Interplay among nocturnal activity, melatonin, corticosterone and performance in the invasive cane toad (Rhinella marinus)

Most animals conduct daily activities exclusively either during the day or at night. Here, hormones such as melatonin and corticosterone, greatly influence the synchronization or regulation of physiological and behavioral cycles needed for daily activity. How then do species that exhibit more flexible daily activity patterns, responses to ecological, environmental or life-history processes, regulate daily hormone profiles important to daily performance? This study examined the consequences of (1) nocturnal activity on diel profiles of melatonin and corticosterone and (2) the effects of experimentally increased acute melatonin levels on physiological and metabolic performance in the cane toad (Rhinella marinus). Unlike inactive captive toads that had a distinct nocturnal melatonin profile, nocturnally active toads sampled under field and captive conditions, exhibited decreased nocturnal melatonin profiles with no evidence for any phase shift. Nocturnal corticosterone levels were significantly higher in field active toads than captive toads. In toads with experimentally increased melatonin levels, plasma lactate and glucose responses following recovery post exercise were significantly different from control toads. However, exogenously increased melatonin did not affect resting metabolism in toads. These results suggest that toads could adjust daily hormone profiles to match nocturnal activity requirements, thereby avoiding performance costs induced by high nocturnal melatonin levels. The ability of toads to exhibit plasticity in daily hormone cycles, could have broad implications for how they and other animals utilize behavioral flexibility to optimize daily activities in response to natural and increasingly human mediated environmental variation.

Short duration heat acclimation in Australian football players

This study examined if five sessions of short duration (27 min), high intensity, interval training (HIIT) in the heat over a nine day period would induce heat acclimation in Australian football (AF) players. Fourteen professional AF players were matched for VO2peak (mL∙kg-1∙min-1) and randomly allocated into either a heat acclimation (Acc) (n = 7) or Control (Con) group (n = 7). The Acc completed five cycle ergometer HIIT sessions within a nine day period on a cycle ergometer in the heat (38.7 ± 0.5 °C; 34.4 ± 1.3 % RH), whereas Con trained in thermo-neutral conditions (22.3 ± 0.2 °C; 35.8 ± 0. % RH). Four days prior and two days post HIIT participants undertook a 30 min constant load cycling test at 60% V̇O2peak in the heat (37.9 ± 0.1 °C; 28.5 ± 0.7 % RH) during which VO2, blood lactate concentration ([Lac-]), heart rate (HR), rating of perceived exertion (RPE), thermal comfort, core and skin temperatures were measured. Heat acclimation resulted in reduced RPE, thermal comfort and [Lac-] (all p < 0.05) during the submaximal exercise test in the heat. Heart rate was lower (p = 0.007) after HIIT, in both groups. Heat acclimation did not influence any other measured variables. In conclusion, five short duration HIIT sessions in hot dry conditions induced limited heat acclimation responses in AF players during the in-season competition phase. In practice, the heat acclimation protocol can be implemented in a professional team environment; however the physiological adaptations result-ing from such a protocol were limited.

Cross-platform urine metabolomics of experimental hyperglycemia in type 2 diabetes

Hyperglycemia causes diabetic nephropathy, a condition for which there are no specific diagnostic markers thatpredict progression to renal failure. Here we describe a multiplatform metabolomic analysis of urine from individualswith type 2 diabetes, collected before and immediately following experimental hyperglycemia. We used targetednuclear magnetic resonance spectroscopy (NMR), liquid chromatography - mass spectrometry (LC-MS) and gaschromatography - MS (GC-MS) to identify markers of hyperglycemia. Following optimization of data normalisation andstatistical analysis, we identified a reproducible NMR and LC-MS based urine signature of hyperglycemia. Significantincreases of alanine, alloisoleucine, isoleucine, leucine, N-isovaleroylglycine, valine, choline, lactate and taurine anddecreases of arginine, gamma-aminobutyric acid, hippurate, suberate and N-acetylglutamate were observed. GC-MSanalysis identified a number of metabolites differentially present in post-glucose versus baseline urine, but these could not be identified using current metabolite libraries. This analysis is an important first step towards identifying biomarkers of early-stage diabetic nephropathy.