1,241 research outputs found

    The Massive Progenitor of the Type II-Linear Supernova 2009kr

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    We present early-time photometric and spectroscopic observations of supernova (SN) 2009kr in NGC 1832. We find that its properties to date support its classification as Type II-linear (SN II-L), a relatively rare subclass of core-collapse supernovae (SNe). We have also identified a candidate for the SN progenitor star through comparison of pre-explosion, archival images taken with WFPC2 on board the Hubble Space Telescope with SN images obtained using adaptive optics plus NIRC2 on the 10 m Keck-II telescope. Although the host galaxy's substantial distance (similar to 26 Mpc) results in large uncertainties in the relative astrometry, we find that if this candidate is indeed the progenitor, it is a highly luminous (M(V)(0) = -7.8 mag) yellow supergiant with initial mass similar to 18-24 M(circle dot). This would be the first time that an SN II-L progenitor has been directly identified. Its mass may be a bridge between the upper initial mass limit for the more common Type II-plateau SNe and the inferred initial mass estimate for one Type II-narrow SN.Hungarian OTKA K76816NSF AST-0707769, AST-0908886Sylvia & Jim Katzman FoundationTABASGO FoundationNASA through STScI AR-11248, GO-10877Harvard UniversityUC BerkeleyUniversity of VirginiaNASA/Swift NNX09AQ66GDOEAstronom

    Assessing the Reliability of Stryd 27 for Variable Speed Running

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    Wearable technology is beneficial when it comes to tracking and optimizing performance. The Stryd 27 is a wearable footpod marketed as being more responsive in measuring power during running than the previous version (Stryd 25). However, the reliability of this newer device to return consistent values has not been determined. PURPOSE: This study aimed to observe whether Stryd 27 gives reliable metrics during variable speed running. METHODS: Sixteen participants (N = 16; 50% female; height = 174.1 ± 8.1 cm; mass = 73.0 ± 12.4 kg) were recruited, each equipped with two Stryd 27 footpods (updated to the same software version) affixed to the shoelaces of their running shoes. The researchers recorded data using the Stryd app on a mobile device that was connected to the Stryd 27 via Bluetooth. Recording on both devices were started and stopped at the same time. Each participant completed two, 10-minute runs on an indoor track. The initial run was used to establish a baseline. Following a 5-minute rest period, participants proceeded with the second run, during which they alternated between faster and slower intervals. The pace for these intervals was set to be 20% faster and 20% slower than what each participant’s average pace was during the first run. Reliability of power, cadence, form power, ground contact time (GCT), vertical oscillation (VO), leg spring stiffness (LSS), and stride length during the interval run was determined using coefficient of variation (CV) and intraclass correlation coefficient (ICC), with CV0.70 (p \u3c 0.05) being considered evidence of reliability. RESULTS: Reliability data are shown in Table 1. The following measures were found to be reliable: power, cadence, form power, GCC, and VO. The measures of LSS and stride length were not found to be reliable. CONCLUSION: Runners using the new Stryd 27 can have confidence that most measures return reliable values (power, cadence, form power, GCT, and VO). Unfortunately, two measures were observed to not meet the threshold for reliability (LSS and stride length). Athletes interested in these measures should be cautious when interpreting their data

    The Effectiveness of Running Power as a Metric of Exercise Intensity During Running Interval Training

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    Wearable power meters are increasingly popular among runners with Coros and Stryd offering running power as a real-time, trackable of a metric. PURPOSE: This study compared running power (RP) to physiological measures, heart rate (HR) and oxygen consumption (VO2), across high and low intensity running intervals. METHODS: Thirteen adult participants (n = 6 male; height = 174.9 ± 6.9 cm; mass = 72.5 ± 12.0 kg) were equipped with a Stryd 27 RP meter, a Polar H10 HR monitor, and a Cosmed K5 portable metabolic unit. Participants’ self-selected RP was obtained during a 10-min run on an indoor track (10 laps/mile). After resting for five minutes, participants ran another 10 min, alternating between equal intervals of RP 20% higher and 20% lower than self-selected RP: 120 s × 2, 60 s × 2, 30 s × 4, and 15 s × 8. All devices were started simultaneously before each run. RP (W/kg) was sampled at 1 Hz. HR (bpm) and VO2 (mL/kg/min) were sampled at 0.1 Hz throughout the interval run. Data were analyzed from the 60 s mark through the end of the run. HR and VO2 data were interpolated to 1 Hz, and cross correlations (max lag = 60 s) were used to compare RP, HR, and VO2 (mean values in Table 1). RESULTS: There were weak to moderate correlations between RP and VO2 (r = 0.351; lag = -29.1 s), RP and HR (r = 0.475; lag = 9.38 s), and HR and VO2 (r = 0.572; lag = -29.1 s; Table 2). CONCLUSION: HR showed the strongest correlation and smallest time delay with RP. This may be practically useful because HR data is more readily available to runners than VO2. However, the correlation is only moderate. While related, the three metrics of running intensity are fundamentally different. When exercising at a moderate intensity, changes in HR or VO2, which take seconds to minutes to stabilize, may be less evident than changes in mechanical power, which are immediate. Thus, it is possible that HR and VO2 would show a stronger relationship with RP across intervals longer than the 120 s maximum observed here. While RP can be a useful metric, it may not be informative about physiological responses to running especially over short intervals or when running at high intensity

    Stryd 25 vs. Stryd 27: Comparing Running Metrics Between a Predecessor and “The Next Gen Stryd”

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    Wearable technology has claimed the top spot in the Worldwide Survey of Fitness Trends in all but two years since 2016. A popular wearable among runners is the Stryd power meter. The company markets its latest model, the Stryd 27, as 5x more responsive in measuring running power. Yet, it is unclear whether the new model performs differently than its predecessor. PURPOSE: This study aimed to compare running metrics of the Stryd 25 and Stryd 27 in self-paced and interval runs. METHODS: Participants consented (N = 16; 50% female; height = 174.1 ± 8.1 centimeters [cm]; mass = 73.0 ± 12.4 kilograms) and were equipped with the Stryd 25 and Stryd 27, attached randomly to the left and right shoelaces. Each Stryd was paired with a separate mobile device using the Stryd app. Researchers started and stopped recording on each Stryd simultaneously. Participants ran for 10 minutes at a self-selected pace counterclockwise around an indoor track (10 laps/mile) before resting for five minutes. Then participants ran 10 more minutes, alternating between fast and slow intervals: 120 seconds (s) × 2, 60 s × 2, 30 s × 4, and 15 s × 8. Fast and slow intervals were 20% faster and 20% slower, respectively, than the participant’s mean pace of the first run. The Stryd app recorded power in watts (W), cadence in steps per minute (spm), vertical oscillation (VO) in cm, and stride length in meters (m). Four independent t-tests were run to compare these measurements between the two Stryd models for the self-paced and interval runs. The alpha level was .05, and the effect size was Cohen’s d (0.2 small, 0.5 medium, 0.8 large). RESULTS: See Table 1. CONCLUSION: Four running metrics were statistically similar between the Stryd 25 and Stryd 27 during two indoor runs. Runners using the predecessor indoors can be confident it returns similar data to the newest model

    Evaluation of Average and Maximum Heart Rate of Wrist-worn Wearable Technology Devices During Trail Running

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    It has been estimated that there are 20 million people who participate in trail running, and these numbers are expected to increase by 15% each year. Our laboratory group has conducted studies on the validity of wearable technology watches and heart rate (HR) during trail running. The previous generation devices were mostly inaccurate, and a limitation was that reliability was not measured. PURPOSE: To determine both validity and reliability in newer models of wearable devices during trail running. METHODS: Seventeen participants (F = 7) ran on the Thunderbird Gardens Lightning Switch trail in Cedar City, UT. Demographic characteristics: Age = 25 (9) years (mean [standard deviation]), ht = 168 (9) cm, mass = 72 (14) kg. Two Garmin Instincts and two Polar Vantage M2s were evaluated, along with the Polar H10 chest strap as the criterion measure. Participants ran out on the trail for 10-minutes, and then returned to the trailhead. Maximum HR and average HR were measured during the run. Data were analyzed for validity (Mean Absolute Percent Error [MAPE] and Lin’s Concordance [CCC]) and reliability (Coefficient of Variation [CV] and Intraclass Correlation Coefficient [ICC]). Predetermined thresholds were: MAPE0.70, CV0.70. RESULTS: The Garmin Instinct met the threshold for both reliability tests for average and maximum HR (see table). The Garmin Instinct and Polar Vantage met the threshold for both validity tests for maximum HR. CONCLUSION: In order for a device to be considered valid, it must meet the predetermined thresholds for both validity and reliability. These results indicate that only the Garmin Instinct is valid and reliable, but only for measuring maximum HR. This is challenging for those who wish to track their HR while trail running, because neither of the studied devices were valid and reliable for maximum and average HR

    Early Growth Response Gene 1–mediated Apoptosis Is Essential for Transforming Growth Factor β1–induced Pulmonary Fibrosis

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    Fibrosis and apoptosis are juxtaposed in pulmonary disorders such as asthma and the interstitial diseases, and transforming growth factor (TGF)-β1 has been implicated in the pathogenesis of these responses. However, the in vivo effector functions of TGF-β1 in the lung and its roles in the pathogenesis of these responses are not completely understood. In addition, the relationships between apoptosis and other TGF-β1–induced responses have not been defined. To address these issues, we targeted bioactive TGF-β1 to the murine lung using a novel externally regulatable, triple transgenic system. TGF-β1 produced a transient wave of epithelial apoptosis that was followed by mononuclear-rich inflammation, tissue fibrosis, myofibroblast and myocyte hyperplasia, and septal rupture with honeycombing. Studies of these mice highlighted the reversibility of this fibrotic response. They also demonstrated that a null mutation of early growth response gene (Egr)-1 or caspase inhibition blocked TGF-β1–induced apoptosis. Interestingly, both interventions markedly ameliorated TGF-β1–induced fibrosis and alveolar remodeling. These studies illustrate the complex effects of TGF-β1 in vivo and define the critical role of Egr-1 in the TGF-β1 phenotype. They also demonstrate that Egr-1–mediated apoptosis is a prerequisite for TGF-β1–induced fibrosis and remodeling

    Leptin signaling in Kiss1 neurons arises after pubertal development

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    The adipocyte-derived hormone leptin is required for normal pubertal maturation in mice and humans and, therefore, leptin has been recognized as a crucial metabolic cue linking energy stores and the onset of puberty. Several lines of evidence have suggested that leptin acts via kisspeptin expressing neurons of the arcuate nucleus to exert its effects. Using conditional knockout mice, we have previously demonstrated that deletion of leptin receptors (LepR) from kisspeptin cells cause no puberty or fertility deficits. However, developmental adaptations and system redundancies may have obscured the physiologic relevance of direct leptin signaling in kisspeptin neurons. To overcome these putative effects, we re-expressed endogenous LepR selectively in kisspeptin cells of mice otherwise null for LepR, using the Cre-loxP system. Kiss1-Cre LepR null mice showed no pubertal development and no improvement of the metabolic phenotype, remaining obese, diabetic and infertile. These mice displayed decreased numbers of neurons expressing Kiss1 gene, similar to prepubertal control mice, and an unexpected lack of re-expression of functional LepR. To further assess the temporal coexpression of Kiss1 and Lepr genes, we generated mice with the human renilla green fluorescent protein (hrGFP) driven by Kiss1 regulatory elements and crossed them with mice that express Cre recombinase from the Lepr locus and the R26-tdTomato reporter gene. No coexpression of Kiss1 and LepR was observed in prepubertal mice. Our findings unequivocally demonstrate that kisspeptin neurons are not the direct target of leptin in the onset of puberty. Leptin signaling in kisspeptin neurons arises only after completion of sexual maturation.National Institutes of Health, R01HD061539National Institutes of Health, R01HD69702National Institutes of Health, R01DA024680National Institutes of Health, R01MH085298National Institutes of Health, K01DK087780National Institutes of Health, DK081182-01National Institutes of Health, UL1RR02492
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