The purpose of this study was to examine the effects of a 2-km swim on markers of subsequent cycling performance in well-trained, age-group triathletes. Fifteen participants (10 males, five females, 38.3 ± 8.4 years) performed two progressive cycling tests between two and ten days apart, one of which was immediately following a 2-km swim (33.7 ± 4.1 min). Cycling power at 4-mM blood lactate concentration decreased after swimming by an average of 3.8% (p = 0.03, 95% CI −7.7, 0.2%), while heart rate during submaximal cycling (220 W for males, 150 W for females) increased by an average of 4.0% (p = 0.02, 95% CI 1.7, 9.7%), compared to cycling without prior swimming. Maximal oxygen consumption decreased by an average of 4.0% (p = 0.01, 95% CI −6.5, −1.4%), and peak power decreased by an average of 4.5% (p < 0.01, 95% CI −7.3, −2.3%) after swimming, compared to cycling without prior swimming. Results from this study suggest that markers of submaximal and maximal cycling are impaired following a 2-km swim.

Participation in surfing has evolved to include all age groups. Therefore, the purpose of this study was to determine whether activity levels and cardiovascular responses to surfing change with age. Surfing time and heart rate (HR) were measured for the total surfing session and within each activity of surfing (paddling, sitting, wave riding, and miscellaneous). Peak oxygen consumption (VO) was also measured during laboratory-based simulated surfboard paddling on a modified swim bench ergometer. VO decreased with age during simulated paddling (r = -.455, p < .001, n = 68). Total time surfing (p = .837) and time spent within each activity of surfing did not differ with age (n = 160). Mean HR during surfing significantly decreased with age (r = -.231, p = .004). However, surfing HR expressed as a percent of age-predicted maximum increased significantly with age. Therefore, recreational surfers across the age spectrum are achieving intensities and durations that are consistent with guidelines for cardiovascular health.

Users actuate touchscreen computers by applying forces with their fingers to the touchscreen, although the amount and direction of the force is unknown. Our aim was to characterize the magnitude, direction and impulse of the force applied during single finger (tapping and sliding in four directions) and two finger gestures (stretch and pinch). Thirteen subjects performed repeated trials of each gesture. Mean(±SD) resultant force was 0.50(0.09)N for tap, 0.79(0.32)N to 1.18(0.47)N for sliding gestures, 1.47(0.63)N for pinch and 2.05(1.13)N for stretch. Mean resultant force was significantly less (p<0.04) for tap than for all gestures except slide right. The direction of force application was more vertical for the two-finger gestures as compared to the single- finger gestures. Tap was the fastest gesture to complete at 133(83)ms, followed by slide right at 421(181)ms. On average, participants took the longest to complete the stretch gesture at 920(398)ms. Overall, there are differences in forces, force direction, and completion times among touchscreen gestures that could be used to estimate musculoskeletal exposure and help forge guidelines to reduce risk of musculoskeletal injury.

Background Swimming economy refers to the rate of energy expenditure relative to swimming speed of movement, is inversely related to the energetic cost of swimming, and is as a key factor influencing endurance swimming performance. The objective of this study was to determine if high-carbohydrate, low-fat (HCLF) and low-carbohydrate, high-fat (LCHF) diets affect energetic cost of submaximal swimming. Methods Eight recreational swimmers consumed two 3-day isoenergetic diets in a crossover design. Diets were tailored to individual food preferences, and macronutrient consumption was 69–16-16% and 16–67-18% carbohydrate-fat-protein for the HCLF and LCHF diets, respectively. Following each 3-day dietary intervention, participants swam in a flume at velocities associated with 50, 60, and 70% of their maximal aerobic capacity (VO2max). Expired breath was collected and analyzed while they swam which enabled calculation of the energetic cost of swimming. A paired t-test compared macronutrient distribution between HCLF and LCHF diets, while repeated-measures ANOVA determined effects of diet and exercise intensity on physiological endpoints. Results Respiratory exchange ratio was significantly higher in HCLF compared to LCHF (p = 0.003), but there were no significant differences in the rate of oxygen consumption (p = 0.499) or energetic cost of swimming (p = 0.324) between diets. Heart rate did not differ between diets (p = 0.712), but oxygen pulse, a non-invasive surrogate for stroke volume, was greater following the HCLF diet (p = 0.029). Conclusions A 3-day high-carbohydrate diet increased carbohydrate utilization but did not affect swimming economy at 50–70% VO2max. As these intensities are applicable to ultramarathon swims, future studies should use higher intensities that would be more relevant to shorter duration events.

We hypothesized that breathing hypoxic, hypercapnic, and CO-containing gases together reduces maximal aerobic capacity (Vo2max) as the sum of each gas' individual effect on Vo2max. To test this hypothesis, goats breathed combinations of inspired O2 fraction (FiO2) of 0.06-0.21 and inspired CO2 fraction of 0.00 or 0.05, with and without inspired CO that elevated carboxyhemoglobin fraction (FHbCO) to 0.02-0.45, while running on a treadmill at speeds eliciting Vo2max. Individually, hypoxia and elevated FHbCO decreased fractional Vo2max (FVo2max, fraction of a goat's Vo2max breathing air) in linear, dose-dependent manners; hypercapnia did not change Vo2max. Concomitant hypoxia and elevated FHbCO decreased Vo2max less than the individual gas effects summed, indicating their combined effects on Vo2max are attenuated, fitting the following regression: FVo2max = 4.24 FiO2 + 0.519 FHbCO - 8.22 (FiO2 × FHbCO) + 0.117, (R(2) = 0.965, P < 0.001). The FVo2max correlated highly with total cardiopulmonary O2 delivery, not peripheral diffusing capacity, and with arterial O2 concentration (CaO2), not cardiac output. Hypoxia and elevated FHbCO decreased CaO2 by different mechanisms: hypoxia decreased arterial O2 saturation (SaO2), whereas elevated FHbCO decreased O2 capacitance {concentration of hemoglobin (Hb) available to bind O2 ([Hbavail])}. When breathing hypoxic gas (FiO2 0.12), CaO2 did not change with increasing FHbCO up to 0.30 because higher SaO2 of Hbavail offset decreased [Hbavail] due to the following: 1) hyperventilation with hypoxia and/or elevated FHbCO; 2) increased Hb affinity for O2 due to both Bohr and direct carboxyhemoglobin effects; and 3) the sigmoid relationship between O2 saturation and partial pressure elevating SaO2 more with hypoxia than normoxia.