The Prevalence and Characteristics of Performance-Enhancing Drug Use Among Bodybuilding Athletes in the South of Iran, Bushehr

Background: Several reports have implied progressive increase of performance-enhancing drug (PED) use among Iranian athletes. More importantly, most of the previous research in the Iranian population had mainly focused on the anabolic steroid abuse, and ignored other agents. Objectives: The aim of this study was to investigate the prevalence and characteristics of PED use among bodybuilding athletes in Bushehr, south of Iran. Methods: Four hundred and fifty three male bodybuilding athletes were recruited from Bushehr gyms between February and May of 2015. Men were eligible to participate in the survey if they had regularly participated in the strength-training exercise (minimum of 1 year and 4 hour/week). Data were collected via a face-to-face interview. The survey consisted of three separate parts including demographic data, exercise pattern and PED use. Results: According to this study, 234 (51.7%) of bodybuilding athletes had used PEDs. The PED users reported an average of 3.80 � 4.52 agents’ use in their programs and they had used PEDs for the average of 3.24 � 3.99 years. The most prevalent agents which had been abused by the athletes were anabolic steroids (used by 185 athletes (79.4% of athletes). Furthermore, 110 (47%) of athletes reported stimulant agents’ use during their routines. The most prevalent motivation for using PEDs was increasing muscle mass that was reported by 164 (70.1%) of PED users. In addition, sexual and dermatologic effects were the most prevalent adverse effects reported by the PED user athletes (114 (49.4%) and 103 (44.2%), respectively). Conclusions: This study showed the high rate of PED use among recreational and professional Iranian bodybuilding athletes that can expose them to the serious side effects of these agents

Can cardiac rehabilitation programs improve functional capacity and left ventricular diastolic function in patients with mechanical reperfusion after ST elevation myocardial infarction?: A double-blind clinical trial

BACKGROUND: Current guidelines recommend cardiac rehabilitation programs (CRP) as a means to improve functional status of patients after coronary revascularization. However, research supporting this recommendation has been limited and positive effects of CRP on diastolic function are controversial. The aim of this study was to examine the effects of an 8-week CRP on left ventricular diastolic function. METHODS: This randomized, clinical trial included 29 men with ST elevation myocardial infarction (MI) who had received reperfusion therapy, i.e. coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI). They were randomized to a training group (n = 15; mean age: 54.2 ± 9.04 years old) and a control group (n = 14; mean age: 51.71 ± 6.98 years old). Patients in the training group performed an 8-week CRP with an intensity of 60-85 of maximum heart rate. Exercise sessions lasted 60-90 minutes and were held three times a week. At the start and end of the study, all patients performed symptom-limited exercise test based on Naughton treadmill protocol. Pulsed-wave Doppler echocardiography was also used to determine peak velocity of early (E) and late (A) waves, E/A ratios, and the deceleration time of E (DT). RESULTS: Left ventricular diastolic indices (E, A, E/A ratio, DT) did not change significantly after the CRP. Compared to baseline, patients in the training group had significant improvements in functional capacity (8.30 ± 1.30 vs. 9.7 ± 1.7) and maximum heart rate (118.50 ± 24.48 vs. 126.85 ± 22.75). Moreover, resting heart rate of the training group was significantly better than the control group at the end of the study (75.36 ± 7.94 vs. 79.80 ± 7.67; P < 0.001). CONCLUSION: An 8-week CRP in post-MI patients revascularized with PCI or CABG led to improved exercise capacity. However, the CRP failed to enhance diastolic function

Novel approach for identification of influenza virus host range and zoonotic transmissible sequences by determination of host-related associative positions in viral genome segments

Background: Recent (2013 and 2009) zoonotic transmission of avian or porcine influenza to humans highlights an increase in host range by evading species barriers. Gene reassortment or antigenic shift between viruses from two or more hosts can generate a new life-threatening virus when the new shuffled virus is no longer recognized by antibodies existing within human populations. There is no large scale study to help understand the underlying mechanisms of host transmission. Furthermore, there is no clear understanding of how different segments of the influenza genome contribute in the final determination of host range. Methods: To obtain insight into the rules underpinning host range determination, various supervised machine learning algorithms were employed to mine reassortment changes in different viral segments in a range of hosts. Our multi-host dataset contained whole segments of 674 influenza strains organized into three host categories: avian, human, and swine. Some of the sequences were assigned to multiple hosts. In point of fact, the datasets are a form of multi-labeled dataset and we utilized a multi-label learning method to identify discriminative sequence sites. Then algorithms such as CBA, Ripper, and decision tree were applied to extract informative and descriptive association rules for each viral protein segment. Result: We found informative rules in all segments that are common within the same host class but varied between different hosts. For example, for infection of an avian host, HA14V and NS1230S were the most important discriminative and combinatorial positions. Conclusion: Host range identification is facilitated by high support combined rules in this study. Our major goal was to detect discriminative genomic positions that were able to identify multi host viruses, because such viruses are likely to cause pandemic or disastrous epidemics.Fatemeh Kargarfard, Ashkan Sami, Manijeh Mohammadi-Dehcheshmeh and Esmaeil Ebrahimi

Effects of a cardiac rehabilitation program on left ventricular systolic function and mass in patient after myocardial infarction

Background: The positive effects of cardiac rehabilitation programs (CRPs) on cardiovascular patients have been demonstrated. However, their effectiveness in improving systolic function and preventing remodeling process needs to be further evaluated. The aim of this study was to examine the effects of an 8-week CRP on left ventricular systolic function and mass in patients after myocardial infarction. Methods: A total number of 29 male patients with myocardial infarction were allocated into cardiac training group (n = 15; mean age = 54.2 ±9.04 years) and control group (n = 14; mean age = 51.71 ± 6.98 years). Patients in the training group performed an 8-week CRP with an intensity of 60-85 of maximum heart rate. The program was performed 3 times a week and each session lasted 60 minutes. Before the CRP and at the end of the study, all patients underwent 2-dimentional echocardiography for left ventricular systolic function and mass to be assessed. Findings: Our findings showed that the 8-week CRP improved left ventricular systolic function in the patients. At the end of the CRP, left ventricular end diastolic dimension increased in the control group. On the other hand, end diastolic volume and end systolic volume decreased significantly in the training group. In addition, ejection fraction and stroke volume increased significantly in the training group. Although left ventricular mass decreased in the training group, the difference between the two groups was not significant. Conclusion: An 8-week CRP in post-myocardial infarction patients can lead to improved systolic function and decreased left ventricular mass and thus prevent cardiomegaly

Identifying mutation positions in all segments of influenza genome enables better differentiation between pandemic and seasonal strains

Influenza has a negative sense, single-stranded, and segmented RNA. In the context of pandemic influenza research, most studies have focused on variations in the surface proteins (Hemagglutinin and Neuraminidase). However, new findings suggest that all internal and external proteins of influenza viruses can contribute in pandemic emergence, pathogenicity and increasing host range. The occurrence of the 2009 influenza pandemic and the availability of many external and internal segments of pandemic and non-pandemic sequences offer a unique opportunity to evaluate the performance of machine learning models in discrimination of pandemic from seasonal sequences using mutation positions in all segments. In this study, we hypothesized that identifying mutation positions in all segments (proteins) encoded by the influenza genome would enable pandemic and seasonal strains to be more reliably distinguished. In a large scale study, we applied a range of data mining techniques to all segments of influenza for rule discovery and discrimination of pandemic from seasonal strains. CBA (classification based on association rule mining), Ripper and Decision tree algorithms were utilized to extract association rules among mutations. CBA outperformed the other models. Our approach could discriminate pandemic sequences from seasonal ones with more than 95% accuracy for PA and NP, 99.33% accuracy for NA and 100% accuracy, precision, specificity and sensitivity (recall) for M1, M2, PB1, NS1, and NS2. The values of precision, specificity, and sensitivity were more than 90% for other segments except PB2. If sequences of all segments of one strain were available, the accuracy of discrimination of pandemic strains was 100%. General rules extracted by rule base classification approaches, such as M1-V147I, NP-N334H, NS1-V112I, and PB1-L364I, were able to detect pandemic sequences with high accuracy. We observed that mutations on internal proteins of influenza can contribute in distinguishing the pandemic viruses, similar to the external ones