Chronic treatment with anesthetic propofol attenuates β-amyloid protein levels in brain tissues of aged mice

Alzheimer’s disease (AD) is the most common form of dementia. At the present time, however, AD still lacks effective treatments. Our recent studies showed that chronic treatment with anesthetic propofol attenuated brain caspase-3 activation and improved cognitive function in aged mice. Accumulation of β-amyloid protein (Aβ) is a major component of the neuropathogenesis of AD dementia and cognitive impairment. We therefore set out to determine the effects of chronic treatment with propofol on Aβ levels in brain tissues of aged mice. Propofol (50 mg/kg) was administrated to aged (18 month-old) wild-type mice once a week for 8 weeks. The brain tissues of mice were harvested one day after the final propofol treatment. The harvested brain tissues were then subjected to enzyme-linked immunosorbent assay (ELISA) and Western blot analysis. Here we report that the propofol treatment reduced Aβ (Aβ40 and Aβ42) levels in the brain tissues of the aged mice. Moreover, the propofol treatment decreased the levels of β-site amyloid precursor protein cleaving enzyme (the enzyme for Aβ generation), and increased the levels of neprilysin (the enzyme for Aβ degradation) in the brain tissues of the aged mice. These results suggested that the chronic treatment with propofol might reduce brain Aβ levels potentially via decreasing brain levels of β-site amyloid precursor protein cleaving enzyme, thus decreasing Aβ generation; and via increasing brain neprilysin levels, thus increasing Aβ degradation. These preliminary findings from our pilot studies have established a system and postulated a new hypothesis for future research

GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects

Articulated objects like cabinets and doors are widespread in daily life. However, directly manipulating 3D articulated objects is challenging because they have diverse geometrical shapes, semantic categories, and kinetic constraints. Prior works mostly focused on recognizing and manipulating articulated objects with specific joint types. They can either estimate the joint parameters or distinguish suitable grasp poses to facilitate trajectory planning. Although these approaches have succeeded in certain types of articulated objects, they lack generalizability to unseen objects, which significantly impedes their application in broader scenarios. In this paper, we propose a novel framework of Generalizable Articulation Modeling and Manipulating for Articulated Objects (GAMMA), which learns both articulation modeling and grasp pose affordance from diverse articulated objects with different categories. In addition, GAMMA adopts adaptive manipulation to iteratively reduce the modeling errors and enhance manipulation performance. We train GAMMA with the PartNet-Mobility dataset and evaluate with comprehensive experiments in SAPIEN simulation and real-world Franka robot. Results show that GAMMA significantly outperforms SOTA articulation modeling and manipulation algorithms in unseen and cross-category articulated objects. We will open-source all codes and datasets in both simulation and real robots for reproduction in the final version. Images and videos are published on the project website at: http://sites.google.com/view/gamma-articulationComment: 8 pages, 5 figures, ICRA 202

Self‐Assembly of Therapeutic Peptide into Stimuli‐Responsive Clustered Nanohybrids for Cancer‐Targeted Therapy

Clinical translation of therapeutic peptides, particularly those targeting intracellular protein–protein interactions (PPIs), has been hampered by their inefficacious cellular internalization in diseased tissue. Therapeutic peptides engineered into nanostructures with stable spatial architectures and smart disease targeting ability may provide a viable strategy to overcome the pharmaceutical obstacles of peptides. This study describes a strategy to assemble therapeutic peptides into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to tumor microenvironment. As a proof of concept, an anticancer peptide termed β‐catenin/Bcl9 inhibitors is copolymerized with gold ion and assembled into a cluster of nanohybrids (pCluster). Through a battery of in vitro and in vivo tests, it is demonstrated that pClusters potently inhibit tumor growth and metastasis in several animal models through the impairment of the Wnt/β‐catenin pathway, while maintaining a highly favorable biosafety profile. In addition, it is also found that pClusters synergize with the PD1/PD‐L1 checkpoint blockade immunotherapy. This new strategy of peptide delivery will likely have a broad impact on the development of peptide‐derived therapeutic nanomedicine and reinvigorate efforts to discover peptide drugs that target intracellular PPIs in a great variety of human diseases, including cancer.A strategy for clinical translation of therapeutic peptides by assembling them into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to the tumor microenvironment, is presented. An anticancer peptide termed β‐catenin/Bcl9 inhibitor is assembled into a cluster of nanohybrids termed pCluster, which potently inhibits tumor growth as well as metastasis, and synergizes with immunotherapy, while maintaining a highly favorable biosafety profile.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/1/adfm201807736.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/2/adfm201807736-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/3/adfm201807736_am.pd

Computational modeling of the cephalic arch with jugulocephalic vein variant predicts hemodynamic profiles in patients with brachiocephalic fistula

Background: The cephalic vein is often used in for arteriovenous fistula creation; however, the cephalic vein variation is common. This study will propose new theoretical explanations for a new discovered variation of cephalic vein draining into external jugular vein with “T-junction” shape by means of 3D computational hemodynamic modeling, which may provide reference for clinical practice. Methods: The precise measurements were conducted for the variant right cephalic vein draining into external jugular vein and for a normal right cephalic vein as a control. After processing the anatomical data, 3D geometrical model was reconstructed. Then, the influent field inside the variant jugulocephalic vein was mathematically modeled to get a detailed description of hemodynamic environment. Results: The anatomical parameters of the “T-junction” jugulocephalic vein variant were much more different from the normal right cephalic vein. The wall shear stress of variant cephalic vein at the corresponding position was higher and changed more rapidly than that of normal cephalic vein. The shear rate contour lines are disordered in several areas of the variant cephalic vein, indicating that the hemodynamic parameters in these areas are unstable. The hemodynamic characteristics at the confluence of the variant cephalic vein are more complex, with more areas where hemodynamic parameters are disrupted. Conclusions: The variation of cephalic arch in a “T-junction” with external jugular vein largely altered the fluid dynamics, especially in hemodialysis patients with brachiocephalic fistula in terms of the simulating flow in 3D computational model. This computational model provides hemodynamic profiles for stabilizing or modulating fluid dynamics in patients with jugulocephalic vein variant after brachiocephalic fistula