Tadayoshi Miyamoto

According to prior research, high-intensity endurance training (HIT) conducted more than twice a week significantly improves the maximum oxygen uptake (V_O2max), a marker of cardiorespiratory fitness, compared to low or moderate-intensity training. This training modality not only benefits athletes but also aids individuals with metabolic syndrome and circulatory and respiratory conditions, enhancing their quality of life. Despite these potentials, exploratory studies of exercise regimens with shorter durations, lower frequencies, and fewer sets remain insufficient; thus minimalistic HIT protocols remain under-investigated. In this research, our objective was to investigate the impact of an even less frequent, once-weekly, maximum effort high-intensity training (HIT) on cardiorespiratory function and exercise performance across various age groups. We enrolled 11 healthy participants (4 males and 7 females;age 36.9±16.7 years;height 163.4±11.7cm;weight 58.4±10.6kg) to participate in exhaustive training sessions for 8 weeks. The intensity was set at 80%of their maximum load reached in an initial ramp test (80%WR_max) . Before and after the training, participants underwent ramp test and head-up tilt (orthostatic load) test to assess adaptations in cardiorespiratory function during maximum exercise and circulatory adjustment to postural changes. Exercise performance was evaluated by maximum exercise duration until exhaustion (Exhaustion Time) . Post-training results indicated significant improvements in V_O2max (＋12%, p=0.02), ＋7.5% (p=0.026) WR_max＋12.7%, and Exhaustion Time. Furthermore, in the head-up tilt test, a significant increase in end-tidal CO₂ partial pressure (P_ETCO2) (＋17.5%, p=0.04) was observed in the supine position, and P_ETCO2 increased by ＋11.9% (p=0.03) while tidal volume decreased by -19.9% (p=0.02) in the tilt position. Although no interaction was found in ANOVA, significant Primary effects of training and condition were observed for P_ETCO2. Our findings suggest that once-weekly HIT to maximum exertion enhances cardiorespiratory function and exercise performance. No changes in parameters maintaining blood pressure were observed during the head-up tilt test. These findings may be valuable for future development of efficient exercise training programs for wider age groups.

Although Gaussian white noise (GWN) inputs offer a theoretical framework for identifying higher-order nonlinearity, an actual application to the data of the neural arc of the carotid sinus baroreflex did not succeed in fully predicting the well-known sigmoidal nonlinearity. In the present study, we assumed that the neural arc can be approximated by a cascade of a linear dynamic (LD) component and a nonlinear static (NS) component. We analyzed the data obtained using GWN inputs with a mean of 120 mmHg and standard deviations (SDs) of 10, 20, and 30 mmHg for 15 min each in anesthetized rats (n = 7). We first estimated the linear transfer function from carotid sinus pressure to sympathetic nerve activity (SNA) and then plotted the measured SNA against the linearly predicted SNA. The predicted and measured data pairs exhibited an inverse sigmoidal distribution when grouped into 10 bins based on the size of the linearly predicted SNA. The sigmoidal nonlinearity estimated via the LD-NS model showed a midpoint pressure (104.1 ± 4.4 mmHg for SD of 30 mmHg) lower than that estimated by a conventional stepwise input (135.8 ± 3.9 mmHg, P < 0.001). This suggests that the NS component is more likely to reflect the nonlinearity observed during pulsatile inputs that are physiological to baroreceptors. Furthermore, the LD-NS model yielded higher R2 values compared with the linear model and the previously suggested second-order Uryson model in the testing dataset.NEW & NOTEWORTHY We examined the input-size dependence of the baroreflex neural arc transfer characteristics during Gaussian white noise inputs. A linear dynamic-static nonlinear model yielded higher R2 values compared with a linear model and captured the well-known sigmoidal nonlinearity of the neural arc, indicating that the nonlinear dynamics contributed to determining sympathetic nerve activity. Ignoring such nonlinear dynamics might reduce our ability to explain underlying physiology and significantly limit the interpretation of experimental data.