Long non-coding RNA DANCR alleviates acute myocardial infarction damage via regulating microRNA-509-5p/KLF transcription factor 13 pathway.

Acute myocardial infarction (AMI) is the most important cause of death among cardiovascular diseases. Long noncoding RNAs (lncRNAs) have been widely implicated in the regulation of AMI progression. Discrimination antagonizing nonprotein coding RNA (DANCR) alleviated hypoxia-caused cardiomyocyte damages, and the underlying mechanisms remain unclear. Here, we investigated the function and mechanism of DANCR in hypoxia-induced cardiomyocytes and AMI model by enzyme-linked immunosorbent assay, reactive oxygen species and adenosine triphosphate measurement, and mitochondrial activity determination. Additionally, luciferase reporter assay, immunoblotting, and qRT-PCR were performed to validate the interactions between DANCR/miR-509-5p and miR-509-5p/Kruppel-like factor 13 (KLF13). The role of DANCR was also verified in AMI model by overexpression. Our results showed that DANCR expression was significantly downregulated in hypoxia-induced cardiomyocytes or AMI model. Overexpression of DANCR significantly alleviated mitochondrial damages, reduced inflammation, and improved cardiac function in the AMI model. Furthermore, we demonstrated that miR-509-5p/KLF13 axis mediated the protective effect of DANCR. The current study highlighted the critical role of DANCR in alleviating AMI progression through targeting the miR-509-5p/KLF13 signaling axis, suggesting that DANCR may serve as a potential diagnostic marker or therapeutic target for AMI.

Optimized Artificial Neural Network for Evaluation: C4 Alkylation Process Catalyzed by Concentrated Sulfuric Acid.

In this work, an artificial neural network was first achieved and optimized for evaluating product distribution and studying the octane number of the sulfuric acid-catalyzed C4 alkylation process in the stirred tank and rotating packed bed. The feedstock compositions, operating conditions, and reactor types were considered as input parameters into the artificial neural network model. Algorithm, transfer function, and framework were investigated to select the optimal artificial neural network model. The optimal artificial neural network model was confirmed as a network topology of 10-20-30-5 with Bayesian Regularization backpropagation and tan-sigmoid transfer function. Research octane number and product distribution were specified as output parameters. The artificial neural network model was examined, and 5.8 × 10-4 training mean square error, 8.66 × 10-3 testing mean square error, and ±22% deviation were obtained. The correlation coefficient was 0.9997, and the standard deviation of error was 0.5592. Parameter analysis of the artificial neural network model was employed to investigate the influence of operating conditions on the research octane number and product distribution. It displays a bright prospect for evaluating complex systems with an artificial neural network model in different reactors.

Data of thermal imprints of late Permian Emeishan basalt effusion: Evidence from zircon fission-track thermochronology.

We present 271 detrital single-grain zircon fission track (ZFT) ages obtained for eight sandstones, which were sampled from the southwestern Yangtze Craton, southern China. Accessory minerals were concentrated using standard crushing, sieving, electro-magnetic and heavy liquid mineral separation techniques. Zircon grains were mounted on FEP Teflon and polished to expose their internal surfaces to 4π geometry. Two to three mounts of each sample were etched in KON:NaOH eutectic melt at ∼228 °C for 12-60 hours to reveal spontaneous fission tracks. Etched mounts were covered with a uranium-free muscovite external detector for the irradiation with thermal neutrons. CN2 standard uranium glasses were embedded with the age standards (Fish Canyon Tuff zircons). After irradiation, external mica detectors were removed from sample mounts and then etched in 48% HF at room temperature for 30 min to reveal induced tracks. Fission track counting was performed using a Zeiss Axiotron microscope at a total magnification of 1250 × . Zircon fission-track ages were calculated using the ζ-calibration technique. The central ages (with 1σ error) vary from 144.7 ± 4.9 Ma to 256.7 ± 9.6 Ma, with variable P(χ2) values of 0%-75%. ZFT ages of the five Cambrian to Ordovician samples are younger than their depositional ages, and thus were fully reset by post-depositional heating. ZFT ages of three Jurassic samples are partially reset, as they overlap with or slightly younger than the corresponding depositional ages.