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The detection of low doses of recombinant growth hormone is a challenge in antidoping testing. Future testing may lead toward the longitudinal monitoring of IGF-I and P-III-NP in an endocrine module. Additional biomarkers, for example vitamin D binding protein, alpha-HS-glycoprotein, fibronectin 1, and decorin have been identified in different omics studies. This was a longitudinal study of the usefulness of these putative biomarkers in relation to 2 weeks administration of low doses of recombinant growth hormone in healthy male volunteers. Moreover, the hematological parameters included in the athlete biological passport were studied as well as the serum concentration of testosterone and dihydrotestosterone. Fibronectin 1 increased by 20% during the treatment period (P ˂ 0.05), confirming the previous finding. Alpha-HS-glycoprotein decreased by 25% up to 3 weeks after treatment (P ˂ 0.05), contradicting previous results. The addition of fibronectin 1 increased the likelihood of detecting recombinant growth hormone intake based on individual calculated thresholds in some of the participants compared with the GH2000, IGF-I, and P-III-NP. The multiplication of fibronectin 1 concentration by IGF-I resulted in the most profound (up to 4-fold) changes. A minor 15% increase (P = 0.003) in the reticulocyte percentage was observed, but the changes did not lead to any atypical profile based on individual passport thresholds. Vitamin D binding protein, decorin, testosterone, and dihydrotestosterone were not affected by growth hormone. Dihydrotestosterone sulfate was negatively correlated with IGF-I at baseline (R = -0.50, P = 0.003) and post dose (R = -0.59, P = 0.01). In conclusion, fibronectin 1 was verified as a promising future biomarker for detecting low doses of recombinant growth hormone.

The efficiency of the immunopurification step of urinary erythropoietin (EPO) and recombinant forms is important for their optimal detection in antidoping screening. Previous investigations of immunopurification techniques have been done for immunomagnetic beads, EPO Purification Kit (EPK) columns (MAIIA Diagnostics), and enzyme-linked immunosorbent assay (ELISA) microplates (Stemcell Technologies) conjugated/coated with anti-EPO antibodies. In this study, a new immunopurification technique using anti-EPO sepharose gel beads, developed by MAIIA Diagnostics, to simplify and minimize sample handling was evaluated. This EPO Purification Gel Kit (EPGK) was compared with our current routine EPK for limit of detection (LOD). Linearity, recovery, repeatability, sample incubation time, and sample volume were also evaluated for EPGK. The LODs and linearity for EPK and EPGK were comparable to each other and the recovery for BRP, NESP, CERA, and EPO-Fc were within the range of other studies, and concentration of the sample eluate improved the recovery results. Little variation was seen within days, between days, and between operators. A 90 minute incubation of the sample with the sepharose gel beads is sufficient for most of the erythropoiesis stimulating agents (ESAs) tested, with 10 mL being an optimal sample volume for EPGK. The improved sample handling, higher sample throughput and the reduced working time demonstrate that the EPGK is a better alternative to the current MAIIA EPK immunopurification method for urine. The EPO Purification Gel Kit (from MAIIA Diagnostics) was evaluated and validated for immunopurification of endogenous erythropoietin and exogenous erythropoiesis stimulating agents from urine samples. The kit was a better alternative to that currently used (EPO Purification Kit) in many antidoping laboratories because it improves sample handling and increases sample throughput.

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices is swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors.

To detect doping with growth hormone (GH), GH isoform and biomarkers tests are available. Both methods use population-based decision limits. Future testing in anti-doping is progressing toward individual-based reference ranges, and it is possible that with such an approach the sensitivity to detect GH doping may increase. In addition to monitoring different proteins, the use of miRNAs as future GH biomarkers has been discussed. Here we have longitudinally studied the serum concentrations of IGF-I, P-III-NP and the different GH isoforms in nine healthy men prior to, during and after two weeks' administration with low doses (1 and 4 IU/day) of recGH. Moreover, three putative miRNAs were analyzed. The results show that 80% of the participants were identified as atypical findings using the GH isoform test. However, the participants were only positive 1.5-3 hours directly after an injection. Only one of the participants reached a GH-2000 score indicative of doping when a population-based decision limit was applied. When IGF-I and P-III-NP were longitudinally monitored, 88% of the participants were identified above an individual upper threshold arbitrarily calculated as three standard deviations above the mean values of four baseline samples. The miRNA levels displayed large intra-subject variations that did not change in relation to recGH administration. Our results show that the GH isoform test is very sensitive in detecting low doses of recGH but with a short detection window. Moreover, longitudinally monitoring of IGF-I and P-III-NP may be a promising future approach to detect GH doping.

Random graphs (or networks) have gained a significant increase of interest due to its popularity in modeling and simulating many complex real-world systems. Degree sequence is one of the most important aspects of these systems. Random graphs with a given degree sequence can capture many characteristics like dependent edges and non-binomial degree distribution that are absent in many classical random graph models such as the Erd\H{o}s-R\'{e}nyi graph model. In addition, they have important applications in the uniform sampling of random graphs, counting the number of graphs having the same degree sequence, as well as in string theory, random matrix theory, and matching theory. In this paper, we present an OpenMP-based shared-memory parallel algorithm for generating a random graph with a prescribed degree sequence, which achieves a speedup of 20.5 with 32 cores. One of the steps in our parallel algorithm requires checking the Erd\H{o}s-Gallai characterization, i.e., whether there exists a graph obeying the given degree sequence, in parallel. This paper presents the first non-trivial parallel algorithm for checking the Erd\H{o}s-Gallai characterization, which achieves a speedup of 23 using 32 cores., Comment: 10 pages