Post-exercise hypotension and skeletal muscle oxygenation is regulated by nitrate-reducing activity of oral bacteria.

Post-exercise hypotension (PEH) is a common physiological phenomenon leading to lower blood pressure after acute exercise, but it is not fully understood how this intriguing response occurs. This study investigated whether the nitrate-reducing activity of oral bacteria is a key mechanism to trigger PEH. Following a randomized, double blind and crossover design, twenty-three healthy individuals (15 males/8 females) completed two treadmill trials at moderate intensity. After exercise, participants rinsed their mouth with antibacterial mouthwash to inhibit the activity of oral bacteria or a placebo mouthwash. Blood pressure was measured before, 1h and 2 h after exercise. The microvascular response to a reactive hyperaemia test, as well as blood and salivary samples were taken before and 2 h after exercise to analyse nitrate and nitrite concentrations and the oral microbiome. As expected, systolic blood pressure (SBP) was lower (1 h: -5.2 ±â€¯1.0 mmHg; P < 0.001); 2 h: -3.8 ±â€¯1.1 mmHg, P = 0.005) after exercise compared to baseline in the placebo condition. This was accompanied by an increase of circulatory nitrite 2 h after exercise (2h: 100 ±â€¯13 nM) compared to baseline (59 ±â€¯9 nM; P = 0.013). Additionally, an increase in the peak of the tissue oxygenation index (TOI) during the reactive hyperaemia response was observed after exercise (86.1 ±â€¯0.6%) compared to baseline levels (84.8 ±â€¯0.5%; P = 0.010) in the placebo condition. On the other hand, the SBP-lowering effect of exercise was attenuated by 61% at 1 h in the recovery period, and it was fully attenuated 2 h after exercise with antibacterial mouthwash. This was associated with a lack of changes in circulatory nitrite (P > 0.05), and impaired microvascular response (peak TOI baseline: 85.1 ±â€¯3.1%; peak TOI post-exercise: 84.6 ±â€¯3.2%; P > 0.05). Diversity of oral bacteria did not change after exercise in any treatment. These findings show that nitrite synthesis by oral commensal bacteria is a key mechanism to induce the vascular response to exercise over the first period of recovery thereby promoting lower blood pressure and greater muscle oxygenation.

The oral nitrate-reducing capacity correlates with peak power output and peak oxygen uptake in healthy humans.

Interest in inorganic nitrate and nitrite has grown substantially over the past decade as research has revealed the role of these anions in enhancing nitric oxide (NO) availability through an oral pathway. Nitrite synthesis in the mouth seems to be an important mechanism to feed the circulatory system with this anion. This is interesting since greater plasma nitrite concentration has been associated with better fitness levels in humans, but this question has not been investigated in relation to salivary nitrite concentration. Additionally, no previous study has investigated the oral nitrate-reducing capacity in regards to peak oxygen uptake (VO2peak) or peak power output (Wpeak) in humans. Thus, the main goal of this study was to investigate whether salivary nitrite and nitrate concentration and the oral nitrate-reducing capacity were associated with VO2peak and Wpeak in healthy humans. Fifty individuals (22 females and 28 males; 38.8 ±â€¯14.3 years/old; BMI = 22.8 ±â€¯3.9) performed a graded exercise test on a cycle ergometer to assess their VO2peak and Wpeak. Unstimulated salivary samples were taken before and 20 min after exercise to measure nitrate/nitrite, pH and lactate. The oral nitrate-reducing capacity was also assessed in 25 subjects before and after exercise. Oral nitrate-reducing capacity was positively associated with Wpeak (rs = 0.64; P = 0.001) and the VO2peak (rs = 0.54; P = 0.005). Similar correlations were found when these variables were analysed after exercise. In addition, a significant decrease in salivary pH (pre: 7.28 ±â€¯0.361; post-exercise: 7.16 ±â€¯0.33; P = 0.003) accompanied by an increase of salivary lactate (pre: 0.17 ±â€¯0.14 mmol/L; post-exercise: 0.48 ±â€¯0.38; P < 0.001) was found after exercise. However, these changes did not have any impact on salivary nitrate/nitrite concentration and the oral nitrate-reducing capacity after exercise. In conclusion, this is the first evidence showing a link between the oral nitrate-reducing capacity and markers of aerobic fitness levels in healthy humans.

Four days of simulated shift work reduces insulin sensitivity in humans.

AIM: The aim of this study was to investigate the effects of 4 consecutive simulated night shifts on glucose homeostasis, mitochondrial function and central and peripheral rhythmicities compared with a simulated day shift schedule. METHODS: Seventeen healthy adults (8M:9F) matched for sleep, physical activity and dietary/fat intake participated in this study (night shift work n = 9; day shift work n = 8). Glucose tolerance and insulin sensitivity before and after 4 nights of shift work were measured by an intravenous glucose tolerance test and a hyperinsulinaemic euglycaemic clamp respectively. Muscles biopsies were obtained to determine insulin signalling and mitochondrial function. Central and peripheral rhythmicities were assessed by measuring salivary melatonin and expression of circadian genes from hair samples respectively. RESULTS: Fasting plasma glucose increased (4.4 ± 0.1 vs. 4.6 ± 0.1 mmol L-1 ; P = .001) and insulin sensitivity decreased (25 ± 7%, P < .05) following the night shift, with no changes following the day shift. Night shift work had no effect on skeletal muscle protein expression (PGC1α, UCP3, TFAM and mitochondria Complex II-V) or insulin-stimulated pAkt Ser473, pTBC1D4Ser318 and pTBC1D4Thr642. Importantly, the metabolic changes after simulated night shifts occurred despite no changes in the timing of melatonin rhythmicity or hair follicle cell clock gene expression across the wake period (Per3, Per1, Nr1d1 and Nr1d2). CONCLUSION: Only 4 days of simulated night shift work in healthy adults is sufficient to reduce insulin sensitivity which would be expected to increase the risk of T2D.

A comparison of fat mass and skeletal muscle mass estimation in maleultra-endurance athletes using bioelectrical impedance analysis anddifferent anthropometric methods / Comparación de la masa grasa y muscular estimada en atletas varones de ultra-resistencia utilizando la bioimpedancia eléctrica y diferentes métodos antropométricos

Two hundred and fifty seven male Caucasian ultraendurance athletes were recruited, pre-race, before different swimming, cycling, running and triathlon races. Fat mass and skeletal muscle mass were estimated using bioelectrical impedance analysis (BIA) and anthropometric methods in order to investigate whether the use of BIA or anthropometry would be useful under field conditions. Total body fat estimated using BIA was significantly high (P < 0.001) compared with anthropometry. When the results between BIA and anthropometry were compared, moderate to low levels of agreement were found. These results were in accordance with the differences found in the Bland-Altman analysis, indicating that the anthropometric equation of Ball et al. had the highest level of agreement (Bias = -3.0 ± 5.8 kg) with BIA, using Stewart et al. (Bias = -6.4 ± 6.3 kg), Faulkner (Bias = -4.7 ± 5.8 kg) and Wilmore-Siri (Bias = -4.8 ± 6.2 kg). The estimation of skeletal muscle mass using BIA was significantly (P < 0.001) above compared with anthropometry. The results of the ICC and Bland-Altman method showed that the anthropometric equation from Lee et al. (Bias = -5.4 ± 5.3 kg) produced the highest level of agreement. The combined method of Janssen et al. between anthropometry and BIA showed a lower level of agreement (Bias = -12.5 ± 5.7 kg). There was a statistically significant difference between the results derived from the equation of Lee et al. and Janssen et al. (P < 0.001). To summarise, the determination of body composition in ultra-endurance athletes using BIA reported significantly high values of fat and skeletal muscle mass when compared with anthropometric equations (AU)

Se reclutaron a 257 hombres caucasianos que eran atletas de alto rendimiento, antes de competir en diferentes pruebas triatlón de natación, ciclismo y carrera. Se estimaron la masa grasa y la masa de músculo esquelético utilizando un análisis de impedancia bioeléctrica (BIA) y métodos antropométricos con el fin de investigar si el uso de BIA o de la antropometría sería útil en tales condiciones de campo. La grasa corporal total estimada por BIA fue significativamente mayor en comparación con la antropometría (P < 0,001). Cuando se compararon los resultados entre BIA y antropometría, se encontraron niveles de concordancia bajos a moderados. Estos resultados concuerdan con las diferencias halladas con el análisis Bland-Altman, lo que indica que la ecuación antropométrica de Ball et al. posee el mayor grado de concordancia (desviación = -3,0 ± 5,8 kg) con BIA, con Stewart et al. (desviación = -6,4 ± 6,3 kg), Faulkner (desviación = -4,7 ± 5,8 kg) y Wilmore-Siri (desviación = -4,8 ± 6,2 kg). La estimación de la masa de músculo esquelético fue significativamente superior con BIAS que con antropometría (P < 0,001). Los resultados de la ICC y del método Bland-Altman muestran que la ecuación antropométrica de Lee et al. (desviación = -5,4 ± 5,3 kg) produjo el mayor grado de concordancia. El método combinado de Janssen et al. entre antropometría y BIA mostró el menor grado de concordancia (desviación = -12,5 ± 5,7 kg). Hubo una diferencia estadísticamente significativa entre los resultados derivados de la ecuación de Lee et al. y de la de Janssen et al. (P < 0,001). En resumen, la determinación de la composición corporal en atletas de alto rendimiento utilizando BIA produjo valores significativamente mayores de masa grasa y músculo esquelético en comparación con las ecuaciones antropométricas (AU)

New indices for quantification of the power spectrum of heart rate variability time series without the need of any frequency band definition.

This paper presents a new family of indices for the frequency domain analysis of heart rate variability time series that do not need any frequency band definition. After proper detrending of the time series, a cumulated power spectrum is obtained and frequencies that contain a certain percentage of the power below them are identified, so median frequency, bandwidth and a measure of the power spectrum asymmetry are proposed to complement or improve the classical spectral indices as the ratio of the powers of LF and HF bands (LF/HF). In normal conditions the median frequency provides similar information as the classical indices, while the bandwidth and asymmetry can be complementary measures of the physiological state of the tested subject. The proposed indices seem to be a good choice for tracking changes in the power spectrum in exercise stress, and they can guide in the determination of frequency band limits in other animal species.

A comparison of fat mass and skeletal muscle mass estimation in male ultra-endurance athletes using bioelectrical impedance analysis and different anthropometric methods.

Two hundred and fifty seven male Caucasian ultra-endurance athletes were recruited, pre-race, before different swimming, cycling, running and triathlon races. Fat mass and skeletal muscle mass were estimated using bioelectrical impedance analysis (BIA) and anthropometric methods in order to investigate whether the use of BIA or anthropometry would be useful under field conditions. Total body fat estimated using BIA was significantly high (P < 0.001) compared with anthropometry. When the results between BIA and anthropometry were compared, moderate to low levels of agreement were found. These results were in accordance with the differences found in the Bland-Altman analysis, indicating that the anthropometric equation of Ball et al. had the highest level of agreement (Bias = -3.0 ± 5.8 kg) with BIA, using Stewart et al. (Bias = -6.4 ± 6.3 kg), Faulkner (Bias = -4.7 ± 5.8 kg) and Wilmore-Siri (Bias = -4.8 ± 6.2 kg). The estimation of skeletal muscle mass using BIA was significantly (P < 0.001) above compared with anthropometry. The results of the ICC and Bland-Altman method showed that the anthropometric equation from Lee et al. (Bias = -5.4 ± 5.3 kg) produced the highest level of agreement. The combined method of Janssen et al. between anthropometry and BIA showed a lower level of agreement (Bias = -12.5 ± 5.7 kg). There was a statistically significant difference between the results derived from the equation of Lee et al. and Janssen et al. (P < 0.001). To summarise, the determination of body composition in ultra-endurance athletes using BIA reported significantly high values of fat and skeletal muscle mass when compared with anthropometric equations.

[Assessment of body fat in physically active young people: anthropometry vs bioimpedance]. / Valoración de la grasa corporal en jóvenes físicamente activos: antropometría vs bioimpedancia.

OBJECTIVE: To assess the level of agreement between the anthropometrical method and several bioimpedance (BIA) devices to estimate the fat mass in a group of physically active young people. SUBJECTS: 55 students of Physical Activity Sciences and Sports of the INEFC of Barcelona; 29 men (age: 24.7 +/- 4.7 years; BMI: 23.4 +/- 1.8) and 26 women (age: 22.9 +/- 3.5; BMI: 21.5 +/- 1.9). All of them voluntarily gave their informed consent. MATERIALS AND METHOD: Anthropometrical assessment was done according to the International Society for the Advancement Kinanthropometry (ISAK) protocol, the fat % was calculated by the Siri's equation and was compared with that obtained by 4 different BIA devices: Biospace Inbody 720, Tanita BC400, Tanita TBF-521, and Omron BF-300. To assess the level of agreement of the results, the interclass correlation coefficient and the Bland Aldman method were used. RESULTS: The estimated fat mass, in men, by the anthropometrical method was 7 +/- 2.2 kg. The results by the BIA systems were: 7.4 +/- 3 kg; 5.6 +/- 2.2 kg; 5.7 +/- 2.5 kg, and 7.4 +/- 3 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively. In women, the results were 10.4 +/- 2.7 kg of fat mass by means of the anthropometrical method and 10.3 +/- 2.9 kg, 11 +/- 3.3 kg, 11.5 +/- 3.0 kg, and 10 +/- 2.9 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively. CONCLUSIONS: In the male group, the level of agreement between anthropometrics and BIA devices was moderate-poor, whereas in women there was a good correlation between both techniques for estimating the body fat when the Biospace Inbody 720 and Tanita BC400 devices were used.

Valoración de la grasa corporal en jóvenes físicamente activos: antropometría vs bioimpedancia / Assessment of body fat in physically active young people: Anthropometry vs bioimpedance

Objetivo: Analizar el nivel de concordancia entre el método antropométrico y diferentes aparatos de bioimpedancia (BIA) para la estimación de la masa grasa en un grupo de personas jóvenes y físicamente activas. Sujetos: Participaron 55 sujetos estudiantes de Ciencias de la Actividad Física y el Deporte del INEFC de Barcelona; 29 hombres (edad: 24,7 ± 4,7 años; IMC: 23,4 ± 1,8) y 26 mujeres (edad: 22,9 ± 3,5; IMC: 21,5 ± 1,9). Todos ellos otorgaron voluntariamente su consentimiento informado Material y métodos: La valoración antropométrica se realizó de acuerdo con el protocolo de la International Society for the Advancement Kinanthropometry (ISAK), el % graso fue calculado mediante la ecuación de Siri y se comparó con el obtenido por 4 aparatos BIA diferentes: Biospace Inbody 720, Tanita BC400, Tanita TBF-521 y Omron BF-300. Para valorar la concordancia de los resultados se utilizó el coeficiente de correlación intraclase y el método de Bland Aldman. Resultados: La masa grasa estimada, en hombres, mediante el método antropométrico fue de 7 ± 2,2 kg. Los resultados de los sistemas BIA fueron 7,4 ± 3 kg; 5,6 ± 2,2 kg; 5,7 ± 2,5 kg y 7,4 ± 3 kg para los aparatos Biospace Inbody 720, Tanita BC400, Tanita TBF521 y Omron BF300 respectivamente. En las mujeres los resultados fueron 10,4 ± 2,7 kg de masa grasa mediante el método antropométrico y 10,3 ± 2,9 kg; 11 ± 3,3 kg; 11,5 ± 3,0 kg; 10 ± 2,9 kg para los aparatos Biospace Inbody 720, Tanita BC400, Tanita TBF521 y Omron BF300 respectivamente. Conclusiones: En el grupo masculino la concordancia entre la antropometría y los aparatos BIA fue moderadabaja, en cambio en las mujeres se halló una buena concordancia entre las dos técnicas para la estimación de la grasa corporal cuando fueron utilizados los aparatos Biospace Inbody 720 y Tanita BC400 (AU)

Objective: To assess the level of agreement between the anthropometrical method and several bioimpedance (BIA) devices to estimate the fat mass in a group of physically active young people. Subjects: 55 students of Physical Activity Sciences and Sports of the INEFC of Barcelona; 29 men (age: 24.7 ± 4.7 years; BMI: 23.4 ± 1.8) and 26 women (age: 22.9 ± 3.5; BMI: 21.5 ± 1.9). All of them voluntarily gave their informed consent. Materials and method: Anthropometrical assessment was done according to the International Society for the Advancement Kinanthropometry (ISAK) protocol, the fat % was calculated by the Siri's equation and was compared with that obtained by 4 different BIA devices: Biospace Inbody 720, Tanita BC400, Tanita TBF-521, and Omron BF-300. To assess the level of agreement of the results, the interclass correlation coefficient and the Bland Aldman method were used. Results: The estimated fat mass, in men, by the anthropometrical method was 7 ± 2.2 kg. The results by the BIA systems were: 7.4 ± 3 kg; 5.6 ± 2.2 kg; 5.7 ± 2.5 kg, and 7.4 ± 3 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively. In women, the results were 10.4 ± 2.7 kg of fat mass by means of the anthropometrical method and 10.3 ± 2.9 kg, 11 ± 3.3 kg, 11.5 ± 3.0 kg, and 10 ± 2.9 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively. Conclusions: In the male group, the level of agreement between anthropometrics and BIA devices was moderate-poor, whereas in women there was a good correlation between both techniques for estimating the body fat when the Biospace Inbody 720 and Tanita BC400 devices were used (AU)