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Diabetic retinopathy is predominantly caused by vascular endothelial growth factor (VEGF)-induced vascular leakage; however, the underlying mechanism is unclear. Here we designed an in vivo transglutaminase (TGase) activity assay in mouse retina and demonstrated that hyperglycemia induced vascular leakage by activating TGase2 in diabetic retina. VEGF elevated TGase2 activity through sequential elevation of intracellular Ca(2+) and reactive oxygen species (ROS) concentrations in endothelial cells. The TGase inhibitors cystamine and monodansylcadaverin or TGase2 small interfering RNA (siRNA) prevented VEGF-induced stress fiber formation and vascular endothelial (VE)-cadherin disruption, which play a critical role in modulating endothelial permeability. Intravitreal injection of two TGase inhibitors or TGase2 siRNA successfully inhibited hyperglycemia-induced TGase activation and microvascular leakage in the retinas of diabetic mice. C-peptide or ROS scavengers also inhibited TGase activation in diabetic mouse retinas. The role of TGase2 in VEGF-induced vascular leakage was further supported using diabetic TGase2(-/-) mice. Thus, our findings suggest that ROS-mediated activation of TGase2 plays a key role in VEGF-induced vascular leakage by stimulating stress fiber formation and VE-cadherin disruption. [ABSTRACT FROM AUTHOR]

The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to affect the risk, severity, and clinical outcome of serious neuro-vascular diseases. However, characterizing the highly variable CoW anatomy is still a manual and time-consuming expert task. The CoW is usually imaged by two angiographic imaging modalities, magnetic resonance angiography (MRA) and computed tomography angiography (CTA), but there exist limited public datasets with annotations on CoW anatomy, especially for CTA. Therefore we organized the TopCoW Challenge in 2023 with the release of an annotated CoW dataset. The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology. It was also the first large dataset with paired MRA and CTA from the same patients. TopCoW challenge formalized the CoW characterization problem as a multiclass anatomical segmentation task with an emphasis on topological metrics. We invited submissions worldwide for the CoW segmentation task, which attracted over 140 registered participants from four continents. The top performing teams managed to segment many CoW components to Dice scores around 90%, but with lower scores for communicating arteries and rare variants. There were also topological mistakes for predictions with high Dice scores. Additional topological analysis revealed further areas for improvement in detecting certain CoW components and matching CoW variant topology accurately. TopCoW represented a first attempt at benchmarking the CoW anatomical segmentation task for MRA and CTA, both morphologically and topologically.