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1.
Eur J Appl Physiol ; 116(11-12): 2135-2144, 2016 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-27632382

RESUMEN

PURPOSE: To delineate the direct effect of physical activity on adiponectin metabolism, we investigated the impact of contrasted physical activity changes, independent of body mass changes, on adiponectin plasma concentration and muscle sensitivity in lean and overweight adult males. METHODS: Eleven physically active lean men (70.6 ± 2.1 kg) were subjected to 1-month detraining; 9 sedentary lean men (73.1 ± 3.3 kg); and 11 sedentary overweight men (97.5 ± 3.0 kg) participated in a 2-month aerobic-exercise training program. Diet was controlled to maintain stable energy balance. Body composition, VO2peak, circulating adiponectin, adipose and muscle tissue adiponectin, muscle adiponectin receptors, and APPL1 mRNAs were measured before and after the interventions. RESULTS: At baseline, plasma high-molecular-weight adiponectin concentration was lower in both active lean (5.44 ± 0.58 µg/mL) and sedentary overweight (5.30 ± 1.06 µg/mL) than in sedentary lean participants (7.44 ± 1.06 µg/mL; both p < 0.05). Training reduced total and high-molecular-weight adiponectin concentrations by, respectively, -32 and -42 % in sedentary lean, and -26 and -35 % in sedentary overweight, while detraining increased them by +25 and +27 % in active lean participants. Total and high-molecular-weight adiponectin changes were inversely correlated with VO2peak changes (respectively, R 2 = 0.45, R 2 = 0.59; both p < 0.001) and positively with changes in fasting plasma insulin (both p < 0.05). Muscle and adipose tissue adiponectin mRNA did not differ between groups and with interventions. Muscle AdipoR2 and APPL1 mRNAs were lower in sedentary groups compared with the active group; and were positively associated with VO2peak and inversely with fasting plasma insulin concentration. CONCLUSION: Plasma adiponectin concentration is inversely correlated with aerobic capacity. Future investigations will need to confirm the contribution of changes in muscle adiponectin sensitivity.


Asunto(s)
Adiponectina/sangre , Músculo Esquelético/fisiopatología , Sobrepeso/fisiopatología , Acondicionamiento Físico Humano/métodos , Conducta Sedentaria , Delgadez/fisiopatología , Adaptación Fisiológica/fisiología , Terapia por Ejercicio/métodos , Humanos , Masculino , Sobrepeso/terapia , Delgadez/terapia
2.
J Appl Physiol (1985) ; 118(6): 716-22, 2015 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-25593289

RESUMEN

"Objective" methods to monitor physical activity and sedentary patterns in free-living conditions are necessary to further our understanding of their impacts on health. In recent years, many software solutions capable of automatically identifying activity types from portable accelerometry data have been developed, with promising results in controlled conditions, but virtually no reports on field tests. An automatic classification algorithm initially developed using laboratory-acquired data (59 subjects engaging in a set of 24 standardized activities) to discriminate between 8 activity classes (lying, slouching, sitting, standing, walking, running, and cycling) was applied to data collected in the field. Twenty volunteers equipped with a hip-worn triaxial accelerometer performed at their own pace an activity set that included, among others, activities such as walking the streets, running, cycling, and taking the bus. Performances of the laboratory-calibrated classification algorithm were compared with those of an alternative version of the same model including field-collected data in the learning set. Despite good results in laboratory conditions, the performances of the laboratory-calibrated algorithm (assessed by confusion matrices) decreased for several activities when applied to free-living data. Recalibrating the algorithm with data closer to real-life conditions and from an independent group of subjects proved useful, especially for the detection of sedentary behaviors while in transports, thereby improving the detection of overall sitting (sensitivity: laboratory model = 24.9%; recalibrated model = 95.7%). Automatic identification methods should be developed using data acquired in free-living conditions rather than data from standardized laboratory activity sets only, and their limits carefully tested before they are used in field studies.


Asunto(s)
Actividad Motora/fisiología , Postura/fisiología , Acelerometría/métodos , Adulto , Algoritmos , Calibración , Femenino , Humanos , Masculino , Persona de Mediana Edad , Monitoreo Fisiológico/métodos , Conducta Sedentaria , Programas Informáticos , Adulto Joven
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