Introduction: Strenuous physical stress induces a range of physiological responses, the extent depending, among others, on the nature and severity of the exercise, a person’s training level and overall physical resilience. This principle can also be used in an experimental set-up by measuring time-dependent changes in biomarkers for physiological processes. In a previous report, we described the effects of workload delivered on a bicycle ergometer on intestinal functionality. As a follow-up, we here describe an analysis of the kinetics of various other biomarkers. Aim: To analyse the time-dependent changes of 34 markers for different metabolic and immunological processes, comparing four different exercise protocols and a rest protocol. Methods: After determining individual maximum workloads, 15 healthy male participants (20–35 years) started with a rest protocol and subsequently performed (in a cross-over design with 1-week wash-out) four exercise protocols of 1-h duration at different intensities: 70% Wmax in a hydrated and a mildly dehydrated state, 50% Wmax and intermittent 85/55% Wmax in blocks of 2 min. Perceived exertion was monitored using the Borg’ Rating of Perceived Exertion scale. Blood samples were collected both before and during exercise, and at various timepoints up to 24 h afterward. Data was analyzed using a multilevel mixed linear model with multiple test correction. Results: Kinetic changes of various biomarkers were exercise-intensity-dependent. Biomarkers included parameters indicative of metabolic activity (e.g., creatinine, bicarbonate), immunological and hematological functionality (e.g., leukocytes, hemoglobin) and intestinal physiology (citrulline, intestinal fatty acid-binding protein, and zonulin). In general, responses to high intensity exercise of 70% Wmax and intermittent exercise i.e., 55/85% Wmax were more pronounced compared to exercise at 50% Wmax. Conclusion: High (70 and 55/85% Wmax) and moderate (50% Wmax) intensity exercise in a bicycle ergometer test produce different time-dependent changes in a broad range of parameters indicative of metabolic activity, immunological and hematological functionality and intestinal physiology. These parameters may be considered biomarkers of homeostatic resilience. Mild dehydration intensifies these time-related changes. Moderate intensity exercise of 50% Wmax shows sufficient physiological and immunological responses and can be employed to test the health condition of less fit individuals.
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With ageing, there is a greater risk of dehydration. This study investigated the diuretic effect of alcoholic beverages varying in alcohol concentration in elderly men. Three alcoholic beverages (beer (AB), wine (AW), and spirits (S)) and their non-alcoholic counterparts (non-alcoholic beer (NAB), non-alcoholic wine (NAW), and water (W)) were tested in a diet-controlled randomized crossover trial. For the alcoholic beverages, alcohol intake equaled a moderate amount of 30 g. An equal volume of beverage was given for the non-alcoholic counterpart. After consumption, the urine output was collected every hour for 4 h and the total 24 h urine output was measured. AW and S resulted in a higher cumulative urine output compared to NAW and W during the first 4 h (effect size: 0.25 mL p < 0.003, effect size: 0.18 mL, p < 0.001, respectively), but not after the 24h urine collection (p > 0.40, p > 0.10). AB and NAB did not differ at any time point (effect size: -0.02 mL p > 0.70). For urine osmolality, and the sodium and potassium concentration, the findings were in line. In conclusion, only moderate amounts of stronger alcoholic beverages, such as wine and spirits, resulted in a short and small diuretic effect in elderly men.
Thermal batteries, which store and release energy by hydrating and dehydrating salt crystals, hold great promise for domestic heating. Such batteries can be charged from waste heat from industrial processes, and discharged to provide neighbourhood heating. Unlike hot water storage systems, the energy is stored at room temperature, so the thermal losses are very low, making a salt battery highly efficient. However, the electrochemical change of the salt due to hydration and dehydration is very small, making it difficult to measure how much energy is stored in a battery. One promising technique is to measure the absolute humidity of the inlet and outlet air flow. The difference in humidity, combined with a rate equation model allows the total mass of water stored in the battery to be calculated, which can then be used to calculate the energy storage and battery power flow. However, there are several uncertainties in this approach. Commercially available sensors age over time, sometimes quite suddenly. It is not yet known if software can be used to compensate for sensor aging, or if a different sensor type is required. In addition to aging, each measurement is subject to random noise, which will be integrated into the model used to calculate the charge of the battery. It is not yet known how the noise will influence charge estimates. On the other hand, the sensor system must be as durable as domestic heating systems (decades). Hence, it is required to understand sensor aging in order to validate the sensor system for its intended use.
