Revisiting the Concept of Targeting NFAT to Control T Cell Immunity and Autoimmune Diseases

The nuclear factor of activated T cells (NFAT) family of transcription factors, which includes NFAT1, NFAT2, and NFAT4, are well-known to play important roles in T cell activation. Most of NFAT proteins are controlled by calcium influx upon T cell receptor and costimulatory signaling results increase of IL-2 and IL-2 receptor. NFAT3 however is not shown to be expressed in T cells and NFAT5 has not much highlighted in T cell functions yet. Recent studies demonstrate that the NFAT family proteins involve in function of lineage-specific transcription factors during differentiation of T helper 1 (Th1), Th2, Th17, regulatory T (Treg), and follicular helper T cells (Tfh). They have been studied to make physical interaction with the other transcription factors like GATA3 or Foxp3 and they also regulate Th cell signature gene expressions by direct binding on promotor region of target genes. From last decades, NFAT functions in T cells have been targeted to develop immune modulatory drugs for controlling T cell immunity in autoimmune diseases like cyclosporine A, FK506, etc. Due to their undesirable side defects, only limited application is available in human diseases. This review focuses on the recent advances in development of NFAT targeting drug as well as our understanding of each NFAT family protein in T cell biology. We also discuss updated detail molecular mechanism of NFAT functions in T cells, which would lead us to suggest an idea for developing specific NFAT inhibitors as a therapeutic drug for autoimmune diseases

The Effects of Loranthus parasiticus

This study is undertaken to evaluate cognitive enhancing effect and neuroprotective effect of Loranthus parasiticus. Cognitive enhancing effect of Loranthus parasiticus was investigated on scopolamine-induced amnesia model in Morris water maze test and passive avoidance test. We also examined the neuroprotective effect on glutamate-induced cell death in HT22 cells by MTT assay. These results of Morris water maze test and passive avoidance test indicated that 10 and 50 mg/kg of Loranthus parasiticus reversed scopolamine-induced memory deficits. Loranthus parasiticus also protected against glutamate-induced cytotoxicity in HT22 cells. As a result of in vitro test for elucidating possible mechanism, Loranthus parasiticus inhibited AChE activity, ROS production, and Ca2+ accumulation. Loranthus parasiticus showed memory enhancing effect and neuroprotective effect and these effects may be related to inhibition of AChE activity, ROS level, and Ca2+ influx

A Multi-Mode ULP Receiver Based on an Injection-Locked Oscillator for IoT Applications

This paper presents an ultra-low-power receiver based on the injection-locked oscillator (ILO), which is compatible with multiple modulation schemes such as on-off keying (OOK), binary frequency-shift keying (BFSK), and differential binary phase-shift keying (DBPSK). The receiver has been fabricated in 0.18-μm CMOS technology and operates in the ISM band of 2.4 GHz. A simple envelope detection can be used even for the demodulation of BFSK and DBPSK signals due to the conversion capability of the ILO from the frequency and phase to the amplitude. In the proposed receiver, a Q-enhanced single-ended-to-differential amplifier is employed to provide high-gain amplification as well as narrow band-pass filtering, which improves the sensitivity and selectivity of the receiver. In addition, a gain-control loop is formed in the receiver to maintain constant lock range and hence frequency-to-amplitude conversion ratio for the varying power of the BFSK-modulated receiver input signal. The receiver achieves the sensitivity of -87, -85, and -82 dBm for the OOK, BFSK, and DBPSK signals respectively at the data rate of 50 kb/s and the BER lower than 0.1% while consuming the power of 324 μW in total.1

Surface currents from hourly variations of suspended particulate matter from Geostationary Ocean Color Imager data

Surface currents in Korean coastal regions were obtained using the maximum cross-correlation method applied to hourly suspended particulate matter images from the Geostationary Ocean Color Imager. Preliminary current vectors were filtered out by applying a series of quality-control procedures. The current vectors resulting from the tests were compared with the currents from a numerical model with tide and wind field. It was found that the estimated currents were more similarly to the currents caused by both tide and wind. A high degree of discrepancy was detected in regions of strong tidal currents, where the fundamental assumption of horizontal movement was limited due to the dominant vertical tidal mixing in the shallow region. The hourly rotations of the current vectors within a day were clarified by a comparison of the time-varying orientation angles of tidal ellipses. This study emphasized how to understand the short-term surface flows from hourly high-resolution geostationary satellite images

Charge-spin correlation in van der Waals antiferromagenet NiPS3

Strong charge-spin coupling is found in a layered transition-metal trichalcogenide NiPS3, a van derWaals antiferromagnet, from our study of the electronic structure using several experimental and theoretical tools: spectroscopic ellipsometry, x-ray absorption and photoemission spectroscopy, and density-functional calculations. NiPS3 displays an anomalous shift in the optical spectral weight at the magnetic ordering temperature, reflecting a strong coupling between the electronic and magnetic structures. X-ray absorption, photoemission and optical spectra support a self-doped ground state in NiPS3. Our work demonstrates that layered transition-metal trichalcogenide magnets are a useful candidate for the study of correlated-electron physics in two-dimensional magnetic material.Comment: 6 pages, 3 figur

*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants

Background: Modern biology uses experimental systems that involve the exploration of phenotypic variation as a result of the recombination of several genomes. Such systems are useful to investigate the functional evolution of metabolic networks. One such approach is the analysis of transcript and metabolite profiles. These kinds of studies generate a large amount of data, which require dedicated computational tools for their analysis.Results: This paper presents a novel software named *omeSOM (transcript/metabol-ome Self Organizing Map) that implements a neural model for biological data clustering and visualization. It allows the discovery of relationships between changes in transcripts and metabolites of crop plants harboring introgressed exotic alleles and furthermore, its use can be extended to other type of omics data. The software is focused on the easy identification of groups including different molecular entities, independently of the number of clusters formed. The *omeSOM software provides easy-to-visualize interfaces for the identification of coordinated variations in the co-expressed genes and co-accumulated metabolites. Additionally, this information is linked to the most widely used gene annotation and metabolic pathway databases.Conclusions: *omeSOM is a software designed to give support to the data mining task of metabolic and transcriptional datasets derived from different databases. It provides a user-friendly interface and offers several visualization features, easy to understand by non-expert users. Therefore, *omeSOM provides support for data mining tasks and it is applicable to basic research as well as applied breeding programs. The software and a sample dataset are available free of charge at http://sourcesinc.sourceforge.net/omesom/.Fil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; ArgentinaFil: Kamenetzky, Laura. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: López, Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Lee, Je M.. Cornell University; Estados UnidosFil: Giovannoni, James J.. Cornell University; Estados UnidosFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentin