CMC Method Research Articles

Isolation and Molecular Identification of Cellulase producing bacteria from soil and litter in Veerakkal forest area, The Western Ghats, India

The cellulolytic bacterial strains were screened from both soil and litter samples in different study sites of Veerakkal forest, Manar beat, The Western Ghats, India. In the current investigation, out of 64 and 48 differentiated total purified isolates, 53 soil isolates and 34 litter isolates were screened based on the CMC method. The percent wise calculation indicated that 82 % were cellulase positive while 18 % were negative in soil isolates. Likewise, 70 % of them were positive while 30 % were negative cellulase strains in litter isolates. The average hydrolysis capacity (HC) values ranged between 1.67 to 3.25 cm. The highly potential cellulolytic bacterial isolates viz. Bacillus thuringiensis, Bacillus licheniformis, Bacillus cereus, Bacillus sporothermodurans, Bacillus circulans, Bacillus albus, Bacillus amyloliquefaciens, Lysinibacillus sphaericus and Bacillus mobilis were identified from soil. Likewise, the litter cellulolytic bacterial species such as Bacillus sp., Lysinibacillus macroides, Bacillus paramycoides, Solibacillus silvestris, Pseudomonas stutzeri, Bacillus toyonensis, Bacillus subtilis, Bacillus pacificus, Bacillus flexus, Bacillus paranthracis and Pseudomonas putida were identified. The cellulolytic bacterial population was higher during the monsoon because of the presence of higher moisture content in leaf litter. However, the cellulolytic bacterial population of soil was higher during the pre-monsoon season because of the continuous breakdown of litter which inhaled more cellulolytic strains in the soil. Finally, it was concluded that corresponding with seasonal changes, the cellulolytic bacterial community also changed and it plays a significant role in the mineralization process.

Fe3O4@SiO2 nanocomposite immobilized with cellulase enzyme: Stability determination and biological activity

The preparation of biocatalysts based on immobilized cellulase is of great importance for proteomic research, industrial applications, and organic synthesis. Herein, Fe3O4 magnetic nanoparticles were synthesized by the coprecipitation method to immobilize the cellulase enzyme and modified to increase its efficiency and stability. Hence, Fe3O4 MNPs were coated with silica by the Stober method, and the surface of Fe3O4@SiO2 nanocomposite was modified with an organosilane. To prevent surface adhesion, the nanocomposite was modified by APTES, and TCT was used as a linker for the immobilization of cellulase. The cellulase enzyme was covalently bonded to the nanocomposite via physical adsorption to synthesize cellulose-Fe3O4@SiO2-NH2 NC and increase its activity and stability. The maximum immobilization of the enzyme occurred at pH = 5, which was close to the isoelectric pH, and the optimum time and temperature for enzyme activity were 1 h and 50 °C. The binding efficiency was around 99 % by using the Bradford method. The maximum activity of the enzyme calculated by the CMC method was 0.08 μmol/min.ml. The adsorption capacity of immobilized cellulase was 33 mg/g toward bovine serum albumin (BSA). The results indicated that the activity and stability of the immobilized enzyme were enhanced in comparison with the free enzyme.

Modelling of hydrogen flame in perfectly clean combustion regimes using LES-CMC

The LES coupled with the first-order CMC method and detailed chemical mechanism is used for the calculations of hydrogen jet burning in the atmosphere of water vapour and oxygen mixture. The flame is initiated by a spark, then it spreads and propagates through the domain and eventually stabilises as a lifted or attached one. Three dimensional calculations were proceeded with analysis of the flame in the mixture fraction space. The main focus of the paper is on the effect of oxidizer composition on the flame characteristics and stabilization mechanisms. The flame structure during the propagation phase is represented based on the so-called pre-ignition species. Time-averaged results show the flame lift-off distance, shape and radial size. It is found that these factors may be effectively controlled by the amount of water vapour in the co-flowing oxidizer.

Simulating realistic geological stratigraphy using direction-dependent coupled Markov chain model

The design of geotechnical structures depends significantly on soil stratigraphy. The determination of geological stratigraphy is generally based on site investigations such as drilling, standard penetration tests and cone penetration tests. When the in-situ tests or boreholes are limited, the characterization of complex strata is difficult. The objective of this study is to develop an improved coupled Markov chain model (CMC) to simulate complex geological stratigraphy based only on limited in-situ data. The traditional CMC model is improved by developing a direction-dependent CMC method to address the strong variation of soil properties among boreholes. The difficulty in simulating different dip directions and prisms in a geological profile is solved by developing proper simulation direction in the modelling. The stratigraphy at a construction site in Hong Kong is characterized using the proposed method. It is found that both upwards and downwards inclined interfaces can be simulated very well. The prisms within a soil layer can be predicted. The accuracy of the method is closely related to the locations of the existing boreholes. The influence distance of a borehole is approximately 14 m.

Application of the Lagrangian CMC method in elliptic bluff body and swirl flames

The Lagrangian CMC method was implemented in the open source programme OpenFOAM and applied to turbulent nonpremixed bluff body and swirl flames. Lagrangian CMC is more efficient than Eulerian CMC with the number of Lagrangian flame groups much less than the number of computational cells for Eulerian CMC equations in general. It is based on the conditional flame structure depending on the residence time of the fuel of fixed Lagrangian identity from the nozzle. According to sensitivity study the injected fuel was divided into ten flame groups according to the injection sequence with the resulting conditional profiles between those by ISR and Eulerian CMC. Minor deviation from Eulerian CMC was attributed to the flame structure that is difficult to be characterised by the residence time only in elliptic recirculating flows of the bluff body and swirl flames. The Eulerian and Lagrangian CMC showed the same trend of deviation from measurements for conditional temperature, H2O, OH, CO and H2 mass fractions. The significant deviation of H2 was due to uncertainty in the reaction chemistry, as observed in the previous works based on other reaction mechanisms for methane and methanol.

Recognition and identification of active components from Radix Bupleuri using human neuroblastoma SH-SY5Y cells.

The aim of the study was to screen active components of Radix Bupleuri (a traditional Chinese herb) and discover novel anti-schizophrenic candidate drugs using human neuroblastoma SH-SY5Y cells. SH-SY5Y cells were used for preparation of the stationary phase in the cell membrane chromatography model. Retention components by the SH-SY5Y/CMC model were collected and then analyzed by GC/MS under the optimized conditions in offline conditions. After investigating the suitability and reliability of the SH-SY5Y/CMC method using amisulpride and haloperidol as standard compounds, this method was applied to screening active components from the extracts of Radix Bupleuri. Retention components of SH-SY5Y/CMC model were saikosaponin A, saikosaponin B1, saikosaponin B2, saikosaponin C and saikosaponin D, which were identified by the GC/MS method. In vitro pharmacological trials-MTT, saikosaponin B1, saikosaponin B2 and saikosaponin C could protect SY5Y cells. The protective effects of saikosaponin B1 and saikosaponin C were concentration dependent. Saikosaponin A and saikosaponin D inhibited cell viability at concentrations >30 µg/mL (p < 0.05). Via SH-SY5Y/CMC method and SH-SY5Y MTT trial, we rapidly detected target components from Radix Bupleuri, accurately identified them and determined their different effects on SH-SY5Y cells. Saikosaponin B1, saikosaponin B2 and saikosaponin C may be anti-schizophrenic candidate drugs.

First and second order lagrangian conditional moment closure method in turbulent nonpremixed flames

The Lagrangian CMC method is developed by conditionally averaging the quantities associated with Lagrangian particles originating from the nozzle exit. It involves multiple flame groups of sequentially injected fuel, each of which shares the same conditional flame structure under the same residence time. The probability, pk, to find the kth group is assumed proportional to the partial mean mixture fraction, ξk∼, to obtain the local conditional flame structure as a weighted average by pk. The Lagrangian CMC method allows flexibility of flamelet based methods and requires less computational load than Eulerian CMC. It is implemented in OpenFOAM and applied with first and second order closure to the piloted jet diffusion flames near extinction, Sandia Flame D and E. Results show good agreement for all conditional profiles and noticeable improvement by second order correction of four rate limiting steps in the GRI 3.0 mechanism. Good agreement is achieved for conditional variances and covariances among temperature and species involved in the rate limiting reaction steps.

1339 – Sh-sy5y/cmc, a new screening method of antipsychotic chinese herbal active ingredients

We describe an analytical method of SH-SY5Y cell membrane chromatography (SH-SY5Y/CMC) for recognition, separation and identification of active components from traditional Chinese medicines (TCMs). SH-SY5Y cells by means of culture with SH-SY5Y cell lines were used for preparation of the stationary phase in the CMC model. Retention components by the SH- SY5Y/CMC model were collected and active components then analyzed by SH-SY5Y/CMC under the optimized conditions. After investigating the suitability and reliability of the SH-SY5Y /CMC method using risperidone, sertraline and clozapine as standard compounds, this method was applied in screening active components from the extracts of TCMs such as Radix Gentianae, Radix Bupleuri, stir-baked semen ziziphi spinosae, rehmannia dride rhizome, uncaria rhynchophylla. Retention components from the extracts in the SH-SY5Y/CMC model were gentiopicrin and rosmarinci acid identified by the GC/MS method. In vitro pharmacological trials indicated that gentiopicrin and rosmarinci acid could concentration dependently protect the SH-SY5Y pre-treated by H 2 O 2 (P

Association studies for next-generation sequencing

Genome-wide association studies (GWAS) have become the primary approach for identifying genes with common variants influencing complex diseases. Despite considerable progress, the common variations identified by GWAS account for only a small fraction of disease heritability and are unlikely to explain the majority of phenotypic variations of common diseases. A potential source of the missing heritability is the contribution of rare variants. Next-generation sequencing technologies will detect millions of novel rare variants, but these technologies have three defining features: identification of a large number of rare variants, a high proportion of sequence errors, and a large proportion of missing data. These features raise challenges for testing the association of rare variants with phenotypes of interest. In this study, we use a genome continuum model and functional principal components as a general principle for developing novel and powerful association analysis methods designed for resequencing data. We use simulations to calculate the type I error rates and the power of nine alternative statistics: two functional principal component analysis (FPCA)-based statistics, the multivariate principal component analysis (MPCA)-based statistic, the weighted sum (WSS), the variable-threshold (VT) method, the generalized T(2), the collapsing method, the CMC method, and individual tests. We also examined the impact of sequence errors on their type I error rates. Finally, we apply the nine statistics to the published resequencing data set from ANGPTL4 in the Dallas Heart Study. We report that FPCA-based statistics have a higher power to detect association of rare variants and a stronger ability to filter sequence errors than the other seven methods.

Measurements of Scalar Dissipation in Turbulent Hydrogen Diffusion Flames and Some Implications on Combustion Modeling

One-dimensional simultaneous measurements of the species mass fractions of O2, H2 H2O, N2 and OH radical as well as flame temperature have been carried out in hydrogen jet diffusion flames diluted with Ar using the line-Raman/Rayleigh/LIPF-OH technique. Statistical information about the mixture fraction Z and scalar dissipation rate x can be obtained for evaluation of current finite-chemistry combustion models for the turbulent nonpremixed flames. At an upstream position of x/d = 8, the flamelet approach is found to be qualitatively valid, in agreement with a larger Favre mixture fraction fluctuation than the reaction zone thickness in the Z-space. Transient effect, however, can be important in view of H2 and O2 superequilibrium. Preferential diffusion effects are negligible due to a relatively large Peclet number. Joint correlations between a reactive scalar T with δ and the conserved scalar Z with γ are found to be different from those reported in nonreacting flows. The observed distinct features can be explained based on the flamelet concept so that statistical independence is argued to be a good approximation. There is evidence showing that large-scale turbulent motion dominates scalar transport in the connected reaction zone regime. Thus, flamelet approach is also favored. Some modeling assumptions used in the flamelet model and the CMC method are discussed. Model refinements based on the present experimental data are suggested as well.