Cellular metabolism has been shown to regulate differentiation and function of immune cells. Tumor associated immune cells undergo phenotypic and functional alterations due to the change of cellular metabolism in tumo...
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Cellular metabolism has been shown to regulate differentiation and function of immune cells. Tumor associated immune cells undergo phenotypic and functional alterations due to the change of cellular metabolism in tumor microenvironments. NKT cells are good candidates for immunotherapies against tumors and have been used in several clinical trials. However, the influences of tumor microenvironments on NKT cell functions remain unclear. In our studies, lactic acid in tumor microenvironments inhibited IFN？ and IL4 productions from NKT cells, and more profound influence on IFN？ was observed. By adjusting the pH of culture medium we fiu-ther showed that, dysfunction of NKT cells could simply be induced by low extracellular pH. Moreover, low extracellular pH inhibited NKT cell functions by inhibiting mammalian target of rapamycin （roTOR） signaling and nuclear translocation of promyelocytic leukemia zinc-finger （PLZF）. Together, our results suggest that tumor acidic microenvironments could interfere with NKT cell functions through metabolic controls.
Natural killer T cells are innate-like and tissue-resident lymphocytes, which recognize lipid antigens and are enriched in the liver. Natural killer T cells play important roles in infections, tumors, autoimmune disea...
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Natural killer T cells are innate-like and tissue-resident lymphocytes, which recognize lipid antigens and are enriched in the liver. Natural killer T cells play important roles in infections, tumors, autoimmune diseases, and metabolic diseases. In this study, we summarize recent findings on biology of natural killer T cells and their roles in hepatitis B virus and hepatitis C virus infection, autoimmune liver diseases, alcoholic liver disease, nonalcoholic fatty liver disease, and hepatocellular carcinoma. Controversial results from previous studies are discussed, and indicate the dynamic alteration in the role of natural killer T cells during the progression of liver diseases, which might be caused by changes in natural killer T subsets, factors skewing cytokine responses, and intercellular crosstalk between natural killer T cells and CDld-expressing cells or bystander cells.
The vehicular sensor network (VSN) is an important part of intelligent transportation, which is used for real-timedetection and operation control of vehicles and real-time transmission of data and information. In the ...
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The vehicular sensor network (VSN) is an important part of intelligent transportation, which is used for real-timedetection and operation control of vehicles and real-time transmission of data and information. In the environmentofVSN, massive private data generated by vehicles are transmitted in open channels and used by other vehicle users,so it is crucial to maintain high transmission efficiency and high confidentiality of data. To deal with this problem, inthis paper, we propose a heterogeneous fault-tolerant aggregate signcryption scheme with an equality test (HFTASET).The scheme combines fault-tolerant and aggregate signcryption,whichnot onlymakes up for the deficiency oflow security of aggregate signature, but alsomakes up for the deficiency that aggregate signcryption cannot tolerateinvalid signature. The scheme supports one verification pass when all signcryptions are valid, and it supportsunbounded aggregation when the total number of signcryptions grows dynamically. In addition, this schemesupports heterogeneous equality test, and realizes the access control of private data in different cryptographicenvironments, so as to achieve flexibility in the application of our scheme and realize the function of quick searchof plaintext or ciphertext. Then, the security of HFTAS-ET is demonstrated by strict theoretical analysis. Finally, weconduct strict and standardized experimental operation and performance evaluation, which shows that the schemehas better performance.
Metaflammation is responsible for several metabolic syndromes,such as type 2 ***,the mechanisms by which metabolic disorders trigger metaflammation remain *** identified a cell type-specific downregulation of CD1d exp...
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Metaflammation is responsible for several metabolic syndromes,such as type 2 ***,the mechanisms by which metabolic disorders trigger metaflammation remain *** identified a cell type-specific downregulation of CD1d expression in M2 macrophages during the progression of obesity prior to the onset of inflammation in visceral adipose tissues.A reduction in CD1d expression influenced the ability of M2 macrophages to present antigens and caused a change in antigen-presenting cells from M2 macrophages to M1 *** CD1d conditional knockout(KO)mice,we further demonstrated that natural killer T(NKT)cell activation by M2 macrophages inhibited metaflammation and insulin resistance by promoting Th2 responses and M2 polarization in visceral adipose tissues of obese mice,whereas NKT cell activation by M1 macrophages exacerbated metaflammation and insulin resistance by promoting Th1 responses and inhibiting M2 *** results suggest that an M2-specific reduction of CD1d is an initiating event that switches NKT cell-mediated immune responses and disrupts the immune balance in visceral adipose tissues in obese mice.
As the scale of training corpora for large language models (LLMs) grows, model developers become increasingly reluctant to disclose details on their data. This lack of transparency poses challenges to scientific evalu...
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Audio-Visual Question Answering (AVQA) is a challenging multimodal reasoning task requiring intelligent systems to answer natural language queries based on paired audio-video inputs accurately. However, existing AVQA ...
Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskde...
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Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.
The extraction of relationships between military entities and descriptive entities is a key task for automated construction of military knowledge graphs. This category of text unstructured imposed problems such as unf...
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Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been applied to this problem and significant i...
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Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been applied to this problem and significant improvements have been achieved. In this paper, we propose to view the generation of the global interaction between two texts as a recursive process: i.e. the interaction of two texts at each position is a composition of the interactions between their prefixes as well as the word level interaction at the current position. Based on this idea, we propose a novel deep architecture, namely Match-SRNN, to model the recursive matching structure. Firstly, a tensor is constructed to capture the word level interactions. Then a spatial RNN is applied to integrate the local interactions recursively, with importance determined by four types of gates. Finally, the matching score is calculated based on the global interaction. We show that, after degenerated to the exact matching scenario, Match-SRNN can approximate the dynamic programming process of longest common subsequence. Thus, there exists a clear interpretation for Match-SRNN. Our experiments on two semantic matching tasks showed the effectiveness of Match-SRNN, and its ability of visualizing the learned matching structure.
In this paper we report on our participation in the Trec 2019 Decision Track[1] which aims to provide a venue for research on retrieval methods that promote better decision making with search engines and develop new o...
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