Fire retardancy of bis[2-(methacryloyloxy)ethyl] phosphate modified poly(methyl methacrylate) nanocomposites containing layered double hydroxide and montmorillonite

Copolymer nanocomposites were prepared by suspension copolymerization of bis[2-(methacryloyloxy)ethyl] phosphate and methyl methacrylate, together with bis(2-ethylhexyl) phosphate layered double hydroxide and a montmorillonite, Cloisite 93A. X-ray diffraction and transmission electron microscopy were used to characterize the morphology of nanocomposites and the dispersion of additives in the polymer. The thermal stability of the nanocomposites has been assessed by thermogravimetric analysis and cone calorimetry has been used to study the fire properties. Bis[2-(methacryloyloxy)ethyl] phosphate not only copolymerized with MMA, but also aids in the dispersion of additives in PMMA. The copolymer nanocomposites have better dispersion and higher degradation temperature and more char mass than the corresponding PMMA nanocomposites. The largest peak reduction in the heat release rate of the copolymer nanocomposites are 52 and 65% for LDH and MMT additives, respectively

Variation of anions in layered double hydroxides: Effects on dispersion and fire properties

Layered double hydroxides (LDHs) are interesting materials for nanocomposite formation because one can vary the identity of the metals, the anions and the stoichiometry to see the effect of these on the ability of the nano-material to disperse in a polymer and to see what effect dispersion has on the properties of the polymer. In this study, the anions 2-ethylhexyl sulfate (SEHS), bis(2-ethylhexyl) phosphate (HDEHP) and dodecyl benzenesulfonate (SDBS) have been utilized as the charge balancing anions to synthesize organo-LDHs. Nanocomposites of poly(methyl methacrylate) (PMMA) and polystyrene (PS) with organo-LDHs were prepared both by melt blending and bulk polymerization. X-ray diffraction and transmission electron microscopy were used to characterize the morphology of the nanocomposites while the thermal stability and fire properties of nanocomposites were studied by thermogravimetric analysis and cone calorimetry; the mechanical properties are also investigated. In general, it is easier to disperse these organo-LDHs in PMMA than in PS, but the sulfate cannot be dispersed at the nanometer level in either material. The addition of these organo-LDHs does not affect the mechanical properties. The best fire properties are obtained with the sulfonate LDH, SDBS; the reduction in the peak heat release rate is almost 50% for both polymers

New Approach to Develop Ultra-High Inhibitory Drug Using the Power Function of the Stoichiometry of the Targeted Nanomachine or Biocomplex

AIMS: To find methods for potent drug development by targeting to biocomplex with high copy number. METHODS: Phi29 DNA packaging motor components with different stoichiometries were used as model to assay virion assembly with Yang Hui\u27s Triangle [Formula: see text], where Z = stoichiometry, M = drugged subunits per biocomplex, p and q are the fraction of drugged and undrugged subunits in the population. RESULTS: Inhibition efficiency follows a power function. When number of drugged subunits to block the function of the complex K = 1, the uninhibited biocomplex equals q(z), demonstrating the multiplicative effect of stoichiometry on inhibition with stoichiometry 1000 \u3e 6 \u3e 1. Complete inhibition of virus replication was found when Z = 6. CONCLUSION: Drug inhibition potency depends on the stoichiometry of the targeted components of the biocomplex or nanomachine. The inhibition effect follows a power function of the stoichiometry of the target biocomplex

Genome-wide identification and characterization of HSP gene superfamily in whitefly (Bemisia tabaci) and expression profiling analysis under temperature stress

Heat shock proteins (HSP) are essential molecular chaperones that play important roles in the stress stimulation of insects. Bemisia tabaci, a phloem feeder and invasive species, can cause extensive crop damage through direct feeding and transmission of plant viruses. Here we employed comprehensive genomics approaches to identity HSP superfamily members in the Middle East Asia Minor 1 whitefly genome. In total, we identified 26 Hsp genes, including three Hsp90, 17 Hsp70, one Hsp60 and five sHSP (small heat shock protein) genes. The HSP gene superfamily of whitefly is expanded compared with the other five insects surveyed here. The gene structures among the same families are relatively conserved. Meanwhile, the motif compositions and secondary structures of BtHsp proteins were predicted. In addition, quantitative polymerase chain reaction analysis showed that the expression patterns of BtHsp gene superfamily were diverse across different tissues of whiteflies. Most Hsp genes were induced or repressed by thermal stress (40°C) and cold treatment (4°C) in whitefly. Silencing the expression of BtHsp70-6 significantly decreased the survival rate of whitefly under 45°C. All the results showed the Hsps conferred thermo-tolerance or cold-tolerance to whiteflies that protect them from being affected by detrimental temperature conditions. Our observations highlighted the molecular evolutionary properties and the response mechanism to temperature assaults of Hsp genes in whitefly

Aqua­(1,10-phenanthroline-κ2 N,N′)bis­(trimethyl­acetato)-κ2 O,O′;κO-cobalt(II)

In the title compound, [Co(C5H9O2)2(C12H8N2)(H2O)], the CoII atom is coordinated in a distorted octahedral environment by three carboxyl O atoms of two trimethyl­acetate ligands, one aqua O atom and two N atoms from 1,10-phen­anthroline. The crystal structure is stabilized by O—H⋯O hydrogen bonds and π–π stacking inter­actions [inter­planar distance between inter­digitating 1,10-phenanthroline ligands = 3.378 (2) Å]

Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions

Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg)

Understanding Variation in Transcription Factor Binding by Modeling Transcription Factor Genome-Epigenome Interactions

Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg).</p