Tianhao Nan

Bio: Tianhao Nan is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Hardware acceleration & Medicine. The author has an hindex of 2, co-authored 5 publications receiving 10 citations.

MiR-25 enhances autophagy and promotes sorafenib resistance of hepatocellular carcinoma via targeting FBXW7

Abstract: Sorafenib resistance is a major challenge in the treatment of patients with advanced hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) are a large family of non-coding RNA molecules, which is an important mechanism of drug resistance. We previously found that knockdown of miR-25 increased the sensitivity of TRAIL-induced apoptosis in liver cancer stem cells. We aimed to study the effects of miR-25 on sorafenib resistance of HCC and the underlying mechanisms. In the present study, we analyzed the expression of miR-25 between HCC and normal tissues and predicted miR-25 target genes through databases. After transfecting miR-25 mimics, inhibitor or FBXW7 Plasmid, CCK-8 and flow cytometry assay was performed to determine the sorafenib resistance. We performed LC3-dual-fluorescence assay and Western blotting to detect the autophagy levels. The expression of miR-25 was upregulated in human HCC tissues and was associated with tumor pathological grade, clinic staging, and lymphatic metastasis. MiR-25 enhanced sorafenib resistance of HCC cells and autophagy. FBXW7 is the direct target of miR-25. Overexpression of FBXW7 could reverse the increase of sorafenib resistance caused by miR-25 mimics. Our results suggested that miR-25 increased the sorafenib resistance of HCC via inducing autophagy. In addition, miR-25 decreases the expression of FBXW7 protein to regulate autophagy. Therefore, miR-25 may represent a novel therapeutic target for the treatment of HCC.

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

Abstract: The SKA (Square Kilometer Array) radio telescope will become the most sensitive telescope by correlating a huge number of antenna nodes to form a vast array of sensors in a region over one hundred kilometers. Faceting, the wide-field imaging algorithm, is a novel approach towards solving image construction from sensing data where earth surface curves cannot be ignored. However, the traditional processor of cloud computing, even if the most sophisticated supercomputer is used, cannot meet the extremely high computation performance requirement. In this paper, we propose the design and implementation of high-efficiency FPGA (Field Programmable Gate Array) -based hardware acceleration of the key algorithm, faceting in SKA by focusing on phase rotation and gridding, which are the most time-consuming phases in the faceting algorithm. Through the analysis of algorithm behavior and bottleneck, we design and optimize the memory architecture and computing logic of the FPGA-based accelerator. The simulation and tests on FPGA are done to confirm the acceleration result of our design and it is shown that the acceleration performance we achieved on phase rotation is 20× the result of the previous work. We then further designed and optimized an efficient microstructure of loop unrolling and pipeline for the gridding accelerator, and the designed system simulation was done to confirm the performance of our structure. The result shows that the acceleration ratio is 5.48 compared to the result tested on software in gridding parts. Hence, our approach enables efficient acceleration of the faceting algorithm on FPGAs with high performance to meet the computational constraints of SKA as a representative vast sensor array.

FAM198B promotes colorectal cancer progression by regulating the polarization of tumor-associated macrophages via the SMAD2 signaling pathway

Abstract: ABSTRACT Colorectal cancer (CRC) is one of the most common malignant tumors. Tumor-associated macrophages (TAMs) promote the progression of CRC, but the mechanism is not completely clear. The present study aimed to reveal the expression and function of FAM198B in TAMs, and the role of FAM198B in mediating macrophage polarization in CRC. The role of FAM198B in macrophage activity, cell cycle, and angiogenesis was evaluated by CCK-8 assay, flow cytometry, and vasculogenic mimicry assay. The effects of FAM198B on macrophage polarization were determined by flow cytometry. The function of FAM198B-mediated macrophage polarization on CRC progression was evaluated by transwell assays. Bioinformatic analyses and rescue assays were performed to identify biological functions and signaling pathways involved in FAM198B regulation of macrophage polarization. Increased FAM198B expression in TAMs is negatively associated with poor CRC prognosis. Functional assays showed that FAM198B promotes M2 macrophage polarization, which leads to CRC cell proliferation, migration, and invasion. Mechanistically, FAM198B regulates the M2 polarization of macrophages by targeting SMAD2, identifying the SMAD2 pathway as a mechanism by which FAM198B promotes CRC progression through regulating macrophage polarization. These findings provide a possible molecular mechanism for FAM198B in TAMs in CRC and suggest that FAM198B may be a novel therapeutic target in CRC. Graphical abstract

Reliable SoC Design and Implementation of SHA-3-HMAC Algorithm with Attack Protection

Abstract: The Keyed-Hash Message Authentication Codes (HMAC) is a widely used method to ensure the integrity and authentication of data and its security is based on the Hash encryption algorithm. As part of HMAC, the secure hash algorithm (SHA)-3 was selected as the winner of the hash function competition in 2012. Though SHA-3 has been implemented individually in hardware, reliable SoC (system on a chip) design with multiple attack protection is still unsolved to support SHA-3-HMAC. In this paper, we propose our design of a SHA-3-HMAC SoC module which has the ability to defend against common side channel attacks and error injection attacks. Our design also supports different digest values of 256/384/512 according to configuration, with automatic padding operation inside SHA-3. Furthermore, through application-specific integrated circuit (ASIC) analysis of the implementation of our design, the maximum clock frequency of our implementation can reach 300MHz. By adding a clock randomization module and a circuit design based on time redundancy, the security and reliability of the SoC module has been greatly improved.

An FPGA-based Hardware Acceleration For Key Steps of Facet Imaging Algorithm

Abstract: SKA (Square Kilometer Array) is an under-construction radio telescope with the largest observation aperture, and also it is an international science project that requires the participation and cooperation of multiple countries and organizations. SKA scientific data processing is an application with huge amount of data and extremely high computation performance requirement, and has strict energy consumption restrictions. The high performance on data I/O rate determine s cloud computing to be a feasible solution to such a strict computing restriction. However, the traditional processor of cloud computing even if the most sophisticated super computer can not meet the requirements. Therefore, it is necessary to explore a new acceleration structure. FPGA (Field-Programmable G ate Array) is a computation platform that combines the advantages of high-level parallelization and low power consumption. Therefore, heterogeneous cloud computing structure of CPU + FPGA becomes available to solve SKA’s data processing requirements. This paper mainly discusses the high efficiency FP GA-based hardware acceleration of the key algorithm Facet i n SKA. There are two time-consuming parts during the Facet procedures—Phase Rotation and Gridding. Firstly, a pipeline acceleration structure designed for Phase Rotation algorithm is determined. The simulation and tests on FPGA are done to confirm the acceleration result of our design and it shows the performance is 32.07 times of the result running on software. Then determined an efficiency optimized core computation acceleration structure of loop expansion + pipeline for Gridding, and the designed system simulation is done to confirm the performance of our structure. The result shows that the acceleration ratio is 5.48 compared to the result tested on software.

Epigenetic regulation of autophagy by non-coding RNAs in gastrointestinal tumors: Biological functions and therapeutic perspectives.

Abstract: Cancer is the manifestation of changes and mutations in genetic and epigenetic levels. Non-coding RNAs (ncRNAs) are commonly dysregulated in disease pathogenesis, and their role in cancer has been well-documented. The ncRNAs regulate various molecular pathways and mechanisms in cancer that can lead to induction/inhibition of carcinogenesis. Autophagy is a molecular “self-digestion” mechanism its function can be pro-survival or pro-death in tumor cells. The aim of the present review is to evaluate the role of ncRNAs in regulating autophagy in gastrointestinal tumors. The role of the ncRNA/autophagy axis in affecting the progression of gastric, liver, colorectal, pancreatic, esophageal, and gallbladder cancers is investigated. Both ncRNAs and autophagy mechanisms can function as oncogenic or onco-suppressor and this interaction can determine the growth, invasion, and therapy response of gastrointestinal tumors. ncRNA/autophagy axis can reduce/increase the proliferation of gastrointestinal tumors via the glycolysis mechanism. Furthermore, related molecular pathways of metastasis, such as EMT and MMPs, are affected by the ncRNA/autophagy axis. The response of gastrointestinal tumors to chemotherapy and radiotherapy can be suppressed by pro-survival autophagy, and ncRNAs are essential regulators of this mechanism. miRNAs can regulate related genes and proteins of autophagy, such as ATGs and Beclin-1. Furthermore, lncRNAs and circRNAs down-regulate miRNA expression via sponging to modulate the autophagy mechanism. Moreover, anti-cancer agents can affect the expression level of ncRNAs regulating autophagy in gastrointestinal tumors. Therefore, translating these findings into clinics can improve the prognosis of patients.

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

Abstract: The SKA (Square Kilometer Array) radio telescope will become the most sensitive telescope by correlating a huge number of antenna nodes to form a vast array of sensors in a region over one hundred kilometers. Faceting, the wide-field imaging algorithm, is a novel approach towards solving image construction from sensing data where earth surface curves cannot be ignored. However, the traditional processor of cloud computing, even if the most sophisticated supercomputer is used, cannot meet the extremely high computation performance requirement. In this paper, we propose the design and implementation of high-efficiency FPGA (Field Programmable Gate Array) -based hardware acceleration of the key algorithm, faceting in SKA by focusing on phase rotation and gridding, which are the most time-consuming phases in the faceting algorithm. Through the analysis of algorithm behavior and bottleneck, we design and optimize the memory architecture and computing logic of the FPGA-based accelerator. The simulation and tests on FPGA are done to confirm the acceleration result of our design and it is shown that the acceleration performance we achieved on phase rotation is 20× the result of the previous work. We then further designed and optimized an efficient microstructure of loop unrolling and pipeline for the gridding accelerator, and the designed system simulation was done to confirm the performance of our structure. The result shows that the acceleration ratio is 5.48 compared to the result tested on software in gridding parts. Hence, our approach enables efficient acceleration of the faceting algorithm on FPGAs with high performance to meet the computational constraints of SKA as a representative vast sensor array.