An Earlier Predictive Rollover Index Designed for Bus Rollover Detection and Prevention

As vehicle rollovers annually cause a great deal of traffic-related deaths, an increasing number of vehicles are being equipped with rollover prevention systems with the aim of avoiding such accidents. To improve the functionality of active rollover prevention systems, this study provided a potential enhanced method with the intention to predict the tendency of the lateral load transfer ratio (LTR), which is the most common rollover index. This will help provide a certain amount of lead time for the control system to respond more effectively. Before the prediction process, an estimation equation was proposed to better estimate the LTR; the equation was validated using Simulink and TruckSim. Further, to eliminate the influence of drawbacks and make this method practical, a buffer operator was added. Simulation results showed that grey LTR (GLTR) was able to roundly predict the future trend of the LTR based on current and previous data. Under the tests of “Sine with Dwell” (Sindwell) and double lane change (DLC), the GLTR could provide the control system with sufficient time beforehand. Additionally, to further examine the performance of the GLTR, a differential system model was adopted to verify its effectiveness. Through the Sindwell maneuver, it was demonstrated that the GLTR index could improve the performance of the rollover prevention systems by achieving the expected response. Document type: Articl

Design of a high-resolution light field miniscope for volumetric imaging in scattering tissue

Integrating light field microscopy techniques with existing miniscope architectures has allowed for volumetric imaging of targeted brain regions in freely moving animals. However, the current design of light field miniscopes is limited by non-uniform resolution and long imaging path length. In an effort to overcome these limitations, this paper proposes an optimized Galilean-mode light field miniscope (Gali-MiniLFM), which achieves a more consistent resolution and a significantly shorter imaging path than its conventional counterparts. In addition, this paper provides a novel framework that incorporates the anticipated aberrations of the proposed Gali-MiniLFM into the point spread function (PSF) modeling. This more accurate PSF model can then be used in 3D reconstruction algorithms to further improve the resolution of the platform. Volumetric imaging in the brain necessitates the consideration of the effects of scattering. We conduct Monte Carlo simulations to demonstrate the robustness of the proposed Gali-MiniLFM for volumetric imaging in scattering tissue.https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-11-3-1662&id=427971https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-11-3-1662&id=427971Published versio

Novel NIR-II organic fluorophores for bioimaging beyond 1550 nm

This work was partially supported by grants from NSFC (81773674, 81573383, and 21473041), NSFHP (2017CFA024, 2017CFB711, and 2016ACA126), the Applied Basic Research Program of WMBST (2019020701011429), Tibet Autonomous Region Science and Technology Plan Project Key Project (XZ201901-GB-11), Project First-Class Disciplines Development Supported by Chengdu University of Traditional Chinese Medicine (CZYJC1903), and Health Commission of Hubei Province Scientific Research Project (WJ2019M177 and WJ2019M178).Peer reviewedPublisher PD

Microbiome-derived bile acids contribute to elevated antigenic response and bone erosion in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, disabling and incurable autoimmune disease. It has been widely recognized that gut microbial dysbiosis is an important contributor to the pathogenesis of RA, although distinct alterations in microbiota have been associated with this disease. Yet, the metabolites that mediate the impacts of the gut microbiome on RA are less well understood. Here, with microbial profiling and non-targeted metabolomics, we revealed profound yet diverse perturbation of the gut microbiome and metabolome in RA patients in a discovery set. In the Bacteroides-dominated RA patients, differentiation of gut microbiome resulted in distinct bile acid profiles compared to healthy subjects. Predominated Bacteroides species expressing BSH and 7a-HSDH increased, leading to elevated secondary bile acid production in this subgroup of RA patients. Reduced serum fibroblast growth factor-19 and dysregulated bile acids were evidence of impaired farnesoid X receptor-mediated signaling in the patients. This gut microbiota-bile acid axis was correlated to ACPA. The patients from the validation sets demonstrated that ACPA-positive patients have more abundant bacteria expressing BSH and 7a-HSDH but less Clostridium scindens expressing 7a-dehydroxylation enzymes, together with dysregulated microbial bile acid metabolism and more severe bone erosion than ACPA-negative ones. Mediation analyses revealed putative causal relationships between the gut microbiome, bile acids, and ACPA-positive RA, supporting a potential causal effect of Bacteroides species in increasing levels of ACPA and bone erosion mediated via disturbing bile acid metabolism. These results provide insights into the role of gut dysbiosis in RA in a manifestation-specific manner, as well as the functions of bile acids in this gut-joint axis, which may be a potential intervention target for precisely controlling RA conditions.Comment: 38 pages, 6 figure

Global intron retention mediated gene regulation during CD4+ T cell activation.

T cell activation is a well-established model for studying cellular responses to exogenous stimulation. Using strand-specific RNA-seq, we observed that intron retention is prevalent in polyadenylated transcripts in resting CD4(+) T cells and is significantly reduced upon T cell activation. Several lines of evidence suggest that intron-retained transcripts are less stable than fully spliced transcripts. Strikingly, the decrease in intron retention (IR) levels correlate with the increase in steady-state mRNA levels. Further, the majority of the genes upregulated in activated T cells are accompanied by a significant reduction in IR. Of these 1583 genes, 185 genes are predominantly regulated at the IR level, and highly enriched in the proteasome pathway, which is essential for proper T cell proliferation and cytokine release. These observations were corroborated in both human and mouse CD4(+) T cells. Our study revealed a novel post-transcriptional regulatory mechanism that may potentially contribute to coordinated and/or quick cellular responses to extracellular stimuli such as an acute infection

Overexpression of LCMR1 is significantly associated with clinical stage in human NSCLC

<p>Abstract</p> <p>Background</p> <p>Lung cancer is one of the most common human cancers and the leading cause of cancer death worldwide. The identification of lung cancer associated genes is essential for lung cancer diagnosis and treatment.</p> <p>Methods</p> <p>Differential Display-PCR technique was used to achieve the novel cDNA, which were then verified by real-time PCR. Northern blot was utilized to observe the expression of LCMR1 in different human tissues. 84 cases human NSCLC tissues and normal counterparts were analyzed for the expression of LCMR1 by immunohistochemistry.</p> <p>Results</p> <p>A novel 778-bp cDNA fragment from human large cell lung carcinoma cell lines 95C and 95D was obtained, and named <it>LCMR1 </it>(Lung Cancer Metastasis Related protein 1). LCMR1 was differentially expressed in different human tissues. LCMR1 was strongly overexpressed in NSCLC and its expression was significantly associated with clinical stage.</p> <p>Conclusion</p> <p>Our data indicated that <it>LCMR1</it>, strongly overexpressed in NSCLC, might have applications in the clinical diagnosis and treatment of lung cancer.</p

Genetic Diversity and Phylogeny of Antagonistic Bacteria against Phytophthora nicotianae Isolated from Tobacco Rhizosphere

The genetic diversity of antagonistic bacteria from the tobacco rhizosphere was examined by BOXAIR-PCR, 16S-RFLP, 16S rRNA sequence homology and phylogenetic analysis methods. These studies revealed that 4.01% of the 6652 tested had some inhibitory activity against Phytophthora nicotianae. BOXAIR-PCR analysis revealed 35 distinct amplimers aligning at a 91% similarity level, reflecting a high degree of genotypic diversity among the antagonistic bacteria. A total of 25 16S-RFLP patterns were identified representing over 33 species from 17 different genera. Our results also found a significant amount of bacterial diversity among the antagonistic bacteria compared to other published reports. For the first time; Delftia tsuruhatensis, Stenotrophomonas maltophilia, Advenella incenata, Bacillus altitudinis, Kocuria palustris, Bacillus licheniformis, Agrobacterium tumefaciens and Myroides odoratimimus are reported to display antagonistic activity towards Phytophthora nicotianae. Furthermore, the majority (75%) of the isolates assayed for antagonistic activity were Gram-positives compared to only 25% that were Gram-negative bacteria

Persistent sulfate formation from London Fog to Chinese haze

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world

Comparative Studies on Feature Extraction Methods for Multispectral Remote Sensing Image Classification

Abstract – Feature extraction of multispectral remote sensing image is an important task before classifying the image. When land areas are clustered into groups of similar land cover, one of the most important things is to extract the key features of a given image. Usually multispectral remote sensing images have many bands, and there may have been much redundancy information and it becomes difficult to extract the key features of the image. Therefore, it is necessary to study methods regarding how to extract the main features of the image effectively. In this paper, five methods are comparatively studied to reduce the multi-bands into lower dimensions in order to extract the most available features. These methods include the Euclid distance measurement (EDM), the discrete measurement criteria function (DMCF), the minimum differentiated entropy (MDE), the probability distance criterion (PDC), and the principle component analysis (PCA) method. The advantage and disadvantage of each method are evaluated by the classification results