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VERITAS and Fermi-LAT Observations of TeV Gamma-Ray Sources Discovered by HAWC in the 2HWC Catalog
(2018)
The High Altitude Water Cherenkov (HAWC) collaboration recently published their 2HWC catalog, listing 39 very high energy (VHE; >100 GeV) gamma-ray sources based on 507 days of observation. Among these, 19 sources are not associated with previously known teraelectronvolt (TeV) gamma-ray sources. We have studied 14 of these sources without known counterparts with VERITAS and Fermi-LAT. VERITAS detected weak gamma-ray emission in the 1 TeV-30 TeV band in the region of DA 495, a pulsar wind nebula coinciding with 2HWC J1953+294, confirming the discovery of the source by HAWC. We did not find any counterpart for the selected 14 new HAWC sources from our analysis of Fermi-LAT data for energies higher than 10 GeV. During the search, we detected gigaelectronvolt (GeV) gamma-ray emission coincident with a known TeV pulsar wind nebula, SNR G54.1+0.3 (VER J1930+188), and a 2HWC source, 2HWC J1930+188. The fluxes for isolated, steady sources in the 2HWC catalog are generally in good agreement with those measured by imaging atmospheric Cherenkov telescopes. However, the VERITAS fluxes for SNR G54.1+0.3, DA 495, and TeV J2032+4130 are lower than those measured by HAWC, and several new HAWC sources are not detected by VERITAS. This is likely due to a change in spectral shape, source extension, or the influence of diffuse emission in the source region.
Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10. 30. 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL (P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM (P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose. we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL (P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (similar to 63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.
Purpose Moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) are associated with different adjustments in motor output. Changes in motor unit (MU) peripheral properties may contribute to these adjustments, but this is yet to be elucidated. This study evaluated early changes in MU conduction velocity (MUCV) and MU action potential amplitude after 2 wk of either HIIT or MICT. Methods Sixteen men were assigned to either an MICT group or HIIT group (n = 8 each), and participated in six training sessions over 14 d. HIIT: 8 to 12 x 60-s intervals at 100% peak power output. Moderate-intensity continuous training: 90 to 120 min continuous cycling at similar to 65% VO2peak. Preintervention and postintervention, participants performed maximal voluntary contractions (MVC) and submaximal (10%, 30%, 50%, and 70% of MVC) isometric knee extensions while high-density EMG was recorded from the vastus medialis (VM) and vastus lateralis (VL) muscles. The high-density EMG was decomposed into individual MU by convolutive blind-source separation and tracked preintervention and postintervention. Results Both training interventions induced changes in MUCV, but these changes depended on the type of training (P < 0.001). The HIIT group showed higher values of MUCV after training at all torque levels (P < 0.05), MICT only displayed changes in MUCV at low torque levels (10%-30% MVC, P < 0.002). There were no changes in MU action potential amplitude for either group (P = 0.2). Conclusions Two weeks of HIIT or MICT elicit differential changes in MUCV, likely due to the contrasting load and volume used in such training regimes. This new knowledge on the neuromuscular adaptations to training has implications for exercise prescription.
We investigated the possibility to identify motor units (MUs) with high-density surface electromyography (HDEMG) over experimental sessions in different days. 10 subjects performed submaximal knee extensions across three sessions in three days separated by one week, while EMG was recorded from the vastus medialis muscle with high-density electrode grids. The shapes of the MU action potentials (MUAPs) over multiple channels extracted from HDEMG decomposition were matched across sessions by cross-correlation. Forty and twenty percent of the MUs decomposed could be tracked across two and three sessions, respectively (average cross correlation 0.85 +/- 0.04). The estimated properties of the matched motor units were similar across the sessions. For example, mean discharge rate and recruitment thresholds were measured with an intra-class correlation coefficient (ICCs) > 0.80. These results strongly suggest that the same MUs were indeed identified across sessions. This possibility will allow monitoring changes in MU properties following interventions or during the progression of neuromuscular disorders.
Purpose Using a novel technique of high-density surface EMG decomposition and motor unit (MU) tracking, we compared changes in the properties of vastus medialis and vastus lateralis MU after endurance (END) and high-intensity interval training (HIIT). Methods Sixteen men were assigned to the END or the HIIT group (n = 8 each) and performed six training sessions for 14 d. Each session consisted of 8-12 x 60-s intervals at 100% peak power output separated by 75 s of recovery (HIIT) or 90-120 min continuous cycling at similar to 65% VO2peak (END). Pre- and postintervention, participants performed 1) incremental cycling to determine VO2peak and peak power output and 2) maximal, submaximal (10%, 30%, 50%, and 70% maximum voluntary contraction [MVC]), and sustained (until task failure at 30% MVC) isometric knee extensions while high-density surface EMG signals were recorded from the vastus medialis and vastus lateralis. EMG signals were decomposed (submaximal contractions) into individual MU by convolutive blind source separation. Finally, MU were tracked across sessions by semiblind source separation. Results After training, END and HIIT improved VO2peak similarly (by 5.0% and 6.7%, respectively). The HIIT group showed enhanced maximal knee extension torque by similar to 7% (P = 0.02) and was accompanied by an increase in discharge rate for high-threshold MU (50% knee extension MVC) (P < 0.05). By contrast, the END group increased their time to task failure by similar to 17% but showed no change in MU discharge rates (P > 0.05). Conclusions HIIT and END induce different adjustments in MU discharge rate despite similar improvements in cardiopulmonary fitness. Moreover, the changes induced by HIIT are specific for high-threshold MU. For the first time, we show that HIIT and END induce specific neuromuscular adaptations, possibly related to differences in exercise load intensity and training volume.