Military divers often operate in cold water eliciting reductions in skin and core temperatures despite the use of thermal protection. Decreases in body temperatures triggers shivering and non-shivering thermogenesis, the latter of which is largely due to the activation of brown adipose tissue (BAT). Ten days of cool air exposure (15-16°C) and seven days of cold-water exposure (14°C) augments non-shivering thermogenesis. However, it is unknown if repeated exposure to cool head out water immersion (CWI) modifies non-shivering thermogenesis. This study tested the hypothesis that fourteen days of CWI for 4 h/d will increase BAT activation. Healthy adults were randomly assigned to either CWI (n=10, 5 women) or thermoneutral head out water immersion (35°C, TNW, n=9, 5 women). CWI and TNW exposures were 4 h in duration and were completed once daily for 14 d in a 16-d period. CWI consisted of the initial immersion in 28°C water and following a 0.5°C reduction in rectal temperature, the water temperature was increased to up to 30°C so that a mild hypothermic state was maintained during the 4 h. Rectal temperature, oxygen uptake (indirect calorimetry), and supraclavicular and trapezius skin temperatures (thermocouples) were measured preexposure and during the middle 3 h of immersion. This analysis was a part of a larger study. Therefore, during the 3 h period, all participants were exposed to hypoxia (FiO2: 0.14). The supraclavicular-trapezius skin temperature difference (Tsk diff) provided an index of BAT activation. Data collected on Day 1 and Day 14 are presented (mean ± SD). Peak decreases in rectal temperature from preexposure were greater in CWI (-0.7±0.3°C) vs. TNW (-0.2±0.4°C, p<0.001) and did not differ between Day 1 and Day 14 in either group (p=0.923). Average oxygen uptake was higher in CWI (0.54±0.09 L/min) vs. TNW (0.38±0.12 L/min, p<0.001) and did not differ between Day 1 and Day 14 in either group (p=0.443). Average Tsk diff did not differ between groups (CWI: 2.2±0.8°C, TNW: 1.6±0.1.1°C, p=0.090) and did not differ between Day 1 and Day 14 in either group (p=0.111). Peak decreases in rectal temperature were significantly correlated with average oxygen uptake (r=-0.552, p<0.001) but not average Tsk diff (r=-0.152, p=0.362). Fourteen days of CWI did not modify thermogenesis (oxygen uptake) nor BAT activation, as estimated from Tsk diff. However, a potential interaction between moderate hypoxia and BAT activation during CWI cannot be excluded. Future work is required to determine the effect of mild hypothermia, such as that experienced by divers operating in cold water even with thermal protection, on more direct markers of BAT activation. Funding: Offce of Naval Research (N00014-20-1-2593 & N00014-21-1-2276). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

PURPOSE: To investigate whether the dysanapsis ratio (DR) predicts expiratory flow limitation in highly trained athletes, as has been shown in healthy, active men and women. METHODS: Data from 124 highly trained men (age 21.9 ± 3.6 yrs) who performed maximal incremental tests to exhaustion were analyzed. The maximum expiratory flow-volume curve, along with inspiratory capacity maneuvers, were used to determine lung volumes, determine expiratory flows, and to quantify flow limitation. The subjects were partitioned into ‘flow-limited’ (EFL) and ‘non flow-limited’ (NEFL) groups, where tidal vs. maximal flow-volume overlap >5% qualifies as EFL. Group differences were evaluated using independent T-tests, while logistic regression was used to assess the predictive ability of DR, forced vital capacity (FVC), and V̇O2max on EFL. RESULTS: 63% of subjects (n = 78) displayed EFL with an average severity of 43.3 ± 21.0 %. EFL showed significantly lower FEV1 (4.5 ± 0.6 vs. 4.9 ± 0.6 L, p < .001), FEV1/FVC (86.3 ± 7.8 vs. 91.3 ± 5.7 %, p < .001), and FEF50 (6.1 ± 2.0 vs.7.6 ± 1.4 L·s-1, p < .001). However, no significant differences were found in FVC (5.2 ± 0.7 vs. 5.3 ± 0.8 L, p = .191) between groups. EFL showed a significantly smaller DR (0.2 ± 0.1 vs. 0.3 ± 0.1, p = .001) compared to NEFL. There were no differences between EFL and NEFL at peak exercise with respect to VO2max (67.1 ± 8.1 vs. 65.4 ± 4.5 ml·min-1·kg-1, p = .246), VE (155.9 ± 26.0 vs. 158.6 ± 26.6 L·min-1, p = .59), or frequency of breathing (56.8 ± 8.6 vs. 55.4 ± 10.3 br·min-1, p = .42). A significant predictive relationship was observed between DR on EFL (Odds Ratio (OR): 0.55, 95% CI 0.36 to 0.81, p < .01). A multivariate analysis indicated that DR (OR 0.35, 95% CI 0.21 to 0.58, p < .001), FVC (OR 0.49, 95% CI 0.31 to 0.78, p = .003), and V̇O2max (OR 1.63, 95% CI 1.05 to 2.53, p = .028) were significant predictors of EFL. CONCLUSIONS: Consistent with previous findings in active subjects, an increase in DR or FVC significantly decreases the likelihood of EFL in highly trained athletes. However, results from this analysis show that when controlling for DR and FVC, an increase in V̇O2max significantly increases the likelihood of EFL. This relationship was previously found to be non-significant in healthy active individuals and may highlight potential differences that exist within endurance trained populations.

Recently, a commercially available starting ‘ledge’ designed to reduce foot slippage during the execution of the backstroke start was introduced in competitive swimming. For the purpose of identifying potential safety consequences, the present study investigated the effect of ledge use on head depths, speeds, and distances in backstroke starts of athletes with no prior or only novice familiarity of the ledge. Competitive backstroke starts were performed with and without ledges by high school-aged (14.5 to 19.2 yr, N = 61) swimmers in 1.52 m of water during a closed testing session. A SIMI Reality Motion System in a calibrated space using three cameras was employed for filming starts. Dependent measures were initial head height (Yset), distance from wall at entry (Xentry), entry angle (Angleentry), horizontal velocity at head entry (XVelentry), resultant velocity at entry (ResVelentry), maximum depth of the center of the head (Ymhd), resultant velocity at maximum head depth (ResVelmhd), and distance from the wall at maximum head depth (Xmhd). The ledge (L) condition showed significant increases compared to the non-ledge (NL) condition in Xentry (L 1.61 ± 0.59 m, NL 1.50 ± 0.53 m, p < .001), ResVelentry (L 3.44 ± 0.97 m·s-1, NL 3.08 ± 1.00 m·s-1, p < .001), Angleentry (L 43.13 ± 16.97°, NL 39.66 ± 18.11°, p = .030), Xmhd (L 4.18 ± 0.58 m, NL 4.09 ± 0.63 m, p = .008), and Ymhd (L 0.54 ± 0.21 m, NL 0.49 ± 0.18, p

Hypercapnic ventilatory response (HCVR) and hypoxic ventilatory response (HVR) are common procedures used to describe an individual’s responsiveness to inhaled increases in CO2 and decreases in O2 respectively. To our knowledge there are no studies of HCVR or HVR of a grand enough scale to determine normative values or a ‘typical’ response. No description of the distribution of values, yet, is available in the literature such that little can currently be said about population-based differences. PURPOSE: To characterize the distribution of and establish reference values for ventilatory responses of the broad population using readily accessible sources. METHODS: Previously published dissertations and peer-reviewed manuscripts (N=25) were used to obtain subjects’ responses (N=312, age = 29.4 ± 13.2 yrs). HCVR tests (n=262) were analyzed using the slope of the linear regression line relating PA CO2 to minute ventilation (V[Combining Dot Above]E), l*min-1*mmHg-1. HVR was calculated using either the calculated slope of the linear regression relating V[Combining Dot Above]E to oxyhemoglobin saturation, l*min-1*%-1 (n=105) or using the hyperbolic shape parameter (A) of the curve relating V[Combining Dot Above]E to PA O2 (n=170). Confidence intervals for mean and median values were calculated using bootstrapping procedures. RESULTS: Data are presented mean/median; ±95% CI width. HCVR values displayed a right skewed non-normal distribution (skew = 5.25, p <.05), mean 2.67; ±0.70 l*min- 1*mmHg-1, median 2.00; ±0.51 l*min-1*mmHg-1 (IQR: 1.50). HVR A values showed a non-normal right skewed distribution (skew = 0.92, p <.05), mean 131.8; ±23.62 l*min- 1*mmHg-1, median 112.50; ±58.25 l*min-1*mmHg-1 (IQR: 118.99). Linearized HVR values using %SaO2 was also a right skewed non-normal distribution (skew=1.33, p<.05), mean 0.35; ±0.10 l*min-1*%-1, median 0.26; ±0.23 l*min-1*%-1 (IQR: 31.00). CONCLUSION: This analysis allows researchers to better place into context assessments of HCVR and HVR by providing distribution parameters derived from the literature. However, as HVR measures contrast due to methodological differences, distribution parameters remain infirm. In an effort to strengthen these distributions, researchers should include individual responses when reporting results of studies.

PURPOSE: It is well known that routine intensive physical activity (PA) will result in positive cardiovascular adaptations. Similarly, it is known that aging will cause decrements in similar common measures of cardiovascular health. However, there is only limited data on the cardiovascular performance of an older, presumably healthy, physically active population who have remained active for decades. METHODS: Thirteen masters level swimmers (MS) and eight controls (IC) (54.3 ± 12.7yrs and 57.5 ± 7.9yrs; respectively) were asked to wear an ambulatory heart rate monitor (Actiheart) for seven consecutive days. Subjects were partitioned based upon self-reported long-term physical activity and asked to maintain their normal daily activities for the entirety of the data collection period. Heart rate was collected during waking hours (14.8 ± 3.2 hrs). All HR data was verified via accelerometer. To measure HRpeak and estimate cardiovascular fitness level, subjects completed a 1-mile timed walk. Independent two-sample t-tests were used for all comparisons, significance set at p<0.05. RESULTS: Mean daily HRmin and HRavg was lower in MS than IC (54 ± 5 vs 67 ± 8bpm, 72 ± 8bpm vs. 83 ± 9bpm; p<0.05, respectively) while mean daily HRmax was higher in MS (139 ± 18bpm vs. 131 ± 19bpm; p<0.05). Mean daily HRmax was higher than HRpeak during the 1-mile test for MS (139 ± 19 vs. 123 ± 20bpm; p<0.05) but not for IC (131 ± 18 vs. 135 ± 18; p = 0.69). CONCLUSIONS: Persistent participation in routine physical activity at any age appears to result in training induced changes consistent with improved cardiovascular health. Results from the present study, however, suggest that a 1 mile walk may not be an appropriate test for the physically active as it tends to underestimate maximum values for heart rate.

Objectives: Clinically pre-hypertensive adults are at a greater risk of developing hypertension, stiffened arteries, and other cardiovascular risks. Endurance exercise training has been shown to improve elevated resting blood pressure and C-reactive protein (CRP) levels. However, a primary barrier preventing individuals from engaging in regular physical activity is a lack of time. The purpose of our study was to determine if a high-intensity interval training (HIIT) protocol would be as effective as continuous aerobic endurance training (ET) on resting blood pressure in pre-hypertensive participants. Additionally, this study investigated the effects of HIIT vs. ET on CRP.Methods: Twelve pre-hypertensive participants (33.36.1 yrs; 3M/9W) participated in 8 weeks of cycle ergometer exercise training. The ET exercised for 30 continuous min/day, 4 days/week at 40% reserve. The HIIT exercised at a 1:1 work-to-rest for 20 min/day, 3 days/week at 60% peak power. Resting mean arterial pressure and CRP were compared throughout the study.Results: Both groups showed decreases (p<0.001) in mean arterial pressure (ET: -11.5 +/- 5.9 mmHg; HIIT: -8.6 +/- 4.8 mmHg) following the 8 weeks. For CRP, there was a significant decrease (p=0.014) as a main effect of time. increased (p<0.001) approximately 25% for both HIIT and ET.Conclusion: These preliminary data suggest HIIT and ET similarly decreased resting blood pressure and increased.

Ventilation while swimming is generally constrained by the medium (water) and the obligatory timing associated with arm mechanics. Attempts at describing ventilation have been similarly constrained and therefore little published data exists on operating lung volumes and pulmonary function while swimming at maximal efforts. This is in contrast to the considerable data available for cycling and running. PURPOSE: To compare swimming and cycling exercise modes on ventilatory variables. METHODS: Ten trained, competitive men swimmers (age = 24.4 ± 1.91yrs) were asked to perform two incremental exercise tests to volitional exhaustion on separate days, one on a cycle ergometer and a second while swimming in a flume. Tidal volume (VT), peak tidal flow inspired (PTi) and expired (PTe), time to inspire (Ti) and expire (Te), total tidal time (Tt), duty cycle (Ti/TT), and ventilatory capacity (Vcap) were assessed repetitively in both conditions via flow-volume loops. Maximum aerobic capacity (VO2peak) and ventilation (VE) were measured via open flow calorimetry. All variables were recorded over the final minute of each incremental exercise test. Paired t-tests were used to compare the exercise modes, with the level of significance set at 0.05. RESULTS: In the final minute of the incremental test to exhaustion, swimming resulted in a smaller PTi (4.74 ± 0.29 vs. 5.66 ± 0.29L·s-1; p<0.05), but a greater PTe (7.00 ± 0.20 vs. 6.03 ± 0.38L·s-1; p<0.05) than for cycling. Ti (0.76 ± 0.05 vs. 0.63 ± 0.38s; p<0.05), Tt (1.48 ± 0.09 vs. 1.28 ± 0.08s; p<0.05), and Ti/TT (56.7 ± 1.1 vs. 49.4 ± 0.7%; p<0.05) were greater for swimming than for cycling. Despite no difference in Te (0.58 ± 0.10 vs. 0.65 ± 0.04s; p=0.13), VO2peak (3.61 ± 0.21 vs. 3.60 ± 0.14 L·min-1, p = 0.95) or Vcap (189.1 ± 63.0 vs. 165.9 ± 61.3L·s-1; p=0.07) between exercise modes, VE was smaller in swimming versus cycling (102.9 ± 5.8 vs. 129.0 ± 7.8 L·s-1; p<0.05). CONCLUSIONS: Swimming appears to require changes in ventilatory strategies during maximal efforts as compared to similar exercise performed on a cycle ergometer despite similar metabolic demands. Whether or not this is due to postural differences, hydrostatic influences or the obligatory ventilatory entrainment remains unclear.

During high intensity exercise, both respiratory muscle fatigue and cardiovascular reflexes occur; however, it is not known how inactive limb blood flow is influenced. The purpose of this study was to determine the influence of moderate and high exercise intensity on respiratory muscle fatigue and inactive limb muscle and cutaneous blood flow during exercise.

An increased work of breathing during heavy whole body exercise can lead to respiratory muscle fatigue (RMF) and decreased leg blood flow. Heavy exercise also increases inactive limb and cutaneous blood flow. It is not known, however, how RMF affects inactive limb and cutaneous blood flow. Therefore, we tested the hypothesis that RMF during heavy exercise would reduce: 1) inactive limb blood flow, 2) inactive limb vascular conductance, and 3) inactive limb cutaneous blood flow. Twelve healthy men (23 ± 2 yrs) completed baseline pulmonary function tests followed by an incremental cycle test to VO2max. Subjects then cycled at both 70% and 85%VO2max (randomized) for 20 minutes. Subjects performed a second 85%VO2max test ingesting N-acetylcysteine (NAC) (1800mg), which has been reported to reduce RMF, 45 minutes prior the test. Maximum inspiratory pressures (PImax) were measured prior to and immediately following each exercise trial to determine RMF. During exercise, brachial artery blood flow (BABF) was measured via Doppler ult