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Tidal breathing in awake humans is variable. This variability causes changes in lung gas stores that affect gas exchange measurements. To overcome this, several algorithms provide solutions for breath‐by‐breath alveolar gas exchange measurement; however, there is no consensus on a physiologically robust method suitable for widespread application. A recent approach, the ‘independent‐breath’ (IND) algorithm, avoids the complexity of measuring breath‐by‐breath changes in lung volume by redefining what is meant by a ‘breath’. Specifically, it defines a single breathing cycle as the time between equal values of the FO2 ${F_{{{\\mathrm{O}}_2}}}$ /FN2 ${F_{{{\\mathrm{N}}_2}}}$(or FCO2 ${F_{{\\mathrm{C}}{{\\mathrm{O}}_2}}}$ /FN2 ${F_{{{\\mathrm{N}}_2}}}$ ) ratio, that is, the ratio of fractional concentrations of lung‐expired O2 (or CO2) and nitrogen (N2). These developments imply that the end of one breath is not, by necessity, aligned with the start of the next. Here we demonstrate how the use of the IND algorithm fails to conserve breath‐by‐breath mass balance of O2 and CO2 exchanged between the atmosphere and tissues (and vice versa). We propose a new term, within the IND algorithm, designed to overcome this limitation. We also present the far‐reaching implications of using algorithms based on alternative definitions of the breathing cycle, including challenges in measuring and interpreting the respiratory exchange ratio, pulmonary gas exchange efficiency, dead space fraction of the breath, control of breathing, and a broad spectrum of clinically relevant cardiopulmonary exercise testing variables. Therefore, we do not support the widespread adoption of currently available alternative definitions of the breathing cycle as a legitimate solution for breath‐by‐breath alveolar gas exchange measurement in research or clinical settings. What is the central question of this study? The IND algorithm for breath‐by‐breath alveolar gas exchange computation redefines ‘a breath’: what are the implications of this approach for the measurement of gas exchange at rest and during exercise? What is the main finding and its importance? The IND algorithm does not maintain continuity between consecutive breaths, violating the conservation of mass for breath‐by‐breath alveolar gas exchange measurements. A volume correction to the algorithm is provided to address this discrepancy and preserve mass balance. However, by redefining the conventional breathing cycle, the IND algorithm has additional implications for cardiopulmonary exercise testing interpretation because variables with demonstrated diagnostic and prognostic value cannot be accurately determined.

This study aimed at: (1) Reporting COVID‐19 symptoms and duration in professional football players; (2) comparing players’ pulmonary function before and after COVID‐19; (3) comparing players’ metabolic power (Pmet) before and after COVID‐19. Thirteen male players (Age: 23.9 ± 4.0 years, V̇O2peak: 49.7 ± 4.0 mL/kg/min) underwent a medical screening and performed a running incremental step test and a spirometry test after COVID‐19. Spirometric data were compared with the ones collected at the beginning of the same season. Players’ mean Pmet of the 10 matches played before COVID‐19 was compared with mean Pmet of the 10 matches played after COVID‐19. Players completed a questionnaire on COVID‐19 symptoms and duration 6 months following the disease. COVID‐19 positivity lasted on average 15 ± 5 days. “General fatigue” and “muscle fatigue” symptoms were reported by all players during COVID‐19 and persisted for 77% (general fatigue) and 54% (muscle fatigue) of the players for 37 ± 28 and 38 ± 29 days after the disease, respectively. No significant changes in spirometric measurements were found after COVID‐19, even though some impairments at the individual level were observed. Conversely, a linear mixed‐effects model analysis showed a significant reduction of Pmet (−4.1 ± 3.5%) following COVID‐19 (t = −2.686, p < 0.05). “General fatigue” and “muscle fatigue” symptoms may persist for several weeks following COVID‐19 in professional football players and should be considered for a safer return to sport. Players’ capacity to compete at high intensities might be compromised after COVID‐19. “General fatigue” and “muscle fatigue” symptoms were the most common long‐term COVID‐19 symptoms reported. Players’ capability to exercise at high intensity was compromised following COVID‐19. Players’ pulmonary function was not affected by COVID‐19, even though some impairments were observed at the individual level.

From the dust of the archives a precious and completely unknown document has re-emerged: the first disposizione scenica of the Milanese musical house Sonzogno, dedicated to Cavalleria rusticana, the opera that inaugurated the season of verismo in the fin de siècle Italian melodrama. The document, published here in a commented edition for the first time, is not exhaustive, as in the case of the disposizioni and mises en scène of the rival house of Ricordi, but it allows to trace a better defined panorama on the performance practice of that time, and to seize some distinctive features of the reception of this opera in the first year of life. Up to grasp a sign of the high-profile reception in the intertextual reference to the Mascagni’s addio alla madre placed at the end of Mahler’s Eighth symphony, who directed Cavalleria for the first time in a foreign language in 1890.

PurposePedalling cadence influences respiratory frequency (fR) during exercise, with group III/IV muscle afferents possibly mediating its effect. However, it is unclear how exercise intensity affects the link between cadence and fR. We aimed to test the hypothesis that the effect of cadence on fR is moderated by exercise intensity, with interest in the underlying mechanisms.MethodsTen male cyclists performed a preliminary ramp incremental test and three sinusoidal experimental tests on separate visits. The experimental tests consisted of 16 min of sinusoidal variations in cadence between 115 and 55 rpm (sinusoidal period of 4 min) performed during passive exercise (PE), moderate exercise (ME) and heavy exercise (HE). The amplitude (A) and phase lag (φ) of the dependent variables were calculated.ResultsDuring PE, fR changed in proportion to variations in cadence (r = 0.85, P < 0.001; A = 3.9 ± 1.4 breaths·min−1; φ = − 5.3 ± 13.9 degrees). Conversely, the effect of cadence on fR was reduced during ME (r = 0.73, P < 0.001; A = 2.6 ± 1.3 breaths·min−1; φ = − 25.4 ± 26.3 degrees) and even more reduced during HE (r = 0.26, P < 0.001; A = 1.8 ± 1.0 breaths·min−1; φ = − 70.1 ± 44.5 degrees). No entrainment was found in any of the sinusoidal tests.ConclusionThe effect of pedalling cadence on fR is moderated by exercise intensity—it decreases with the increase in work rate—and seems to be mediated primarily by group III/IV muscle afferents, at least during passive exercise.

Differentiating between respiratory frequency (fR) and tidal volume (VT) may improve our understanding of exercise hyperpnoea because fR and VT seem to be regulated by different inputs. We designed a series of exercise manipulations to improve our understanding of how fR and VT are regulated during exercise. Twelve cyclists performed an incremental test and three randomized experimental sessions in separate visits. In two of the three experimental visits, participants performed a moderate‐intensity sinusoidal test followed, after recovery, by a moderate‐to‐severe‐intensity sinusoidal test. These two visits differed in the period of the sinusoid (2 min vs. 8 min). In the third experimental visit, participants performed a trapezoidal test where the workload was self‐paced in order to match a predefined trapezoidal template of rating of perceived exertion (RPE). The results collectively reveal that fR changes more with RPE than with workload, gas exchange, VT or the amount of muscle activation. However, fR dissociates from RPE during moderate exercise. Both VT and minute ventilation (V˙E) showed a similar time course and a large correlation with V˙CO2in all the tests. Nevertheless, V˙CO2 was associated more with V˙E than with VT because VT seems to adjust continuously on the basis of fR levels to match V˙E with V˙CO2. The present findings provide novel insight into the differential control of fR and VT – and their unbalanced interdependence – during exercise. The emerging conceptual framework is expected to guide future research on the mechanisms underlying the long‐debated issue of exercise hyperpnoea. By proposing a series of exercise manipulations, we provide novel insight into the differential control of respiratory frequency (fR) and tidal volume (VT) – and their unbalanced interdependence – during exercise. Respiratory frequency changes more with perceived exertion than with workload, metabolic variables, VT or the amount of muscle activation. Unlike fR, VT mediates the close association between minute ventilation and carbon dioxide output, while continuously adjusting its value on the basis of fR levels.

Purpose Despite their widespread use in exercise physiology, time-to-exhaustion (TTE) tests present an often-overlooked challenge to researchers, which is how to computationally deal with between- and within-subject differences in exercise duration. We aimed to verify the best analysis method to overcome this problem. Methods Eleven cyclists performed an incremental test and three TTE tests differing in workload as preliminary tests. The TTEs were used to derive the individual power–duration relationship needed to set the workload (corresponding to an estimated TTE of 1200 s) for four identical experimental TTE tests. Within individuals, the four tests were subsequently rank ordered by performance. Physiological and psychological variables expected to change with performance were analysed using different methods, with the main aim being to compare the traditional “group isotime” method and a less-used “individual isotime” method. Results The four tests, ranked from the best to the worst, had a TTE of 1526 ± 332, 1425 ± 313, 1295 ± 325, and 1026 ± 265 s. Ratings of perceived exertion, minute ventilation, respiratory frequency, and affective valence were sensitive to changes in performance when their responses were analysed with the “individual isotime” method ( P  < 0.022, η p 2  > 0.144) but not when using the “group isotime” method, because the latter resulted in partial data loss. Conclusions The use of the “individual isotime” method is strongly encouraged to avoid the misinterpretation of the phenomenon under study. Important implications are not limited to constant-workload exercise, but extend to incremental exercise, which is another commonly used test of exercise tolerance.

Purpose This study aimed at comparing the predictive accuracy of the power law (PL), 2-parameter hyperbolic (HYP) and linear (LIN) models on elite 1-h track running performance, and evaluating pacing profile and running pattern of the men’s best two 1-h track running performances of all times. Methods The individual running speed–distance profile was obtained for nine male elite runners using the three models. Different combinations of personal bests times (3000 m-marathon) were used to predict performance. The level of absolute agreement between predicted and actual performance was evaluated using intraclass correlation coefficient (ICC), paired t test and Bland–Altman analysis. A video analysis was performed to assess pacing profile and running pattern. Results Regardless of the predictors used, no significant differences ( p  > 0.05) between predicted and actual performances were observed for the PL model. A good agreement was found for the HYP and LIN models only when the half-marathon was the longest event predictor used (ICC = 0.718–0.737, p  < 0.05). Critical speed (CS) was highly dependent on the predictors used. Unlike CS , PL V20 (i.e., the running speed corresponding to a 20-min performance estimated using the PL model) was associated with 1-h track running performances ( r  = 0.722–0.807, p  < 0.05). An even pacing profile with minimal changes of step length and frequency was observed. Conclusions The PL model may offer the more realistic 1-h track running performance prediction among the models investigated. An even pacing might be the best strategy for succeeding in such running events.