Is pain temporary and glory forever? Detection of tramadol using dried blood spot in cycling competitions.

Tramadol is a synthetic opioid drug used in the treatment of chronic and acute pain. An abnormal prevalence of its misuse in elite sport to overcome pain resulting from prolonged physical effort was recently reported. However, besides its antinociceptive effects, tramadol consumption is associated with negative effects such as numbness, confusion, and reduced alertness. This fact prompted the Union Cycliste Internationale to ban the use of tramadol in cycling competitions. Herein, we present the development of a dried blood spot (DBS) sample collection and preparation method followed by a liquid-chromatography mass spectrometry (LC-MS) analysis to rapidly determine the presence of tramadol and its two main metabolites in blood samples. The detection window of each analyte was evaluated and the analysis of performance on various MS platforms (HRMS and MS/MS) was assessed. Tramadol and its two main metabolites were detected up to 12 h after the intake of a single dose of 50 mg of tramadol in positive controls. In professional cycling competitions, 711 DBS samples collected from 361 different riders were analysed using the developed methodology, but all returned negative results (absence of parent and both metabolite compounds). In the context of professional cycling, we illustrate a valid method bringing together the easiness of collection and minimal sample preparation required by DBS, yet affording the performance standards of MS determination. The proposed method to detect tramadol and its metabolites was successfully implemented in cycling races with a probable strong deterrent effect.

Steroid profile analysis by LC-HRMS in human seminal fluid.

Steroids are essential hormones that play a crucial role in homeostasis of many biological processes including sexual development, spermatogenesis, sperm physiology and fertility. Although steroids have been largely studied in many biological matrices (such as urine and plasma), there is very limited information of the steroid content and their study as potential indicators of the quality of the seminal fluid. In this study, a LC-HRMS (liquid chromatography-high resolution mass spectrometry) strategy has been developed in order to obtain the extended steroid profile of human seminal fluid. A comparison between supported liquid extraction (SLE) and solid liquid extraction (SPE) was carried out and the chosen SPE method was further optimized to evidence the largest possible number of compounds. Steroids were automatically annotated by using DynaStI, a publicly available retention time prediction tool developed in our lab, to match the experimental data (i.e. accurate mass and tR). Altogether, these resources allowed us to develop a post-targeted approach able to consistently detect 41 steroids in seminal fluid (with half of them being androgens). Such steroid pattern was found to be stable across different extraction times and injection days. In addition to accurate mass and retention time, the identity of 70% of the steroids contained in such steroid profile was confirmed by comparing their fragmentation patterns in real samples to those of pure commercial standards. Finally, the workflow was applied to compare and distinguish the steroid profile in seminal fluid from healthy volunteers (n = 7, with one of them being a vasectomized subject). In all, the developed steroidomics strategy allows to reliably monitor an extended panel of 41 steroids in human seminal fluid.

DynaStI: A Dynamic Retention Time Database for Steroidomics.

: Steroidomics studies face the challenge of separating analytical compounds with very similar structures (i.e., isomers). Liquid chromatography (LC) is commonly used to this end, but the shared core structure of this family of compounds compromises effective separations among the numerous chemical analytes with comparable physico-chemical properties. Careful tuning of the mobile phase gradient and an appropriate choice of the stationary phase can be used to overcome this problem, in turn modifying the retention times in different ways for each compound. In the usual workflow, this approach is suboptimal for the annotation of features based on retention times since it requires characterizing a library of known compounds for every fine-tuned configuration. We introduce a software solution, DynaStI, that is capable of annotating liquid chromatography-mass spectrometry (LC-MS) features by dynamically generating the retention times from a database containing intrinsic properties of a library of metabolites. DynaStI uses the well-established linear solvent strength (LSS) model for reversed-phase LC. Given a list of LC-MS features and some characteristics of the LC setup, this software computes the corresponding retention times for the internal database and then annotates the features using the exact masses with predicted retention times at the working conditions. DynaStI (https://dynasti.vital-it.ch) is able to automatically calibrate its predictions to compensate for deviations in the input parameters. The database also includes identification and structural information for each annotation, such as IUPAC name, CAS number, SMILES string, metabolic pathways, and links to external metabolomic or lipidomic databases.

Steroid profiles in both blood serum and seminal plasma are not correlated and do not reflect sperm quality: Study on the male reproductive health of fifty young Swiss men.

Steroids play an important role in sperm production and quality. These hormones have been extensively studied in blood, but poorly investigated in semen. The purpose of our study was to evaluate the relationship between sperm quality and steroid profiles in blood and semen in a small cohort of young Swiss men. Another objective was to determine whether the presence of xenobiotics or drugs could influence these profiles. Semen analysis was performed according to WHO guidelines, and steroid profiles in blood serum and seminal plasma were determined by two complementary approaches: a targeted investigation involving the quantification of a limited number of relevant steroids for testing putative correlations with sperm parameters and a global "steroidomic" analysis highlighting their complex metabolic relationship. Results showed that steroid profiles are distinct within blood and seminal fluid. No significant correlation was found between individual steroids measured in blood and in semen, demonstrating the relevance of assessing hormone levels in both fluids. Moreover, testosterone and androstenedione levels were significantly correlated in semen but not in blood. None of the evaluated spermiogram parameters was linked to steroid levels measured in any medium. The steroidomic analyses confirmed that the steroids present in both fluids are different and that there is no correlation with spermiogram parameters. Finally, upon toxicological screening, we observed that all the three samples positive for tetrahydrocannabinol, which is known to act as an endocrine disruptor, displayed low seminal testosterone concentrations. In conclusion, we did not find any evidence suggesting using steroid profiles, neither in blood nor in semen, as surrogates for sperm analyses. However, steroid profiles could be useful biomarkers of individual exposure to endocrine disruptors.

Informatics in radiology (infoRAD): benefits of content-based visual data access in radiology.

The field of medicine is often cited as an area for which content-based visual retrieval holds considerable promise. To date, very few visual image retrieval systems have been used in clinical practice; the first applications of image retrieval systems in medicine are currently being developed to complement conventional text-based searches. An image retrieval system was developed and integrated into a radiology teaching file system, and the performance of the retrieval system was evaluated, with use of query topics that represent the teaching database well, against a standard of reference generated by a radiologist. The results of this evaluation indicate that content-based image retrieval has the potential to become an important technology for the field of radiology, not only in research, but in teaching and diagnostics as well. However, acceptance of this technology in the clinical domain will require identification and implementation of clinical applications that use content-based access mechanisms, necessitating close cooperation between medical practitioners and medical computer scientists. Nevertheless, content-based image retrieval has the potential to become an important technology for radiology practice.