CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials

Improved approaches and methodologies are needed to conduct comparative effectiveness research (CER) in oncology. While cancer therapies continue to emerge at a rapid pace, the review, synthesis, and dissemination of evidence-based interventions across clinical trials lag in comparison. Rigorous and systematic testing of competing therapies has been clouded by age-old problems: poor patient adherence, inability to objectively measure the environmental influences on health, lack of knowledge about patients’ lifestyle behaviors that may affect cancer’s progression and recurrence, and limited ability to compile and interpret the wide range of variables that must be considered in the cancer treatment. This lack of data integration limits the potential for patients and clinicians to engage in fully informed decision-making regarding cancer prevention, treatment, and survivorship care, and the translation of research results into mainstream medical care. Particularly important, as noted in a 2009 report on CER to the President and Congress, the limited focus on health behavior-change interventions was a major hindrance in this research landscape (DHHS 2009). This paper describes an initiative to improve CER for cancer by addressing several of these limitations. The Cyberinfrastructure for Comparative Effectiveness Research (CYCORE) project, informed by the National Science Foundation’s 2007 report “Cyberinfrastructure Vision for 21st Century Discovery” has, as its central aim, the creation of a prototype for a user-friendly, open-source cyberinfrastructure (CI) that supports acquisition, storage, visualization, analysis, and sharing of data important for cancer-related CER. Although still under development, the process of gathering requirements for CYCORE has revealed new ways in which CI design can significantly improve the collection and analysis of a wide variety of data types, and has resulted in new and important partnerships among cancer researchers engaged in advancing health-related CI

Structural Characterization and Ligand/Inhibitor Identification Provide Functional Insights into the Mycobacterium tuberculosis Cytochrome P450 CYP126A1

The Mycobacterium tuberculosis H37Rv genome encodes 20 cytochromes P450, including P450s crucial to infection and bacterial viability. Many M. tuberculosis P450s remain uncharacterized, suggesting that their further analysis may provide new insights into M. tuberculosis metabolic processes and new targets for drug discovery. CYP126A1 is representative of a P450 family widely distributed in mycobacteria and other bacteria. Here we explore the biochemical and structural properties of CYP126A1, including its interactions with new chemical ligands. A survey of azole antifungal drugs showed that CYP126A1 is inhibited strongly by azoles containing an imidazole ring but not by those tested containing a triazole ring. To further explore the molecular preferences of CYP126A1 and search for probes of enzyme function, we conducted a high throughput screen. Compounds containing three or more ring structures dominated the screening hits, including nitroaromatic compounds that induce substrate-like shifts in the heme spectrum of CYP126A1. Spectroelectrochemical measurements revealed a 155-mV increase in heme iron potential when bound to one of the newly identified nitroaromatic drugs. CYP126A1 dimers were observed in crystal structures of ligand-free CYP126A1 and for CYP126A1 bound to compounds discovered in the screen. However, ketoconazole binds in an orientation that disrupts the BC-loop regions at the P450 dimer interface and results in a CYP126A1 monomeric crystal form. Structural data also reveal that nitroaromatic ligands "moonlight" as substrates by displacing the CYP126A1 distal water but inhibit enzyme activity. The relatively polar active site of CYP126A1 distinguishes it from its most closely related sterol-binding P450s in M. tuberculosis, suggesting that further investigations will reveal its diverse substrate selectivity.This work was supported by Biotechnology and Biological Research Council (BBSRC) Grants BB/I019227/1 (to A. W. M.) and BB/I019669/1 (to C. A.) underpinning this research program and supporting the research of A. J. C. and K. J. M

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

SCOPE: SCUBA-2 Continuum Observations of Pre-protostellar Evolution - Survey description and compact source catalogue

We present the first release of the data and compact-source catalogue for the JCMT Large Program SCUBA-2 Continuum Observations of Pre-protostellar Evolution (SCOPE). SCOPE consists of 850 μm continuum observations of 1235 Planck Galactic Cold Clumps (PGCCs) made with the Submillimetre Common-User Bolometer Array 2 on the James Clerk Maxwell Telescope. These data are at an angular resolution of 14.4 arcsec, significantly improving upon the 353 GHz resolution of Planck at 5 arcmin, and allowing for a catalogue of 3528 compact sources in 558 PGCCs. We find that the detected PGCCs have significant sub-structure, with 61 per cent of detected PGCCs having three or more compact sources, with filamentary structure also prevalent within the sample. A detection rate of 45 per cent is found across the survey, which is 95 per cent complete to Planck column densities of NH2 > 5 × 1021 cm−2. By positionally associating the SCOPE compact sources with young stellar objects, the star formation efficiency, as measured by the ratio of luminosity to mass, in nearby clouds is found to be similar to that in the more distant Galactic Plane, with the column density distributions also indistinguishable from each other

Statistical models of morphology predict eye-tracking measures during visual word recognition

We studied how statistical models of morphology that are built on different kinds of representational units, i.e., models emphasizing either holistic units or decomposition, perform in predicting human word recognition. More specifically, we studied the predictive power of such models at early vs. late stages of word recognition by using eye-tracking during two tasks. The tasks included a standard lexical decision task and a word recognition task that assumedly places less emphasis on postlexical reanalysis and decision processes. The lexical decision results showed good performance of Morfessor models based on the Minimum Description Length optimization principle. Models which segment words at some morpheme boundaries and keep other boundaries unsegmented performed well both at early and late stages of word recognition, supporting dual- or multiple-route cognitive models of morphological processing. Statistical models based on full forms fared better in late than early measures. The results of the second, multi-word recognition task showed that early and late stages of processing often involve accessing morphological constituents, with the exception of short complex words. Late stages of word recognition additionally involve predicting upcoming morphemes on the basis of previous ones in multimorphemic words. The statistical models based fully on whole words did not fare well in this task. Thus, we assume that the good performance of such models in global measures such as gaze durations or reaction times in lexical decision largely stems from postlexical reanalysis or decision processes. This finding highlights the importance of considering task demands in the study of morphological processing.Peer reviewe