DNA-based carrier detection and prenatal diagnosis of tyrosinase-negative oculocutaneous albinism (OCA1A)

We describe molecular prenatal diagnosis and carrier detection of tyrosinase-negative oculocutaneous albinism (OCA1A) in two families. In one family, we carried out DNA-based prenatal diagnosis of OCA1A. In the other family, mutation analysis and carrier detection obviated the need for prenatal diagnosis. Molecular analysis is safer and probably more accurate than fetoscopy and fetal scalp biopsy, and should become the method of first choice for prenatal diagnosis of OCA1.     

Identification and field bioassays of the sex pheromone of the yellow-legged clearwing Synanthedon vespiformis (Lepidoptera: Sesiidae)

The yellow-legged clearwing (YLC) Synanthedon vespiformis (Lepidoptera: Sesiidae) occurs in the Mediterranean and central Europe. It is polyphagous, boring into the woody parts of broadleaf species including forest trees as well as various Rosaceae species. S. vespiformis has been reported as an economically important pest causing severe injury to stone fruit plantations. Many attractants for sesiid species were discovered by random field screening using 2,13- and 3,13-octadecadienyl alcohols, acetates and aldehydes, including one for S. vespiformis; and about 20 sex pheromones of sesiids have been identified so far. In the present study we identified the natural composition of the sex pheromone of YLC laboratory reared females as a blend of E3,Z13- and Z3,Z13-octadecadienyl acetates, at a ratio of 4:1. We developed an efficient lure for monitoring the pest. Pheromone funnel traps with rubber septa, impregnated with 1 mg pheromone blend, efficiently captured males for 10 weeks. Suspension of Shin-Etsu^? ropes containing a 2:1 blend of E3,Z13-18:Ac and Z3,Z13-18:Ac at 13.74 mg/ha/h, resulted in shutdown of trap catches in the treated plots and closely situated neighboring plots indicating that mating disruption is feasible.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

Committing driving violations: An observational study comparing city, town and village

Introduction

This article compares observed driving behavior in a city, a town, and a village.

Method

Unobtrusive observations were made at intersections in each residential type. Five violation types were observed: (a) not wearing a seat belt (seat belt violation); (b) not using a safety seat for a child (safety seat violation for children); (c) not using a speaker while speaking on the phone (on-phone violation); (d) failing to comply with a ‘give way’ sign (‘give way’ sign violation); and (e) stopping in an undesignated area (undesignated stop violation). It was expected that in accordance with the anonymity hypothesis that the bigger residential areas' rate of traffic violations would be higher. The effects of the residential type, drivers' gender, and age were assessed using the multiple regression model. The stepwise method of evaluation was employed. The model converged on step 3 (Adjusted R square = 0.039). Residential type and gender contributed significantly to the model. Results: Consistent with prior research, male drivers committed more violations than female drivers. Chi-square analyses were used to test the distribution of violations by the settlement types. Overall, more drivers committed violations in the two small residential areas than in the city, with 30% of city drivers, 43% of town drivers, and 51% of village drivers committing at least one violation (χ2 (2) = 37.65, p < 0.001). Moreover, in the town and the village, a combination of one or more violations was committed more often than in the city (χ2 (1) = 34.645, p < 0.001). Accordingly, more drivers committed violations in the two small settlements (48.4%) than in the city (30.6%). Possible explanations for the observed results were provided in the Discussion section.

Impact on Industry

The conclusions of this paper are that drivers in small villages tend to disobey traffic laws. Therefore, efforts have to be made in companies to take this issue in consideration while running fleets in companies located in small places far from the center.