Beyond nanosilica: Geopolymeric nanoaluminosilicates for functional nanocomposites

Nanoaggregates such as nanosilica and carbon black are two of the most important inorganic nanomaterials used in modern technologies including nanocomposites. By using sustainable geopolymer chemistry, we introduce new aluminosilicate nanoaggregates and nanostructured zeolites which may become as important as the aforementioned materials in nanocomposites, with their own unique functionalities. Geopolymer has been extensively studied and utilized as “green cement” in addressing global warming issues, one of the most challenging problems in human sustainability. At the same time, it is one of the few inorganic material systems that can be produced in a large scale and thus has a potential to meet the demand of large-scale applications. We will describe the nature of the sustainable, scalable production methods and discuss the key features of the materials including morphologies, surface areas, porosity, aggregate size, and zeolitic crystallinity. The nanostructured zeolite products demonstrate the ”nano” effect of their own, in terms of the short diffusion lengths within individual crystals and of the high surface area. Examples of their superior performances will be given for their applications in their neat form. Expansion of the original synthetic method has allowed organic-modified nanoaluminosilicates with increased hydrophobicity which can be important in nanocomposite fabrication

Immense potential of geopolymeric nanomaterials for sustainability applications

Geopolymer has been extensively studied and utilized as “green cement” in addressing global warming issues, one of the most challenging problems in human sustainability. It is one of the few inorganic material systems that can be produced in a large scale and thus has a potential to truly address such large-scale problems. In connection to the innate “nano” properties of geopolymer materials, we present some of our new progresses in the pursuit of new geopolymeric aluminosilicate nanomaterials and their sustainability applications. We will first briefly describe syntheses and properties of three different types of the new nanomaterials (Figure 1) and will illustrate their uses. For example, nanoporous geopolymer materials could be produced and used as an excellent arsenic absorbent for ground water purification and as a highly effective biodiesel catalyst. High-structure geopolymer nanoaggregates can be synthesized with controlled zeolicity for polymer nanocomposite applications with excellent energy-saving performances. Highly-crystalline hierarchical zeolites have been discovered to show an exceptional CO2 capacity, sorption kinetics, selectivity and regeneration capability essential for cost-effective CO2 separation. Superior ion exchange kinetics of the material has been observed for silver-ion zeolite with a superb antibacterial efficacy against antibiotics-resistant MRSA bacteria. Their out-of-the-lab usages are currently being realized in industry with future goal of megatonic production. Please click Additional Files below to see the full abstract

Immunometabolism changes in fibrosis: from mechanisms to therapeutic strategies

Immune cells are essential for initiating and developing the fibrotic process by releasing cytokines and growth factors that activate fibroblasts and promote extracellular matrix deposition. Immunometabolism describes how metabolic alterations affect the function of immune cells and how inflammation and immune responses regulate systemic metabolism. The disturbed immune cell function and their interactions with other cells in the tissue microenvironment lead to the origin and advancement of fibrosis. Understanding the dysregulated metabolic alterations and interactions between fibroblasts and the immune cells is critical for providing new therapeutic targets for fibrosis. This review provides an overview of recent advances in the pathophysiology of fibrosis from the immunometabolism aspect, highlighting the altered metabolic pathways in critical immune cell populations and the impact of inflammation on fibroblast metabolism during the development of fibrosis. We also discuss how this knowledge could be leveraged to develop novel therapeutic strategies for treating fibrotic diseases

Novel technologies in doubled haploid line development

haploid inducer line can be transferred (DH) technology can not only shorten the breeding process but also increase genetic gain. Haploid induction and subsequent genome doubling are the two main steps required for DH technology. Haploids have been generated through the culture of immature male and female gametophytes, and through inter- and intraspecific via chromosome elimination. Here, we focus on haploidization via chromosome elimination, especially the recent advances in centromere-mediated haploidization. Once haploids have been induced, genome doubling is needed to produce DH lines. This study has proposed a new strategy to improve haploid genome doubling by combing haploids and minichromosome technology. With the progress in haploid induction and genome doubling methods, DH technology can facilitate reverse breeding, cytoplasmic male sterile (CMS) line production, gene stacking and a variety of other genetic analysis

Research on Coordination Planning Model of Source-Grid-Load-Storage Considering Demand Response Uncertainty

With the integration of wind power, photovoltaic, and other new energy into the grid, the growth of carbon emissions has been effectively suppressed, which greatly contributes to the realization of the “Carbon peak, Carbon neutral’’. However, the randomness and instability of new energy generation also greatly affect the stable operation of the power grid. At present, the combination of demand response and power system can give full play to the maximum potential of new energy. This is an effective method to realize stable and optimal operation of power system. Based on this, this paper first constructs the SOC output characteristic model of energy storage and considers the DLC and time-of-use price as well as different demand response types. The robust optimization method is used to deal with the uncertainty of demand response. Secondly, a multi-objective function and constraint conditions are constructed to minimize the system planning cost, operation cost, and pollution emission. Finally, the genetic algorithm is used to analyze an example in a certain area of Fujian. In the example, the economy of planning schemes under different robust control parameters is compared and analyzed. The results show that the model and calculation method in this paper are beneficial to delaying the investment in power systems, and can provide decision-making reference for mining and utilizing demand response resources, reducing system planning costs and improving operation efficiency

Growth and stability of Pb intercalated phases under graphene on SiC

Graphene intercalation is a novel way to control graphene\u27s band structure and generate two-dimensional quantum materials with unusual spintronic and electronic properties. Despite its importance, information about the intercalation mechanism is lacking, especially the role of low density domain boundaries between regions of graphene of different thickness. With high resolution surface diffraction we have systematically studied Pb intercalation on epi-graphene grown on SiC, with domain boundaries between buffer and single layer graphene. By examining the evolution of different diffraction spots as a function of temperature, the location of Pb and stability of the intercalated phases underneath were determined

Estimation of quantitative genetic and stability parameters in maize under high and low N levels

AB It is important to breed maize (Zea mays L) cultivars with high performance under variable N levels. We studied the effect of N levels and estimated quantitative genetic parameters for grain yield, quality, and other traits, and examined stability of performance for grain yield in diverse Chinese maize germplasm. From 2006 to 2008, each year 20 and in total 30 maize hybrids, including commercial hybrids currently grown in this region and other ex¬perimental hybrids as well as high-oil hybrids, were tested using nine environments (location-year combinations) in North China Plain. In each environment, two replicated trials were grown: one under high N application rate (HN, 225 kg N ha-1) and the other under low N application rate (LN, no N fertilization). Compared to HN, grain yield was significantly reduced (35.6%) under LN level, as well as kernel number per ear, 1000-kernel weight, plant and ear heights, and protein concentration. In the analysis over environments under each N level, genotypic variance was significant and heritability was high for all traits. In the analyses across N levels and environments, genotypic variance was significant for all traits and larger than the genotype × N and/or environment interaction variance components except for protein concentration. In stability analyses across N levels, hybrids differed for their linear response to environments, and some showed dissimilar response under HN and LN levels. Our results indicated that breeding maize adapted to variable N levels is feasible with the Chinese germplasm available in the summer breeding programs in North China Plain. Multi-environment tests are required to identify hybrids with high grain yield under variable N conditions, and examining yield stability separately under HN and LN would be useful

Cloning and expression characterization of elongation of very long-chain fatty acids protein 6 (elovl6) with dietary fatty acids, ambient salinity and starvation stress in Scylla paramamosain

Introduction: Elongation of very long-chain fatty acids protein 6 (ELOVL6) played crucial roles in regulating energy expenditure and fatty acid metabolism. Many studies have performed to investigate the physiological roles and regulatory mechanisms of elovl6 in fish and animals, while few studies were reported in crustaceans.Methods: Here we reported on the molecular cloning, tissue distribution and expression profiles in response to dietary fatty acids, ambient salinity and starvation stress in Scylla paramamosain by using rapid amplification of cDNA ends (RACE) and quantitative real-time PCR.Results: Three elovl6 isoforms (named elovl6a, elovl6b and elovl6c) were isolated from S. paramamosain in the present study. The complete sequence of elovl6a was 1345 bp, the full-length sequence of elovl6b was 1419 bp, and the obtained elovl6c sequence was 1375 bp in full length. The elovl6a, elovl6b and elovl6c encoded 287, 329 and 301 amino acids respectively, and exhibited the typical structural features of ELOVL protein family members. Phylogenetic analysis showed that the ELOVL6a from S. paramamosain clustered most closely to ELOVL6 from Portunus trituberculatus and Eriocheir sinensis, while the ELOVL6b and ELOVL6c from S. paramamosain gathered alone into a single branch. Quantitative real-time PCR exhibited that the relatively abundant expression of elovl6b was observed in intestine and stomach, and the elovl6a and elovl6c were highly expressed in hepatopancreas. In addition, studies found that replacing fish oil with soybean oil could significantly increase the transcriptional levels of three elovl6 in hepatopancreas of S. paramamosain, and the expression of elovl6a and elovl6c in hepatopancreas were more sensitive to dietary fatty acids than the elovl6b. Compared with the normal sea water group (27‰), the expression of sterol-regulatory element binding protein1c (srebp-1), elovl6a, elovl6b and elovl6c were upregulated in the low salinity groups, particularly in 7‰. On the contrary, the starvation stress suppressed the expression of srebp-1, elovl6a, elovl6b and elovl6c.Discussion: These results may contribute to understand the functions of elovl6 in fatty acid synthesis and regulatory mechanisms in crustaceans

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding