90 research outputs found
MiR-135a-5p suppresses breast cancer cell proliferation, migration, and invasion by regulating BAG3
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
Real-time scheduling of renewable power systems through planning-based reinforcement learning
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
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
The effects of ECMO on neurological function recovery of critical patients: A double-edged sword
Extracorporeal membrane oxygenation (ECMO) played an important role in the treatment of patients with critical care such as cardiac arrest (CA) and acute respiratory distress syndrome. ECMO is gradually showing its advantages in terms of speed and effectiveness of circulatory support, as it provides adequate cerebral blood flow (CBF) to the patient and ensures the perfusion of organs. ECMO enhances patient survival and improves their neurological prognosis. However, ECMO-related brain complications are also important because of the high risk of death and the associated poor outcomes. We summarized the reported complications related to ECMO for patients with CA, such as north–south syndrome, hypoxic–ischemic brain injury, cerebral ischemia–reperfusion injury, impaired intracranial vascular autoregulation, embolic stroke, intracranial hemorrhage, and brain death. The exact mechanism of ECMO on the role of brain function is unclear. Here we review the pathophysiological mechanisms associated with ECMO in the protection of neurologic function in recent years, as well as the ECMO-related complications in brain and the means to improve it, to provide ideas for the treatment of brain function protection in CA patients
Comparative Analysis of the Genomes of Two Field Isolates of the Rice Blast Fungus Magnaporthe oryzae.
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
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
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Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic
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
Global patterns of daily CO2 emissions reductions in the first year of COVID-19
Day-to-day changes in CO2 emissions from human activities, in particular fossil-fuel combustion and cement production, reflect a complex balance of influences from seasonality, working days, weather and, most recently, the COVID-19 pandemic. Here, we provide a daily CO2 emissions dataset for the whole year of 2020, calculated from inventory and near-real-time activity data. We find a global reduction of 6.3% (2,232 MtCO2) in CO2 emissions compared with 2019. The drop in daily emissions during the first part of the year resulted from reduced global economic activity due to the pandemic lockdowns, including a large decrease in emissions from the transportation sector. However, daily CO2 emissions gradually recovered towards 2019 levels from late April with the partial reopening of economic activity. Subsequent waves of lockdowns in late 2020 continued to cause smaller CO2 reductions, primarily in western countries. The extraordinary fall in emissions during 2020 is similar in magnitude to the sustained annual emissions reductions necessary to limit global warming at 1.5°C. This underscores the magnitude and speed at which the energy transition needs to advance
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