Estimativa das contribuições dos sistemas anaeróbio lático e alático durante exercícios de cargas constantes em intensidades abaixo do VO2max

O objetivo do estudo foi estimar as contribuições do metabolismo anaeróbio lático (MAL) e alático (MAA) em intensidades abaixo do consumo máximo de oxigênio (VO2max). Dez homens (23 ± 4 anos, 176,4 ± 6,8 cm, 72,4 ± 8,2 kg, 12,0 ± 4,5 % de gordura corporal) realizaram um teste progressivo até a exaustão voluntária para identificação do VO2max, da potência correspondente ao VO2max (WVO2max) e do segundo limiar ventilatório (LV2). Na segunda e na terceira visita foram realizados seis testes de cargas constantes (três testes por sessão) com intensidades abaixo do VO2max. Houve uma predominância do MAL sobre o MAA durante os exercícios submáximos a partir da intensidade correspondente ao LV2, sendo significativamente maior em 90% VO2max (p < 0,05). Dessa forma, esses resultados podem auxiliar treinadores a aplicarem cargas de treinamento adequadas aos seus atletas, de acordo com a exigência metabólica da competição

Multimodel ensembles of wheat growth: many models are better than one.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models

Caffeine Alters Anaerobic Distribution and Pacing during a 4000-m Cycling Time Trial

The purpose of the present study was to investigate the effects of caffeine ingestion on pacing strategy and energy expenditure during a 4000-m cycling time-trial (TT). Eight recreationally-trained male cyclists volunteered and performed a maximal incremental test and a familiarization test on their first and second visits, respectively. On the third and fourth visits, the participants performed a 4000-m cycling TT after ingesting capsules containing either caffeine (5 mg.kg−1 of body weight, CAF) or cellulose (PLA). The tests were applied in a double-blind, randomized, repeated-measures, cross-over design. When compared to PLA, CAF ingestion increased mean power output [219.1±18.6 vs. 232.8±21.4 W; effect size (ES) = 0.60 (95% CI = 0.05 to 1.16), p = 0.034] and reduced the total time [419±13 vs. 409±12 s; ES = −0.71 (95% CI = −0.09 to −1.13), p = 0.026]. Furthermore, anaerobic contribution during the 2200-, 2400-, and 2600-m intervals was significantly greater in CAF than in PLA (p0.05). Similarly, there were no significant differences between CAF and PLA for anaerobic work (26363±7361 vs. 23888±6795 J), aerobic work (68709±2118 vs. 67739±3912 J), or total work (95245±8593 vs. 91789±7709 J), respectively. There was no difference for integrated electromyography, blood lactate concentration, heart rate, and ratings of perceived exertion between the conditions. These results suggest that caffeine increases the anaerobic contribution in the middle of the time trial, resulting in enhanced overall performance