Blood coagulation factors as inflammatory mediators

After the first observations about blood coagulation by Hippocrates, it took until the early 1900s before the classic theory of blood coagulation was presented. As more and more other coagulation factors were discovered, the four-factor coagulation scheme became more complex, but better understood, leading to the current coagulation cascade. As during the last decade it turned out that coagulation factors might do more than just promoting (or inhibiting) blood coagulation, new scientific avenues were pursued focusing on coagulation-independent properties of individual coagulation factors. This led to the current understanding that coagulation factors, like tissue factor (TF), FVII, FX, and thrombin, are important players in inflammation, vascular development, angiogenesis, and tumorigenesis. However, the molecular mechanism by which coagulation factors exert their pleiotropic effects in pathophysiology remains one of the major challenges in the field. This overview presents current insight in how the main coagulation factors might induce inflammation.     

Learning to Synchronize: Midfrontal Theta Dynamics during Rule Switching

In recent years, several hierarchical extensions of well-known learning algorithms have been proposed. For example, when stimulus-action mappings vary across time or context, the brain may learn two or more stimulus-action mappings in separate modules, and additionally (at a hierarchically higher level) learn to appropriately switch between those modules. However, how the brain mechanistically coordinates neural communication to implement such hierarchical learning remains unknown. Therefore, the current study tests a recent computational model that proposed how midfrontal theta oscillations implement such hierarchical learning via the principle of binding by synchrony (Sync model). More specifically, the Sync model uses bursts at theta frequency to flexibly bind appropriate task modules by synchrony. The 64-channel EEG signal was recorded while 27 human subjects (female: 21, male: 6) performed a probabilistic reversal learning task. In line with the Sync model, postfeedback theta power showed a linear relationship with negative prediction errors, but not with positive prediction errors. This relationship was especially pronounced for subjects with better behavioral fit (measured via Akaike information criterion) of the Sync model. Also consistent with Sync model simulations, theta phase-coupling between midfrontal electrodes and temporoparietal electrodes was stronger after negative feedback. Our data suggest that the brain uses theta power and synchronization for flexibly switching between task rule modules, as is useful, for example, when multiple stimulus-action mappings must be retained and used.SIGNIFICANCE STATEMENT Everyday life requires flexibility in switching between several rules. A key question in understanding this ability is how the brain mechanistically coordinates such switches. The current study tests a recent computational framework (Sync model) that proposed how midfrontal theta oscillations coordinate activity in hierarchically lower task-related areas. In line with predictions of this Sync model, midfrontal theta power was stronger when rule switches were most likely (strong negative prediction error), especially in subjects who obtained a better model fit. Additionally, also theta phase connectivity between midfrontal and task-related areas was increased after negative feedback. Thus, the data provided support for the hypothesis that the brain uses theta power and synchronization for flexibly switching between rules.     

A Standardized Framework for Fluorescence-Guided Margin Assessment for Head and Neck Cancer Using a Tumor Acidosis Sensitive Optical Imaging Agent

Molecular Imaging and Biology - Intra-operative management of the surgical margin in patients diagnosed with head and neck squamous cell carcinoma (HNSCC) remains challenging as surgeons still have...