102 research outputs found

    MiR-135a-5p suppresses breast cancer cell proliferation, migration, and invasion by regulating BAG3

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    Background: MicroRNAs (miRNAs) are involved in the progression of diverse human cancers. This work aimed to delve into how microRNA-135a-5p (miR-135a-5p) affects the biological behaviors of Breast Cancer (BC) cells. Methods: Gene Expression Omnibus (GEO) datasets were used to analyze the expression differences of miR-135a-5p in cancer tissues of BC patients. Quantitative real-time PCR and western blot were conducted to detect miR-135a-5p and Bcl-2 Associated Athanogene (BAG3) expression levels in BC tissues and cells, respectively. The proliferation, migration, invasion, and cell cycle of BC cells were detected by cell counting kit-8 assay, BrdU assay, wound healing assay, transwell assay, and flow cytometry. The targeted relationship between miR-135a-5p and BAG3 mRNA 3′UTR predicted by bioinformatics was further testified by a dual-luciferase reporter gene assay. Pearson's correlation analysis was adopted to analyze the correlation between miR-135a-5p expression and BAG3 expression. The downstream pathways of BAG3 were analyzed by the LinkedOmics database. Results: MiR-135a-5p was significantly down-regulated and BAG3 expression was significantly raised in BC tissues. MiR-135a-5p overexpression repressed the viability, migration and invasion of BC cells, and blocked cell cycle progression in G0/G1 phase while inhibiting miR-135a-5p worked oppositely. BAG3 was verified as a target of miR-135a-5p. Overexpression of BAG3 reversed the impacts of miR-135a-5p on the malignant biological behaviors of BC cells. The high expression of BAG3 was associated with the activation of the cell cycle, mTOR and TGF-β signaling pathways. Conclusion: MiR-135a-5p regulates BAG3 to repress the growth, migration, invasion, and cell cycle progression of BC cells

    Burden of ischemic stroke attributable to a high red meat diet in China, 1990–2019: analysis based on the 2019 Global Burden of Disease Study

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    BackgroundThe burden of ischemic stroke (IS) linked to high consumption of red meat is on the rise. This study aimed to analyze the mortality and disability-adjusted life years (DALYs) trends for IS attributed to high red meat intake in China between 1990 and 2019 and to compare these trends with global trends.MethodsThis study extracted data on IS attributed to diets high in red meat in China from 1990 to 2019 from the Global Burden of Disease Study (GBD) database. Key measures, including mortality, DALYs, age-standardized mortality rates (ASMR), and age-standardized DALYs rates (ASDR), were used to estimate the disease burden. The estimated annual percentage change and joinpoint regression models were employed to assess the trends over time. An age-period-cohort analysis was used to assess the contribution of a diet high in red meat to the age, period, and cohort effects of IS ASMR and ASDR.ResultsBetween 1990 and 2019, deaths and DALYs from IS attributed to a diet high in red meat in China, along with corresponding age-standardized rates, significantly increased. The overall estimated annual percentage change for the total population and across sex categories ranged from 1.01 to 2.08. The average annual percentage changes for overall ASDR and ASMR were 1.4 and 1.33, respectively, with male ASDR and ASMR average annual percentage changes at 1.69 and 1.69, respectively. Contrastingly, female ASDR and ASMR average annual percentage changes were 1.07 and 0.87, respectively. Except for a few periods of significant decrease in females, all other periods indicated a significant increase or nonsignificant changes. Incidence of IS linked to a diet high in red meat rose sharply with age, displaying increasing period and cohort effects in ASDR. Female ASMR period and cohort effect ratios initially increased and then decreased, whereas the male ratio showed an upward trend.ConclusionThis study comprehensively analyzed epidemiological characteristics that indicated a marked increase in mortality and DALYs from IS attributable to high red meat consumption, contrasting with a global downtrend. This increase was more pronounced in males than females. This research provides valuable insights for enhancing IS prevention in China

    Real-time scheduling of renewable power systems through planning-based reinforcement learning

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    The growing renewable energy sources have posed significant challenges to traditional power scheduling. It is difficult for operators to obtain accurate day-ahead forecasts of renewable generation, thereby requiring the future scheduling system to make real-time scheduling decisions aligning with ultra-short-term forecasts. Restricted by the computation speed, traditional optimization-based methods can not solve this problem. Recent developments in reinforcement learning (RL) have demonstrated the potential to solve this challenge. However, the existing RL methods are inadequate in terms of constraint complexity, algorithm performance, and environment fidelity. We are the first to propose a systematic solution based on the state-of-the-art reinforcement learning algorithm and the real power grid environment. The proposed approach enables planning and finer time resolution adjustments of power generators, including unit commitment and economic dispatch, thus increasing the grid's ability to admit more renewable energy. The well-trained scheduling agent significantly reduces renewable curtailment and load shedding, which are issues arising from traditional scheduling's reliance on inaccurate day-ahead forecasts. High-frequency control decisions exploit the existing units' flexibility, reducing the power grid's dependence on hardware transformations and saving investment and operating costs, as demonstrated in experimental results. This research exhibits the potential of reinforcement learning in promoting low-carbon and intelligent power systems and represents a solid step toward sustainable electricity generation.Comment: 12 pages, 7 figure

    COVID-19 causes record decline in global CO2 emissions

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    The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply or estimated parameters, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for 206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures

    Comparative Analysis of the Genomes of Two Field Isolates of the Rice Blast Fungus Magnaporthe oryzae.

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    Rice blast caused by Magnaporthe oryzae is one of the most destructive diseases of rice worldwide. The fungal pathogen is notorious for its ability to overcome host resistance. To better understand its genetic variation in nature, we sequenced the genomes of two field isolates, Y34 and P131. In comparison with the previously sequenced laboratory strain 70-15, both field isolates had a similar genome size but slightly more genes. Sequences from the field isolates were used to improve genome assembly and gene prediction of 70-15. Although the overall genome structure is similar, a number of gene families that are likely involved in plant-fungal interactions are expanded in the field isolates. Genome-wide analysis on asynonymous to synonymous nucleotide substitution rates revealed that many infection-related genes underwent diversifying selection. The field isolates also have hundreds of isolate-specific genes and a number of isolate-specific gene duplication events. Functional characterization of randomly selected isolate-specific genes revealed that they play diverse roles, some of which affect virulence. Furthermore, each genome contains thousands of loci of transposon-like elements, but less than 30% of them are conserved among different isolates, suggesting active transposition events in M. oryzae. A total of approximately 200 genes were disrupted in these three strains by transposable elements. Interestingly, transposon-like elements tend to be associated with isolate-specific or duplicated sequences. Overall, our results indicate that gain or loss of unique genes, DNA duplication, gene family expansion, and frequent translocation of transposon-like elements are important factors in genome variation of the rice blast fungus

    Near-real-time monitoring of global COâ‚‚ emissions reveals the effects of the COVID-19 pandemic

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    The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO₂) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO₂ emissions (−1551 Mt CO₂) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially

    Experimental Study of Composite Members in Spatial Grid Structure Subjected to Ultralow-Cyclic Axial Force

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    This paper presents the results of ultralow-cycle fatigue tests for three full-scale assemblies consisting of steel tubes and bolt-sphere joints, which are widely used in public buildings. Each assembly was tested six times under a varying loading history. The ultralow-cycle fatigue performance was investigated considering the joint stiffness and loading history. The deformation patterns, hysteretic characteristics, skeleton curves, bearing-capacity degradation features, cumulative energy dissipation, and cumulative damage index of the assembly were obtained and analysed. The results show that the joint stiffness and loading system have a significant effect on the ultralow-cycle fatigue performance of the assembly. Based on these results, an equation that describes the relationship between the cumulative damage index and the bearing degradation of the assembly for an ultralow-cycle fatigue test was derived

    Recent advances in light-regulated non-radical polymerisations

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    Light is one of the non-invasive stimuli which can be used in the spatiotemporal control of chemical reactions. Over the past decade, light has found wide applications in polymer science such as polymer synthesis, release of small molecules from polymers and polymeric photosensors etc. Reviews on light-regulated polymerisations have predominately focused on the free radical process. However, the marriage of light to non-radical polymerisations, e.g. ionic, ring-opening, metathesis, step-growth and supramolecular photopolymerisations, has also spurred tremendous research interest to develop materials. These kinds of non-radical photopolymerisations, compared to the free radical approach, are advantageous in overcoming oxygen inhibition, accessing novel polymer structures and fabricating degradable and dynamic polymers. The relevant light-regulation techniques involved in these polymerisations are usually based on photolinking reactions and photoactivation of latent species. These species produce initiators, catalysts or monomers upon light irradiation to manipulate polymer formation. These techniques have been successfully implemented to adapt conditional polymerisations under light, discover novel polymerisation methods and precisely control polymer structures. This review aims to highlight the recent progress in light-regulated non-radical polymerisations in the development of polymerisation techniques as well as the applications in materials science, emphasising the remaining challenges and promising perspective in the relevant fields.HL acknowledges China Postdoctoral Science Foundation Grant (2019TQ0119
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