Acute hypoxia improves insulin sensitivity (SI2*) and β cell function in individuals with Type 2 Diabetes

Type 2 diabetes is a multifactorial metabolic disease characterized by defects in β-cells function, insulin sensitivity, glucose effectiveness and endogenous glucose production (1). It is widely accepted that insulin and exercise are potent stimuli for glucose transport (2). Acute exercise is known to promote glucose uptake in skeletal muscle via an intact contraction stimulated mechanism (3), while post-exercise improvements in glucose control are due to insulin-dependant mechanisms (2). Hypoxia is also known to promote glucose uptake in skeletal muscle using the contraction stimulated pathway. This has been shown to occur in vitro via an increase in β-cell function, however data in vivo is lacking. The aim of this study was to examine the effects of acute hypoxia with and without exercise on insulin sensitivity (SI2*), glucose effectiveness (SG2*) and β-cell function in individuals with type 2 diabetes. Following an overnight fast, six type 2 diabetics, afer giving informed written consent, completed 60 min of the following: 1) normoxic rest (Nor Rest); 2) hypoxic rest [Hy Rest; O2 = 14.6 (0.4)%]; 3) normoxic exercise (Nor Ex); 4) hypoxic exercise [Hy Ex; O2 = 14.6 (0.4)%]. Exercise trails were set at 90% of lactate threshold. Each condition was followed by a labelled intravenous glucose tolerance test (IVGTT) to provide estimations of SI2*, SG2* and β-cell function. Values are presented as means (SEM). Two-compartmental minimal model analysis showed SI2* to be higher following Hy Rest when comparisons were made with Nor Rest (P = 0.047). SI2* was also higher following Hy Ex [4.37 (0.48) x10-4 . min-1 (μU/ml)] compared to Nor Ex [3.24 (0.51) x10-4 . min-1 (μU/ml)] (P = 0.048). Acute insulin response to glucose (AIRg) was reduced following Hy Rest vs. Nor Rest (P = 0.014 - Table 1). This study demonstrated that 1) hypoxia has the ability to increase glucose disposal; 2) hypoxic-induced improvements in glucose tolerance in the 4 hr following exposure can be attributed to improvements in peripheral SI2*; 3) resting hypoxic exposure improves β-cell function and 4) exercise and hypoxia have an additive effect on SG2* in type 2 diabetics. These findings suggest a possible use for hypoxia both with and without exercise in the clinical treatment of type 2 diabetes.

The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency

Objective: The Finometer (FMS, Finapres Measurement Systems, Amsterdam) records the beat-to-beat finger pulse contour and has been recommended for research studies assessing shortterm changes of blood pressure and its variability. Variability measured in the frequency domain using spectral analysis requires that the impact of breathing be restricted to high frequency spectra (> 0.15 Hz) so data from participants needs to be excluded when the breathing impact occurs in the low frequency spectra (0.04 - 0.15 Hz). This study tested whether breathing frequency can be estimated from standard Finometer recordings using either stroke volume oscillation frequency or spectral stroke volume variability maximum scores. Methods: 22 healthy volunteers were tested for 270s in the supine and upright positions. Finometer recorded the finger pulse contour and a respiratory transducer recorded breathing. Stoke volume oscillation frequency was calculated manually while the stroke volume spectral maximums were obtained using the software Cardiovascular Parameter Analysis (Nevrokard Kiauta, Izola, Slovenia). These estimates were compared to the breathing frequency using the Bland-Altman procedures. Results: Stroke volume oscillation frequency estimated breathing frequency to <±10% 95% levels of agreement in both supine (-7.7 to 7.0%) and upright (-6.7 to 5.4%) postures. Stroke volume variability maximum scores did not accurately estimate breathing frequency. Conclusions: Breathing frequency can be accurately derived from standard Finometer recordings using stroke volume oscillations for healthy individuals in both supine and upright postures. The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency.

Respiratory and non-respiratory sinus arrhythmia: implications for heart rate variability

The quantity of blood arriving at the left side of the heart oscillates throughout the breathing cycle due to the mechanics of breathing. Neurally regulated fluctuations in the length of the heart period act to dampen oscillations of the left ventricular stroke volume entering the aorta. We have reported that stroke volume oscillations but not spectral frequency variability stroke volume measures can be used to estimate the breathing frequency. This study investigated with the same recordings whether heart period oscillations or spectral heart rate variability measures could function as estimators of breathing frequency. Continuous 270 s cardiovascular recordings were obtained from 22 healthy adult volunteers in the supine and upright postures. Breathing was recorded simultaneously. Breathing frequency and heart period oscillation frequency were calculated manually, while heart rate variability spectral maximums were obtained using heart rate variability software. These estimates were compared to the breathing frequency using the Bland–Altman agreement procedure. Estimates were required to be \±10% (95% levels of agreement). The 95% levels of agreement measures for the heart period oscillation frequency (supine: -27.7 to 52.0%, upright: -37.8 to 45.9%) and the heart rate variability spectral maximum estimates (supine: -48.7 to 26.5% and -56.4 to 62.7%, upright: -37.8 to 39.3%) exceeded 10%. Multiple heart period oscillations were observed to occur during breathing cycles. Both respiratory and non-respiratory sinus arrhythmia was observed amongst healthy adults. This observation at least partly explains why heart period parameters and heart rate variability parameters are not reliable estimators of breathing frequency. In determining the validity of spectral heart rate variability measurements we suggest that it is the position of the spectral peaks and not the breathing