Competitor analysis of functional group H-bond donor and acceptor properties using the Cambridge Structural Database.

Intermolecular interactions found in the Cambridge Structural Database (CSD) are analysed as the outcomes of competitions between the different functional groups that are present in each structure: the most energetically favourable interactions are expected to win more often than weaker interactions. Tracking winners and losers through each crystal structure in the CSD provides data that can be analysed using paired comparison algorithms to rank functional group H-bonding properties based on how frequently they outcompete other functional groups in the crystal. This treatment is superior to simple statistical analyses of whether functional groups H-bond or not, because the distribution of H-bond donors and acceptors in the structures of the molecules found in the CSD is non-random. Most organic molecules contain more acceptors than donors, so that all H-bond donors are almost always H-bonded in all crystal structures, and most acceptors are not. The rankings of H-bond acceptors obtained by applying the TrueSkill paired comparison algorithm to the CSD agree well with the corresponding experimentally determined solution phase H-bond acceptor parameters β, but there is insufficient data to corroborate H-bond donor rankings calculated in the same way. The method is used to make predictions of the H-bond acceptor properties of functional groups for which solution phase measurements are not available.Engineering and Physical Sciences Research Council, Cambridge Crystallographic Data Centr

“Structural Transformations in Ceramics: Perovskite-like Oxides and Group III, IV, and V Nitrides”

1 Overview of Results and their Significance Ceramic perovskite-like oxides with the general formula (A. A0. ...)(B. B0. ...)O3and titanium-based oxides are of great technological interest because of their large piezoelectric and dielectric response characteristics.[1] In doped and nanoengineered forms, titantium dioxide finds increasing application as an organic and hydrolytic photocatalyst. The binary main-group-metal nitride compounds have undergone recent advancements of in-situ heating technology in diamond anvil cells leading to a burst of experimental and theoretical interest. In our DOE proposal, we discussed our unique theoretical approach which applies ab initio electronic calculations in conjunction with systematic group-theoretical analysis of lattice distortions to study two representative phase transitions in ceramic materials: (1) displacive phase transitions in primarily titanium-based perovskite-like oxide ceramics, and (2) reconstructive phase transitions in main-group nitride ceramics. A sub area which we have explored in depth is doped titanium dioxide electrical/optical properties

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning.

MOTIVATION: While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a normalization strategy to account for input data heterogeneity, and conical layers to model drug synergies. RESULTS: DeepSynergy was compared to other machine learning methods such as Gradient Boosting Machines, Random Forests, Support Vector Machines and Elastic Nets on the largest publicly available synergy dataset with respect to mean squared error. DeepSynergy significantly outperformed the other methods with an improvement of 7.2% over the second best method at the prediction of novel drug combinations within the space of explored drugs and cell lines. At this task, the mean Pearson correlation coefficient between the measured and the predicted values of DeepSynergy was 0.73. Applying DeepSynergy for classification of these novel drug combinations resulted in a high predictive performance of an AUC of 0.90. Furthermore, we found that all compared methods exhibit low predictive performance when extrapolating to unexplored drugs or cell lines, which we suggest is due to limitations in the size and diversity of the dataset. We envision that DeepSynergy could be a valuable tool for selecting novel synergistic drug combinations. AVAILABILITY AND IMPLEMENTATION: DeepSynergy is available via www.bioinf.jku.at/software/DeepSynergy. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Comment on 'Geoengineering with seagrasses: Is credit due where credit is given?'

Over the past decade scientists around the world have sought to estimate the capacity of seagrass meadows to sequester carbon, and thereby understand their role in climate change mitigation. The number of studies reporting on seagrass carbon accumulation rates is still limited, but growing scientific evidence supports the hypothesis that seagrasses have been efficiently locking away CO2 for decades to millennia (e.g. Macreadie et al 2014, Mateo et al 1997, Serrano et al 2012). Johannessen and Macdonald (2016), however, challenge the role of seagrasses as carbon traps, claiming that gains in carbon storage by seagrasses may be \u27illusionary\u27 and that \u27their contribution to the global burial of carbon has not yet been established\u27. The authors warn that misunderstandings of how sediments receive, process and store carbon have led to an overestimation of carbon burial by seagrasses. Here we would like to clarify some of the questions raised by Johannessen and Macdonald (2016), with the aim to promote discussion within the scientific community about the evidence for carbon sequestration by seagrasses with a view to awarding carbon credits

Mesonic Form Factors

We have started a program to compute the electromagnetic form factors of mesons. We discuss the techniques used to compute the pion form factor and present preliminary results computed with domain wall valence fermions on MILC asqtad lattices, as well as Wilson fermions on quenched lattices. These methods can easily be extended to rho-to-gamma-pi transition form factors.Comment: 7 pages, 6 figures, Workshop on Lattice Hadron Physics 2003 (LHP2003

Antiproton catalyzed microfission/fusion propulsion

Inertial confinement fusion (ICF) utilizing an antiproton catalyzed hybrid fission/fusion target is discussed as a potential energy source for interplanetary propulsion. A proof-of-principle experiment underway at Phillips Laboratory, Kirtland AFB and antiproton trapping experiments at CERN, Geneva, Switzerland, are presented. The ICAN propulsion concept is described and results of performance analyses are reviewed. Future work to further define the ICAN concept is outlined

Towards precision medicine for hypertension: a review of genomic, epigenomic, and microbiomic effects on blood pressure in experimental rat models and humans

Compelling evidence for the inherited nature of essential hypertension has led to extensive research in rats and humans. Rats have served as the primary model for research on the genetics of hypertension resulting in identification of genomic regions that are causally associated with hypertension. In more recent times, genome-wide studies in humans have also begun to improve our understanding of the inheritance of polygenic forms of hypertension. Based on the chronological progression of research into the genetics of hypertension as the "structural backbone," this review catalogs and discusses the rat and human genetic elements mapped and implicated in blood pressure regulation. Furthermore, the knowledge gained from these genetic studies that provide evidence to suggest that much of the genetic influence on hypertension residing within noncoding elements of our DNA and operating through pervasive epistasis or gene-gene interactions is highlighted. Lastly, perspectives on current thinking that the more complex "triad" of the genome, epigenome, and the microbiome operating to influence the inheritance of hypertension, is documented. Overall, the collective knowledge gained from rats and humans is disappointing in the sense that major hypertension-causing genes as targets for clinical management of essential hypertension may not be a clinical reality. On the other hand, the realization that the polygenic nature of hypertension prevents any single locus from being a relevant clinical target for all humans directs future studies on the genetics of hypertension towards an individualized genomic approach

An antiproton driver for ICF propulsion

Inertial confinement fusion (ICF) utilizing an anitprotoncatalyzed target is discussed as a possible source of propulsion for rapid interplanetary manned space missions. The relevant compression, ignition, and thrust mechanisms are presented. Progress on an experiment presently in progress at the Phillips Laboratory, Kirtland AFB, NM to demonstrate proof-of-principle is reviewed

Carbon sequestration by Australian tidal marshes

Australia's tidal marshes have suffered significant losses but their recently recognised importance in CO2 sequestration is creating opportunities for their protection and restoration. We compiled all available data on soil organic carbon (OC) storage in Australia's tidal marshes (323 cores). OC stocks in the surface 1 m averaged 165.41 (SE 6.96) Mg OC ha-1 (range 14-963 Mg OC ha-1). The mean OC accumulation rate was 0.55 ± 0.02 Mg OC ha-1 yr -1. Geomorphology was the most important predictor of OC stocks, with fluvial sites having twice the stock of OC as seaward sites. Australia's 1.4 million hectares of tidal marshes contain an estimated 212 million tonnes of OC in the surface 1 m, with a potential CO2 -equivalent value of $USD7.19 billion. Annual sequestration is 0.75 Tg OC yr -1, with a CO2 -equivalent value of$USD28.02 million per annum. This study provides the most comprehensive estimates of tidal marsh blue carbon in Australia, and illustrates their importance in climate change mitigation and adaptation, acting as CO2 sinks and buffering the impacts of rising sea level. We outline potential further development of carbon offset schemes to restore the sequestration capacity and other ecosystem services provided by Australia tidal marshes

Evolution of ecological specialization and venom of a predatory marine gastropod

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74591/1/j.1365-294X.2007.03627.x.pd