Ligand-based virtual screening using binary kernel discrimination

This paper discusses the use of a machine-learning technique called binary kernel discrimination (BKD) for virtual screening in drug- and pesticide-discovery programmes. BKD is compared with several other ligand-based tools for virtual screening in databases of 2D structures represented by fragment bit-strings, and is shown to provide an effective, and reasonably efficient, way of prioritising compounds for biological screening

The star formation histories of low surface brightness galaxies

We have performed deep imaging of a diverse sample of 26 low surface brightness galaxies (LSBGs) in the optical and the near-infrared. Using stellar population synthesis models, we find that it is possible to place constraints on the ratio of young to old stars (which we parametrize in terms of the average age of the galaxy), as well as the metallicity of the galaxy, using optical and near-infrared colours. LSBGs have a wide range of morphologies and stellar populations, ranging from older, high-metallicity earlier types to much younger and lower-metallicity late-type galaxies. Despite this wide range of star formation histories, we find that colour gradients are common in LSBGs. These are most naturally interpreted as gradients in mean stellar age, with the outer regions of LSBGs having lower ages than their inner regions. In an attempt to understand what drives the differences in LSBG stellar populations, we compare LSBG average ages and metallicities with their physical parameters. Strong correlations are seen between an LSBG's star formation history and its K-band surface brightness, K-band absolute magnitude and gas fraction. These correlations are consistent with a scenario in which the star formation history of an LSBG primarily correlates with its surface density and its metallicity correlates with both its mass and its surface densit

Global patterns of diapycnal mixing from measurements of the turbulent dissipation rate

The authors present inferences of diapycnal diffusivity from a compilation of over 5200 microstructure profiles. As microstructure observations are sparse, these are supplemented with indirect measurements of mixing obtained from (i) Thorpe-scale overturns from moored profilers, a finescale parameterization applied to (ii) shipboard observations of upper-ocean shear, (iii) strain as measured by profiling floats, and (iv) shear and strain from full-depth lowered acoustic Doppler current profilers (LADCP) and CTD profiles. Vertical profiles of the turbulent dissipation rate are bottom enhanced over rough topography and abrupt, isolated ridges. The geography of depth-integrated dissipation rate shows spatial variability related to internal wave generation, suggesting one direct energy pathway to turbulence. The global-averaged diapycnal diffusivity below 1000-m depth is O(10?4) m2 s?1 and above 1000-m depth is O(10?5) m2 s?1. The compiled microstructure observations sample a wide range of internal wave power inputs and topographic roughness, providing a dataset with which to estimate a representative global-averaged dissipation rate and diffusivity. However, there is strong regional variability in the ratio between local internal wave generation and local dissipation. In some regions, the depth-integrated dissipation rate is comparable to the estimated power input into the local internal wave field. In a few cases, more internal wave power is dissipated than locally generated, suggesting remote internal wave sources. However, at most locations the total power lost through turbulent dissipation is less than the input into the local internal wave field. This suggests dissipation elsewhere, such as continental margins

Exploring patient information needs in type 2 diabetes: A cross sectional study of questions

This study set out to analyze questions about type 2 diabetes mellitus (T2DM) from patients and the public. The aim was to better understand people's information needs by starting with what they do not know, discovered through their own questions, rather than starting with what we know about T2DM and subsequently finding ways to communicate that information to people affected by or at risk of the disease. One hundred and sixty-four questions were collected from 120 patients attending outpatient diabetes clinics and 300 questions from 100 members of the public through the Amazon Mechanical Turk crowdsourcing platform. Twenty-three general and diabetes-specific topics and five phases of disease progression were identified; these were used to manually categorize the questions. Analyses were performed to determine which topics, if any, were significant predictors of a question's being asked by a patient or the public, and similarly for questions from a woman or a man. Further analysis identified the individual topics that were assigned significantly more often to the crowdsourced or clinic questions. These were Causes (CI: [-0.07, -0.03], p < .001), Risk Factors ([-0.08, -0.03], p < .001), Prevention ([-0.06, -0.02], p < .001), Diagnosis ([-0.05, -0.02], p < .001), and Distribution of a Disease in a Population ([-0.05,-0.01], p = .0016) for the crowdsourced questions and Treatment ([0.03, 0.01], p = .0019), Disease Complications ([0.02, 0.07], p < .001), and Psychosocial ([0.05, 0.1], p < .001) for the clinic questions. No highly significant gender-specific topics emerged in our study, but questions about Weight were more likely to come from women and Psychosocial questions from men. There were significantly more crowdsourced questions about the time Prior to any Diagnosis ([(-0.11, -0.04], p = .0013) and significantly more clinic questions about Health Maintenance and Prevention after diagnosis ([0.07. 0.17], p < .001). A descriptive analysis pointed to the value provided by the specificity of questions, their potential to disclose emotions behind questions, and the as-yet unrecognized information needs they can reveal. Large-scale collection of questions from patients across the spectrum of T2DM progression and from the public-a significant percentage of whom are likely to be as yet undiagnosed-is expected to yield further valuable insights

The effectiveness of schemes that refine referrals between primary and secondary care - the UK experience with glaucoma referrals: the Health Innovation & Education Cluster (HIEC) Glaucoma Pathways Project

Objectives: A comparison of glaucoma referral refinement schemes (GRRS) in the UK during a time period of considerable change in national policy and guidance. Design: Retrospective multisite review. Setting: The outcomes of clinical examinations by optometrists with a specialist interest in glaucoma (OSIs) were compared with optometrists with no specialist interest in glaucoma (non-OSIs). Data from Huntingdon and Nottingham assessed non-OSI findings, while Manchester and Gloucestershire reviewed OSI findings. Participants: 1086 patients. 434 patients were from Huntingdon, 179 from Manchester, 204 from Gloucestershire and 269 from Nottingham. Results: The first-visit discharge rate (FVDR) for all time periods for OSIs was 14.1% compared with 36.1% from non-OSIs (difference 22%, CI 16.9% to 26.7%; p<0.001). The FVDR increased after the April 2009 National Institute for Health and Clinical Excellence (NICE) glaucoma guidelines compared with pre-NICE, which was particularly evident when pre-NICE was compared with the current practice time period (OSIs 6.2–17.2%, difference 11%, CI −24.7% to 4.3%; p=0.18, non-OSIs 29.2–43.9%, difference 14.7%, CI −27.8% to −0.30%; p=0.03). Elevated intraocular pressure (IOP) was the commonest reason for referral for OSIs and non-OSIs, 28.7% and 36.1%, respectively, of total referrals. The proportion of referrals for elevated IOP increased from 10.9% pre-NICE to 28.0% post-NICE for OSIs, and from 19% to 45.1% for non-OSIs. Conclusions: In terms of ‘demand management’, OSIs can reduce FVDR of patients reviewed in secondary care; however, in terms of ‘patient safety’ this study also shows that overemphasis on IOP as a criterion for referral is having an adverse effect on both the non-OSIs and indeed the OSIs ability to detect glaucomatous optic nerve features. It is recommended that referral letters from non-OSIs be stratified for risk, directing high-risk patients straight to secondary care, and low-risk patients to OSIs

1974

History of Golf (1) The Nine Toughest Holes in the World (2) Stockie Madness (3) Bartender, One More Round for Pythium (3) Panel: 1973 Turf Problems in Review - 1974 Possible Remedies (A1-A12) Movement of Water to a Holding Pond (A13) Maintenance of Low Budget, Short Season Golf Courses (A16) Turfgrass Fertilization (A18) Determining Turfgrass Fertilizer Needs (A25) Shortage of Plant Food and How to Adjust to Supply and Cost (A29) Panel: Tricalcium Arsenate - Use and Abuse (A33-A46) Operating and Maintaining Municipal Golf Courses (A48) Maintenance of a High Budget Golf Course (A51) Trends in Agricultural Education and Where Are the Emphases (A58) Maintenance of Municipal Parks and Recreation Areas (A60) Maintenance of Grass Tennis Courts (A63) Transition from Natural to Artificial Turf (A67) Plant materials for Outlying Areas (A71) Care of University Grounds (A76) Maintenance of Industrial Sites (A79) Turfgrass Diseases and Systemic Fungicides (A81) A Look at the Future (A 84) Watering of Golf Course Turf (A92

Training of Instrumentalists and Development of New Technologies on SOFIA

This white paper is submitted to the Astronomy and Astrophysics 2010 Decadal Survey (Astro2010)1 Committee on the State of the Profession to emphasize the potential of the Stratospheric Observatory for Infrared Astronomy (SOFIA) to contribute to the training of instrumentalists and observers, and to related technology developments. This potential goes beyond the primary mission of SOFIA, which is to carry out unique, high priority astronomical research. SOFIA is a Boeing 747SP aircraft with a 2.5 meter telescope. It will enable astronomical observations anywhere, any time, and at most wavelengths between 0.3 microns and 1.6 mm not accessible from ground-based observatories. These attributes, accruing from the mobility and flight altitude of SOFIA, guarantee a wealth of scientific return. Its instrument teams (nine in the first generation) and guest investigators will do suborbital astronomy in a shirt-sleeve environment. The project will invest $10M per year in science instrument development over a lifetime of 20 years. This, frequent flight opportunities, and operation that enables rapid changes of science instruments and hands-on in-flight access to the instruments, assure a unique and extensive potential - both for training young instrumentalists and for encouraging and deploying nascent technologies. Novel instruments covering optical, infrared, and submillimeter bands can be developed for and tested on SOFIA by their developers (including apprentices) for their own observations and for those of guest observers, to validate technologies and maximize observational effectiveness.Comment: 10 pages, no figures, White Paper for Astro 2010 Survey Committee on State of the Professio

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed