Practical Science and Environmental Education Workshop in Manaus, Brazil

It is an unequivocal fact that Amazonian tropical forest is the largest remaining primary forest in the world. The ecosystem in the region is e tremely comple with high biodiversity (Peres et al. 2010). Conservation and protection of the dynamic forest and river regions is e tremely important not only for the natural environments, but also for the economy and social dependence of benefits from such abundant natural environments. Important natural parameters that affect status of the natural environments include light (natural sunlight), soil, and water, which abundantly e ist in the Amazon region. Solar energy is the primary energy source for the majority of living organisms in both terrestrial and aquatic ecosystems, and drives the diurnal and seasonal cycles of biogeochemical processes (Monteith & Unsworth 2013). In particular, in situ light data remains one of the most underappreciated data measurements although having a significant impact on the physical, chemical and biological processes in the ecosystem (Johnsen 2012). Soil provides the fundamental basis for all terrestrial living organisms including the Amazonian forests as well as life-sustaining infrastructure for human society. Water is the most essential single entity to constitute all organisms from a single cell to the earth. Understanding of importance and roles of each factor and interaction of such comple dynamics in the natural environments can serve as fundamental platform for natural scientists, particularly for young scientists such as university students. The objective of this workshop was to provide hand- on scientific and environmental education for university students in Manaus, Amazonas, Brazil through practical field measurements using the three most important parameters in the natural ecosystem composed of natural sunlight, soil, and water. The workshop was divided into a series of lectures, in situ field sampling, and data processing, analysis and interpretation with the ultimate goal of empowering the undergraduate students with research-centered environmental education and e perience of developing international collaboration.departmental bulletin pape

Post-Exercise Hypotension and Its Mechanisms Differ after Morning and Evening Exercise: A Randomized Crossover Study

<div><p>Post-exercise hypotension (PEH), calculated by the difference between post and pre-exercise values, it is greater after exercise performed in the evening than the morning. However, the hypotensive effect of morning exercise may be masked by the morning circadian increase in blood pressure. This study investigated PEH and its hemodynamic and autonomic mechanisms after sessions of aerobic exercise performed in the morning and evening, controlling for responses observed after control sessions performed at the same times of day. Sixteen pre-hypertensive men underwent four sessions (random order): two conducted in the morning (7:30am) and two in the evening (5pm). At each time of day, subjects underwent an exercise (cycling, 45 min, 50%VO₂peak) and a control (sitting rest) session. Measurements were taken pre- and post-interventions in all the sessions. The net effects of exercise were calculated for each time of day by [(post-pre exercise)-(post-pre control)] and were compared by paired t-test (P<0.05). Exercise hypotensive net effects (e.g., decreasing systolic, diastolic and mean blood pressure) occurred at both times of day, but systolic blood pressure reductions were greater after morning exercise (-7±3 vs. -3±4 mmHg, P<0.05). Exercise decreased cardiac output only in the morning (-460±771 ml/min, P<0.05), while it decreased stroke volume similarly at both times of day and increased heart rate less in the morning than in the evening (+7±5 vs. +10±5 bpm, P<0.05). Only evening exercise increased sympathovagal balance (+1.5±1.6, P<0.05) and calf blood flow responses to reactive hyperemia (+120±179 vs. -70±188 U, P<0.05). In conclusion, PEH occurs after exercise conducted at both times of day, but the systolic hypotensive effect is greater after morning exercise when circadian variations are considered. This greater effect is accompanied by a reduction of cardiac output due to a smaller increase in heart rate and cardiac sympathovagal balance.</p></div

Polymorphisms in CYP2E1, GSTM1 and GSTT1 and anti-tuberculosis drug-induced hepatotoxicity

Anti-tuberculosis drug-induced hepatitis (ATD- induced hepatitis) has been linked to polymorphisms in genes encoding drug metabolizing enzymes. N-acetyltransferase 2 (NAT2), cytochrome P450 2E1 (CYP2E1) and glutathione S-transferase (loci GSTM1 and GSTT1) are involved in the metabolism of isoniazid, the most toxic drug for the treatment of tuberculosis (TB). This study was designed to determine the frequency and to evaluate whether polymorphisms at CYP2E1, GSTM1 and GSTT1 genes are associated with drug response, as well as to identify clinical risk factors for ATD-induced hepatitis. A total of 245 Brazilian patients undergoing treatment for TB were genotyped using polymerase chain reaction and restriction fragment length polymorphism and sequencing methods. The frequencies of the CYP2E1 polymorphic alleles RsaI, PstI and DraI are 8%, 8.5% and 12%, respectively. GSTM1 and GSTT1 genes are deleted in 42.9% and 12.4% of the population, respectively. Fifteen patients (6.1%) developed hepatotoxicity. Clinical (HIV, female sex and extrapulmonary TB) and genetic characteristics (CYP2E1 without any mutations, having NAT2 slow acetylator profile) are at higher risk of developing ATD-induced hepatitis in this population. Genotyping for GSTM1 and GSTT1 showed no influence on drug response

Physical and functional characteristics of the sample.

<p>Values in mean±SD. BP—blood pressure. VO₂ –oxygen uptake</p><p>Physical and functional characteristics of the sample.</p

Flowchart.

<p>Flowchart.</p

Physical and functional characteristics of the sample.

<p>Values in mean±SD. BP—blood pressure. VO₂ –oxygen uptake</p><p>Physical and functional characteristics of the sample.</p

Experimental sessions.

<p>Experimental sessions.</p

Hemodynamic, autonomic and vascular data assessed pre and post interventions in the morning control (MC) and exercise (ME).

<p>Values in mean±SD. BP—blood pressure. LF—low frequency. HF—high frequency. CVR–calf vascular resistance. AUC–area under the curve.</p><p>* significantly different from pre-intervention (P≤0.05)</p><p># significantly different from control session (P≤0.05).</p><p>Hemodynamic, autonomic and vascular data assessed pre and post interventions in the morning control (MC) and exercise (ME).</p

Comparison between the net effect of exercise in the morning and evening.

<p>(a) Systolic blood pressure (SBP), (b) cardiac output (CO), (c) heart rate (HR), (d) logarithmic of low to high frequency ratio of R-R interval variability (lnLF/HF), (e) diastolic blood pressure (DBP), (f) systemic vascular resistance (SVR), (g) normalized high-frequency component of R-R interval variability (HF_R-R), (h) calf vascular resistance (CVR), (i) mean blood pressure (MBP), (j) stroke volume (SV), (l) normalized low-frequency component of R-R interval variability (LF_R-R) and (m) calf vascular resistance (CVR) and area under the curve of calf blood flow response to reactive hyperemia (calf AUC). , , , , , , † Significant net effect (P≤0.05), & significantly different from evening net effect (P≤0.05).</p

Hemodynamic, autonomic and vascular data assessed pre and post-interventions in the evening control (EC) and exercise (EE).

<p>Values in mean±SD. BP—blood pressure. LF—low frequency. HF—high frequency. CVR–calf vascular resistance. AUC–area under the curve.</p><p>* significantly different from pre-intervention (P≤0.05)</p><p># significantly different from control session (P≤0.05).</p><p>Hemodynamic, autonomic and vascular data assessed pre and post-interventions in the evening control (EC) and exercise (EE).</p