Protein synthesis is associated with high-speed dynamics and broad-band stability of functional hubs in the brain.

L-[1-11C]leucine PET can be used to measure in vivo protein synthesis in the brain. However, the relationship between regional protein synthesis and on-going neural dynamics is unclear. We use a graph theoretical approach to examine the relationship between cerebral protein synthesis (rCPS) and both static and dynamical measures of functional connectivity (measured using resting state functional MRI, R-fMRI). Our graph theoretical analysis demonstrates a significant positive relationship between protein turnover and static measures of functional connectivity. We compared these results to simple measures of metabolism in the cortex using [18F]FDG PET). Whilst some relationships between [18F]FDG binding and graph theoretical measures was present, there remained a significant relationship between protein turnover and graph theoretical measures, which were more robustly explained by L-[1-11C]Leucine than [18F]FDG PET. This relationship was stronger in dynamics at a faster temporal resolution relative to dynamics measured over a longer epoch. Using a Dynamic connectivity approach, we also demonstrate that broad-band dynamic measures of Functional Connectivity (FC), are inversely correlated with protein turnover, suggesting greater stability of FC in highly interconnected hub regions is supported by protein synthesis. Overall, we demonstrate that cerebral protein synthesis has a strong relationship independent of tissue metabolism to neural dynamics at the macroscopic scale.

Use of biomarkers for predicting a malignant course in acute ischemic stroke: an observational case-control study.

Acute ischemic stroke is a sudden neurological event caused by brain ischemia. Patients with large vessel occlusion are at high risk of developing significant cerebral edema, which can lead to rapid neurological decline. The optimal timing for decompressive hemicraniectomy to prevent further brain damage is still uncertain. This study aimed to identify potential predictors of severe brain edema. The data indicate that specific cytokines may help identify patients with a higher risk of developing life-threatening brain swelling in the early phase post-stroke. The association between a positive biomarker and the outcome was calculated, and three biomarkers-S100B protein, MMP-9, and IL-10-were found to be significantly associated with malignant edema. A model was derived for early predicting malignant cerebral edema, including S100B protein and IL-1 beta. These findings suggest that molecular biomarkers related to the ischemic cascade may be a helpful way of predicting the development of malignant cerebral edema in ischemic stroke patients, potentially widening the time window for intervention and assisting in decision-making. In conclusion, this study provides insights into the molecular mechanisms of severe brain edema and highlights the potential use of biomarkers in predicting the course of ischemic stroke.