Hepatic acute-phase proteins control innate immune responses during infection by promoting myeloid-derived suppressor cell function

Acute-phase proteins (APPs) are an evolutionarily conserved family of proteins produced mainly in the liver in response to infection and inflammation. Despite vast pro- and antiinflammatory properties ascribed to individual APPs, their collective function during infections remains poorly defined. Using a mouse model of polymicrobial sepsis, we show that abrogation of APP production by hepatocyte-specific gp130 deletion, the signaling receptor shared by IL-6 family cytokines, strongly increased mortality despite normal bacterial clearance. Hepatic gp130 signaling through STAT3 was required to control systemic inflammation. Notably, hepatic gp130–STAT3 activation was also essential for mobilization and tissue accumulation of myeloid-derived suppressor cells (MDSCs), a cell population mainly known for antiinflammatory properties in cancer. MDSCs were critical to regulate innate inflammation, and their adoptive transfer efficiently protected gp130-deficient mice from sepsis-associated mortality. The hepatic APPs serum amyloid A and Cxcl1/KC cooperatively promoted MDSC mobilization, accumulation, and survival, and reversed dysregulated inflammation and restored survival of gp130-deficient mice. Thus, gp130-dependent communication between the liver and MDSCs through APPs controls inflammatory responses during infection

Follistatin is a novel therapeutic target and biomarker in FLT3/ITD acute myeloid leukemia

Corrigendum, refer to https://doi.org/10.15252/emmm.202012911202012 bcrcVersion of RecordPublishe

Inverse Kinematics Analysis and COG Trajectory Planning Algorithms for Stable Walking of a Quadruped Robot with Redundant DOFs

This paper presents a new Center of Gravity (COG) trajectory planning algorithm for a quadruped robot with redundant Degrees of Freedom (DOFs). Each leg has 7 DOFs, which allow the robot to exploit its kinematic redundancy for various locomotion and manipulation tasks. Also, the robot can suitably adapt to different environment (e.g., passing through a narrow gap) by simply changing the body posture. However, the robot has significant COG movement during the leg swinging phase due to the heavy leg weights; the weight of all the four legs takes up 80% of the robot???s total weight. To achieve stable walking in the presence of undesired COG movements, a new COG trajectory planning algorithm was proposed by using a combined Jacobian of COG and centroid of a support polygon including a foot contact constraint. Additionally, the inverse kinematics of each leg was solved by modified improved Jacobian pseudoinverse (mIJP) algorithm. The mIJP algorithm could generate desired trajectories for the joints even when the robot???s leg is in a singular posture. Owing to these proposed methods, the robot was able to perform various modes of locomotion both in simulations and experiments with improved stability