Some debilitating mutations in RNA viruses are repairable; however, the triggering factors of mutation repair remain largely unknown. In this study, multiple triggering factors of mutation repair are ...identified based on genetic damage to the TLS in CMV. TLS mutations in different RNAs distinctively impact viral pathogenicity and present different types of mutation repair. RNA2 relative reduction level or RNA3 sequence change resulting from TLS mutation is correlated with a high rate of mutation repair, and the TLS mutation of RNA1 fails to be repaired at the high inoculum dose. However, the TLS mutation of RNA1 can be repaired at a low dose of inoculation, particularly around the dilution end-point or in the mixed inoculation with RNA2 having a pre-termination mutation of the 2b gene, an RNAi suppressor. Taken together, TLS mutations resulting in quality or quantity defects of the viral genome or TLS mutations at low doses around the dilution end-point are likely to be repaired. Different levels of TLS mutation repair necessarily require cell-to-cell movement, therefore implying its obligated effect on the evolution of low-fitness viruses and providing a new insight into Muller’s ratchet. This study provides important information on virus evolution and the application of mild viral vaccines.
Continuously improving performance and reducing cost targets for oxygen evolution reaction (OER) drive a growing interest in optimizing functionalities of ionomer binders in catalyst layer. The ...actual properties of catalysts significantly depend on the applied ionomers. Herein, we systematically examine five perfluorinated acid ionomers binders for OER on IrOx catalysts, including four Aquivion® short side chain ionomers and a long side chain Nafion™. Electrochemical measurements indicate that a combination of short side chain and increased equivalent weight can facilitate OER due to the optimized ionomer-catalyst interactions. Meanwhile, ionomers impact on OER by adjusting mass transport behaviors rather than reaction pathways. The accelerated durability tests further reveal that the long side chain and higher equivalent weight can decrease activity losses from 50% to 28%, implying enhancement of long-term electrochemical stability. Therefore, combining the advanced ionomer chemistry with the interfacial science provides a new opportunity to facilitate OER for energy conversion and storage.
Display omitted
•Illustrating ionomer-dependent oxygen evolution well from interface science.•Short side chain and high equivalent weight facilitate acidic oxygen evolution.•Long side chain and high equivalent weight improve electrochemical stability.•Ionomer greatly impacts on interfacial mass transport but not reaction pathways.
This paper demonstrates the applicability of machine learning algorithms in sand production problems with natural gas hydrate (NGH)-bearing sands, which have been regarded as a grave concern for ...commercialization. The sanding problem hinders the commercial exploration of NGH reservoirs. The common sand production prediction methods need assumptions for complicated mathematical derivations. The main contribution of this paper was to introduce machine learning into the prediction sand production by using data from laboratory experiments. Four main machine learning algorithms were selected, namely, K-Nearest Neighbor, Support Vector Regression, Boosting Tree, and Multi-Layer Perceptron. Training datasets for machine learning were collected from a sand production experiment. The experiment considered both the geological parameters and the sand control effect. The machine learning algorithms were mainly evaluated according to their mean absolute error and coefficient of determination. The evaluation results showed that the most accurate results under the given conditions were from the Boosting Tree algorithm, while the K-Nearest Neighbor had the worst prediction performance. Considering an ensemble prediction model, the Support Vector Regression and Multi-Layer Perceptron could also be applied for the prediction of sand production. The tuning process revealed that the Gaussian kernel was the proper kernel function for improving the prediction performance of SVR. In addition, the best parameters for both the Boosting Tree and Multi-Layer Perceptron were recommended for the accurate prediction of sand production. This paper also involved one case study to compare the prediction results of the machine learning models and classic numerical simulation, which showed the capability of machine learning of accurately predicting sand production, especially under stable pressure conditions.
Display omitted
•Mn1Co1 exhibits almost 100% decomposition of HCHO into CO2 and H2O at room temperature.•Mn1Co1 shows different HCHO catalytic activity under different relative humidity.•Mn modified ...MnxCo3-xO4 solid solution catalysts with various Co/Mn mole ratios were prepared by calcination of MOFs.•Mn incorporation increased specific surface area, pore volume, and active surface oxygen species.
Developing cost-effective non-noble catalysts for completely decomposing formaldehyde (HCHO) into harmless CO2 and H2O at room temperature remains great challenges for indoor air purification. Herein, MnxCo3-xO4 solid solutions are prepared via the calcination of metal-organic frameworks (MOFs) with different Co/Mn molar ratios. The catalyst (Mn1Co1) achieves 100 % HCHO removal at room temperature for the first time, and possesses excellent stability. During an intermittent test and a non-stop 34 -h test, the HCHO removal efficiency remains almost 100 %. The complete oxidation of HCHO is confirmed by the disappearance of HCHO peaks and the increase of CO2 peak intensity in effluent gas analysis. In situ DRIFTS results show that formate species is the main intermediate and it can be further oxidized to CO2 and H2O as final products in the presence of water vapor. The superior catalytic activity and stability of the Mn1Co1 catalyst endow its great potential in the HCHO removal application.
Acquiring the firing sequence of neurons located in varying depths with cellular resolution is essential to understand the underlying functional neural circuits of living animals. Light-sheet ...fluorescence microscopy (LSFM) enables neuronal activities recording with high temporal and spatial resolutions. However, constrained by the single-plane illumination and detection configuration, neurons located in varying depths are impossible to be recorded simultaneously. To address this challenge, we develop the simultaneous multi-plane imaging light-sheet fluorescence microscopy (SIMPLE-LSFM) by combining multi-plane or region-of-interest illumination of a sample, and spherical-aberration-assisted point spread function in detection space for simultaneous imaging of different depth within a sample. SIMPLE-LSFM is demonstrated by acquiring neuronal activities of six depths simultaneously in the larval zebrafish; while keeping cellular resolution, millimeter-scale field of view, and > 100 H z temporal resolution. Firing sequences of the neurons located in varying depths were successfully captured. The SIMPLE light-sheet methods enable high-speed cellular-resolution multi-depth-resolved mapping of anatomic structure and fast dynamics in three dimensions.
Mouse senile amyloidosis is a disorder in which apolipoprotein A-II deposits extracellularly in many organs as amyloid fibrils (AApoAII). In this study, we intravenously injected 1 μg of isolated ...AApoAII fibrils into R1.P1-Apoa2c mice, to induce AApoAII amyloidosis. We observed that the unfolded protein response was induced by deposition of AApoAII amyloid. We found that the mRNA and the protein expression levels of heat shock protein A5 (HSPA5; also known as glucose-regulated protein 78) were increased in the liver with AApoAII amyloid deposits. Immunohistochemistry showed that HSPA5 was only detected in hepatocytes close to AApoAII amyloid deposits. Furthermore, gene transcription of several endoplasmic reticulum (ER) stress-related proteins increased, including eukaryotic translation initiation factor 2 alpha kinase 3 (Eif2ak3), activating transcription factor 6 (Atf6), activating transcription factor 4 (Atf4), X-box-binding protein 1 splicing (Xbp1s), DNA-damage inducible transcript 3 (Ddit3), and autophagy protein 5 (Atg5). Moreover, apoptosis-positive cells were increased in the liver. Similar results were seen in the kidney but not in the heart. Our study indicates that ER stress responses differed among tissues with extracellular AApoAII amyloid fibril deposition. Although upregulated HSPA5 and the activated unfolded protein response might have roles in protecting tissues against aggregated extracellular AApoAII amyloid deposition, prolonged ER stress induced apoptosis in the liver and the kidney.
In computational photolithography modeling, there are limitations for the commonly used parameter optimization algorithms. This situation will be more serious when a large number of physical ...parameters with large search range are to be optimized. Here, we use genetic algorithm (GA) for the parameter optimization. It can largely shorten the model calibration time, and the model accuracy is promised. In addition, an optimized flow called fast GA is developed to further reduce the model calibration time. Through further integrating GA modeling with the metrology, it can even reduce the traditional metrology and modeling time from 1 month to 4 days.
PDF
