A novel histone deacetylase inhibitor Se-SAHA attenuates isoproterenol-induced heart failure via antioxidative stress and autophagy inhibition.

Heart failure is associated with histone deacetylase (HDAC) regulation of gene expression, the inhibition of which is thought to be beneficial for heart failure therapy. Here, we explored the cardioprotective effects and underlying mechanism of a novel selenium-containing HDAC inhibitor, Se-SAHA, on isoproterenol (ISO)-induced heart failure. We found that pretreatment with Se-SAHA attenuated ISO-induced cardiac hypertrophy and fibrosis in neonatal rat ventricular myocytes (NRVMs). Se-SAHA significantly attenuated the generation of ISO-induced reactive oxygen species (ROS) and restored the expression levels of superoxide dismutase 2 (SOD2) and heme oxygenase-1 (HO-1) in vitro. Furthermore, Se-SAHA pretreatment prevented the accumulation of autophagosomes. Se-SAHA reversed the high expression of HDAC1 and HDAC6 induced by ISO incubation. However, after the addition of the HDAC agonist, the effect of Se-SAHA on blocking autophagy was inhibited. Using ISO-induced mouse models, cardiac ventricular contractile dysfunction, hypertrophy, and fibrosis was reduced treated by Se-SAHA. In addition, Se-SAHA inhibited HDAC1 and HDAC6 overexpression in ISO-treated mice. Se-SAHA treatment significantly increased the activity of SOD2 and improved the ability to eliminate free radicals. Se-SAHA hindered the excessive levels of the microtubule-associated protein 1 light chain 3 (LC3)-II and Beclin-1 in heart failure mice. Collectively, our results indicate that Se-SAHA exerts cardio-protection against ISO-induced heart failure via antioxidative stress and autophagy inhibition.

Fluid Inverse Volumetric Modeling and Applications from Surface Motion.

In this study, we devise a framework for volumetrically reconstructing fluid from observable, measurable free surface motion. Our innovative method amalgamates the benefits of deep learning and conventional simulation to preserve the guiding motion and temporal coherence of the reproduced fluid. We infer surface velocities by encoding and decoding spatiotemporal features of surface sequences, and a 3D CNN is used to generate the volumetric velocity field, which is then combined with 3D labels of obstacles and boundaries. Concurrently, we employ a network to estimate the fluid's physical properties. To progressively evolve the flow field over time, we input the reconstructed velocity field and estimated parameters into the physical simulator as the initial state. Our approach yields promising results for both synthetic fluid generated by different fluid solvers and captured real fluid. The developed framework naturally lends itself to a variety of graphics applications, such as 1) effective reproductions of fluid behaviors visually congruent with the observed surface motion, and 2) physics-guided re-editing of fluid scenes. Extensive experiments affirm that our novel method surpasses state-of-the-art approaches for 3D fluid inverse modeling and animation in graphics.

A Unified Particle-Based Solver for Non-Newtonian Behaviors Simulation.

In this article, we present a unified framework to simulate non-Newtonian behaviors. We combine viscous and elasto-plastic stress into a unified particle solver to achieve various non-Newtonian behaviors ranging from fluid-like to solid-like. Our constitutive model is based on a Generalized Maxwell model, which incorporates viscosity, elasticity and plasticity in one non-linear framework by a unified way. On the one hand, taking advantage of the viscous term, we construct a series of strain-rate dependent models for classical non-Newtonian behaviors such as shear-thickening, shear-thinning, Bingham plastic, etc. On the other hand, benefiting from the elasto-plastic model, we empower our framework with the ability to simulate solid-like non-Newtonian behaviors, i.e., visco-elasticity/plasticity. In addition, we enrich our method with a heat diffusion model to make our method flexible in simulating phase change. Through sufficient experiments, we demonstrate a wide range of non-Newtonian behaviors ranging from viscous fluid to deformable objects. We believe this non-Newtonian model will enhance the realism of physically-based animation, which has great potential for computer graphics.

Syringaresinol Alleviates Early Diabetic Retinopathy by Downregulating HIF-1α/VEGF via Activating Nrf2 Antioxidant Pathway.

SCOPE: Early diabetic retinopathy (DR) is characterized by chronic inflammation, excessive oxidative stress, and retinal microvascular damage. Syringaresinol (SYR), as a natural polyphenolic compound, has been proved to inhibit many disease progression due to its antiinflammatory and antioxidant properties. The present study focuses on exploring the effect of SYR on hyperglycemia-induced early DR as well as the underlying mechanisms. METHODS AND RESULTS: Wild-type (WT) and nuclear factor erythroid 2-related factor 2 (Nrf2)-knockout C57BL/6 mice of type 1 diabetes and high glucose (HG)-induced RF/6A cells are used as in vivo and in vitro models, respectively. This study finds that SYR protects the retinal structure and function in diabetic mice and reduces the permeability and apoptosis of HG-treated RF/6A cells. Meanwhile, SYR distinctly mitigates inflammation and oxidative stress in vivo and vitro. The retinal microvascular damages are suppressed by SYR via downregulating hypoxia-inducible factor-1α (HIF-1α)/vascular endothelial growth factor (VEGF) pathway. Whereas, SYR-provided protective effects are diminished in Nrf2-knockout mice, indicating that SYR improves DR progression by activating Nrf2. Similarly, SYR cannot exert protective effects against HG-induced oxidative stress and endothelial injury in small interfering RNA (siRNA)-Nrf2-transfected RF/6A cells. CONCLUSION: In summary, SYR suppresses oxidative stress via activating Nrf2 antioxidant pathway, which ameliorates retinal microvascular damage by downregulating HIF-1α/VEGF, thereby alleviating early DR progression.