Activation of Protein Serine/Threonine Phosphatase PP2Cα Efficiently Prevents Liver Fibrosis

Over-activation of TGFβ signaling pathway and uncontrolled cell proliferation of hepatic stellate cells (HSCs) play pivotal roles in liver fibrogenesis, while the protein serine/threonine phosphatase PP2Cα was reported to negatively regulate TGFβ signaling pathway and cell cycle. Our study aimed to investigate the role of PP2Cα in liver fibrogenesis.The effects of PP2Cα activation on liver fibrosis were investigated in human HSCs and primary rat HSCs in vitro using western blotting, real-time PCR, nuclear translocation, cell viability and cell cycle analyses. The antifibrogenic effects in carbon tetrachloride (CCl(4))- and bile duct ligation (BDL)-induced mice in vivo were assessed using biochemical, histological and immunohistochemical analyses. The results demonstrated that activation of PP2Cα by overexpression or the new discovered small molecular activator NPLC0393 terminated TGFβ-Smad3 and TGFβ-p38 signaling pathways, induced cell cycle arrest in HSCs and decreased α-smooth muscle actin (α-SMA) expression, collagen deposition and hepatic hydroxyproline (HYP) level in CCl(4)- and BDL-induced mice.Our findings suggested that PP2Cα activation might be an attractive new strategy for treating liver fibrosis while the small molecular activator NPLC0393 might represent a lead compound for antifibrogenic drug development. Moreover, our study might provide the first evidence for the role of PP2C family members in the fibrotic disease

NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis

Expert demonstrations are a rich source of supervision for training visual robotic manipulation policies, but imitation learning methods often require either a large number of demonstrations or expensive online expert supervision to learn reactive closed-loop behaviors. In this work, we introduce SPARTN (Synthetic Perturbations for Augmenting Robot Trajectories via NeRF): a fully-offline data augmentation scheme for improving robot policies that use eye-in-hand cameras. Our approach leverages neural radiance fields (NeRFs) to synthetically inject corrective noise into visual demonstrations, using NeRFs to generate perturbed viewpoints while simultaneously calculating the corrective actions. This requires no additional expert supervision or environment interaction, and distills the geometric information in NeRFs into a real-time reactive RGB-only policy. In a simulated 6-DoF visual grasping benchmark, SPARTN improves success rates by 2.8$\times$ over imitation learning without the corrective augmentations and even outperforms some methods that use online supervision. It additionally closes the gap between RGB-only and RGB-D success rates, eliminating the previous need for depth sensors. In real-world 6-DoF robotic grasping experiments from limited human demonstrations, our method improves absolute success rates by $22.5\%$ on average, including objects that are traditionally challenging for depth-based methods. See video results at \url{https://bland.website/spartn}

SENP3 Aggravates Renal Tubular Epithelial Cell Apoptosis in Lipopolysaccharide-Induced Acute Kidney Injury via deSUMOylation of Drp1

Background: Sepsis causes acute kidney injury (AKI) in critically ill patients, although the mechanisms underlying the pathophysiology are not fully understood. SUMO-specific proteases 3 (SENP3), a member of the deSUMOylating enzyme family, is known as a redox sensor and could regulate multiple cellular signaling pathways. However, the role of SENP3 in septic AKI remains unclear. Objectives: The purpose of this study was to investigate the role of SENP3 in lipopolysaccharide (LPS)-induced AKI model. Methods: C57BL/6 mice were given intraperitoneal injection of LPS (10 mg/kg). NRK-52E cells were treated with LPS in vitro. The SENP3 protein expression was analyzed by Western blotting. The levels of reactive oxygen species (ROS) in cells were measured using DCFH-DA. SENP3-siRNA or SENP3-plasmid was, respectively, transfected into NRK-52E cells to knock down or overexpress the SENP3 expression. Western blotting was performed to analyze the protein expression of cleaved caspase 3, cytochrome c, and dynamin-related protein 1 (Drp1). The mitochondrial membrane potential was measured using JC-1 assay kit. Co-immunoprecipitation was used to determine the interaction of Drp1 and SMUO2/3. Results: SENP3 protein expression was obviously increased in renal tissues from the mouse model of LPS-induced AKI. Accordingly, SENP3 expression was upregulated in NRK-52E cells treated with LPS in a ROS-dependent manner in vitro. Knockdown of SENP3 dramatically ameliorated LPS-induced apoptosis of NRK-52E cells, whereas overexpression of SENP3 further aggravated LPS-induced apoptosis of NRK-52E cells. Mechanistically, SENP3 triggered Drp1 recruitment to mitochondria by increasing the deSUMOylation of Drp1. Conclusion: SENP3 aggravated renal tubular epithelial cell apoptosis in LPS-induced AKI via Drp1 deSUMOylation manner

The impact of long-term care insurance in China on beneficiaries and caregivers: A systematic review

Background China’s long-term care insurance (LTCI) policy has been minimally evaluated. This systematic review aimed to assess the impact of China’s LTCI pilot on beneficiaries and their caregivers. Methods This review is based on a search of peer-reviewed studies in English (Embase, MEDLINE, Web of Science) and Chinese (China National Knowledge Infrastructure [CNKI], VIP, Wanfang) databases from January 2016 through July 2020, with all studies published in English or Chinese included. We included quantitative analyses of beneficiary-level data that assessed the impact of LTCI on beneficiaries and their caregivers, with no restriction placed on the outcomes studied. Results Nine studies met our inclusion criteria. One study was a randomised trial and two used quasi-experimental approaches. Four studies examined LTCI’s effect on beneficiaries’ quality of life, physical pain, and health service utilisation; one study reported the effect on beneficiaries’ healthcare expenditures; and one study evaluated the impact on caregivers’ care tasks. These studies generally found LTCI to be associated with an improvement in patients’ quality of life (including decreased physical pain), a reduction in the number of outpatient visits and hospitalisations, decreased patient-level health expenditures (e.g. one study reported a reduction in the length of stay, inpatient expenditures, and health insurance expenditures in tertiary hospitals by 41.0%, 17.7%, and 11.4%, respectively), and reduced informal care tasks for caregivers. In addition, four out of four studies that evaluated this outcome found that beneficiaries’ overall satisfaction with LTCI was high. Conclusion The current evidence base for the effects of LTCI in China on beneficiaries and their caregivers is sparse. Nonetheless, the existing studies suggest that LTCI has positive effects on beneficiaries and their caregivers. Further rigorous research on the impacts of LTCI in China is needed to inform the future expansion of the program

3D Neural Embedding Likelihood for Robust Probabilistic Inverse Graphics

The ability to perceive and understand 3D scenes is crucial for many applications in computer vision and robotics. Inverse graphics is an appealing approach to 3D scene understanding that aims to infer the 3D scene structure from 2D images. In this paper, we introduce probabilistic modeling to the inverse graphics framework to quantify uncertainty and achieve robustness in 6D pose estimation tasks. Specifically, we propose 3D Neural Embedding Likelihood (3DNEL) as a unified probabilistic model over RGB-D images, and develop efficient inference procedures on 3D scene descriptions. 3DNEL effectively combines learned neural embeddings from RGB with depth information to improve robustness in sim-to-real 6D object pose estimation from RGB-D images. Performance on the YCB-Video dataset is on par with state-of-the-art yet is much more robust in challenging regimes. In contrast to discriminative approaches, 3DNEL's probabilistic generative formulation jointly models multi-object scenes, quantifies uncertainty in a principled way, and handles object pose tracking under heavy occlusion. Finally, 3DNEL provides a principled framework for incorporating prior knowledge about the scene and objects, which allows natural extension to additional tasks like camera pose tracking from video

A HIV-1 heterosexual transmission chain in Guangzhou, China: a molecular epidemiological study

<p>Abstract</p> <p>Background</p> <p>We conducted molecular analyses to confirm four clustering HIV-1 infections (Patient A, B, C & D) in Guangzhou, China. These cases were identified by epidemiological investigation and suspected to acquire the infection through a common heterosexual transmission chain.</p> <p>Methods</p> <p><it>Env C2V3V4 </it>region, <it>gag p17/p24 </it>junction and partial <it>pol </it>gene of HIV-1 genome from serum specimens of these infected cases were amplified by reverse transcription polymerase chain reaction (RT-PCR) and nucleotide sequenced.</p> <p>Results</p> <p>Phylogenetic analyses indicated that their viral nucleotide sequences were significantly clustered together (bootstrap value is 99%, 98% and 100% in <it>env</it>, <it>gag </it>and <it>pol </it>tree respectively). Evolutionary distance analysis indicated that their genetic diversities of <it>env</it>, <it>gag </it>and <it>pol </it>genes were significantly lower than non-clustered controls, as measured by unpaired <it>t</it>-test (<it>env </it>gene comparison: <it>p </it>< 0.005; <it>gag </it>gene comparison: <it>p </it>< 0.005; <it>pol </it>gene comparison: <it>p </it>< 0.005).</p> <p>Conclusion</p> <p>Epidemiological results and molecular analyses consistently illustrated these four cases represented a transmission chain which dispersed in the locality through heterosexual contact involving commercial sex worker.</p