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Peroxisome proliferator-activated receptor γ (PPARγ) is expressed at low levels in skeletal muscle, where it protects against adiposity and insulin resistance via unclear mechanisms. To test the hypothesis that PPARγ directly modulates skeletal muscle metabolism, we created two models that isolate direct PPARγ actions on skeletal myocytes. PPARγ was overexpressed in murine myotubes by adenotransfection and in mouse skeletal muscle by plasmid electroporation. In cultured myotubes, PPARγ action increased fatty acid uptake and incorporation into myocellular lipids, dependent upon a 154 ± 20-fold up-regulation of CD36 expression. PPARγ overexpression more than doubled insulin-stimulated thymoma viral proto-oncogene (AKT) phosphorylation during low lipid availability. Furthermore, in myotubes exposed to palmitate levels that inhibit insulin signaling, PPARγ overexpression increased insulin-stimulated AKT phosphorylation and glycogen synthesis over 3-fold despite simultaneously increasing myocellular palmitate uptake. The insulin signaling enhancement was associated with an increase in activating phosphorylation of phosphoinositide-dependent protein kinase 1 and a normalized expression of palmitate-induced genes that antagonize AKT phosphorylation. In vivo, PPARγ overexpression more than doubled insulin-dependent AKT phosphorylation in lipid-treated mice but did not augment insulin-stimulated glucose uptake. We conclude that direct PPARγ action promotes myocellular storage of energy by increasing fatty acid uptake and esterification while simultaneously enhancing insulin signaling and glycogen formation. However, direct PPARγ action in skeletal muscle is not sufficient to account for the hypoglycemic actions of PPARγ agonists during lipotoxicity.

Accurate assessment of burn severity is a critical need for an improved understanding of fire behavior and ecology and effective post-fire management. Although NASA Landsat satellites have a long history of use for remotely sensed mapping of burn severity, the recently launched (2015 and 2017) European Space Agency Sentinel-2 satellite constellation offers increased temporal and spatial resolution with global coverage, combined with free data access. Evaluations of burn severity derived from Landsat and Sentinel generally show comparable results, but these studies only assessed a small number of fires with limited field data. We used 912 ground calibration plots from 26 fires that burned between 2016 and 2019 in western North America to compare Sentinel- and Landsat-derived burn severity estimates with the field-based composite burn index. We mapped burn severity using two methods; the well-established paired scene approach, in which a single pre- and post-fire scene are selected for each fire, and also a mean image compositing approach that automatically integrates multiple scenes using the cloud-based remote sensing platform Google Earth Engine. We found that Sentinel generally performed as well or better than Landsat for four spectral indices of burn severity, particularly when using atmospherically corrected Sentinel imagery. Additionally, we tested the effects of mapping burn severity at Sentinel’s finer spatial resolution (10 m) on estimates of the spatial complexity of stand-replacing fire, resulting in a 5% average reduction per-fire in area mapped as high-severity patch interiors (24,273 ha total) compared to mapping at the resolution of Landsat (30 m). These findings suggest Sentinel may improve ecological discrimination of fine-scale fire effects, but also warrant caution when comparing estimates of burn severity spatial patterns derived at different resolutions. Overall, these results indicate that burn severity mapping will benefit substantially from the integration of Sentinel imagery through increased imagery availability, and that Sentinel’s higher spatial resolution improves opportunities for examining finer-scale fire effects across ecosystems.

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