Interchangeability between two breath-by-breath O2 uptake calculation algorithms in asthmatic and healthy volunteers

Biomonitoring of urinary metals in athletes according to particulate matter air pollution before and after exercise

Exposure to air pollution during physical exercise is a health issue because fine particulate matter (dimension < 10 μm; PM₁₀) includes several inhalable toxic metals. Body metal changes in athletes according to air pollution are poorly known. Urinary concentrations of 15 metals: beryllium (Be⁹), aluminum (Al²⁷), vanadium (V⁵¹), chromium (Cr⁵¹ + Cr⁵²), manganese (Mn⁵⁵), cobalt (Co⁵⁹), nickel (Ni⁶¹), copper (Cu⁶³), zinc (Zn⁶¹), arsenic (As⁷⁵), selenium (Se⁸²), cadmium (Cd¹¹¹ + Cd¹¹²), thallium (Tl¹²⁵), lead (Pb²⁰⁷), and uranium (U²³⁸) were measured before and after ten 2-h training sessions in 8 non-professional Italian American-football players (18-28 years old, body mass index 24.2-33.6 kg/m²). Collectively, post-training sessions, urinary concentrations of As, Cd, Co, Cu, Mn, Ni, Pb, Se, Tl, and Zn were higher than pre-training sessions; Al, Be, Cr, and U did not change; conversely, V decreased. Subdividing training sessions according to air PM₁₀ levels: low (< 20 μg/m³), medium (20-40 μg/m³), and high (> 40 μg/m³), pre-session and post-session urinary concentrations of Be, Cd, Cu, and Tl were significantly higher (p < 0.05) in more polluted days, whereas V concentrations were lower (p < 0.001). All the remaining metals were unaffected. We first showed that PM₁₀ levels modulate urinary excretion of some toxic metals suggesting an effect of air pollution. The effects of toxic metals inhaled by athletes exercising in polluted air need further studies.

Influence of the fitting window on the O2 uptake kinetics at the onset of moderate intensity exercise

The O₂ uptake (V̇o₂) data at the onset of an exercise are usually fitted with a mono-exponential function, after removal of the data pertaining to a conventional initial time period (ΔTr) lasting ∼20 s. We performed a thorough quantitative analysis on the effects of removing data pertaining to different ΔTr, aiming at identifying an objective method to establish the appropriate ΔTr. Breath-by-breath O₂ uptake responses, acquired from 25 healthy adults performing a step moderate-intensity exercise, and 10⁴ simulated biexponential responses, were analyzed. For all the responses, the kinetic parameters of a mono-exponential function and the corresponding asymptotic standard errors (ASEs) were estimated by nonlinear regression, removing the data pertaining to progressively longer initial periods (1 s each) up to 60 s. Four methods to establish objectively ΔTr were compared. The minimum estimated τ was obtained for ΔTr ≅ 35 s in both the V̇o₂ and simulated data, that was about 30% lower compared with that obtained for ΔTr ≅ 0s. The average ASE values remained quite constant up to ΔTr ≅ 35 s, thereafter they increased remarkably. The τ used to generate the simulated response fell within the confidence intervals of the estimated τ in ∼85% of cases for ΔTr = 20 s ("20 s-w" method); this percentage increased to ∼92% of cases when ΔTr was established according to both the minimum τ and its narrowest confidence interval ("Mixed" method). In conclusion, the effects of removing V̇o₂ data pertaining to different ΔTr are remarkable. The "Mixed" method provided estimated parameters close to those used to generate the simulated responses and is thus endorsed.NEW & NOTEWORTHY We propose a method to objectively establish the initial time period to be removed from the fitting window when, using a mono-exponential model, the kinetics of the fundamental component is determined on breath-by-breath O₂ uptake data collected at the onset of a moderate-intensity exercise. Innovative statistical parameters ("Coverage" and "Concordance_5%," applicable on simulated responses) were used to compare its performance with that of other three methods. The proposed method yielded the best "Coverage" and "Concordance_5%."