Guanidinoacetic Acid Supplementation Promotes Skeletal Muscle Fiber Type Transformation from Fast-to-Slow-Twitch via Increasing the PPARGC1A Based Mitochondrial Function and CaN/NFAT Pathway in Finishing Pigs

Guanidinoacetic acid can improve pork quality. Previous studies have demonstrated that pork quality is closely linked to the muscle fiber type mediated by PPARGC1A. Therefore, this study aimed to evaluate the influence of dietary GAA supplementation on the skeletal muscle fiber type transformation. A total of 180 healthy Duroc × Landrace × Meishan cross castrated male pigs with a similar average weight (90 ± 1.5 kg) were randomly divided into three treatments with five replicates per treatment and 12 pigs per replicate, including a GAA-free basal diet and basal diet with 0.05% or 0.10% GAA for 15 days. Our results showed that 0.10% GAA supplementation increased the contents of Ca2+ in sarcoplasm (p < 0.05). Compared with the control group, both GAA supplementation groups upregulated the expression of Troponin I-ss (p < 0.05), and 0.10% GAA supplementation downregulated the expression of Troponin T3 (p < 0.05). GAA supplementation increased the expression of peroxisome proliferator activated receptor-γ coactivator-1alpha (PPARGC1A) (p < 0.05), and further upregulated the mitochondrial transcription factor A (TFAM), increased the level of membrane potential, and the activities of mitochondrial respiratory chain complex I, III (p < 0.05). The 0.10% GAA supplementation upregulated the protein expression of calcineurin catalytic subunit α (CnAα) and nuclear factor of activated T cells (NFATc1) (p < 0.05). Overall, dietary GAA supplementation promotes skeletal muscle fiber types transformation from fast-to-slow-twitch via increasing the PPARGC1A based mitochondrial function and the activation of CaN/NFAT pathway in finishing pigs.

Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang

Time-series normalized difference vegetation index (NDVI) is commonly used to conduct vegetation dynamics, which is an important research topic. However, few studies have focused on the relationship between vegetation type and NDVI changes. We investigated changes in vegetation in Xinjiang using linear regression of time-series MOD13Q1 NDVI data from 2001 to 2020. MCD12Q1 vegetation type data from 2001 to 2019 were used to analyze transformations among different vegetation types, and the relationship between the transformation of vegetation type and NDVI was analyzed. Approximately 63.29% of the vegetation showed no significant changes. In the vegetation-changed area, approximately 93.88% and 6.12% of the vegetation showed a significant increase and decrease in NDVI, respectively. Approximately 43,382.82 km2 of sparse vegetation and 25,915.44 km2 of grassland were transformed into grassland and cropland, respectively. Moreover, 17.4% of the area with transformed vegetation showed a significant increase in NDVI, whereas 14.61% showed a decrease in NDVI. Furthermore, in areas with NDVI increased, the mean NDVI slopes of pixels in which sparse vegetation transferred to cropland, sparse vegetation transferred to grassland, and grassland transferred to cropland were 9.8 and 3.2 times that of sparse vegetation, and 1.97 times that of grassland, respectively. In areas with decreased NDVI, the mean NDVI slopes of pixels in which cropland transferred to sparse vegetation, grassland transferred to sparse vegetation were 1.75 and 1.36 times that of sparse vegetation, respectively. The combination of vegetation type transformation NDVI time-series can assist in comprehensively understanding the vegetation change characteristics.