Detection of insulin analogues and large peptides >2 kDa in urine.

Insulin analogues and large bioactive peptides may be used by athletes to enhance performance and are banned by the World Anti-Doping Agency (WADA). In addition to insulin analogues, the large peptides include a structurally diverse set of peptides including analogues of growth hormone releasing hormone (GHRH), insulin-like growth factor-1 (IGF-1), and mechano-growth factor (MGF). Detection of this class of peptides is difficult due to their absorptive losses and presence at very low concentrations in urine. In this report, a high throughput method is described that allows sensitive detection of four classes of large peptides in one assay. Sample extraction is performed by ultrafiltration to concentrate the urine followed by solid phase extraction in a 96-well micro-elution plate. Peptides in the urine samples are detected on a triple quadrupole mass spectrometer coupled to standard flow liquid chromatography. The method was validated and evaluated for limit of detection, limit of identification, specificity, precision, carryover, recovery, matrix interference, and post-extraction stability. The limit of detection for insulin analogues is between 5 and 25 pg/ml and between 5 and 50 pg/ml for the other peptide classes. Specificity was good with no detection of interfering peaks in blank urine samples. Carryover from a high concentration sample was not observed and the post-extraction stability was between 77% and 107%. The method was able to detect insulin analogues in three diabetic urine samples. Increased screening for this class of peptides will improve detection and deterrence.

Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images.

Background and purpose: Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements. Materials and methods: Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures. Results: ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles. Conclusion: Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.