Taken together, our results reveal that P. aeruginosa DnaK potently upregulates EBI3 expression, which in turn drives production of the prominent anti-inflammatory cytokine IL-27, as a consequence of TLR4-dependent activation of NF-κB and TLR4-independent activation of the Akt signaling pathway.Luminescent organic-inorganic hybrids containing lanthanides (Ln3+) have been prominent for applications such as luminescent bio-probes in biological assays. In this sense, a luminescent hybrid based on dense silica (SiO2) nanospheres decorated with Eu3+ β-diketonate complexes using dibenzoylmethane (Hdbm) as a luminescent antenna was developed by using a hierarchical organization in four steps (i) anchoring of 3-aminopropyltriethoxysilane (APTES) organosilane on the SiO2 surface, (ii) formation of a carboxylic acid ligand, (iii) coordination of Eu3+ to the carboxylate groups and (iv) coordination of dbm- to Eu3+. The hybrid structure was elucidated through the correlation of thermogravimetry, silicon nuclear magnetic resonance and photoluminescence. Results indicate that the carboxylic acid-Eu3+-dbm hybrid was formed on the surface of the particles with no detectable changes on their size or shape after all the four steps (average size of 32 ± 7 nm). A surface charge of -27.8 mV was achieved for the hybrid, assuring a stable suspension in aqueous media. The Eu3+ complex provides intense red luminescence, characteristic of Eu3+5D0→7FJ electronic transitions, with an intrinsic emission quantum yield of 38%, even in an aqueous suspension. Therefore, the correlation of luminescence, structure, particle morphology and fluorescence microscopy images make the hybrid promising for application in bioimaging.Reverse transcription quantitative polymerase chain reaction (RT-qPCR) enables the monitoring of changes in cell phenotype via the high-throughput screening of numerous genes. RT-qPCR is a fundamental approach in numerous research fields, including biomaterials, yet little attention has been given to the potential impact of 3D versus monolayer (2D) cell culture and to the requirement for a constant validation of the multiple steps of gene expression analysis. The aim of this study is to use high-quality RNA to identify the most suitable reference genes for RT-qPCR analysis during the osteogenic differentiation of human bone marrow mesenchymal stem/stromal cells (BM-MSCs). BM-MSCs are cultured under osteogenic conditions for 28 days in 2D or within hyaluronic acid hydrogels (3D). RNA is subject to quality controls and is then used to identify the most stable reference genes using geNorm, NormFinder, and the ∆Cq method. The effect of the reverse transcriptase is investigated, as well as the expression of osteogenic-related markers. This study shows marked differences in the stability of reference genes between 2D (RPLP0/GAPDH) and 3D (OAZ1/PPIA) culture, suggesting that it is critical to choose appropriate reference genes for 3D osteogenic cell cultures. Thus, a thorough validation under specific experimental settings is essential to obtain meaningful gene expression results.The emergence of Low-Power Wide-Area Network (LPWAN) technologies allowed the development of revolutionary Internet Of Things (IoT) applications covering large areas with thousands of devices. However, connectivity may be a challenge for non-line-of-sight indoor operation or for areas without good coverage. Technologies such as LoRa and Sigfox allow connectivity for up to 50,000 devices per cell, several devices that may be exceeded in many scenarios. To deal with these problems, this paper introduces a new multi-hop protocol, called JMAC, designed for improving long range wireless communication networks that may support monitoring in scenarios such smart cities or Industry 4.0. JMAC uses the LoRa radio technology to keep low consumption and extend coverage area, and exploits the potential mesh behaviour of wireless networks to improve coverage and increase the number of supported devices per cell. JMAC is based on predictive wake-up to reach long lifetime on sensor devices. Our proposal was validated using the OMNeT++ simulator to analyze how it performs under different conditions with promising results.An accurate vehicle driving state observer is a necessary condition for a safe automotive electronic control system. Vehicle driving state observer is challenged by unknown measurement noise and transient disturbances caused by complex working conditions and sensor failure. For the classical adaptive unscented Kalman filter (AUKF) algorithm, transient disturbances will cause the failure of state estimation and affect the subsequent process. This paper proposes an AUKF based on a modified Sage-Husa filter and divergence calculation technique for multi-dimensional vehicle driving state observation. Based on the seven-degrees-of-freedom vehicle model and the Dugoff tire model, the proposed algorithm corrects the measurement noise by using modified Sage-Husa maximum posteriori. To reduce the influence of transient disturbance on the subsequent process, covariance matrix is updated after divergence is detected. selleck compound The effectiveness of the algorithm is tested on the double lane change and Sine Wave road conditions. The robustness of the algorithm is tested under severe transient disturbance. The results demonstrate that the modified Sage-Husa UKF algorithm can accurately detect transient disturbance and effectively reduce the resulted accumulated error. Compared to classical AUKF, our algorithm significantly improves the accuracy and robustness of vehicle driving state estimation. The research in this paper provides a reference for multi-dimensional data processing under changeable vehicle driving states.According to data from the U.S. National Cancer Institute, cancer is one of the leading causes of death worldwide with approximately 14 million new cases and 8.2 million cancer-related deaths in 2018. More than 60% of the new annual cases in the world occur in Africa, Asia, Central America, and South America, with 70% of cancer deaths in these regions. Breast cancer is the most common cancer in women, with 266,120 new cases in American women and an estimated 40,920 deaths for 2018. Approximately one in six women diagnosed with breast cancer will die in the coming years. Recently, novel therapeutic strategies have been implemented in the fight against breast cancer, including molecules able to block signaling pathways, an inhibitor of poly [ADP-ribose] polymerase (PARP), growth receptor blocker antibodies, or those that reactivate the immune system by inhibiting the activities of inhibitory receptors like cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed death protein 1 (PD-1). However, novel targets include reactivating the Th1 immune response, changing tumor microenvironment, and co-activation of other components of the immune response such as natural killer cells and CD8+ T cells among others.