| 1. |
- Correia, Jorge C., et al.
(författare)
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Muscle-secreted neurturin couples myofiber oxidative metabolism and slow motor neuron identity
- 2021
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 33:11, s. 2215-2230
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Tidskriftsartikel (refereegranskat)abstract
- Endurance exercise promotes skeletal muscle vascularization, oxidative metabolism, fiber-type switching, and neuromuscular junction integrity. Importantly, the metabolic and contractile properties of the muscle fiber must be coupled to the identity of the innervating motor neuron (MN). Here, we show that muscle-derived neurturin (NRTN) acts on muscle fibers and MNs to couple their characteristics. Using a muscle-specific NRTN transgenic mouse (HSA-NRTN) and RNA sequencing of MN somas, we observed that retrograde NRTN signaling promotes a shift toward a slow MN identity. In muscle, NRTN increased capillary density and oxidative capacity and induced a transcriptional reprograming favoring fatty acid metabolism over glycolysis. This combination of effects on muscle and MNs makes HSA-NRTN mice lean with remarkable exercise performance and motor coordination. Interestingly, HSA-NRTN mice largely recapitulate the phenotype of mice with muscle-specific expression of its upstream regulator PGC-1a1. This work identifies NRTN as a myokine that couples muscle oxidative capacity to slow MN identity.
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| 2. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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