Ferritin light chain and squamous cell carcinoma antigen 1 are coreceptors for cellular attachment and entry of hepatitis B virus

Overexpression of squamous cell carcinoma antigen 1 (SCCA1) in hepatitis G2 (HepG2) and Chinese hamster ovary cells can increase hepatitis B virus (HBV) binding capacity by interacting with the preS1 domain of the HBV surface antigen. However, the magnitude of increase in binding capacity was higher by several orders in the former, indicating the existence of additional factor(s) produced by HepG2 cells, which facilitates HBV attachment. Ferritin light chain (FTL) was identified as the sole high hit candidate by screening human liver cDNA library using a bacterial two-hybrid system with either preS or SCCA1 as the bait. Subsequent in vitro protein–protein interaction assays confirmed the binding activity of FTL to both preS and SCCA1, as well as the formation of triple complex preS-FTL-SCCA1, and narrowed down the binding sites on FTL. In vitro overexpression of FTL could further enhance HBV attachment in both HepG2 and Chinese hamster ovary cells, which were already overexpressing SCCA1. Importantly, in vivo co-expression of human FTL and SCCA1 in mouse liver by means of tailvein hydrodynamic injection increased serum levels of HBV surface antigen transiently 24 hours post challenge with HBV-positive human sera, and a large amount of HBV core antigen-positive hepatocytes around blood vessels could be identified by immunohistochemical staining 48 hours post challenge. The data strongly suggest that FTL and SCCA1 may serve as coreceptors in HBV cellular attachment and virus entry into hepatocytes

FROM ACADEMY TO MARKET

In today’s world, research institutes are playing an increasingly important role in bringing new technology to market. Researchers and scientists are becoming more entrepreneurial in trying to commercialize their findings as new technologies and products. However, academic research focuses very little on the whole commercialization process and the management tools needed by entrepreneurial scientists. This paper looks at commercialization from the viewpoint of a group of scientists seeking to develop a new product from successful research. It takes a business eco-system perspective and presents a theoretical framework developed by mapping a wide range of literature. This framework is then compared to data collected during a longitudinal case study on the development of a fibre optic sensor analyser with application in the construction industry. A key finding is that relationships with partners and other supporting organizations need to be formed earlier than the literature currently suggests, and that an awareness of the business ecosystem within which the technology fits is as important to scientists as knowledge of available innovation and technology management tools. Hence an early focus on communication and partnership is highlighted as an important factor for commercialization success

Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning

End-to-end deep reinforcement learning (DRL) for quadrotor control promises many benefits -- easy deployment, task generalization and real-time execution capability. Prior end-to-end DRL-based methods have showcased the ability to deploy learned controllers onto single quadrotors or quadrotor teams maneuvering in simple, obstacle-free environments. However, the addition of obstacles increases the number of possible interactions exponentially, thereby increasing the difficulty of training RL policies. In this work, we propose an end-to-end DRL approach to control quadrotor swarms in environments with obstacles. We provide our agents a curriculum and a replay buffer of the clipped collision episodes to improve performance in obstacle-rich environments. We implement an attention mechanism to attend to the neighbor robots and obstacle interactions - the first successful demonstration of this mechanism on policies for swarm behavior deployed on severely compute-constrained hardware. Our work is the first work that demonstrates the possibility of learning neighbor-avoiding and obstacle-avoiding control policies trained with end-to-end DRL that transfers zero-shot to real quadrotors. Our approach scales to 32 robots with 80% obstacle density in simulation and 8 robots with 20% obstacle density in physical deployment. Video demonstrations are available on the project website at: https://sites.google.com/view/obst-avoid-swarm-rl.Comment: Submitted to ICRA 202

Neuromorphic Neuromodulation: Towards the next generation of on-device AI-revolution in electroceuticals

Neuromodulation techniques have emerged as promising approaches for treating a wide range of neurological disorders, precisely delivering electrical stimulation to modulate abnormal neuronal activity. While leveraging the unique capabilities of artificial intelligence (AI) holds immense potential for responsive neurostimulation, it appears as an extremely challenging proposition where real-time (low-latency) processing, low power consumption, and heat constraints are limiting factors. The use of sophisticated AI-driven models for personalized neurostimulation depends on back-telemetry of data to external systems (e.g. cloud-based medical mesosystems and ecosystems). While this can be a solution, integrating continuous learning within implantable neuromodulation devices for several applications, such as seizure prediction in epilepsy, is an open question. We believe neuromorphic architectures hold an outstanding potential to open new avenues for sophisticated on-chip analysis of neural signals and AI-driven personalized treatments. With more than three orders of magnitude reduction in the total data required for data processing and feature extraction, the high power- and memory-efficiency of neuromorphic computing to hardware-firmware co-design can be considered as the solution-in-the-making to resource-constraint implantable neuromodulation systems. This could lead to a new breed of closed-loop responsive and personalised feedback, which we describe as Neuromorphic Neuromodulation. This can empower precise and adaptive modulation strategies by integrating neuromorphic AI as tightly as possible to the site of the sensors and stimulators. This paper presents a perspective on the potential of Neuromorphic Neuromodulation, emphasizing its capacity to revolutionize implantable brain-machine microsystems and significantly improve patient-specificity.Comment: 17 page

CERKL regulates autophagy via the NAD-dependent deacetylase SIRT1

<p>Macroautophagy/autophagy is an important intracellular mechanism for the maintenance of cellular homeostasis. Here we show that the <i>CERKL</i> (ceramide kinase like) gene, a retinal degeneration (RD) pathogenic gene, plays a critical role in regulating autophagy by stabilizing SIRT1. <i>In vitro</i> and <i>in vivo</i>, suppressing CERKL results in impaired autophagy. SIRT1 is one of the main regulators of acetylation/deacetylation in autophagy. In CERKL-depleted retinas and cells, SIRT1 is downregulated. ATG5 and ATG7, 2 essential components of autophagy, show a higher degree of acetylation in CERKL-depleted cells. Overexpression of SIRT1 rescues autophagy in CERKL-depleted cells, whereas CERKL loses its function of regulating autophagy in SIRT1-depleted cells, and overexpression of CERKL upregulates SIRT1. Finally, we show that CERKL directly interacts with SIRT1, and may regulate its phosphorylation at Ser27 to stabilize SIRT1. These results show that CERKL is an important regulator of autophagy and it plays this role by stabilizing the deacetylase SIRT1.</p

RAGE Mediates Accelerated Diabetic Vein Graft Atherosclerosis Induced by Combined Mechanical Stress and AGEs via Synergistic ERK Activation

Aims/Hypothesis: Diabetes with hypertension rapidly accelerates vascular disease, but the underlying mechanism remains unclear. We evaluated the hypothesis that the receptor of advanced glycation end products (RAGE) might mediate combined signals initiated by diabetes-related AGEs and hypertension-induced mechanical stress as a common molecular sensor. Methods: In vivo surgical vein grafts created by grafting vena cava segments from C57BL/6J mice into the common carotid arteries of streptozotocin (STZ)-treated and untreated isogenic mice for 4 and 8 weeks were analyzed using morphometric and immunohistochemical techniques. In vitro quiescent mouse vascular smooth muscle cells (VSMCs) with either knockdown or overexpression of RAGE were subjected to cyclic stretching with or without AGEs. Extracellular signalregulated kinase (ERK) phosphorylation and Ki-67 expression were investigated. Results: Significant increases in neointimal formation, AGE deposition, Ki-67 expression, and RAGE were observed in the vein grafts of STZ-induced diabetic mice. The highest levels of ERK phosphorylation and Ki-67 expression in VSMCs were induced by simultaneous stretch stress and AGE exposure. The synergistic activation of ERKs and Ki-67 in VSMCs was significantly inhibited by siRNA-RAGE treatment and enhanced by over-expression of RAGE. Conclusion: RAGE may mediate synergistically increased ERK activation and VSMC proliferation induced by mechanica