48 research outputs found
Inhibition of the JAK/STAT Pathway with Baricitinib Reduces the Multiple Organ Dysfunction Caused by Hemorrhagic Shock in Rats.
OBJECTIVE: The aim of this study was to investigate (a) the effects of the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway inhibitor (baricitinib) on the MODS in a rat model of hemorrhagic shock (HS) and (b) whether treatment with baricitinib attenuates the activation of JAK/STAT, NF-ÎșB and NLRP3 caused by HS. BACKGROUND: Post-traumatic MODS, which is in part due to excessive systemic inflammation, is associated with high morbidity and mortality. The JAK/STAT pathway is a regulator of numerous growth factor and cytokine receptors and, hence, is considered a potential master regulator of many inflammatory signaling processes. However, its role in trauma-hemorrhage is unknown. METHODS: An acute HS rat model was performed to determine the effect of baricitinib on MODS. The activation of JAK/STAT, NF-ÎșB and NLRP3 pathways were analyzed by western blotting in the kidney and liver. RESULTS: We demonstrate here for the first time that treatment with baricitinib (during resuscitation following severe hemorrhage) attenuates the organ injury and dysfunction and the activation of JAK/STAT, NF-ÎșB and NLRP3 pathways caused by HS in the rat. CONCLUSIONS: Our results point to a role of the JAK/STAT pathway in the pathophysiology of the organ injury and dysfunction caused by trauma/hemorrhage and indicate that JAK inhibitors, such as baricitinib, may be repurposed for the treatment of the MODS after trauma and/or hemorrhage
Engineering Art Galleries
The Art Gallery Problem is one of the most well-known problems in
Computational Geometry, with a rich history in the study of algorithms,
complexity, and variants. Recently there has been a surge in experimental work
on the problem. In this survey, we describe this work, show the chronology of
developments, and compare current algorithms, including two unpublished
versions, in an exhaustive experiment. Furthermore, we show what core
algorithmic ingredients have led to recent successes