Shear Modulus of a Carbonate Sand–Silt Mixture with THF Hydrate

The maximum shear modulus (Gmax) is an important factor determining soil deformation, and it is closely related to engineering safety and seafloor stability. In this study, a series of bender element tests was carried out to investigate the Gmax of a hydrate-bearing carbonate sand (CS)–silt mixture. The soil mixture adopted a CS:silt ratio of 1:4 by weight to mimic the fine-grained deposit of the South China Sea (SCS). Tetrahydrofuran (THF) was used to form the hydrate. Special specimen preparation procedures were adopted to form THF hydrate inside the intraparticle voids of the CS. The test results indicate that hydrate contributed to a significant part of the skeletal stiffness of the hydrate-bearing CS–silt mixture, and its Gmax at 5% hydrate saturation (Sh) was 4–6 times that of the host soil mixture. Such stiffness enhancement at a low Sh may be related to the cementation hydrate morphology. However, the Gmax of the hydrate-bearing CS–silt mixture was also sensitive to the effective stress for an Sh ranging between 5% and 31%, implying that the frame-supporting hydrate morphology also plays a key role in the skeletal stiffness of the soil mixture. Neither the existing cementation models nor the theoretical frame-supporting (i.e., Biot–Gassmann theory by Lee (BGTL)), could alone provide a satisfactory prediction of the test results. Thus, further theoretical study involving a combination of cementation and frame-supporting models is essential to understand the effects of complicated hydrate morphologies on the stiffness of soil with a substantial amount of intraparticle voids

Functional metagenomic analysis of quorum sensing signaling in a nitrifying community.

Quorum sensing (QS) can function to shape the microbial community interactions, composition, and function. In wastewater treatment systems, acylated homoserine lactone (AHL)-based QS has been correlated with the conversion of floccular biomass into microbial granules, as well as EPS production and the nitrogen removal process. However, the role of QS in such complex communities is still not fully understood, including the QS-proficient taxa and the functional QS genes involved. To address these questions, we performed a metagenomic screen for AHL genes in an activated sludge microbial community from the Ulu Pandan wastewater treatment plant (WWTP) in Singapore followed by functional validation of luxI activity using AHL biosensors and LC-MSMS profiling. We identified 13 luxI and 30 luxR homologs from the activated sludge metagenome. Of those genes, two represented a cognate pair of luxIR genes belonging to a Nitrospira spp. and those genes were demonstrated to be functionally active. The LuxI homolog synthesized AHLs that were consistent with the dominant AHLs in the activated sludge system. Furthermore, the LuxR homolog was shown to bind to and induce expression of the luxI promoter, suggesting this represents an autoinduction feedback system, characteristic of QS circuits. Additionally, a second, active promoter was upstream of a gene encoding a protein with a GGDEF/EAL domain, commonly associated with modulating the intracellular concentration of the secondary messenger, c-di-GMP. Thus, the metagenomic approach used here was demonstrated to effectively identify functional QS genes and suggests that Nitrospira spp. maybe QS is active in the activated sludge community

Review of multi-scale electromagnetic modeling

This paper reviews various methods to solve multiscale problems ranging from low-frequency methods to very high-frequency methods. ©2010 IEEE.published_or_final_versionThe 2010 International Conference on Electromagnetics in Advanced Applications (ICEAA), Sydney, N.S.W., 20-24 September 2010. In Proceedings of ICEAA'10, 2010, p. 641-64

Ruthenium polypyridyl complexes and their modes of interaction with DNA : is there a correlation between these interactions and the antitumor activity of the compounds?

Various interaction modes between a group of six ruthenium polypyridyl complexes and DNA have been studied using a number of spectroscopic techniques. Five mononuclear species were selected with formula [Ru(tpy) L1L2](2-n)?, and one closely related dinuclear cation of formula [{Ru(apy)(tpy)}2{l-H2N(CH2)6NH2}]4?. The ligand tpy is 2,20:60,200-terpyridine and the ligand L1 is a bidentate ligand, namely, apy (2,20-azobispyridine), 2-phenylazopyridine, or 2-phenylpyridinylmethylene amine. The ligand L2 is a labile monodentate ligand, being Cl-, H2O, or CH3CN. All six species containing a labile L2 were found to be able to coordinate to the DNA model base 9-ethylguanine by 1H NMR and mass spectrometry. The dinuclear cationic species, which has no positions available for coordination to a DNA base, was studied for comparison purposes. The interactions between a selection of four representative complexes and calf-thymus DNA were studied by circular and linear dichroism. To explore a possible relation between DNA-binding ability and toxicity, all compounds were screened for anticancer activity in a variety of cancer cell lines, showing in some cases an activity which is comparable to that of cisplatin. Comparison of the details of the compound structures, their DNA binding, and their toxicity allows the exploration of structure–activity relationships that might be used to guide optimization of the activity of agents of this class of compounds

The Shark Assemblage at French Frigate Shoals Atoll, Hawai‘i: Species Composition, Abundance and Habitat Use

Empirical data on the abundance and habitat preferences of coral reef top predators are needed to evaluate their ecological impacts and guide management decisions. We used longline surveys to quantify the shark assemblage at French Frigate Shoals (FFS) atoll from May to August 2009. Fishing effort consisted of 189 longline sets totaling 6,862 hook hours of soak time. A total of 221 sharks from 7 species were captured, among which Galapagos (Carcharhinus galapagensis, 36.2%), gray reef (Carcharhinus amblyrhynchos, 25.8%) and tiger (Galeocerdo cuvier, 20.4%) sharks were numerically dominant. A lack of blacktip reef sharks (Carcharhinus melanopterus) distinguished the FFS shark assemblage from those at many other atolls in the Indo-Pacific. Compared to prior underwater visual survey estimates, longline methods more accurately represented species abundance and composition for the majority of shark species. Sharks were significantly less abundant in the shallow lagoon than adjacent habitats. Recaptures of Galapagos sharks provided the first empirical estimate of population size for any Galapagos shark population. The overall recapture rate was 5.4%. Multiple closed population models were evaluated, with Chao Mh ranking best in model performance and yielding a population estimate of 668 sharks with 95% confidence intervals ranging from 289–1720. Low shark abundance in the shallow lagoon habitats suggests removal of a small number of sharks from the immediate vicinity of lagoonal islets may reduce short-term predation on endangered monk seal (Monachus schauinslandi) pups, but considerable fishing effort would be required to catch even a small number of sharks. Additional data on long-term movements and habitat use of sharks at FFS are required to better assess the likely ecological impacts of shark culling

3-Methyl-1-butanol production in Escherichia coli: random mutagenesis and two-phase fermentation

Interest in producing biofuels from renewable sources has escalated due to energy and environmental concerns. Recently, the production of higher chain alcohols from 2-keto acid pathways has shown significant progress. In this paper, we demonstrate a mutagenesis approach in developing a strain of Escherichia coli for the production of 3-methyl-1-butanol by leveraging selective pressure toward l-leucine biosynthesis and screening for increased alcohol production. Random mutagenesis and selection with 4-aza-d,l-leucine, a structural analogue to l-leucine, resulted in the development of a new strain of E. coli able to produce 4.4 g/L of 3-methyl-1-butanol. Investigation of the host’s sensitivity to 3-methyl-1-butanol directed development of a two-phase fermentation process in which titers reached 9.5 g/L of 3-methyl-1-butanol with a yield of 0.11 g/g glucose after 60 h

Ensemble Modeling for Aromatic Production in Escherichia coli

Ensemble Modeling (EM) is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate) to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt), transaldolase (Tal), and phosphoenolpyruvate synthase (Pps) to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning

Risk Assessment of Gastric Cancer Caused by Helicobacter pylori Using CagA Sequence Markers

As a marker of Helicobacter pylori, Cytotoxin-associated gene A (cagA) has been revealed to be the major virulence factor causing gastroduodenal diseases. However, the molecular mechanisms that underlie the development of different gastroduodenal diseases caused by cagA-positive H. pylori infection remain unknown. Current studies are limited to the evaluation of the correlation between diseases and the number of Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs in the CagA strain. To further understand the relationship between CagA sequence and its virulence to gastric cancer, we proposed a systematic entropy-based approach to identify the cancer-related residues in the intervening regions of CagA and employed a supervised machine learning method for cancer and non-cancer cases classification.An entropy-based calculation was used to detect key residues of CagA intervening sequences as the gastric cancer biomarker. For each residue, both combinatorial entropy and background entropy were calculated, and the entropy difference was used as the criterion for feature residue selection. The feature values were then fed into Support Vector Machines (SVM) with the Radial Basis Function (RBF) kernel, and two parameters were tuned to obtain the optimal F value by using grid search. Two other popular sequence classification methods, the BLAST and HMMER, were also applied to the same data for comparison.Our method achieved 76% and 71% classification accuracy for Western and East Asian subtypes, respectively, which performed significantly better than BLAST and HMMER. This research indicates that small variations of amino acids in those important residues might lead to the virulence variance of CagA strains resulting in different gastroduodenal diseases. This study provides not only a useful tool to predict the correlation between the novel CagA strain and diseases, but also a general new framework for detecting biological sequence biomarkers in population studies