Variability of the Human Serum Metabolome over 3 Months in the EXPOsOMICS Personal Exposure Monitoring Study.

Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and untargeted metabolomics are increasingly used in exposome studies to study the interactions between nongenetic factors and the blood metabolome. To reliably and efficiently link detected compounds to exposures and health phenotypes in such studies, it is important to understand the variability in metabolome measures. We assessed the within- and between-subject variability of untargeted LC-HRMS measurements in 298 nonfasting human serum samples collected on two occasions from 157 subjects. Samples were collected ca. 107 (IQR: 34) days apart as part of the multicenter EXPOsOMICS Personal Exposure Monitoring study. In total, 4294 metabolic features were detected, and 184 unique compounds could be identified with high confidence. The median intraclass correlation coefficient (ICC) across all metabolic features was 0.51 (IQR: 0.29) and 0.64 (IQR: 0.25) for the 184 uniquely identified compounds. For this group, the median ICC marginally changed (0.63) when we included common confounders (age, sex, and body mass index) in the regression model. When grouping compounds by compound class, the ICC was largest among glycerophospholipids (median ICC 0.70) and steroids (0.67), and lowest for amino acids (0.61) and the O-acylcarnitine class (0.44). ICCs varied substantially within chemical classes. Our results suggest that the metabolome as measured with untargeted LC-HRMS is fairly stable (ICC > 0.5) over 100 days for more than half of the features monitored in our study, to reflect average levels across this time period. Variance across the metabolome will result in differential measurement error across the metabolome, which needs to be considered in the interpretation of metabolome results

Intervju: akademik Jakša Barbić

Over the past 20 years evidence has accumulated confirming the immunomodulatory role of the appendix in ulcerative colitis (UC). This led to the idea that appendectomy might alter the clinical course of established UC. The objective of this body of research is to evaluate the short-term and medium-term efficacy of appendectomy to maintain remission in patients with UC, and to establish the acceptability and cost-effectiveness of the intervention compared to standard treatment. These paired phase III multicenter prospective randomised studies will include patients over 18 years of age with an established diagnosis of ulcerative colitis and a disease relapse within 12 months prior to randomisation. Patients need to have been medically treated until complete clinical (Mayo score <3) and endoscopic (Mayo score 0 or 1) remission. Patients will then be randomised 1:1 to a control group (maintenance 5-ASA treatment, no appendectomy) or elective laparoscopic appendectomy plus maintenance treatment. The primary outcome measure is the one year cumulative UC relapse rate - defined both clinically and endoscopically as a total Mayo-score ≥5 with endoscopic subscore of 2 or 3. Secondary outcomes that will be assessed include the number of relapses per patient at 12 months, the time to first relapse, health related quality of life and treatment costs, and number of colectomies in each arm. The ACCURE and ACCURE-UK trials will provide evidence on the role and acceptability of appendectomy in the treatment of ulcerative colitis and the effects of appendectomy on the disease course. NTR2883 ; ISRCTN5652301

Note--A Note on Dynamic Programming with Unbounded Rewards

In a recent paper, Lippman presents sufficient conditions for Denardo's N-stage contraction in discounted semi-Markov decision processes with unbounded rewards. In this note it is demonstrated that Lippman's conditions may be replaced by weaker conditions which even imply 1-stage contraction. The verification of the conditions of this note is somewhat easier.

Computing Optimal Control Limits for GI/M/S Queuing Systems with Controlled Arrivals

We consider a GI/M/s queuing system that is controlled by either accepting or rejecting arriving customers. Under weak conditions on the cost structure, Stidham (Stidham, S., Jr., 1978. Socially and individually optimal control of arrivals to a GI/M/1 queue. Management Sci. 24 1598--1610.) showed that a control limit policy is optimal. In this paper we show how the special structure of this queuing system can be exploited to develop efficient procedures to determine an optimal control limit. An explicit algorithm for computing the optimal control as well as an example and some computational results are included.queuing control, Markov decision processes, computational methods