In understanding the relationship between exercise and immunity, the “open window theory” is a well-known theory stating that immediately after high intensity exercise, temporary immunosuppression occurs, which increases the risk of infections such as upper respiratory tract infections. Why does such a phenomenon occur? Does immunosuppression after severe exercise have physiological significance? In this paper, we propose a theory of super homeostasis. In other words, we verify that the open window theory is an important biological reaction when trying to understand the reason why we do exercise, more than it is the indispensable physiological response to the whole body.
The ventilatory response to moderate-intensity step load exercise has three temporal phases: an initial rapidly increasing phase I, followed by a slower exponential phase II, that leads to the steady state phase III. In muscles with mechanical hyperalgesia (delayed onset muscle soreness) and/or muscle damage a few days after eccentric exercise (ECC), an interesting phenomenon of increased ventilatory response at phases II and III during constant-load exercise and incremental exercise has been reported. However, the mechanisms behind this phenomenon have not been clarified. At least a neural mechanism is partly responsible for this phenomenon because the ventilatory response at neurally modulated phase I has been shown to be exaggerated 2 days after ECC (D2). In the present review, we focus on our previous work to identify the potential mechanism underlying the exaggerated modulation in phase I ventilatory response at D2, in which ECC-induced muscle pain is assumed to be at the peak. We also discuss the physiological and practical implications of this phenomenon.
The oxygen uptake efficiency slope (OUES) is the slope of a regression line of oxygen uptake (VO2) on logarithmically converted minute ventilation (VE) measured during incremental exercise: VO2 = alog10VE + b. Here, a is the OUES. The higher the OUES, the more efficient the uptake of oxygen. The OUES has been widely accepted to estimate maximum oxygen uptake without maximal exercise. Nevertheless, the unit of OUES is unsettled in the literature having eight different descriptions. We introduced a new equation for the OUES using resting VO2 (VO2 rest) and resting VE (VE rest): VO2 = alog10(VE/VE rest) + VO2 rest. This equation is based on the mathematical principle that an antilogarithm such as VE/VE rest is dimensionless. It is clear from this equation that OUES has the same unit as VO2, because log10(VE/VE rest) is just a numerical value without the unit. The new equation is written as VO2 = alog10VE - alog10VE rest + VO2 rest, where b = - alog10VE rest + VO2 rest. The OUES value is obtained from Baba’s original equation with VO2 and VE during incremental exercise. The new equation is useful to identify the unit of OUES and the y-intercept b.
The behavioral response of mice to infection is often demonstrated by a reduction in physical activity. Although it is known that single-stranded (ss) RNA, one of the genomes found in viruses, activates to produce type I interferon (IFNs) and pro-inflammatory cytokine via toll-like receptor (TLR) 7, the effect of TLR7 activation on spontaneous wheel-running activity is little known. To determine whether physical activity is regulated by TLR7 activation or not, we measured R-848 (which is a TLR7 agonist) -induced changes in spontaneous wheel-running activity in mice. Male C3H/HeN mice were IV injected with R-848 (0, 1 and 5 mg/kg), and their wheel-running activity was measured. Also, to clarify the effects of R-848-induced IFN-α, tumor necrosis factor (TNF)-α and prostaglandin (PG) E2 on wheel-running behavior, the R-848-injected wheel-running mice were treated with an inhibitor such as a neutralizing antibody specific to IFN-α, pentoxifylline (PTX) and indomethacin (IDM), respectively. It was observed that dose-dependent R-848 treatment reduced wheel-running activity, and the treatment induced an increase in plasma IFN-α, TNF-α, and PGE2 concentrations. However, the wheel-running activity was not attenuated by the anti-IFN-α antibody, PTX and IDM treatments. Our results suggest that the transient reduction in physical activity after R-848 injection is dose dependent, and that these phenomena might occur independently of the behavior caused by R-848-induced IFN-α, TNF-α and PGE2 via TLR7.
The purposes of this study were to examine the effectiveness of the gamification-based intervention on health behavior change. Participants were 53 Japanese undergraduate and graduate students, of whom 30 were allocated to the intervention group and 23 were allocated to the control group. In the intervention group, daily physical activity and dietary behavior were assessed using a mobile phone application called The Way of Health. The application includes various functions, such as recording daily steps and checking the accomplishment of health behavior challenges. The program was conducted for 100 days from May 2016 to August 2016. ANOVA results for daily steps per week revealed a significant increase in daily steps only in the intervention group. Similarly, concerning the results of ANOVA for the diet behavior score, the intervention group was shown to be significantly higher than the control group along with time. Descriptive statistics revealed that 92.8%, 89.3%, and 82.1% of participants “agreed” or “somewhat agreed” that the points, badges, and leaderboards, respectively, were useful. This study indicated the possibility that gamification could work well for promoting healthy behaviors. Elements of gamification might be recognized as a facilitating factor for participant engagement in an intervention for health behavior change.
This study examined the energy expenditure (EE) of healthy adults during typical use of a manual wheelchair by attaching sensors to the subjects’ upper limbs. The aim was to determine whether the measured EE values depend on the sensor attachment site and whether the addition of angular velocity information to the acceleration value was advantageous to the EE assessment. Subjects were 11 males and 10 females. Their wrists and mid-upper arms were fitted with sensors to monitor their daily physical activities. Triaxial acceleration, triaxial angular velocity, and EE were measured while performing activities with a manual wheelchair. Coefficients of determination for estimating EE at each sensor location ranged from 0.66 to 0.79 (based on gender, the calculated three axis value of acceleration and angular velocity) and from 0.65 to 0.78 (based on gender and the calculated three axis value of acceleration, without angular velocity). Furthermore, angular velocity was not selected as a significant explanatory variable for estimating EE at the wrist. The average percent error for estimating the EE of daily physical activity in healthy adults using a manual wheelchair and factoring in gender and the calculated three axis value of acceleration at each sensor location ranged from 5.2 to 7.2%. Angular velocity information added to the calculated three axis value of acceleration at the upper arms slightly improved the estimation of EE. In addition, it was found that there was no difference in the assessment at different sensor locations.