Genetic and Cellular Studies of The Podocyte in Focal Segmental Glomerulosclerosis

The podocyte forms the outer layer of the filtration barrier in the glomerulus to prevent albumin leakage. Podocyte damage leads to focal segmental glomerulosclerosis (FSGS), a leading cause of chronic kidney disease. The cause of the majority of FSGS cases is unknown and referred to as sporadic FSGS. Genetic studies have identified genes as monogenic causes of FSGS in patients with a strong family history, but these cases account for only a small proportion of the FSGS population. Whether genetic susceptibility contributes to sporadic FSGS and which cellular process in the podocyte initiates the pathogenesis of FSGS are important questions that remain to be elucidated. To answer these questions, my research followed two different lines of inquiry. I performed a genetic analysis of both familial and sporadic FSGS patients, and I investigated the role of the actin cytoskeleton in podocytes. Based on expression analysis, we identified a new FSGS susceptibility gene, ARHGAP24, and showed that it was mutated in a family with FSGS. Since ARHGAP24 functions to maintain high Rho and low Rac levels, my work suggested that this balance might be important in FSGS. Using an inducible transgenic mouse model and multi-photon intravital microscopy, we validated that high activity of Rac1, one of the Rho family GTPases, is responsible for podocyte foot process effacement, increased membrane dynamics, and podocyte shedding into the urine, three important processes that lead to proteinuria and FSGS. By sequencing a large cohort of sporadic FSGS patients, I identified 16 potential FSGS susceptibility genes that were novel. Using a novel podocyte-specific indicible RNAi mouse model that I developed, four of these genes were validated. Some of these genes function as regulators of the actin cytoskeleton. Our genetic study further reinforces the role of actin cytoskeletal regulation in the pathogenesis of FSGS

Design and Implementation of a FPGA and DSP Based MIMO Radar Imaging System

The work presented in this paper is aimed at the implementation of a real-time multiple-input multiple-output (MIMO) imaging radar used for area surveillance. In this radar, the equivalent virtual array method and time-division technique are applied to make 16 virtual elements synthesized from the MIMO antenna array. The chirp signal generater is based on a combination of direct digital synthesizer (DDS) and phase locked loop (PLL). A signal conditioning circuit is used to deal with the coupling effect within the array. The signal processing platform is based on an efficient field programmable gates array (FPGA) and digital signal processor (DSP) pipeline where a robust beamforming imaging algorithm is running on. The radar system was evaluated through a real field experiment. Imaging capability and real-time performance shown in the results demonstrate the practical feasibility of the implementation

Research on Large-scale Energy Storage of Chinese Power System Based on Demand Analysis

With the construction and development of a low carbon and environmental protection society, China is promoting the construction of a clean, low carbon, safe and efficient energy supply system, the most critical of which is to promote the rapid construction of new energy installed capacity. However, with the continuous expansion of the new energy installed capacity, the random volatility of the power supply has become an important factor that puzzles the power balance of the current power system, not only formed a larger peak pressure, but also became one of the important factors restricting the development of new energy. At the same time, the new energy power electronic equipment has weak supporting characteristics, which also makes the proportion of new energy power system continues to increase, and has a high impact on security. In this context, this paper carries out a demand analysis, firstly discussing the demand for large-scale energy storage in the development of new energy for power system, and secondly analyzing the demand for large-scale energy storage in the safe operation of large power grid, so as to promote the construction of GW-level electrochemical energy storage power station and effectively deal with the power imbalance and safety problems

Unified Language Representation for Question Answering over Text, Tables, and Images

When trying to answer complex questions, people often rely on multiple sources of information, such as visual, textual, and tabular data. Previous approaches to this problem have focused on designing input features or model structure in the multi-modal space, which is inflexible for cross-modal reasoning or data-efficient training. In this paper, we call for an alternative paradigm, which transforms the images and tables into unified language representations, so that we can simplify the task into a simpler textual QA problem that can be solved using three steps: retrieval, ranking, and generation, all within a language space. This idea takes advantage of the power of pre-trained language models and is implemented in a framework called Solar. Our experimental results show that Solar outperforms all existing methods by 10.6-32.3 pts on two datasets, MultimodalQA and MMCoQA, across ten different metrics. Additionally, Solar achieves the best performance on the WebQA leaderboardComment: Findings of ACL 202

Finding Efficient Collective Variables: The Case of Crystallization

Several enhanced sampling methods such as umbrella sampling or metadynamics rely on the identification of an appropriate set of collective variables. Recently two methods have been proposed to alleviate the task of determining efficient collective variables. One is based on linear discriminant analysis, the other on a variational approach to conformational dynamics, and uses time-lagged independent component analysis. In this paper, we compare the performance of these two approaches in the study of the homogeneous crystallization of two simple metals. We focus on Na and Al and search for the most efficient collective variables that can be expressed as a linear combination of X-ray diffraction peak intensities. We find that the performances of the two methods are very similar. However, the method based on linear discriminant analysis, in its harmonic version, is to be preferred because it is simpler and much less computationally demanding