62 research outputs found

    Validation of whole-blood transcriptome signature during microdose recombinant human erythropoietin (rHuEpo) administration

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    BACKGROUND: Recombinant human erythropoietin (rHuEpo) can improve human performance and is therefore frequently abused by athletes. As a result, the World Anti-Doping Agency (WADA) introduced the Athlete Biological Passport (ABP) as an indirect method to detect blood doping. Despite this progress, challenges remain to detect blood manipulations such as the use of microdoses of rHuEpo. METHODS: Forty-five whole-blood transcriptional markers of rHuEpo previously derived from a high-dose rHuEpo administration trial were used to assess whether microdoses of rHuEpo could be detected in 14 trained subjects and whether these markers may be confounded by exercise (n = 14 trained subjects) and altitude training (n = 21 elite runners and n = 4 elite rowers, respectively). Differential gene expression analysis was carried out following normalisation and significance declared following application of a 5% false discovery rate (FDR) and a 1.5 fold-change. Adaptive model analysis was also applied to incorporate these markers for the detection of rHuEpo. RESULTS: ALAS2, BCL2L1, DCAF12, EPB42, GMPR, SELENBP1, SLC4A1, TMOD1 and TRIM58 were differentially expressed during and throughout the post phase of microdose rHuEpo administration. The CD247 and TRIM58 genes were significantly up- and down-regulated, respectively, immediately following exercise when compared with the baseline both before and after rHuEpo/placebo. No significant gene expression changes were found 30 min after exercise in either rHuEpo or placebo groups. ALAS2, BCL2L1, DCAF12, SLC4A1, TMOD1 and TRIM58 tended to be significantly expressed in the elite runners ten days after arriving at altitude and one week after returning from altitude (FDR > 0.059, fold-change varying from 1.39 to 1.63). Following application of the adaptive model, 15 genes showed a high sensitivity (≄ 93%) and specificity (≄ 71%), with BCL2L1 and CSDA having the highest sensitivity (93%) and specificity (93%). CONCLUSIONS: Current results provide further evidence that transcriptional biomarkers can strengthen the ABP approach by significantly prolonging the detection window and improving the sensitivity and specificity of blood doping detection. Further studies are required to confirm, and if necessary, integrate the confounding effects of altitude training on blood doping

    Asymptomatic oral yeast carriage in HIV-infected patients: frequency and fluconazole susceptibility profile.

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    OBJECTIVES: Fluconazole-resistant oropharyngeal candidiasis (OPC) is a rapidly growing problem in HIV-infected patients. To better understand the pathogenesis of fluconazole resistance in this setting, asymptomatic candidal carriage was determined by means of oral swabs regularly performed in all patients without clinical signs of OPC seen at our HIV outpatient clinic. Controls were 204 asymptomatic healthcare workers without previous exposure to fluconazole. METHODS: Swabs were plated on three solid media and put in a Sabouraud broth. Phenotypically different colonies were identified to the species level. Susceptibility to fluconazole was determined using a disk diffusion test with 50 microg fluconazole disks on yeast nitrogen agar, with a cut-off value of 25 mm. RESULTS: Swabs were performed in 538 consecutive HIV-positive patients, of whom 216 (40%) had had prior episode(s) of OPC and/or were previously exposed to fluconazole. Yeasts were grown in 418/538 HIV-positive patients (78%), compared to 57/204 controls (28%) (p < 0.05). In HIV-positive patients, yeasts were grown in 189/216 (88%) of those with past fluconazole exposure, and in 229/322 (71%) without exposure (p < 0.05). A total of 589 isolates were grown in the 538 HIV-positive patients (451 C. albicans, 88 C. glabrata, 22 C. tropicalis, 11 C. krusei, and 17 isolates from 12 other species). Resistance to fluconazole was present in 121/589 (21%) Candida species isolates in HIV-positive patients and in 2/59 (3%) in controls. Among C. albicans isolates, there were 18 fluconazole-resistant strains in HIV-positive patients (4%) and none in controls.CONCLUSIONS: Using sensitive culture methods, oral yeast colonization was detected significantly more frequently in HIV-infected patients (78%) than in a control group of HIV-negative persons (28%). In addition, yeast colonization was quantitatively more important in patients with lower CD4+ lymphocyte counts and for those who had been exposed to fluconazole for episode(s) of OPC. Fluconazole-resistant C. albicans isolates were observed only in HIV-positive patients, and all patients (17/18) for whom this information could be ascertained had had prior exposure to fluconazole

    Better economy in field running than on the treadmill: evidence from high-level distance runners

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    Given the ongoing interest in ways to improve the specificity of testing elite athletes in their natural environment, portable metabolic systems provide an opportunity to assess metabolic demand of exercise in sport-specific settings. Running economy (RE) and maximal oxygen uptake ( ·VO 2 max) were compared between track and treadmill (1% inclination) conditions in competitive level European distance runners who were fully habituated to treadmill running (n = 13). All runners performed an exercise test on running track and on treadmill. While ·VO 2 max was similar on the track and on the treadmill (68.5 ± 5.3 vs. 71.4 ± 6.4 ml∙kg -1 ∙min -1 , p = 0.105, respectively), superior RE was found on the track compared to the treadmill (215.4 ± 12.4 vs. 236.8 ± 18.0 O2 ml∙kg -1 ∙km -1 , p < 0.001). RE on the track was strongly correlated with RE on the treadmill (r = 0.719, p = 0.006). The present findings indicate that high-level distance runners have significantly better RE but not ·VO2max on the track compared to treadmill. This difference may be due to biomechanical adjustments. As RE is strongly correlated between the two conditions, it would be reasonable to assume that interventions affecting RE on the treadmill will also affect RE on the track
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