'Mitochondrial energy imbalance and lipid peroxidation cause cell death in Friedreich's ataxia'

Friedreich's ataxia (FRDA) is an inherited neurodegenerative disease. The mutation consists of a GAA repeat expansion within the FXN gene, which downregulates frataxin, leading to abnormal mitochondrial iron accumulation, which may in turn cause changes in mitochondrial function. Although, many studies of FRDA patients and mouse models have been conducted in the past two decades, the role of frataxin in mitochondrial pathophysiology remains elusive. Are the mitochondrial abnormalities only a side effect of the increased accumulation of reactive iron, generating oxidative stress? Or does the progressive lack of iron-sulphur clusters (ISCs), induced by reduced frataxin, cause an inhibition of the electron transport chain complexes (CI, II and III) leading to reactive oxygen species escaping from oxidative phosphorylation reactions? To answer these crucial questions, we have characterised the mitochondrial pathophysiology of a group of disease-relevant and readily accessible neurons, cerebellar granule cells, from a validated FRDA mouse model. By using live cell imaging and biochemical techniques we were able to demonstrate that mitochondria are deregulated in neurons from the YG8R FRDA mouse model, causing a decrease in mitochondrial membrane potential (▵Ψm) due to an inhibition of Complex I, which is partially compensated by an overactivation of Complex II. This complex activity imbalance leads to ROS generation in both mitochondrial matrix and cytosol, which results in glutathione depletion and increased lipid peroxidation. Preventing this increase in lipid peroxidation, in neurons, protects against in cell death. This work describes the pathophysiological properties of the mitochondria in neurons from a FRDA mouse model and shows that lipid peroxidation could be an important target for novel therapeutic strategies in FRDA, which still lacks a cure

Assessing the Acceptability of Climate Policy From Three Perspectives: Policy-Specific Beliefs, Policy Characteristics, and Individual Characteristics

To meet the goals of the Paris Climate Agreement, effective climate policies need to be implemented. However, climate policies are often not implemented due to low (expected) acceptability among citizens. To gain insight into acceptability levels of various policy types, we examined how individual characteristics (personal values and concern about climate change), policy-specific beliefs (perceived effectiveness and fairness) and policy characteristics (e.g., communicative, financial, and legal) affect the acceptability of climate policies. A representative sample of the Dutch population (n = 1,536) completed an online questionnaire containing 18 climate policy measures. Results showed that perceived fairness and effectiveness were the main predictors of policy acceptability. Concern about climate change and personal values were of lesser importance. Communicative policies were evaluated as the most acceptable, most effective, and among the fairest policies, while financial policies were perceived as somewhat acceptable and fair and were also among the most effective policies. Legislative policies received the lowest scores on all ratings. Further, participants perceived punishing, push measures as more acceptable, effective, and fair compared to rewarding, pull measures. Packages combining a push and a pull measure received the lowest acceptability and fairness ratings but were seen as somewhat effective. This suggests that not only the type of policy but the policy itself and the targeted domain and behaviour also play a role. Additionally, policies targeting efficiency behaviour were perceived as more acceptable, effective, and fair compared to policies targeting curtailment behaviour

A probabilistic tool for geotechnical assessment of Jack-Up leg penetration

Prediction of jack-up leg penetration behaviour requires assessment of uncertainties in calculation models and their input parameter values, including quality and extent of site investigation information. Commonly, uncertainty assessment is achieved by sensitivity analysis. This publication presents a probabilistic tool (JURIG4) for more rigorous prediction of jack-up leg penetration behaviour, as an add-on for conventional SNAME (2002) calculation methods. JURIG4 allows systematic input of expected variability of the important input parameters: (1) soil layer thickness, (2) trends in clay strength versus depth, (3) angle of internal friction of sand, (4) submerged unit weight and (5) lateral continuity of soil characteristics. Probabilistic calculations are performed by Monte Carlo simulation. Important output consists of probability of punch-through failure for any of the legs, as a function of distance between the geotechnical borehole and the leg. Probability density functions are provided for leg penetration and leg plunge in case of punch-through conditions

D6.2.2: Community compensation and engagement: report on best practices and closing of knowledge gaps (ALIGN-CCUS)

Horizon 2020(H2020)691712Social decision makin

Report on compensation schemes and effectiveness in different countries (D6.2.1)

Horizon 2020(H2020)691712Social decision makin