No abstract

Inner-city youth are at high risk for dropping out of high school. Within this article, risk factors associated with dropout and strategies for effective prevention and intervention are reviewed. An example of a school-based drop-out prevention program is highlighted. The FUTURES Program is a school-based drop-out prevention program designed to address the needs of high-risk youth through smaller classes, character development, career preparation, case management/mentoring, positive incentives, and access to mental health services. Components of the program are described in detail and data evaluating the effectiveness of the program are presented. Directions for the future development of programs and conducting research to prevent dropout by inner-city youth are discussed.

Genomic mismatch scanning (GMS) is a new method of genetic linkage analysis that does not require conventional polymorphic markers or gel electrophoresis. GMS is ideally suited to affected-relative-pair mapping. DNA fragments from all regions of identity-by-descent between two relatives are isolated based on their ability to form extensive mismatch-free hybrid molecules. The genomic origin of this selected pool of DNA fragments is then mapped in a single hybridization step. Here we demonstrate the practicality of GMS in a model organism, Saccharomyces cerevisiae. GMS is likely to be applicable to other organisms, including humans, and may be of particular value in mapping complex genetic traits.

Detailed structural information on metabolites serving as target analytes in clinical, forensic, and sports drug testing programmes is of paramount importance to ensure unequivocal test results. In the present study, the utility of collision cross section (CCS) analysis by travelling wave ion mobility measurements to support drug metabolite characterization efforts was tested concerning recently identified glucuronic acid conjugates of the anabolic-androgenic steroid stanozolol. Employing travelling-wave ion mobility spectrometry/quadrupole-time-of-flight mass spectrometry, drift times of five synthetically derived and fully characterized steroid glucuronides were measured and subsequently correlated to respective CCSs as obtained in silico to form an analyte-tailored calibration curve. The CCSs were calculated by equilibrium structure minimization (density functional theory) using the programmes ORCA with the data set B3LYP/6-31G and MOBCAL utilizing the trajectory method (TM) with nitrogen as drift gas. Under identical experimental conditions, synthesized and/or urinary stanozolol-N and O-glucuronides were analyzed to provide complementary information on the location of glucuronidation. Finally, the obtained data were compared to CCS results generated by the system's internal algorithm based on a calibration employing a polyalanine analyte mixture. The CCSs ΩN2 calculated for the five steroid glucuronide calibrants were found between 180 and 208 Å(2) , thus largely covering the observed and computed CCSs for stanozolol-N1'-, stanozolol-N2'-, and stanozolol-O-glucuronide found at values between 195.1 and 212.4 Å(2) . The obtained data corroborated the earlier suggested N- and O-glucuronidation of stanozolol, and demonstrate the exploit of ion mobility and CCS computation in structure characterization of phase-II metabolic products; however, despite reproducibly measurable differences in ion mobility of stanozolol-N1'-, N2'-, and O-glucuronides, the discriminatory power of the chosen CCS computation algorithm was found to be not appropriate to allow for accurate assignments of the two N-conjugated structures. Using polyalanine-based calibrations, significantly different absolute values were obtained for all CCSs, but due to a constant offset of approximately 45 Å(2) an excellent correlation (R(2)  = 0.9997) between both approaches was observed. This suggests a substantially accelerated protocol when patterns of computed and polyalanine-based experimental data can be used for structure elucidations instead of creating individual analyte-specific calibration curves.