New technology enables high precision multislit collimators for microbeam radiation therapy

During the past decade microbeam radiation therapy has evolved from preclinical studies to a stage in which clinical trials can be planned, using spatially fractionated, highly collimated and high intensity beams like those generated at the x-ray ID17 beamline of the European Synchrotron Radiation Facility. The production of such microbeams typically between 25 and 100 microm full width at half maximum (FWHM) values and 100-400 microm center-to-center (c-t-c) spacings requires a multislit collimator either with fixed or adjustable microbeam width. The mechanical regularity of such devices is the most important property required to produce an array of identical microbeams. That ensures treatment reproducibility and reliable use of Monte Carlo-based treatment planning systems. New high precision wire cutting techniques allow the fabrication of these collimators made of tungsten carbide. We present a variable slit width collimator as well as a single slit device with a fixed setting of 50 microm FWHM and 400 microm c-t-c, both able to cover irradiation fields of 50 mm width, deemed to meet clinical requirements. Important improvements have reduced the standard deviation of 5.5 microm to less than 1 microm for a nominal FWHM value of 25 microm. The specifications of both devices, the methods used to measure these characteristics, and the results are presented.

Growth curves for cardio-metabolic risk factors in children and adolescents

OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US children and adolescents. STUDY DESIGN: A representative sample of US children and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total cholesterol, LDL cholesterol, triglycerides, and HDL cholesterol from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. Triglycerides were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL cholesterol were constructed for both males and females. When data from the additional child studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US children and adolescents, with identification of values that transition to adult abnormalities. They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.

Assigning Bug Reports using a Vocabulary-Based Expertise Model of Developers

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming reports is a time consuming task. Part of the bug triage is the assignment of a report to a developer with the appropriate expertise. In this paper, we present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report. We model developer expertise using the vocabulary found in their source code contributions and compare this vocabulary to the vocabulary of bug reports. We evaluate our approach by comparing the suggested experts to the persons who eventually worked on the bug. Using eight years of Eclipse development as a case study, we achieve 33.6\% top-1 precision and 71.0\% top-10 recall.