RESUMO
AIM: The present study was undertaken to determine the effects of type 2 diabetes (T2D) on plasma kallikrein activity (PKA) and postexercise hypotension (PEH). METHODS: Ten T2D patients (age: 53.6±1.3 years; body mass index: 30.6±1.0kg/m(2); resting blood glucose: 157.8±40.2mgdL(-1)) and 10 non-diabetic (ND) volunteers (age: 47.5±1.0 years; body mass index: 28.3±0.9kg/m(2); resting blood glucose: 91.2±10.5mgdL(-1)) underwent two experimental sessions, consisting of 20min of rest plus 20min of exercise (EXE) at an intensity corresponding to 90% of their lactate threshold (90LT) and a non-exercise control (CON) session. Blood pressure (BP; Microlife BP 3AC1-1 monitor) and PKA were measured during rest and every 15min for 135min of the postexercise recovery period (RP). RESULTS: During the RP, the ND individuals presented with PEH at 30, 45 and 120min (P<0.05) while, in the T2D patients, PEH was not observed at any time. PKA increased at 15min postexercise in the ND (P<0.05), but not in the T2D patients. CONCLUSION: T2D individuals have a lower PKA response to exercise, which probably suppresses its hypotensive effect, thus reinforcing the possible role of PKA on PEH.
Assuntos
Diabetes Mellitus Tipo 2/sangue , Exercício Físico/fisiologia , Hipotensão/etiologia , Calicreínas/sangue , Pressão Sanguínea/fisiologia , Diabetes Mellitus Tipo 2/complicações , Feminino , Humanos , Cinética , Masculino , Pessoa de Meia-IdadeRESUMO
AIM: The lactate minimum (LM) protocol has been used to assess aerobic fitness and to predict exercise intensity associated with the maximal blood lactate steady state. The aim of this study was to compare different methods to identify the lactate minimum velocity (LMV) on cycling. METHODS: Fourteen male cyclists (26.8+/-4.5 years; 173.2+/-6.1 cm; 67.3+/-5.2 kg; 5,8+/-2.9 years of training) performed the LM test in a velodrome. The protocol consisted of an all out 2 km time trial to elevate blood lactate (bLAC), followed by 8 min of recovery and then 6 bouts of 2 km starting 5 kmxh(-1) below the individual mean velocity for the 6 km performance. The velocity was incremented by 1 kmxh(-1) at each bout with 25 microL of capillary blood being collected for bLAC measurements (YSI 2700 STAT). The LMV was identified visually (vLMV), and by applying a second grade polynomial function on 6 (pLMV(6)) and 3 (pLMV(3)) incremental bouts. Additionally, a method where the bLACx work velocity(-1) quotients (LMVQ) were plotted against the correspondent velocity during the incremental test, identified the LMV by considering 6 (LMVQ(6)) or 3 bouts (LMVQ(3)). RESULTS: ANOVA showed no differences between vLMV (33.1+/-2.5 kmxh(-1)), pLMV(6) (32.9+/-2.5 kmxh(-1)), pLMV(3) (33.2+/-2.3 kmxh(-1)), LMVQ(6) (32.8+/-2.5 kmxh(-1)) and LMVQ(3) (33.4+/-2.3 kmxh(-1)), with high correlation among them. CONCLUSIONS: It was possible to identify the LMV by the methods proposed in the present study, even when the results of only 3 bouts of the test were modeled by polynomial function. Such an approach enables a more practical and economical test in addition to minimizing the discomfort due to several blood collections.