Identification of three high molecular mass cysteine proteinases from rat skeletal muscle

AbstractThree cysteine proteinases were isolated from the post-myofibrillar fraction of rat skeletal muscle. Proteinase I preferentially hydrolyzes Z-Phe—Arg-NMec with pH optimum at 8–9. The enzyme activity is stabilized by ATP against thermal inactivation. Proteinase II and III were not resolved by anion-exchange chromatography, by affinity chromatography on Arginine—Sepharose or by gel filtration. Proteinase II, splitting Bz-ValGlyArg-NMec optimally at pH 10–10.5, is inactivated by ATP, whereas Proteinase III, hydrolyzing Suc-AlaAlaPhe-NMec at pH 7–7.5 is not affected by the nucleotide. The molecular mass of proteinase I is about 750 000 and that of proteinase II and III is about 650 000, as determined by gel filtration

Evaluation of the use of decision-support software in carcino-embryonic antigen (CEA)-based follow-up of patients with colorectal cancer

BACKGROUND: The present paper is a first evaluation of the use of "CEAwatch", a clinical support software system for surgeons for the follow-up of colorectal cancer (CRC) patients. This system gathers Carcino-Embryonic Antigen (CEA) values and automatically returns a recommendation based on the latest values. METHODS: Consecutive patients receiving follow-up care for CRC fulfilling our in- and exclusion criteria were identified to participate in this study. From August 2008, when the software was introduced, patients were asked to undergo the software-supported follow-up. Safety of the follow-up, experiences of working with the software, and technical issues were analyzed. RESULTS: 245 patients were identified. The software-supported group contained 184 patients; the control group contained 61 patients. The software was safe in finding the same amount of recurrent disease with fewer outpatient visits, and revealed few technical problems. Clinicians experienced a decrease in follow-up workload of up to 50% with high adherence to the follow-up scheme. CONCLUSION: CEAwatch is an efficient software tool helping clinicians working with large numbers of follow-up patients. The number of outpatient visits can safely be reduced, thus significantly decreasing workload for clinicians