Diurnal Regulation of Exercise-Induced Myocardial Signaling and Transcription

Introduction: Exercise is well known for its many benefits on the body and most notably the heart. Recent emphasis, and significant resources, have been dedicated to elucidating the molecular mechanisms through which exercise exerts its pluripotent beneficial effects on health and the prevention of disease. A continuous evolution in this field has sought to modulate and optimize exercise in various ways to maximize the benefits. In recent years, a growing appreciation for the impact of circadian rhythms has gained traction and their influence on many essential biological functions have been integrated into exercise physiology (i.e. - chrono-exercise), as well as other important areas of research like medicine (‘chrono-pharmacology’) and nutrition (‘chrono nutrition’). Recently, several excellent studies have provided evidence in various peripheral tissues that support a robust effect of time-of-day on exercise-induced responses at the transcriptional (via RNA-sequencing), metabolic (via metabolomics), and protein levels (via proteomics). In large part, these studies have focused on the skeletal muscle, our primary mover during exercise, and have neglected the heart. The purpose of this dissertation was to address this limitation in the field and explore the impact of time-of-day on exercise-induced signaling and transcription in the heart. Methods: We investigated the effects of exercise in the hearts of 12-week-old C57/BL6 male mice (n= 42) at two time points; Zeitgeber time (ZT) 0 (beginning of light phase) and ZT12 (beginning of dark phase). Mice were habituated to treadmill exercise for 5 days at ~ZT12 (under red light) and allowed to recover for 2 days. Mice performed a single 60-minute bout of treadmill exercise beginning at ZT0 or ZT12, and were sacrificed at 3 time points; pre-exercise (SED), immediately post exercise (POST), and 1-hour post exercise (1HR). Serum was separated and tissues (hearts and quadriceps) were excised and snap frozen. Clock genes were measured via RT-PCR. Cardioprotective signaling was assessed via western blotting analysis and Enzyme Linked Immunosorbent Assay (ELISA). RNA sequencing of hearts was performed for exploration of pathway enrichment by exercise and time-of-day. Group comparisons were made using 2x3 ANOVAs. Results: The major findings of this study are a significant interaction of exercise and time-of-day on p-STAT3 in the heart. Phosphorylation of STAT3 was increased at ZT0-POST (2.74 ± 0.34), and ZT0-1HR (1.66 ± 0.09) compared to ZT0-SED (1.00 ± 0.17), as well as compared to exercised mice at ZT12 (ZT12-POST = 1.25 ± 0.13, and ZT12-1HR = 1.15 ± 0.18) (Figure 6). A significant interaction between time-of-day and exercise on autophagy was present with LC3II/I ratios increased at ZT12-POST (4.13 ± 0.32) compared to ZT0-POST (2.56 ± 0.32) (p \u3c 0.001) (Figure 11). Transcriptional results revealed 264 DEGs at ZT0 and 216 at ZT12 with more genes being upregulated by exercise at ZT0 and the reverse (more genes down regulated by exercise) at ZT12 (186 and 108 respectively) (Figure 16 & 17). Time of day distinctly affected the transcriptional response to an acute bout of exercise in the heart. Overall, the results from this study highlight novel interactions between exercise and time-of-day, suggesting temporal coordination of exercise prescription with favorable cardiac responses that can be used to promote beneficial cardiovascular phenotypes. Conclusions: This experiment identified time as a critical mediator of exercise-induced cardiovascular signaling and transcription. Specifically, phosphorylation of STAT3 at ZT0 while Autophagy signaling at ZT12. While these data are in the context of a single bout of acute exercise, future studies will build upon these findings to test the effects of temporally specific exercise interventions in the context of cardiovascular disease including ischemia-reperfusion injury as well as cardiac rehabilitation

The Risk of Bias in Validity and Reliability Studies Testing Physiological Variables using Consumer-Grade Wearable Technology: A Systematic Review and WEAR-BOT Analysis

INTRODUCTION: Wearable technology is a quickly evolving field, and new devices with new features to measure/estimate physiological variables are being released constantly. Despite their use, the validity of the devices are largely unknown to the users or researchers, and the quality of the studies that do test validity and reliability vary widely. PURPOSE: Therefore, the purpose of this systematic review was to review the current validity and reliability literature concerning consumer-grade wearable technology measurements/estimates of physiological variables during exercise. Additionally, we sought to perform risk of bias assessments utilizing the novel WEArable technology Risk of Bias and Objectivity Tool (WEAR-BOT). METHODS: This review was conducted following PRISMA guidelines, searching 3 databases: Google Scholar, Scopus, and SPORTDiscus. After screening, 46 papers were identified that met the pre-determined criteria. Then data was extracted and risk of bias assessment performed by independent researchers. Descriptive statistics, weighted averages of mean absolute percentage error (MAPE) and Pearson correlations were calculated. Sample size statistics were performed utilizing the lower 95% confidence interval of the weighted correlation average. RESULTS: Of the 46 papers reviewed, 44 performed validity testing, while 9 performed reliability. The weighted average for MAPE was 12.48% for heart rate (HR) and 30.70% for energy expenditure (EE). The weighted average for Pearson correlations was 0.737 for HR and 0.672 for EE. Risk of bias assessment of validity studies resulted in 30/44 studies being classified as having a “High Risk of Bias”, and 14/44 having “Some Risk of Bias”. None had a “Low Risk of Bias”, according to the novel WEAR-BOT. For reliability studies, 7/9 were classified as “High Risk of Bias”, 2 as “Some Risk of Bias”, and 0 as “Low Risk of Bias”. CONCLUSION: The risk of bias assessment and descriptive statistics paint a troubling picture of the overall state of validity and reliability studies. Statistical analyses, methods, and reporting vary excessively. This review and associated WEAR-BOT analysis can be used by researchers to help standardize methodology, analytics, and reporting of validation and reliability studies of consumer-grade wearable technology

Chronotype and Social Jetlag Influence Performance and Injury during Reserve Officers’ Training Corps Physical Training

Sleep and circadian rhythms are critically important for optimal physical performance and maintaining health during training. Chronotype and altered sleep may modulate the response to exercise training, especially when performed at specific times/days, which may contribute to musculoskeletal injury. The purpose of this study was to determine if cadet characteristics (chronotype, sleep duration, and social jetlag) were associated with injury incidence and inflammation during physical training. Reserve Officers’ Training Corps (ROTC) cadets (n = 42) completed the Morningness/Eveningness Questionnaire to determine chronotype, and 1-week sleep logs to determine sleep duration and social jetlag. Salivary IL-6 was measured before and after the first and fourth exercise sessions during training. Prospective injury incidence was monitored over 14 weeks of training, and Army Physical Fitness Test scores were recorded at the conclusion. Chronotype, sleep duration, and social jetlag were assessed as independent factors impacting IL-6, injury incidence, and APFT scores using ANOVAs, chi-squared tests, and the t-test where appropriate, with significance accepted at p \u3c 0.05. Evening chronotypes performed worse on the APFT (evening = 103.8 ± 59.8 vs. intermediate = 221.9 ± 40.3 vs. morning = 216.6 ± 43.6; p \u3c 0.05), with no difference in injury incidence. Sleep duration did not significantly impact APFT score or injury incidence. Social jetlag was significantly higher in injured vs. uninjured cadets (2:40 ± 1:03 vs. 1:32 ± 55, p \u3c 0.05). Exercise increased salivary IL-6, with no significant effects of chronotype, sleep duration, or social jetlag. Evening chronotypes and cadets with social jetlag display hampered performance during morning APFT. Social jetlag may be a behavioral biomarker for musculoskeletal injury risk, which requires further investigation

The Effects of Sitting and Walking in Green Space on State Mindfulness and Connectedness to Nature

People report feeling connected to nature while spending time in green space. The modulators of this relationship are unclear. One modulator may be state mindfulness, which is how mindful someone is in a specific moment. The first step of studying state mindfulness as a potential modulator is describing how state mindfulness and connectedness to nature respond to acute exposure to green space. PURPOSE: This study aimed to determine whether sitting and walking in green space change state mindfulness and connectedness to nature in tandem. METHODS: Participants arrived at one of two green spaces: the Thunderbird Gardens Trailhead in Cedar City, UT, or the Clark County Wetlands Park in Las Vegas, NV. After giving verbal and written consent, the participants completed the State Mindfulness Scale (SMS) and Love and Care of Nature Scale (LCN). The participants then sat alone and undisturbed for 10 minutes near the trailhead and completed the SMS and LCN again. Next, the participants walked alone for 10 minutes on the trail and completed the SMS and LCN once more. The SMS and LCN scores were compared among pre-sit, post-sit, and post-walk via two separate one-way repeated-measures ANOVAs. Population effect sizes were estimated as partial omega squared (ωp2; large effect \u3e 0.14). After each ANOVA, the post hoc pairwise comparisons were dependent-samples t-tests with Bonferroni adjustments. The α-level was 0.05 for all the statistical analyses. RESULTS: Forty-two participants completed the study (22 females, 20 males, 0 intersex; 4 African American/Black, 4 Asian, 19 Caucasian/White, 9 Hispanic/Latino, 1 Mediterranean, 1 Middle Eastern, 3 Multi-Racial, 1 Polynesian; 26 ± 9 years, 170 ± 9 cm, 69 ± 16 kg, 24 ± 4 kg/m2). The SMS scores significantly increased from pre-sit to post-sit (+29 arbitrary units [AU], 95% CI: 20, 38; p \u3c 0.001) but not from post-sit to post-walk (p = 0.23). The LCN scores significantly increased from pre-sit to post-sit (+5 AU, 95% CI: 2, 8; p = 0.003) and from post-sit to post-walk (+4 AU, 95% CI: 1, 6; p = 0.002). CONCLUSION: Sitting for 10 minutes in green space increases state mindfulness and connectedness to nature. Walking for 10 minutes further increases connectedness to nature but not state mindfulness. The next step is determining whether state mindfulness predicts connectedness to nature while in green space

Repetition Count Concurrent Validity of Various Garmin Wrist Watches During Light Circuit Resistance Training

Wearable technology and strength training with free weights are two of the top 5 fitness trends worldwide. However, minimal physiological research has been conducted on the two together and none have measured the accuracy of devices measuring repetition counts across exercises. PURPOSE: The purpose of this study was to determine the concurrent validity of four wrist-worn Garmin devices, Instinct (x2), Fenix 6 Pro, and Vivoactive 3, to record repetition counts while performing 4 different exercises during circuit resistance training. METHODS: Twenty participants (n=10 female, n=10 male; age: 23.2 ± 7.7 years) completed this study. Participants completed 4 circuits of 4 exercises (front squat, reverse lunge, push-ups, and shoulder press) using dumbbells at a light intensity with 1 set of 10 repetitions per exercise and 30 seconds rest between exercises and 1-1.5 min rest between circuits. Mean absolute percent error (MAPE, ≤10%) and Lin’s Concordance Coefficient (CCC, ρ≥0.7) were used to validate the device’s repetitions counts in all exercises compared to the criterion reference manual count. Dependent T-tests determined differences (p≤0.05). RESULTS: No devices were considered valid (meeting both the threshold for MAPE and CCC) for measuring repetition counts during front squats (MAPE range: 3.0-18.5% and CCC range: 0.27-0.68, p value range: 0.00-0.94), reverse lunge (MAPE range: 44.5-67.0% and CCC range: 0.19-0.31, p value range: 0.00-0.28), push-ups (MAPE range: 12.5-67.5% and CCC range: 0.10-0.34, p value range: 0.07-0.83), and shoulder press (MAPE range: 18.0-51.0% and CCC range: 0.11-0.43, p value range: 0.00-0.79) exercises. CONCLUSION: The wearable wrist-worn devices were not considered accurate for repetition counts and thus manual counting should be utilized. People who strength train using free weights will need to wait for either improved repetition counting algorithms or increased sensitivity of devices before this measure can be obtained with confidence

Heart Rate and Energy Expenditure Concurrent Validity of Identical Garmin Wrist Watches During Moderately Heavy Resistance Training

Consistent with previous years, ACSM has found that wearable technology and resistance training (RT) are two of the top 5 fitness trends in 2023. Our lab recently found that wrist-worn devices, such as Garmin Instinct, are neither valid nor reliable at measuring average or maximal heart rate (HR) or estimating energy expenditure (EE) following light intensity circuit RT. We postulated that the errors may have been due to the device’s algorithms assuming higher intensity during RT. PURPOSE: The purpose of this study was to determine the concurrent validity of identical Garmin Instinct wrist-watches to record valid measures of average and maximal HR as well as estimated EE following moderately heavy RT. METHODS: Twenty-one adult participants completed this study (n=10 female, n=11 male). Two Garmin Instinct wrist-watches were evaluated, along with the Polar H10 chest strap and Cosmed K5 portable metabolic unit as the criterion devices for average/maximal HR and EE, respectively. Participants completed 8 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (4 sets) and moderately heavy (4 sets) intensity with 1 superset of 6 repetitions per exercise (12 repetitions per superset) and 1 min rest between supersets. Data were analyzed for validity (Mean Absolute Percent Error [MAPE] and Lin’s Concordance Coefficient [CCC]), with predetermined thresholds of MAPE\u3c10% and CCC\u3e0.70. A one-way repeated measures ANOVA with Sidak post-hoc test was used to determine differences (p\u3c0.05). RESULTS: The identical Garmin Instinct devices were not considered valid for average HR (MAPE range: 36.5-81.6%; CCC range: 0.07-0.18), maximal HR (MAPE range: 18.6-18.8%; CCC range: 0.15-0.31), or estimated EE (MAPE range: 14.0-16.4%; CCC range: 0.08-0.32) compared to the criterion references. The devices were significantly different than each other for average HR (p=0.005), maximal HR (p\u3c0.001), and estimated EE (p\u3c0.0001). CONCLUSION: The wearable wrist-worn devices tested herein should not be utilized for accurate measurements of HR or EE during RT, and there are even differences between identical devices. People who RT while using these devices should do so with caution if wishing to utilize them for physiological measures

Rating of Perceived Exertion, Average Heart Rate, and Energy Expenditure Following Indoor and Outdoor Moderately Heavy Superset Resistance Training

Our lab recently found that light intensity circuit resistance training outdoors had a significantly lower perception of effort (RPE) compared to indoor resistance training, despite no physiological differences in heart rate and energy expenditure. However, no study has examined other intensities or set schemes in differing environmental settings. PURPOSE: To determine how indoor or outdoor environments effect rating of perceived exertion (RPE) following light and moderately heavy intensity superset resistance training in recreationally resistance trained adults. METHODS: Twenty-three adult participants completed this study (n=10 female, n=13 male; age: 26.1±8.8 yrs; height: 172.2±9.5 cm; mass: 73.4±18.7 kg; RT experience: 5.3±4.8 yrs). Participants wore devices to measure heart rate (Polar H10 chest strap) and energy expenditure (Cosmed K5 Portable Metabolic Cart). Randomly in indoor and outdoor settings, participants completed 4 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (2 sets) and moderately heavy (2 sets) intensity with 1 superset of 6 repetitions per exercise (12 repetitions per superset) and 1 min rest between supersets. The OMNI Rating of Perceived Exertion Scale for Resistance Exercise 0-10 RPE scale was used following each superset. A paired T-test was used to determine differences between environmental setting (pRESULTS: No significant differences were observed between indoor and outdoor environments for average heart rate (129.4±17.2 and 127.8±23.3 bpm, p=0.67), energy expenditure (30.6±11.5 and 28.3±9.9 kcals; p=0.06), as well as RPE during light intensity (2.9±0.9 and 2.9±0.8 arbitrary units/AU’s, p=0.70) and moderately heavy intensity (6.5±1.7 and 6.3±1.5 AU’s, p=0.27) supersets. CONCLUSION: In recreationally resistance trained adults, light intensity and moderately heavy intensity superset resistance training in indoor or outdoor settings does not alter heart rate, energy expenditure, or perceived effort

Perceived Fatigue and Physical Activity Enjoyment Following Indoor and Outdoor Moderately Heavy Superset Resistance Training

ACSM has again determined that resistance training (RT) and outdoor activities are two of the top ten worldwide fitness trends for 2023. We previously found that RT outdoors had a significantly lower perception of effort (RPE) compared to indoor RT, despite no physiological differences in heart rate (HR) and energy expenditure (EE). However, no study has examined other feelings during RT in indoor or outdoor settings. PURPOSE: To determine how indoor or outdoor environments effect perceptions of fatigue and physical activity enjoyment following RT in recreationally resistance trained adults. METHODS: Twenty-three adult participants (n=10 female, n=13 male) completed this study. The Visual Analog Scale Fatigue (VAS-F) measured perceived fatigue and the Physical Activity Enjoyment Scale – Short Version (PACES-S) measured PA enjoyment, and both were measured at baseline and then immediately following an acute session of indoor or outdoor RT. HR was obtained from a chest strap (Polar H10) and EE from a Portable Metabolic Cart (COSMED K5). Randomly in indoor and outdoor settings, participants completed 4 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (2 sets) and moderately heavy (2 sets) intensity with 1 superset of 6 repetitions per exercise and 1 min rest between supersets. A paired T-test (for HR & EE comparisons) or one-way repeated measures ANOVA with Sidak post-hoc test (for VAS-F & PACES-S comparisons) were used to determine differences (p\u3c0.05). RESULTS: No significant differences were observed between indoor and outdoor RT for the physiological variables of average HR (129.4±17.2 and 127.75±23.3 bpm, respectively, p=0.66) and EE (30.6±11.5 and 28.3±9.9 kcals, respectively, p=0.06). Perceived fatigue significantly (p\u3c0.0001) increased from baseline (1.13±0.94 arbitrary units, AU’s) following indoor (4.54±1.91 AU’s) and outdoor (3.99±1.54 AU’s) RT, but no environmental differences (p=0.36) were observed. PA enjoyment was not significantly (p range: 0.27-0.93) different between baseline (18.73±1.83 AU’s) and following indoor (18.18±1.99 AU’s) or outdoor (18.36±1.99 AU’s) RT. CONCLUSION: In recreationally resistance trained adults, moderately heavy superset RT in indoor or outdoor settings does not alter perceived fatigue or physical activity enjoyment

Concurrent Validity and Reliability of Average Heart Rate and Energy Expenditure of Identical Garmin Instinct Watches During Low Intensity Resistance Training

ABSTRACT Wearable technology and resistance training are two of the top five worldwide fitness trends for 2022 as determined by ACSM. Many devices, such as Garmin’s Instinct, have functions to track various physiological aspects during resistance training. However, to our knowledge, independent verification of the validity and reliability of these devices for estimating average heart rate (HR) and energy expenditure (EE) during resistance training are nonexistent. PURPOSE: To determine the concurrent validity and reliability of identical Garmin Instinct watches during resistance training. METHODS: Twenty subjects (n=10 female and male; age: 23.2±7.7 years; height: 169.7±11.1; weight: 76.3±15.7 kg) completed this study. Two Garmin Instinct watches were evaluated, along with the Polar H10 chest strap and Cosmed K5 portable metabolic unit as the criterion devices for average HR and EE, respectively. Subjects completed 4 circuits of 4 exercises (front squat, reverse lunge, push-ups, and shoulder press) using dumbbells at a light intensity with 1 set of 10 repetitions per exercise, 30 seconds rest between exercises, and 1-1.5 min. rest between circuits. Data were analyzed for validity (Mean Absolute Percent Error [MAPE] and Lin’s Concordance Coefficient [CCC]) and reliability (Coefficient of Variation [CV]), with predetermined thresholds of MAPE0.70, and CVRESULTS: Garmin Instinct 1 and Instinct 2 were significantly (

Average Heart Rate and Energy Expenditure Validity of Garmin Vivoactive 3 and Fenix 6 Wrist Watches During Light Circuit Resistance Training

Our laboratory recently found wrist-worn wearable technology devices to be valid for measuring average heart rate (HR), but not valid for estimated energy expenditure (EE) compared to criterion devices, during steady state aerobic training (walking, running, biking). However, the validity of wrist-worn devices for HR and EE measures during resistance training is largely unknown. PURPOSE: The purpose of this study was to determine if two wrist-worn devices, Garmin Vivoactive 3 and Garmin Fenix 6 Pro, record valid measures of average HR and EE while performing circuit resistance training. METHODS: Twenty participants (n=10 female, n=10 male; age: 23.2 ± 7.7 years) completed this study. The Garmin Vivoactive 3 and Garmin Fenix 6 Pro were tested along with the Polar H10 chest strap and Cosmed K5 portable metabolic unit as the criterions for average HR and EE, respectively. Participants completed 4 circuits of 4 exercises (front squat, reverse lunge, push-ups, and shoulder press) using dumbbells at a light intensity with 1 set of 10 repetitions per exercise and 30 seconds rest between exercises and 1-1.5 min. rest between circuits. Mean absolute percent error (MAPE, ≤10%) and Lin’s Concordance (ρ≥0.7) were used to validate the device’s average HR (in bpm) and estimated EE (in kcals) compared to criterion reference devices. Dependent T-tests determined differences (p≤0.05). RESULTS: Average HR for Garmin Vivoactive 3 and Fenix 6 Pro were significantly different (p\u3c0.01) than the Polar H10 (115.0±23.9 and 124.5±15.4 vs 128.9±19.0 bpm, respectively), and were not considered valid (MAPE: 44.8% and 25.1%; Lin’s Concordance: 0.50 and 0.63, respectively). Estimated EE for Garmin Vivoactive 3 and Fenix 6 Pro were significantly different (p\u3c0.0001) than the Cosmed K5 (31.7±12.3 and 39.7±13.1 vs 20.3±5.5 kcals, respectively), and were not considered valid (MAPE: 309.7% and 322.1%; Lin’s Concordance: 0.04 and 0.15, respectively). CONCLUSION: Anyone involved in any resistance training aspect should be aware of the limitations of these wrist-worn devices in measuring average HR or EE