Follicular helper T cells mediate IgE antibody response to airborne allergens

BACKGROUND: TH2 cells have long been believed to play a pivotal role in allergic immune responses, including IgE antibody production and type 2 cytokine-mediated inflammation and pathology. A new T-cell subset, follicular helper T (TFH) cells, is specialized in supporting B-cell maturation and antibody production. OBJECTIVE: We sought to investigate the roles of TFH cells in allergic immune responses. METHODS: Naive mice were exposed to cytokines or natural allergens through the airways. Development of allergic immune responses was analyzed by collecting draining lymph nodes and sera and by challenging the animals. Cytokine reporter mice and gene-deficient mice were used to dissect the immunologic mechanisms. RESULTS: We observed the development of IL-4-producing TFH cells and TH2 cells in draining lymph nodes after airway exposure to IL-1 family cytokines or natural allergens. TFH and TH2 cells demonstrated unique phenotypes, tissue localization, and cytokine responses. TFH cells supported the sustained production of IgE antibody in vivo in the absence of other T-cell subsets or even when TH2 cell functions were severely compromised. Conversely, conditional deficiency of the master regulator Bcl6 in CD4+ T cells resulted in a marked reduction in TFH cell numbers and IgE antibody levels, but type 2 cytokine responses and eosinophilic inflammation in the airways remained unaffected. CONCLUSION: TFH cells play critical roles in the regulation of IgE antibody production. Allergic immune responses to airborne allergens likely involve 2 distinct subsets of IL-4-producing CD4+ T cells, namely TFH and Th2 cells

Optimization of capacitive coupled Low Gain Avalanche Diode (AC-LGAD) sensors for precise time and spatial resolution

Capacitive-coupled Low-Gain Avalanche Diode (AC-LGAD) sensors are being developed for high-energy particle physics experiments as a detector which provides fast time information with fine spatial resolution. This paper describes optimizations of AC-LGAD sensor fabrication parameters, such as doping concentrations of the gain and electrode layers as well as the AC insulator capacitance, to realize $\mathcal{O}$(10)~\um{} spacial resolution, small charge cross talk to the neighboring electrodes, detection efficiency higher than 99\% at a 10$^{-4}$ fake rate and time resolution of about 30~ps. The radiation tolerance of the sensor is presented. In addition, further application to a device capable of visible and infra-red light detection is discussed.Comment: 11 pages, 25 figures, Submitted to Nuclear Instruments & Methods in physics research A (NIMA

Fabrication of SiO2/4H-SiC (0001) interface with nearly ideal capacitance-voltage characteristics by thermal oxidation

UTokyo Research掲載「次世代パワーデバイスの理想性能に近づく絶縁膜材料作製手法を開発」 URI: http://www.u-tokyo.ac.jp/ja/utokyo-research/research-news/advanced-dielectric-film-growth-technique-for-next-generation-power-devices/UTokyo Research "Advanced dielectric film growth technique for next generation power devices" URI: http://www.u-tokyo.ac.jp/en/utokyo-research/research-news/advanced-dielectric-film-growth-technique-for-next-generation-power-devices

Twitter User’s Hobby Estimation Based on Sequential Statements Using Deep Neural Networks

With more and more frequency, users communicate with each other on social media. Many users start on Twitter or Facebook to find friends who have the same hobby. Our study proposes a method to estimate the users’ interests (hobby) based on tweets on Twitter. One tweet does not, in and of itself, contain a lot of information, and some tweets are not related to the user’s hobby. Therefore, we propose a reliable hobby estimation method by extracting features from multiple, sequential tweets. The proposed method uses Recurrent Neural Networks (RNN) which can accommodate time-series information. We also used a Convolutional Neural Networks (CNN) which can treat contextual information. We used an averaged vector of word distributed representation as a feature. Using the proposed method based on Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN), we obtained a 23.72% improvement as compared with a baseline method using a Random Forest (RF) regression as a machine learning algorithm

Airway exposure initiates peanut allergy by involving the IL-1 pathway and T follicular helper cells in mice

BACKGROUND: Little is currently known regarding the immunologic mechanism(s) that initiate peanut allergy. Notably, peanut proteins have been detected in house dust, and their levels correlate with peanut allergy prevalence. OBJECTIVE: This study aimed to develop a new mouse model for peanut allergy and to investigate the immunologic mechanisms involved in peanut allergen sensitization. METHODS: To mimic environmental exposure, naive mice were exposed to peanut flour by inhalation for up to 4 weeks. We then analyzed serum levels of IgE antibody and challenged mice with peanut proteins. Immunological mechanisms involved in sensitization were analyzed using cytokine reporter mice, an adoptive cell transfer model, and gene knockout mice. RESULTS: When exposed to peanut flour by inhalation, both BALB/c and C57BL/6 mice developed peanut allergy, as demonstrated by the presence of peanut-specific IgE antibodies and manifestation of acute anaphylaxis on challenge. A large number of follicular helper T (Tfh) cells were also detected in draining lymph nodes of allergic mice. These cells produced IL-4 and IL-21, and they more robustly promoted peanut-specific IgE production than Th2 cells did. Genetic depletion of Tfh cells decreased IgE antibody levels and protected mice from anaphylaxis, without affecting Th2 cells. Furthermore, peanut flour exposure increased lung levels of IL-1α and IL-1β, and mice deficient in the receptor for these cytokines showed a significant decrease in Tfh cells compared with in wild-type mice. CONCLUSIONS: Tfh cells play a key role in peanut allergy, and the IL-1 pathway is involved in the Tfh response to peanut allergen exposure

MicroRNA-133 regulates the expression of GLUT4 by targeting KLF15 and is involved in metabolic control in cardiac myocytes

GLUT4 shows decreased levels in failing human adult hearts. We speculated that GLUT4 expression in cardiac muscle may be fine-tuned by microRNAs. Forced expression of miR-133 decreased GLUT4 expression and reduced insulin-mediated glucose uptake in cardiomyocytes. A computational miRNA target prediction algorithm showed that KLF15 is one of the targets of miR-133. It was confirmed that over-expression of miR-133 reduced the protein level of KLF15, which reduced the level of the downstream target GLUT4. Cardiac myocytes infected with lenti-decoy, in which the 3′UTR with tandem sequences complementary to miR-133 was linked to the luciferase reporter gene, had decreased miR-133 levels and increased levels of GLUT4. The expression levels of KLF15 and GLUT4 were decreased at the left ventricular hypertrophy and congestive heart failure stage in a rat model. The present results indicated that miR-133 regulates the expression of GLUT4 by targeting KLF15 and is involved in metabolic control in cardiomyocytes