Time-Course of Changes in Inflammatory Response after Whole-Body Cryotherapy Multi Exposures following Severe Exercise

The objectives of the present investigation was to analyze the effect of two different recovery modalities on classical markers of exercise-induced muscle damage (EIMD) and inflammation obtained after a simulated trail running race. Endurance trained males (n = 11) completed two experimental trials separated by 1 month in a randomized crossover design; one trial involved passive recovery (PAS), the other a specific whole body cryotherapy (WBC) for 96 h post-exercise (repeated each day). For each trial, subjects performed a 48 min running treadmill exercise followed by PAS or WBC. The Interleukin (IL) -1 (IL-1), IL-6, IL-10, tumor necrosis factor alpha (TNF-α), protein C-reactive (CRP) and white blood cells count were measured at rest, immediately post-exercise, and at 24, 48, 72, 96 h in post-exercise recovery. A significant time effect was observed to characterize an inflammatory state (Pre vs. Post) following the exercise bout in all conditions (p<0.05). Indeed, IL-1β (Post 1 h) and CRP (Post 24 h) levels decreased and IL-1ra (Post 1 h) increased following WBC when compared to PAS. In WBC condition (p<0.05), TNF-α, IL-10 and IL-6 remain unchanged compared to PAS condition. Overall, the results indicated that the WBC was effective in reducing the inflammatory process. These results may be explained by vasoconstriction at muscular level, and both the decrease in cytokines activity pro-inflammatory, and increase in cytokines anti-inflammatory

Sustainable energy transition and its demand for scarce resources: insights into the German Energiewende through a new risk assessment framework

In this study, a new framework to analyze resource-demanding projects in regard to their risk of resource scarcity is proposed and exemplary applied on the German energy transition (Energiewende). With the interpretation of a commodity’s price as an economic scarcity indicator, price thresholds are defined, which, once exceeded, determine a commodity to be scarce. The corresponding probability of scarcity is derived via a logistic regression model, given pre-selected price determinants. The combination of this probability of scarcity with the substitutability of a commodity, as well as the scaled demand per project, results in the commodity-specific expected loss due to scarcity, which, aggregated over all commodities, marks the final risk indicator, the expected loss due to scarcity per project. In a case study, the framework is applied to the resource requirements for eight transformation pathways of the German energy system, differing in the climate targets as well as the German societies acceptance for the required actions. The results highlight the general high demand in cobalt, mainly used for energy storage. In combination with a relatively high probability of scarcity, this reveals a potential bottleneck for the German Energiewende