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Invariant NKT cells (iNKT cells) are a unique subset of T lymphocytes that rapidly carry out effector functions. In this study, we report that a majority of sterile house dust extracts (HDEs) tested contained antigens capable of activating mouse and human iNKT cells. HDEs had adjuvant-like properties in an ovalbumin (OVA)-induced asthma model, which were(More)
Natural killer T cells (NKT cells) recognize glycolipid antigens presented by CD1d. These cells express an evolutionarily conserved, invariant T cell antigen receptor (TCR), but the forces that drive TCR conservation have remained uncertain. Here we show that NKT cells recognized diacylglycerol-containing glycolipids from Streptococcus pneumoniae, the(More)
Invariant natural killer T (iNKT) cells are an evolutionary conserved T cell population characterized by features of both the innate and adaptive immune response. Studies have shown that iNKT cells are required for protective responses to Gram-positive pathogens such as Streptococcus pneumoniae, and that these cells recognize bacterial diacylglycerol(More)
Autophagy regulates cell differentiation, proliferation, and survival in multiple cell types, including cells of the immune system. In this study, we examined the effects of a disruption of autophagy on the differentiation of invariant NKT (iNKT) cells. Using mice with a T lymphocyte-specific deletion of Atg5 or Atg7, two members of the macroautophagic(More)
BACKGROUND Integrated 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is widely performed for staging solitary pulmonary nodules (SPNs). However, the diagnostic efficacy of SPNs based on PET/CT is not optimal. Here, we propose a method of detection based on PET/CT that can differentiate malignant and benign SPNs with(More)
—To avoid the drawbacks caused by the long-distance and large-area features of the outdoor forest fires in the traditional fire detection methods. A new forest fire recognition method based on the neural network is proposed, which recognizes the fire based on the static and dynamic features of the fire. The method combines the multiple parameters of the(More)
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