Impaired Akt phosphorylation in insulin-resistant human muscle is accompanied by selective and heterogeneous downstream defects.

AIMS/HYPOTHESIS: Muscle insulin resistance, one of the earliest defects associated with type 2 diabetes, involves changes in the phosphoinositide 3-kinase/Akt network. The relative contribution of obesity vs insulin resistance to perturbations in this pathway is poorly understood. METHODS: We used phosphospecific antibodies against targets in the Akt signalling network to study insulin action in muscle from lean, overweight/obese and type 2 diabetic individuals before and during a hyperinsulinaemic-euglycaemic clamp. RESULTS: Insulin-stimulated Akt phosphorylation at Thr309 and Ser474 was highly correlated with whole-body insulin sensitivity. In contrast, impaired phosphorylation of Akt substrate of 160 kDa (AS160; also known as TBC1D4) was associated with adiposity, but not insulin sensitivity. Neither insulin sensitivity nor obesity was associated with defective insulin-dependent phosphorylation of forkhead box O (FOXO) transcription factor. In view of the resultant basal hyperinsulinaemia, we predicted that this selective response within the Akt pathway might lead to hyperactivation of those processes that were spared. Indeed, the expression of genes targeted by FOXO was downregulated in insulin-resistant individuals. CONCLUSIONS/INTERPRETATION: These results highlight non-linearity in Akt signalling and suggest that: (1) the pathway from Akt to glucose transport is complex; and (2) pathways, particularly FOXO, that are not insulin-resistant, are likely to be hyperactivated in response to hyperinsulinaemia. This facet of Akt signalling may contribute to multiple features of the metabolic syndrome.

Classification of basic daily movements using a triaxial accelerometer.

A generic framework for the automated classification of human movements using an accelerometry monitoring system is introduced. The framework was structured around a binary decision tree in which movements were divided into classes and subclasses at different hierarchical levels. General distinctions between movements were applied in the top levels, and successively more detailed subclassifications were made in the lower levels of the tree. The structure was modular and flexible: parts of the tree could be reordered, pruned or extended, without the remainder of the tree being affected. This framework was used to develop a classifier to identify basic movements from the signals obtained from a single, waist-mounted triaxial accelerometer. The movements were first divided into activity and rest. The activities were classified as falls, walking, transition between postural orientations, or other movement. The postural orientations during rest were classified as sitting, standing or lying. In controlled laboratory studies in which 26 normal, healthy subjects carried out a set of basic movements, the sensitivity of every classification exceeded 87%, and the specificity exceeded 94%; the overall accuracy of the system, measured as the number of correct classifications across all levels of the hierarchy, was a sensitivity of 97.7% and a specificity of 98.7% over a data set of 1309 movements.

Detection of daily physical activities using a triaxial accelerometer.

Triaxial accelerometers have been employed to monitor human movements in a variety of circumstances. The study considered the use of data from a single waist-mounted triaxial accelerometer to distinguish between activity states and rest A method using acceleration magnitude was applied to data collected from 26 normal subjects performing sit-to-stand and stand-to-sit transitions and walking. The effects of three parameters were investigated: the length n of a smoothing median filter, the width w of the averaging window used to process the signal and the value of the acceleration magnitude threshold th. These were found to be inter-related, and sets of parameters that resulted in accurate discrimination were determined by the relationship between th and the product of w and n, and by the relationship between n and w. The subjects were randomly divided into control (N = 13) and test (N = 13) groups. Optimum parameter sets were determined using the control group. Eleven sets of parameters yielded the same optimum results of a sensitivity of 1.0 and a specificity of 0.96 in the control group. Upon application to the test group, using these parameters, the system successfully distinguished between activity and rest, giving sensitivities greater than 0.98 and specificities between 0.88 and 0.94.

Phase response of model sinoatrial node cells.

When a brief current pulse is incident on excitable cells in cardiac and other nervous tissue, a change in phase of the cell's response is usually observed. In cardiac tissue, the cells are exposed to external stimulation of mainly positive currents, which depolarize the cells. We performed a systematic study of the effect of depolarizing stimuli, covering timing, magnitude, and duration, and demonstrated that all of these parameters influence the phase response of the cell. The phase response of our model cell compares favorably with measurements on isolated sinoatrial node cells. We investigated the phase response to single depolarizing stimuli as a function of the stimulus parameters (phase response curves), and then studied cell responses to the combined effect of a pulse train (entrainment phenomena). The range of magnitudes and durations for the stimuli were 0.01-5 nA and 0.01-50 ms. Comparisons of the entrainment properties of the model with experimental results show good agreement with similar modes and different entrainment ratios occurring for similar basic cycle lengths (as functions of the unperturbed cell period). Our results demonstrate that any combination of parameters that provide the same charge transfer to the cell causes a similar phase response, independent of the specific magnitude and duration for the entire range of stimuli investigated.