Verification of DNA motifs in Arabidopsis using CRISPR/Cas9-mediated mutagenesis.

Transcription factors (TFs) and chromatin-modifying factors (CMFs) access chromatin by recognizing specific DNA motifs in their target genes. Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) has been widely used to discover the potential DNA-binding motifs for both TFs and CMFs. Yet, an in vivo method for verifying DNA motifs captured by ChIP-seq is lacking in plants. Here, we describe the use of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) to verify DNA motifs in their native genomic context in Arabidopsis. Using a single-guide RNA (sgRNA) targeting the DNA motif bound by REF6, a DNA sequence-specific H3K27 demethylase in plants, we generated stable transgenic plants where the motif was disrupted in a REF6 target gene. We also deleted a cluster of multiple motifs from another REF6 target gene using a pair of sgRNAs, targeting upstream and downstream regions of the cluster, respectively. We demonstrated that endogenous genes with motifs disrupted and/or deleted become inaccessible to REF6. This strategy should be widely applicable for in vivo verification of DNA motifs identified by ChIP-seq in plants

The LDL1/2-HDA6 Histone Modification Complex Interacts With TOC1 and Regulates the Core Circadian Clock Components in Arabidopsis

In Arabidopsis, the circadian rhythm is associated with multiple important biological processes and maintained by multiple interconnected loops that generate robust rhythms. The circadian clock central loop is a negative feedback loop composed of the core circadian clock components. TOC1 (TIMING OF CAB EXPRESSION 1) is highly expressed in the evening and negatively regulates the expression of CCA1 (CIRCADIAN CLOCK ASSOCIATED 1)/LHY (LATE ELONGATED HYPOCOTYL). CCA1/LHY also binds to the promoter of TOC1 and represses the TOC1 expression. Our recent research revealed that the histone modification complex comprising of LYSINE-SPECIFIC DEMETHYLASE 1 (LSD1)-LIKE 1/2 (LDL1/2) and HISTONE DEACETYLASE 6 (HDA6) can be recruited by CCA1/LHY to repress TOC1 expression. In this study, we found that HDA6, LDL1, and LDL2 can interact with TOC1, and the LDL1/2-HDA6 complex is associate with TOC1 to repress the CCA1/LHY expression. Furthermore, LDL1/2-HDA6 and TOC1 co-target a subset of genes involved in the circadian rhythm. Collectively, our results indicate that the LDL1/2-HDA6 histone modification complex is important for the regulation of the core circadian clock components

Rapid detection of coal ash based on machine learning and X-ray fluorescence

Real-time testing of coal ash plays a vital role in the chemical, power generation, metallurgical, and coal separation sectors. The rapid online testing of coal ash using radiation measurement as the mainstream technology has problems such as strict coal sample requirements, poor radiation safety, low accuracy, and complicated equipment replacement. In this study, an intelligent detection technique based on feed-forward neural networks and improved particle swarm optimization (IPSO-FNN) is proposed to predict coal quality ash content in a fast, accurate, safe，and convenient manner. The data set was obtained by testing the elemental content of 198 coal samples with X-ray fluorescence (XRF). The types of input elements for machine learning (Si, Al, Fe, K, Ca, Mg, Ti, Zn, Na, P) were determined by combining the X-ray photoelectron spectroscopy (XPS) data with the change in the physical phase of each element in the coal samples during combustion. The mean squared error and coefficient of determination were chosen as the performance measures for the model. The results show that the IPSO algorithm is useful in adjusting the optimal number of nodes in the hidden layer. The IPSO-FNN model has strong prediction ability and good accuracy in coal ash prediction. The effect of the input element content of the IPSO-FNN model on the ash content was investigated, and it was found that the potassium content was the most significant factor affecting the ash content. This study is essential for real-time online, accurate, and fast prediction of coal ash

Synthesis and self-assembly of metal-organic frameworks

Metal-organic frameworks (MOFs), also known as porous coordination polymer(PCPs), are organic-inorganic compounds which are self-assembled from metal ions/clusters with organic ligands attaining permanent pores, ultrahigh surface area and infinite structure tailorability. These unique properties have rendered MOFs as great candidates in gas adsorption and separation, catalysis, sensing, drug delivery, etc. Structural control over both the molecular level and particle level is believed to be an efficient way for both creating new properties and enhancing the current performance of MOFs. To further developing the properties of MOFs, MOFs particles were modified through various techniques to achieve the goal above. Techniques, including self-assembly, were applied to make structure based new or enhanced properties of MOFs.Doctor of Philosophy (MSE

Self-assembled metal-organic frameworks crystals for chemical vapor sensing

A 3D metal-organic frameworks (MOFs) crystals film is obtained via Langmuir-Blodgett technique and used as a photonic sensor for chemical vapor detection. The MOFs crystals film exhibits both acute responses towards various chemical vapors and high controllability in terms of peak intensity and position. The method represents a general, facile and flexible strategy for the fabrication of MOFs-based photonic sensors

Synthesis and self-assembly of monodispersed metal-organic framework microcrystals

How to make super latt(ic)e: Monodispersed octahedral microcrystals of a zirconium-carboxylate metal-organic framework (MOF), UiO-66, were synthesized, under optimized experimental conditions, by using acetic acid as a modulator. Due to their uniform size and shape, the obtained MOF microcrystals can be assembled not only into large-area two-dimensional (2D) monolayers with oriented facets through a liquid-air interfacial assembly technique, but also into long-range three-dimensional (3D) superlattices by sedimentation

Self-Healing Microcapsule-Thickened Oil Barrier Coatings

Low-viscosity oils could potentially act as self-healing barrier coatings because they can readily flow and reconnect to heal minor damage. For the same reason, however, they typically do not form stable coatings on metal surfaces. Increasing viscosity helps to stabilize the oil coating, but it also slows down the healing process. Here, we report a strategy for creating highly stable oil coatings on metal surfaces without sacrificing their remarkable self-healing properties. Low-viscosity oil films can be immobilized on metal surfaces using lightweight microcapsules as thickeners, which form a dynamic network to prevent the creep of the coating. When the coating is scratched, oil around the opening can rapidly flow to cover the exposed area, reconnecting the particle network. Use of these coatings as anticorrosion barriers is demonstrated. The coatings can be easily applied on metal surfaces, including those with complex geometries, both in air or under water, and remain stable even in turbulent water. They can protect metal in corrosive environments for extended periods of time and can self-heal repeatedly when scratched at the same spot. Such a strategy may offer effective mitigation of the dangerous localized corrosion aggravated by minor imperfections or damage in protective coatings, which are typically hard to prevent or detect, but can drastically degrade metal properties

Triple-Frequency Code-Phase Combination Determination: A Comparison with the Hatch-Melbourne-Wübbena Combination Using BDS Signals

Considering the influence of the ionosphere, troposphere, and other systematic errors on double-differenced ambiguity resolution (AR), we present an optimal triple-frequency code-phase combination determination method driven by both the model and the real data. The new method makes full use of triple-frequency code measurements (especially the low-noise of the code on the B3 signal) to minimize the total noise level and achieve the largest AR success rate (model-driven) under different ionosphere residual situations (data-driven), thus speeding up the AR by directly rounding. With the triple-frequency Beidou Navigation Satellite System (BDS) data collected at five stations from a continuously-operating reference station network in Guangdong Province of China, different testing scenarios are defined (a medium baseline, whose distance is between 20 km and 50 km; a medium-long baseline, whose distance is between 50 km and 100 km; and a long baseline, whose distance is larger than 100 km). The efficiency of the optimal code-phase combination on the AR success rate was compared with that of the geometry-free and ionosphere-free (GIF) combination and the Hatch-Melbourne-Wübbena (HMW) combination. Results show that the optimal combinations can always achieve better results than the HMW combination with B2 and B3 signals, especially when the satellite elevation angle is larger than 45°. For the wide-lane AR which aims to obtain decimeter-level kinematic positioning service, the standard deviation (STD) of ambiguity residuals for the suboptimal combination are only about 0.2 cycles, and the AR success rate by directly rounding can be up to 99%. Compared with the HMW combinations using B1 and B2 signals and using B1 and B3 signals, the suboptimal combination achieves the best results in all baselines, with an overall improvement of about 40% and 20%, respectively. Additionally, the STD difference between the optimal and the GIF code-phase combinations decreases as the baseline length increases. This indicates that the GIF combination is more suitable for long baselines. The proposed optimal code-phase combination determination method can be applied to other multi-frequency global navigation satellite systems, such as new-generation BDS, Galileo, and modernized GPS