Characteristics of DNA-AuNP networks on cell membranes and real-time movies for viral infection

AbstractThis data article provides complementary data for the article entitled “DNA-AuNP networks on cell membranes as a protective barrier to inhibit viral attachment, entry and budding” Li et al. (2016) [1]. The experimental methods for the preparation and characterization of DNA-conjugated nanoparticle networks on cell membranes were described. Confocal fluorescence images, agarose gel electrophoresis images and hydrodynamic diameter of DNA-conjugated gold nanoparticle (DNA-AuNP) networks were presented. In addition, we have prepared QDs-labeled RSV (QDs-RSV) to real-time monitor the RSV infection on HEp-2 cells in the absence and presence of DNA-AuNP networks. Finally, the cell viability of HEp-2 cells coated by six types of DNA-nanoparticle networks was determined after RSV infection

Innovative and Responsible Governance of Nanotechnology for Societal Development

The one-pot synthesis of iron-doped carbon quantum dots (Fe-CQDs) for use as both magnetic resonance (MR) and fluorescent (dual-mode) imaging nanoprobes is described. Comprehensive characterizations of the material confirmed the successful doping of the CQDs with Fe(II) ions. The imaging probe has a longitudinal relaxivity of 3.92 mM−1∙s−1 and a low r2/r1 ratio of 1.27, both of which are critical for T1-weighted contrast agents. The maximum emission of Fe-CQDs locates at 450 nm under 375 nm excitation, which also can be applied to fluorescence imaging. Biotoxicity assessment showed good biocompatibility of the Fe-CQDs. The in-vitro experiments with A549 cells indicated that the Fe-CQDs are viable candidates as dual-mode (MR/fluorescence) imaging nanoprobes. For in-vivo experiments, they exhibit high contrast efficiency, thereby improving the positive contrast in T1-weighted MR images. In-vivo time-dependent MRI of major organs showed that the Fe-CQDs undergo fast glomerular filtration and can evade immuno-absorption due to their ultra-small size and excellent biocompatibility. [Figure not available: see fulltext.]

Transcriptomic profiling suggests candidate molecular responses to waterlogging in cassava

Owing to climate change impacts, waterlogging is a serious abiotic stress that affects crops, resulting in stunted growth and loss of productivity. Cassava (Manihot esculenta Grantz) is usually grown in areas that experience high amounts of rainfall; however, little research has been done on the waterlogging tolerance mechanism of this species. Therefore, we investigated the physiological responses of cassava plants to waterlogging stress and analyzed global gene transcription responses in the leaves and roots of waterlogged cassava plants. The results showed that waterlogging stress significantly decreased the leaf chlorophyll content, caused premature senescence, and increased the activities of superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) in the leaves and roots. In total, 2538 differentially expressed genes (DEGs) were detected in the leaves and 13364 in the roots, with 1523 genes shared between the two tissues. Comparative analysis revealed that the DEGs were related mainly to photosynthesis, amino metabolism, RNA transport and degradation. We also summarized the functions of the pathways that respond to waterlogging and are involved in photosynthesis, glycolysis and galactose metabolism. Additionally, many transcription factors (TFs), such as MYBs, AP2/ERFs, WRKYs and NACs, were identified, suggesting that they potentially function in the waterlogging response in cassava. The expression of 12 randomly selected genes evaluated via both quantitative real-time PCR (qRT-PCR) and RNA sequencing (RNA-seq) was highly correlated (R2 = 0.9077), validating the reliability of the RNA-seq results. The potential waterlogging stress-related transcripts identified in this study are representatives of candidate genes and molecular resources for further understanding the molecular mechanisms underlying the waterlogging response in cassava

An Optimized Coordination Strategy between Line Main Protection and Hybrid DC Breakers for VSC-Based DC Grids Using Overhead Transmission Lines

Compared with alternating current (AC) power grids, the voltage-sourced converter (VSC)-based direct current (DC) grid is a system characterized by “low damping„, as a result, once there is a short-circuit fault on the DC transmission line, the fault current will rise more sharply and the influence range will be much wider within the same time scale. Moreover the phenomenon that a local fault causes a whole power grid outage is more likely to occur. Overhead transmission lines (OHLs) have been regarded as the mainstream form of power transmission in future high-voltage, large-capacity and long-distance VSC-based DC grids. However, the application of overhead transmission lines will inevitably lead to a great increase in the probability of DC line failure. Therefore, research on how to isolate the DC fault line quickly is of great significance. Based on the technology route for fault line isolation using DC breakers, on the basis of in-depth analysis of traditional coordination strategy, an optimized coordination strategy between line main protection and a hybrid DC breaker for VSC-based DC grids using overhead transmission lines is proposed in this paper, which takes the start-up output signal of line main protection as the pre-operation instruction of the corresponding hybrid DC breaker. As a result, the risks of blockage of the modular multilevel converter (MMC) closer to the fault position and of damage to power electronic devices in main equipment can be reduced effectively. Finally, the proposed coordination strategy was verified and analyzed through simulation

Comprehensive analyses of glycolysis-related lncRNAs for ovarian cancer patients

Abstract Background Not only glycolysis but also lncRNAs play a significant role in the growth, proliferation, invasion and metastasis of of ovarian cancer (OC). However, researches about glycolysis -related lncRNAs (GRLs) remain unclear in OC. Herein, we first constructed a GRL-based risk model for patients with OC. Methods The processed RNA sequencing (RNA-seq) profiles with clinicopathological data were downloaded from TCGA and glycolysis-related genes (GRGs) were obtained from MSigDB. Pearson correlation coefficient between glycolysis-related genes (GRGs) and annotated lncRNAs (|r| > 0.4 and p < 0.05) were calculated to identify GRLs. After screening prognostic GRLs, a risk model based on five GRLs was constructed using Univariate and Cox regression. The identified risk model was validated by two validation sets. Further, the differences in clinicopathology, biological function, hypoxia score, immune microenvironment, immune checkpoint, immune checkpoint blockade, chemotherapy drug sensitivity, N6-methyladenosine (m6A) regulators, and ferroptosis-related genes between risk groups were explored by abundant algorithms. Finally, we established networks based on co-expression, ceRNA, cis and trans interaction. Results A total of 535 GRLs were gained and 35 GRLs with significant prognostic value were identified. The prognostic signature containing five GRLs was constructed and validated and can predict prognosis. The nomogram proved the accuracy of the model for predicting prognosis. After computing hypoxia score of each sample by ssGSEA, we found patients with higher risk scores exhibited higher hypoxia score and high hypoxia score was a risk factor. It was revealed that a total of 21 microenvironment cells (such as Central memory CD4 T cell, Neutrophil, Regulatory T cell and so on) and Stromal score had significant differences between the two groups. Four immune checkpoint genes (CD274, LAG3, VTCN1, and CD47) showed disparate expression levels in the two groups. Besides, 16 m6A regulators and 126 ferroptosis-related genes were expressed higher in the low-risk group. GSEA revealed that the risk groups were associated with tumor-related pathways. The two risk groups were confirmed to be sensitive to several chemotherapeutic agents and patients in the low-risk group were more sensitive to ICB therapy. The networks based on co-expression, ceRNA, cis and trans interaction provided insights into the regulatory mechanisms of GRLs. Conclusions Our identified and validated risk model based on five GRLs is an independent prognostic factor for OC patients. Through comprehensive analyses, findings of our study uncovered potential biomarker and therapeutic target for the risk model based on the GRLs

Quantum yield and lifetime data analysis for the UV curable quantum dot nanocomposites

The quantum yield (QY) and lifetime are the important parameters for the photoluminescent materials. The data here report the changes of the QY and lifetime for the quantum dot (QD) nanocomposite after the UV curing of the urethane acrylate prepolymer. The data were collected based on the water soluble CdTe QDs and urethane acrylate prepolymer. Colloidal QDs were in various concentration from 0.5×10−3 molL−1 to 10×10−3 molL−1, and 1% (wt%) 1173 was the photoinitiator. The QY before the curing was 56.3%, 57.8% and 58.6% for the QDs 510 nm, 540 nm and 620 nm, respectively. The QY after the curing was changed to 8.9%, 9.6% and 13.4% for the QDs 510 nm, 540 nm and 620 nm, respectively. Lifetime data showed that the lifetime was changed from 23.71 ns, 24.55 ns, 23.52 ns to 1.29 ns, 2.74 ns, 2.45 ns for the QDs 510 nm, 540 nm and 620 nm, respectively

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Background. Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. Methods. The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the “limma” R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. Results. An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. Conclusion. In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC

Quantitative evaluation of protective antibody response induced by hepatitis E vaccine in humans

The authors provide a comprehensive characterization of the human antibody response to a licensed hepatitis E virus (HEV) vaccine, Hecolin, in four individuals over the course of six months post vaccination. They demonstrate diverse patterns of antibody response underlying the vaccine protection

Characterizing the epidemiology, virology, and clinical features of influenza in China’s first severe acute respiratory infection sentinel surveillance system, February 2011 – October 2013

BACKGROUND: After the 2009 influenza A(H1N1)pdm09 pandemic, China established its first severe acute respiratory infections (SARI) sentinel surveillance system. METHODS: We analyzed data from SARI cases in 10 hospitals in 10 provinces in China from February 2011 to October 2013. RESULTS: Among 5,644 SARI cases, 330 (6%) were influenza-positive. Among these, 62% were influenza A and 38% were influenza B. Compared with influenza-negative cases, influenza-positive SARI cases had a higher median age (20.0 years vs.11.0, p=0.003) and were more likely to have at least one underlying chronic medical condition (age adjusted percent: 28% vs. 25%, p<0.001). The types/subtypes of dominant strains identified by SARI surveillance was almost always among dominant strains identified by the influenza like illness (ILI) surveillance system and influenza activity in both systems peaked at the same time. CONCLUSIONS: Data from China's first SARI sentinel surveillance system suggest that types/subtypes of circulating influenza strains and epidemic trends among SARI cases were similar to those among ILI cases