Antioxidant Metabolism, Photosystem II, and Fatty Acid Composition of Two Tall Fescue Genotypes With Different Heat Tolerance Under High Temperature Stress

Tall fescue (Festuca arundinacea Schreb.) is a typical and widely used cool-season turf grass. High temperature is a key factor that limits its utility. The objectives of this study were to investigate the behaviors of fatty acid composition and its gene expression patterns in heat-resistant genotype “TF71” and heat-sensitive genotype “TF133” exposed to heat stress (40/35°C, 14/10 h), and to broaden our comprehension about the relationship between heat tolerance and fatty acid function. The result showed that heat stress increased the malondialdehyde (MDA) content and relative electrolyte leakage (EL), but decreased the level of chlorophyll and the activity of superoxide dismutase (SOD) and peroxidase (POD) when compared to the controls, to a greater extent in “TF133.” This result proved that “TF71” had superior high-temperature resistance. Furthermore, comparing the changes in the composition of fatty acid and the expression of the genes involved in its synthesis between the two different genotypes under heat stress, we found that heat stress increased the degree of unsaturation, UFA/SFA, and double bond index (DBI) in “TF71.” Moreover, quantitative RT-PCR revealed that heat stress altered the expression of the genes involved in fatty acid synthesis, including ACAC, FabD, FabF, FabH, FabI, and FatA. According to these findings, we can speculate that increasing the unsaturation degree of fatty acid or controlling the equilibrium ratio of UFA/SFA might be closely associated with the improving of the heat resistance in tall fescue

Transcriptomic and metabolic regulatory network characterization of drought responses in tobacco

Drought stress usually causes huge economic losses for tobacco industries. Drought stress exhibits multifaceted impacts on tobacco systems through inducing changes at different levels, such as physiological and chemical changes, changes of gene transcription and metabolic changes. Understanding how plants respond and adapt to drought stress helps generate engineered plants with enhanced drought resistance. In this study, we conducted multiple time point-related physiological, biochemical,transcriptomic and metabolic assays using K326 and its derived mutant 28 (M28) with contrasting drought tolerance. Through integrative analyses of transcriptome and metabolome,we observed dramatic changes of gene expression and metabolic profiles between M28 and K326 before and after drought treatment. we found that some of DEGs function as key enzymes responsible for ABA biosynthesis and metabolic pathway, thereby mitigating impairment of drought stress through ABA signaling dependent pathways. Four DEGs were involved in nitrogen metabolism, leading to synthesis of glutamate (Glu) starting from NO−3 /NO−2 that serves as an indicator for stress responses. Importantly, through regulatory network analyses, we detected several drought induced TFs that regulate expression of genes responsible for ABA biosynthesis through network, indicating direct and indirect involvement of TFs in drought responses in tobacco. Thus, our study sheds some mechanistic insights into how plant responding to drought stress through transcriptomic and metabolic changes in tobacco. It also provides some key TF or non-TF gene candidates for engineering manipulation for breeding new tobacco varieties with enhanced drought tolerance

3D Cu Pyramid Array Grown on Planar Cu Foil for Stable and Dendrite-free Lithium Deposition

Lithium metal is recognized as the anticipated anode for rechargeable batteries because of its inherent physicochemical properties. Unfortunately, the industrialization of Li metal anodes (LMAs) has been entangled in some intractable problems stemming from the uncontrollable growth of Li dendrites, which could result in the issue of short-circuit, thereby leading to cell failure. Here, a three-dimensional structured Cu pyramid array (CPA@CF) is constructed on planar Cu foil (CF) by the simple electrodeposition method. Owing to the features of large surface area and 3D porous structure, the proposed CPA@CF not only can promote Li-ion diffusion and charge transfer, but also effectively slow down the volume change of Li. Consequently, an even and steady Li plating/stripping process up to 360 h is realized using such a CPA@CF current collector. The Li@CPA@CF|LiFePO4 full cell achieves an excellent Coulombic efficiency (CE) of 99.3 % for 160 cycles at 0.3 C with a superior capacity retention of 84.2 %

An Open Invitation to Join the International Brugada Electrocardiographic Indices Registry

Background: The Brugada Electrocardiographic Indices Registry is a comprehensive data registry composed of patients with Brugada patterns on the electrocardiogram (ECG). The aim is to test the hypotheses that (i) ECG indices combining both depolarization and repolarization abnormalities can better predict spontaneous ventricular arrhythmias than existing ECG markers in Brugada syndrome and (ii) that serial ECG measurements will provide additional information for risk stratification, especially in asymptomatic patients. Methods: Patients with both Brugada pattern ECGs and Brugada syndrome are eligible for inclusion in this registry. Baseline characteristics and ECG variables reflecting depolarization and repolarization will be determined. The primary outcome is spontaneous ventricular tachycardia/ventricular fibrillation or sudden cardiac death. Secondary outcomes are inducible ventricular tachycardia/ventricular fibrillation and syncope. Results: As of November 15, 2019, 39 investigators from 32 cities in 18 countries had joined this registry. As of December 15, 2019, 1383 cases had been enrolled. Conclusions: The Brugada Electrocardiographic Indices Registry will evaluate the disease life course, risk factors, and prognosis in a large series of Brugada patients. It will therefore provide insights for improving risk stratification

Single Endemic Genotype of Measles Virus Continuously Circulating in China for at Least 16 Years

The incidence of measles in China from 1991 to 2008 was reviewed, and the nucleotide sequences from 1507 measles viruses (MeV) isolated during 1993 to 2008 were phylogenetically analyzed. The results showed that measles epidemics peaked approximately every 3 to 5 years with the range of measles cases detected between 56,850 and 140,048 per year. The Chinese MeV strains represented three genotypes; 1501 H1, 1 H2 and 5 A. Genotype H1 was the predominant genotype throughout China continuously circulating for at least 16 years. Genotype H1 sequences could be divided into two distinct clusters, H1a and H1b. A 4.2% average nucleotide divergence was found between the H1a and H1b clusters, and the nucleotide sequence and predicted amino acid homologies of H1a viruses were 92.3%–100% and 84.7%–100%, H1b were 97.1%–100% and 95.3%–100%, respectively. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Cluster H1a and H1b viruses were co-circulating during 1993 to 2005, while no H1b viruses were detected after 2005 and the transmission of that cluster has presumably been interrupted. Analysis of the nucleotide and predicted amino acid changes in the N proteins of H1a and H1b viruses showed no evidence of selective pressure. This study investigated the genotype and cluster distribution of MeV in China over a 16-year period to establish a genetic baseline before MeV elimination in Western Pacific Region (WPR). Continuous and extensive MeV surveillance and the ability to quickly identify imported cases of measles will become more critical as measles elimination goals are achieved in China in the near future. This is the first report that a single endemic genotype of measles virus has been found to be continuously circulating in one country for at least 16 years

Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women

Background The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years. Principal findings We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders. Conclusions In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype

HalO [Indoor Positioning Mobile Platform]: A Data-Driven, Indoor-Positioning System With Bluetooth Low Energy Technology To Datafy Indoor Circulation And Classify Social Gathering Patterns For Assisting Post Occupancy Evaluation

Post-Occupancy Evaluation (POE) as an integrated field between architecture and sociology has created practical guidelines for evaluating indoor human behavior within a built environment. This research builds on recent attempts to integrate datafication and machine learning into POE practices that may one day assist Building Information Modeling (BIM) and multi-agent modeling. This research is based on two premises: 1) that the proliferation of Bluetooth Low Energy (BLE) technology allows us to collect a building user’s data cost-effectively and 2) that the growing application of machine learning algorithms allows us to process, analyze and synthesize data efficiently. This study illustrates that the mobile platform HalO can serve as a generic tool for datafication and automation of data analysis of the movement of a building user. In this research, the iOS mobile application HalO, combined with BLE beacons enable building providers (architects, developers, engineers and facility managers etc.) to collect the user’s indoor location data. Triangulation was used to pinpoint the user’s indoor positions, and k-means clustering was applied to classify users into different gathering groups. Through four research procedures—Design Intention Analysis, Data Collection, Data Storage and Data Analysis—the visualized and classified data helps building providers to better evaluate building performance, optimize building operations and improve the accuracy of simulations.1