Exopolysaccharide of Enterococcus faecium L15 promotes the osteogenic differentiation of human dental pulp stem cells via p38 MAPK pathway

Abstract Background Bone has important functions in the body. Several researchers have reported that the polysaccharides and lipopolysaccharide derived from microbes can promote osteogenic differentiation of stem cells. Enterococcus faecium, a lactic acid bacterium (LAB), produces several bioactive metabolites and has been widely applied in the food and nutraceutical industries. The exopolysaccharide (EPS) from LAB has also been extensively examined for its postbiotic effects and for its in vivo and in vitro functionalities. However, studies on promoting bone differentiation using polysaccharides from LAB are lacking. Therefore, the purpose of this study was to investigate the effect of E. faecium L15 extract and EPS on osteogenic differentiation of human dental pulp stem cells (hDPSCs) and to identify the underlying mechanisms. Methods hDPSCs were obtained from dental pulp tissue, and L15 extract and EPS were isolated from L15. Gene and protein expression of the osteogenic differentiation markers were analyzed with qPCR and western blotting and the possible signaling pathways were also investigated using western blotting. Osteogenic differentiation potential was examined by alkaline phosphatase (ALP) staining and alizarin red s (ARS) staining. In addition, osteogenic differentiation potential of L15 EPS was explored in ex vivo culture of neonate murine calvaria. Results The calcium deposition and ALP activity were enhanced by addition of L15 extract or EPS. The expression levels of RUNX2, ALP, and COL1A1 mRNA and the protein expression levels of RUNX2, ALP, and BMP4 were increased in hDPSCs treated with the L15 extract or EPS. The L15 EPS treatment enhanced phosphorylation of the p38 mitogen-activated protein kinase (MAPK). The L15 EPS-induced increases in RUNX2, ALP, and BMP4 expression were suppressed by the p38 MAPK inhibitor SB203580. The promoting effect of L15 EPS on osteogenic differentiation was not only seen in hDPSCs, but also in osteoblast precursors. ALP activity and the expression of RUNX2, ALP, and COL1A1 increased in the L15 EPS-treated osteoblast precursors. In addition, L15 EPS increased bone thickness of neonate murine calvaria in ex vivo culture. Conclusions The stimulatory effect of L15 extract and EPS on osteogenic differentiation occurred through the p38 MAPK pathway, and L15 EPS enhanced new bone formation in neonate murine calvaria. These data suggest that L15 EPS has therapeutic potential applicable to bone regeneration

Aptamer-based single-molecule imaging of insulin receptors in living cells

We present a single-molecule imaging platform that quantitatively explores the spatiotemporal dynamics of individual insulin receptors in living cells. Modified DNA aptamers that specifically recognize insulin receptors (IRs) with a high affinity were selected through the SELEX process. Using quantum dot-labeled aptamers, we successfully imaged and analyzed the diffusive motions of individual IRs in the plasma membranes of a variety of cell lines (HIR, HEK293, HepG2). We further explored the cholesterol-dependent movement of IRs to address whether cholesterol depletion interferes with IRs and found that cholesterol depletion of the plasma membrane by methyl-??-cyclodextrin reduces the mobility of IRs. The aptamer-based single-molecule imaging of IRs will provide better understanding of insulin signal transduction through the dynamics study of IRs in the plasma membrane.open1

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's TEMPO and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)

Exopolysaccharide Isolated from Lactobacillus plantarum L-14 Has Anti-Inflammatory Effects via the Toll-Like Receptor 4 Pathway in LPS-Induced RAW 264.7 Cells

Inflammation is a biological response of the immune system to defend the body from negative stimulation. However, the excessive inflammatory response can damage host tissues and pose serious threats. Exopolysaccharide (EPS), one of the postbiotics, is secreted from lactic acid bacteria. Although many studies have described the beneficial effects of EPS, such as its anti-inflammatory and anti-oxidant effects, its underlying mechanisms have remained to be poorly understood. Thus, we identified that EPS obtained from Lactobacillus plantarum L-14 was a homogeneous polysaccharide primarily comprised of glucose. To examine these anti-inflammatory effects, an inflammatory response was induced by lipopolysaccharide (LPS) administration to mouse macrophage RAW 264.7 cells that were pretreated with EPS. The anti-inflammatory effects of EPS were identified by analyzing the changes within inflammatory markers at the molecular level. We demonstrate here that EPS suppressed proinflammatory mediators, such as cyclooxygenase-2, interleukin-6, tumor necrosis factor-α, and interleukin-1β, and downregulated the expression of an inducible nitric oxide synthase known to lead to oxidative stress. It was also confirmed that EPS had anti-inflammatory effects by blocking the interaction of LPS with Toll-like receptor 4 (TLR4), as demonstrated by using the known TLR4 inhibitor TAK-242. In addition, we found that EPS itself could suppress the expression of TLR4. Consequently, our data suggest that EPS can be a potential target for the development of natural product-derived medicine for treating inflammatory diseases related to TLR4

Functional selectivity and integration across affective and cognitive processes in the insula

Functional selectivity and integration across affective and cognitive processes in the insula: * This study was conducted as part of the Affective Neuroimaging Consortium (ANiC), a new collaborative data-sharing initiative for task-based neuroimaging data for affective process. For the full list of collaborators and instructions to join the consortium, please visit us at our website (www.anic.science)

Representations of emotion concepts: Comparison across pairwise, appraisal feature-based, and word embedding-based similarity spaces

A question that has long interested cognitive scientists is how to best represent the different emotions we experience and attribute to others. For example, constructionist and appraisal theories propose that differences between emotions can be captured in part by their variation along a set of appraisal dimensions. More recently, researchers have used language models to capture the differences across different emotion terms. Both approaches allow us to represent emotions as occupying different locations in high-dimensional representational spaces. To ask how well these different approaches capture the similarity between emotion concepts, we collected pairwise similarity and appraisal feature ratings for 58 different emotion concepts and then employed representational similarity analysis to investigate the overlap between people’s pairwise similarity judgments and emotion similarity in a 14-dimensional appraisal space and three word embedding spaces from two word2vec models (300 dimensions) and the newer GPT-3 model (12288 dimensions). The results indicate that while there is a high correlation between appraisal feature-based similarity and pairwise similarity judgments, word embedding-based similarity exhibits lower correlations, though GPT-3 showed much better performance than the word2vec models. Finally, characterizing the errors made by word embedding models showed that they can be largely attributed to an over-reliance on the valence of emotion concepts

The relationships between capabilities and values of big data analytics

This study aims to investigate the effect of big data analytics capability on big data values and business performance from the organizations performing big data analytics, which is one of the leading technologies in the fourth industrial revolution. For this study, the values of big data include transactional, strategic, transformational, and informational values. We conducted a survey and analyzed data from 200 professionals in organizations who had the experience of performing big data analytics. Structural equation modeling is used to test the research hypotheses. The results suggest that big data analytics capability has positive relationships with values of big data analytics and business performance. Of the values of big data analytics, however, the informational value of big data does not affect business performance. The results of this research are expected to provide researchers and practitioners who are interested in big data with useful information