Impact of resistance exercise on ribosome biogenesis is acutely regulated by post-exercise recovery strategies

Muscle hypertrophy occurs following increased protein synthesis, which requires activation of the ribosomal complex. Additionally, increased translational capacity via elevated ribosomal RNA (rRNA) synthesis has also been implicated in resistance training-induced skeletal muscle hypertrophy. The time course of ribosome biogenesis following resistance exercise (RE) and the impact exerted by differing recovery strategies remains unknown. In the present study, the activation of transcriptional regulators, the expression levels of pre-rRNA, and mature rRNA components were measured through 48 h after a single-bout RE. In addition, the effects of either low-intensity cycling (active recovery, ACT) or a cold-water immersion (CWI) recovery strategy were compared. Nine male subjects performed two bouts of high-load RE randomized to be followed by 10 min of either ACT or CWI. Muscle biopsies were collected before RE and at 2, 24, and 48 h after RE. RE increased the phosphorylation of the p38-MNK1-eIF4E axis, an effect only evident with ACT recovery. Downstream, cyclin D1 protein, total eIF4E, upstream binding factor 1 (UBF1), and c-Myc proteins were all increased only after RE with ACT. This corresponded with elevated abundance of the pre-rRNAs (45S, ITS-28S, ITS-5.8S, and ETS-18S) from 24 h after RE with ACT. In conclusion, coordinated upstream signaling and activation of transcriptional factors stimulated pre-rRNA expression after RE. CWI, as a recovery strategy, markedly blunted these events, suggesting that suppressed ribosome biogenesis may be one factor contributing to the impaired hypertrophic response observed when CWI is used regularly after exercise.

Optimal production resource reallocation for CO2 emissions reduction in manufacturing sectors

To mitigate the effects of climate change, countries worldwide are advancing technologies to reduce greenhouse gas emissions. This paper proposes and measures optimal production resource reallocation using data envelopment analysis. This research attempts to clarify the effect of optimal production resource reallocation on CO2 emissions reduction, focusing on regional and industrial characteristics. We use finance, energy, and CO2 emissions data from 13 industrial sectors in 39 countries from 1995 to 2009. The resulting emissions reduction potential is 2.54 Gt-CO2 in the year 2009, with former communist countries having the largest potential to reduce CO2 emissions in the manufacturing sectors. In particular, basic material industry including chemical and steel sectors has a lot of potential to reduce CO2 emissions.