Chiral Assemblies of Pinwheel Superlattices on Substrates

The unique topology and physics of chiral superlattices make their self-assembly from nanoparticles a holy grail for (meta)materials. Here we show that tetrahedral gold nanoparticles can spontaneously transform from a perovskite-like low-density phase with corner-to-corner connections into pinwheel assemblies with corner-to-edge connections and denser packing. While the corner-sharing assemblies are achiral, pinwheel superlattices become strongly mirror-asymmetric on solid substrates as demonstrated by chirality measures. Liquid-phase transmission electron microscopy and computational models show that van der Waals and electrostatic interactions between nanoparticles control thermodynamic equilibrium. Variable corner-to-edge connections among tetrahedra enable fine-tuning of chirality. The domains of the bilayer superlattices display strong chiroptical activity identified by photon-induced near-field electron microscopy and finite-difference time-domain simulations. The simplicity and versatility of the substrate-supported chiral superlattices facilitate manufacturing of metastructured coatings with unusual optical, mechanical and electronic characteristics

Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2

Background: Diabetes mellitus of type 2 (T2D), also known as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, is a common disease. It is estimated that more than 300 million people worldwide suffer from T2D. In this study, we investigated the T2D, pre-diabetic and healthy human (no diabetes) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of T2D, and provided useful information for further effective prevention and treatment of the disease. Results: A total of 142 bloodstream samples were collected, including 47 healthy humans, 22 pre-diabetic and 73 T2D patients. Whole genome scale gene expression profiles were obtained using the Agilent Oligo chips that contain over 20,000 human genes. We identified 79 significantly differentially expressed genes that have fold change ≥ 2. We mapped those genes and pinpointed locations of those genes on human chromosomes. Amongst them, 3 genes were not mapped well on the human genome, but the rest of 76 differentially expressed genes were well mapped on the human genome. We found that most abundant differentially expressed genes are on chromosome one, which contains 9 of those genes, followed by chromosome two that contains 7 of the 76 differentially expressed genes. We performed gene ontology (GO) functional analysis of those 79 differentially expressed genes and found that genes involve in the regulation of cell proliferation were among most common pathways related to T2D. The expression of the 79 genes was combined with clinical information that includes age, sex, and race to construct an optimal discriminant model. The overall performance of the model reached 95.1% accuracy, with 91.5% accuracy on identifying healthy humans, 100% accuracy on pre-diabetic patients and 95.9% accuract on T2D patients. The higher performance on identifying pre-diabetic patients was resulted from more significant changes of gene expressions among this particular group of humans, which implicated that patients were having profound genetic changes towards disease development. Conclusion: Differentially expressed genes were distributed across chromosomes, and are more abundant on chromosomes 1 and 2 than the rest of the human genome. We found that regulation of cell proliferation actually plays an important role in the T2D disease development. The predictive model developed in this study has utilized the 79 significant genes in combination with age, sex, and racial information to distinguish pre-diabetic, T2D, and healthy humans. The study not only has provided deeper understanding of the disease molecular mechanisms but also useful information for pathway analysis and effective drug target identification

Synthesis of YVO4:Eu3+/YBO3Heteronanostructures with Enhanced Photoluminescence Properties

Novel YVO4:Eu3+/YBO3core/shell heteronanostructures with different shell ratios (SRs) were successfully prepared by a facile two-step method. X-ray diffraction, transmission electron microscopy and X-ray photoelectron spectroscopy were used to characterize the heteronanostructures. Photoluminescence (PL) study reveals that PL efficiency of the YVO4:Eu3+nanocrystals (cores) can be improved by the growth of YBO3nanocoatings onto the cores to form the YVO4:Eu3+/YBO3core/shell heteronanostructures. Furthermore, shell ratio plays a critical role in their PL efficiency. The heteronanostructures (SR = 1/7) exhibit the highest PL efficiency; its PL intensity of the5D0–7F2emission at 620 nm is 27% higher than that of the YVO4:Eu3+nanocrystals under the same conditions

Molecular structure of the largemouth bass (Micropterus salmoides) Myf5 gene and its effect on skeletal muscle growth

Myogenic Regulatory Factors (MRFs), a family of basic helix-loop-helix (bHLH) transcription factors, play important roles in regulating skeletal muscle development and growth. Myf5, the primary factor of MRFs, initiates myogenesis. Its expression pattern during somitomyogenesis in some fish has been revealed. To further study its effect on fish muscle during postembryonic growth, characterization and function analysis of myf5 cDNA were carried out in largemouth bass. The 1,093 bp cDNA sequence was identified by RT-PCR and 3′RACE, then the ORF of Myf5 cDNA was cloned into the expression vector pcDNA3.1(−)/mycHisB. The recombinant plasmid pcDNA3.1(−)/mycHisB-Myf5 was injected into the dorsal muscle of tilapias. RT-PCR and histochemical results showed that the exogenous gene was transcribed and translated in vivo. Its effect on muscle growth focused on myofiber hypertrophy in white muscle 60 days post injection. This indicated that overexpression of Myf5 can promote myogenesis during the fish muscle postembryonic growth period

Y-Chromosome Evidence for Common Ancestry of Three Chinese Populations with a High Risk of Esophageal Cancer

High rates of esophageal cancer (EC) are found in people of the Henan Taihang Mountain, Fujian Minnan, and Chaoshan regions of China. Historical records describe great waves of populations migrating from north-central China (the Henan and Shanxi Hans) through coastal Fujian Province to the Chaoshan plain. Although these regions are geographically distant, we hypothesized that EC high-risk populations in these three areas could share a common ancestry. Accordingly, we used 16 East Asian-specific Y-chromosome biallelic markers (single nucleotide polymorphisms; Y-SNPs) and six Y-chromosome short tandem repeat (Y-STR) loci to infer the origin of the EC high-risk Chaoshan population (CSP) and the genetic relationship between the CSP and the EC high-risk Henan Taihang Mountain population (HTMP) and Fujian population (FJP). The predominant haplogroups in these three populations are O3*, O3e*, and O3e1, with no significant difference between the populations in the frequency of these genotypes. Frequency distribution and principal component analysis revealed that the CSP is closely related to the HTMP and FJP, even though the former is geographically nearer to other populations (Guangfu and Hakka clans). The FJP is between the CSP and HTMP in the principal component plot. The CSP, FJP and HTMP are more closely related to Chinese Hans than to minorities, except Manchu Chinese, and are descendants of Sino-Tibetans, not Baiyues. Correlation analysis, hierarchical clustering analysis, and phylogenetic analysis (neighbor-joining tree) all support close genetic relatedness among the CSP, FJP and HTMP. The network for haplogroup O3 (including O3*, O3e* and O3e1) showed that the HTMP have highest STR haplotype diversity, suggesting that the HTMP may be a progenitor population for the CSP and FJP. These findings support the potentially important role of shared ancestry in understanding more about the genetic susceptibility in EC etiology in high-risk populations and have implications for determining the molecular basis of this disease

Conducting polymer nanocomposite-based supercapacitors

The use of nanocomposites of electronically-conducting polymers for supercapacitors has increased significantly over the past years, due to their high capacitances and abilities to withstand many charge-discharge cycles. We have recently been investigating the use of nanocomposites of electronically-conducting polymers containing conducting and non-conducting nanomaterials such as carbon nanotubes and cellulose nanocrystals, for use in supercapacitors. In this contribution, we provide a summary of some of the key issues in this area of research. This discussion includes some history, fundamental concepts, the physical and chemical processes involved, and the challenges that these nanocomposite materials must overcome in order to become technologically viable. Due to space limitations, this is not a complete review of all the work that has been done in this field and we have focused on common themes that appear in the published work. Our aim is that this chapter will help readers to understand the advantages and challenges involved in the use of these materials in supercapacitors and to identify areas for further development

An NNwC MPPT-Based Energy Supply Solution for Sensor Nodes in Buildings and Its Feasibility Study

Sensors for data collecting are vital in the development of IoT and intelligent systems. High power consuming current and voltage monitors are indispensable in conducting maximum power point tracking (MPPT) in traditional PV energy wireless sensor nodes. This paper presents a sensor node system based on Neural Network MPPT with cloud method (NNwC) which utilizes information sharing process that is specific to sensor networks. NNwC uses a few sample sensor nodes to collect environmental parameter data such as light intensity (L) and temperature (T) to build the MPPT regression model by Neural Network. Then all other functional sensor nodes implement the model with their environmental parametervalues to conduct MPPT. As a result, the new sensor node system reduces energy consumption as well as the size and cost of the harvester. Then, this paper provides a SPICE simulation to estimate the percentage of power consumption reduced in the new sensor node system and also estimates the percentage of loss in neural network MPPT power generation compared with the perfect MPPT. Finally, the study compares the economic and environmental performance of the proposed system and the traditional ones through a case in a real building situation

Wetting of Inkjet Polymer Droplets on Porous Alumina Substrates

The resolution of inkjet printing technology is determined by wetting and evaporation processes after the jet drop contacts the substrate. Here, the wetting of different picoliter solubilized polymer droplets jetting onto one-end-closed porous alumina was investigated. The selected polymers are commonly used in inkjet ink. The synergistic effects of the hierarchical structure and substrate surface modification were used to control the behavior of polymer-based ink drops. A model that invokes the effect of surface tension was applied to calculate the amount of polymer solution penetrating into the pores. The calculation corroborates experimental observations and shows that the volume of polymer solution in the pores increases with an increase in pore radius and depth, resulting in less solution remaining on the substrate surface. The structure of the porous substrate coupled with intrinsic polymer properties and surface modifications all contribute to the resolution that can be achieved via inkjet printing