasite. Overall, these data confirm the CO2 fixing activity of PEPC and suggest that it provides metabolites essential for TCA cycle anaplerosis and the maintenance of cytosolic and mitochondrial redox balance. Moreover, these findings imply that PEPC may be an exploitable target for future drug discovery

Neutral Gauge Boson Contributions to the Dimuon Charge Asymmetry in B Decays

Recently, the D0 Collaboration measured the CP-violating like-sign dimuon charge asymmetry in neutral B decays, finding a 3.2sigma difference from the standard-model (SM) prediction. A non-SM charge asymmetry a_sl^s suggests a new-physics (NP) contribution to Bs-Bsbar mixing. In this case, in order to explain the measured value of a_sl^s within its 1sigma range, NP must be present in Gamma_12^s, the absorptive part of the mixing. In this paper, we examine whether such an explanation is possible in models with flavor-changing Z (ZFCNC) or Z' (Z'FCNC) gauge bosons. The models must also reproduce the measured values of the indirect CP asymmetry S_psi-phi in Bs -> J/psi phi, and Delta Gamma_s, the Bs-Bsbar width difference. We find that the ZFCNC model cannot reproduce the present measured values of S_psi-phi and a_sl^s within their 1sigma ranges. On the other hand, in the Z'FCNC model, the values of all three observables can be simultaneously reproduced.Comment: 18 pages, 7 figures, JHEP format. Some ZFCNC equations corrected, ZFCNC analysis redone, references added, conclusions unchange

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

Functional and Structural Insights Revealed by Molecular Dynamics Simulations of an Essential RNA Editing Ligase in Trypanosoma brucei

RNA editing ligase 1 (TbREL1) is required for the survival of both the insect and bloodstream forms of Trypanosoma brucei, the parasite responsible for the devastating tropical disease African sleeping sickness. The type of RNA editing that TbREL1 is involved in is unique to the trypanosomes, and no close human homolog is known to exist. In addition, the high-resolution crystal structure revealed several unique features of the active site, making this enzyme a promising target for structure-based drug design. In this work, two 20 ns atomistic molecular dynamics (MD) simulations are employed to investigate the dynamics of TbREL1, both with and without the ATP substrate present. The flexibility of the active site, dynamics of conserved residues and crystallized water molecules, and the interactions between TbREL1 and the ATP substrate are investigated and discussed in the context of TbREL1's function. Differences in local and global motion upon ATP binding suggest that two peripheral loops, unique to the trypanosomes, may be involved in interdomain signaling events. Notably, a significant structural rearrangement of the enzyme's active site occurs during the apo simulations, opening an additional cavity adjacent to the ATP binding site that could be exploited in the development of effective inhibitors directed against this protozoan parasite. Finally, ensemble averaged electrostatics calculations over the MD simulations reveal a novel putative RNA binding site, a discovery that has previously eluded scientists. Ultimately, we use the insights gained through the MD simulations to make several predictions and recommendations, which we anticipate will help direct future experimental studies and structure-based drug discovery efforts against this vital enzyme