In this issue

Abstract

AbstractA line in the sand: Late summer starting point for workflow designpp. 383–396Security is handled by the rising tide. Remily‐Wood et al. developed a procedure for high‐throughput quantitative analysis for cancer research and clinical studies. The process begins with some bench and library work to define the target to be quantitated by determining amino acid sequences, isoforms, post‐translational modifications, and Western blots. Data go into QuAD, a JavaServer supplying other resources (Swiss‐Prot, etc.) and summary statistics of the target proteins. Target proteins and pathways must have ≥3 distinctive peptides, quantitative assays and have cultured cell line equivalents. Heavy isotope‐labeled synthetic peptides and cultured cell sequences are used to follow the LC‐Multiple Reaction Monitoring. The molecular weight equivalent SDS‐PAGE region is excised for screening peptides after in‐gel digestion. The screening conditions use minimal amounts of labeled peptides. magnified imageGetting your ducks in a row: A tough herding jobpp. 405–414French medical practices require testing all newborns for sickle cell disease. There is a standard method for the test – isoelectric focusing (IEF) followed by HPLC on a cation exchange column. The HPLC ducks can be readily automated and labor costs minimized, but not so for IEF. It is tedious, uses expensive materials and is generally disliked in the lab, especially when many samples need to be run. Hachani et al. report on the development of a MALDI‐MS method that deals with most of problems. Previous research work had been incomplete for a variety of reasons. The new method used the same sample cards, a robotic commercial sample prep method, and automated analysis of samples using a MALDI‐TOF/TOF instrument. Failures of the new method against IEF were informative – most were premature or heterozygous neonatal infants. Conclusion: automated herding of 1000 samples/day looks feasible. magnified imageDouble or nothing for the kidney?pp. 422–431It is a sucker's bet on some streets in New York and serious business for patients waiting for a kidney transplant. Chronic allograft nephropathy (CAN) is the leading cause of kidney graft failure in the first year after transplant, being responsible for a 50–80% loss rate. The ability to reduce the failure rate by early recognition and treatment of CAN would markedly increase the number of kidneys available. Johnston et al. report here an improved urine protein marker pattern that can distinguish normal from CAN urine protein patterns. The principal element of the pattern (SELDI‐TOF‐MS hardware) was the amount of β2 microglobulin (11.7 kDa). A single β2 microglobulin point is insufficiently discriminating so further work will have to be done in a more complex setting. magnified image