Retention of the developmental pluripotency in medaka embryonic stem cells after gene transfer and long-term drug selection for gene targeting in fish

Embryonic stem (ES) cells provide a unique tool for introducing random or targeted genetic alterations, because it is possible that the desired, but extremely rare recombinant genotypes can be screened by drug selection. ES cell-mediated transgenesis has so far been limited to the mouse. In the fish medaka (Oryzias latipes) several ES cell lines have been made available. Here we report the optimized conditions for gene transfer and drug selection in the medaka ES cell line MES1 as a prelude for gene targeting in fish. MES1 cells gave rise to a moderate to high transfection efficiency by the calcium phosphate co-precipitation (5%), commercial reagents Fugene (11%), GeneJuice (21%) and electroporation (>30%). Transient gene transfer and CAT reporter assay revealed that several enhancers/promoters and their combinations including CMV, RSV and ST (the SV40 virus early gene enhancer linked to the thymidine kinase promoter) were suitable regulatory sequences to drive transgene expression in the MES1 cells. We show that neo, hyg or pac conferred resistance to G418, hygromycin or puromycin for positive selection, while the HSV-tk generated sensitivity to ganciclovir for negative selection. The positive-negative selection procedure that is widely used for gene targeting in mouse ES cells was found to be effective also in MES1 cells. Importantly, we demonstrate that MES1 cells after gene transfer and long-term drug selection retained the developmental pluripotency, as they were able to undergo induced differentiation in vitro and to contribute to various tissues and organs during chimeric embryogenesis.

Dissociated screw dislocation which can relieve strain energy in the epitaxial layer of GeSi on Si(001)

A dissociated screw dislocation parallel to the interface was found in the epitaxial layer of the Ge0.17Si0.83 Si(001) system. It is shown that this dissociated screw dislocation which consists of two 30 degrees partials can relieve misfit strain energy, and the relieved misfit energy is proportional to the width of the stacking fault between the two partials.

Molecular-dynamics investigation on polarization retention of barium titanate nanofilm arising from ordered oxygen vacancy

Molecular-dynamics simulations have been carried out to investigate the electric hysteresis of barium titanate nanofilm containing oxygen vacancy ordering array parallel to the {101} crystal plane. The results obtained show a significant weakening of polarization retention from non-zero value to zero as the size of the array was reduced to a critical level, which was attributed to the formation and motion of head-to-head domain wall structure under external field loading process. By comparing with materials containing isolated oxygen vacancies, it was found that the zero retention was due to the oxygen vacancy ordering array rather than to the concentration of oxygen vacancy. Copyright (C) EPLA, 2010

Using HPLC retention parameters to estimate fish bioconcentration factors of organic compounds

Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.

New uniform algorithm to predict reversed phase retention values under different gradient conditions

A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC with several retention times under different linear or nonlinear binary gradient elution conditions and further predict the retention time under any other binary gradient conditions. A program was written according to this algorithm and nine solutes were used to test the program. The prediction results were excellent. The maximum relative error of predicted retention time was less than 0.45%. (C) 2002 Elsevier Science B.V. All rights reserved.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Abnormal phenomenon of the dependence of the retention factors for uncharged species on applied voltage in capillary electrochromatography

Polymethacrylate-based monolithic columns were prepared for capillary electrochromatography (CEC) by in situ copolymerization of butyl methacrylate (BMA), 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS), and ethylene dimethacrylate (EDMA) in the presence of a porogen in fused-silica capillaries of 100 mum I.D. The abnormal phenomenon that retention factors for neutral species decreases with applied voltage in CEC was observed. Capillary electrophoresis (CE) instruments usually require a period of time to increase voltage from 0 kV to desired value, which is called as ramp time. Such ramp time and any error in the determination of dead time should be taken into account during the accurate calculation of retention factors. After the correction of the retention factors, the plots of the corrected factors for alkylbenzene versus applied voltage were made, the absolute value of the plot slopes are less than 1.8 X 10(-4), Which indicates that the corrected retention times for neutral species do not show any dependence on applied voltage. Further, the plots of the corrected retention times for acidic and basic compounds versus the reciprocal of applied voltage were drawn, where the target compounds were eluted in neutral form. The very nice linearity of the plots was obtained. The linear correlation coefficients are over 0.999. Here, the slopes of the plots represent

Correlation analysis of the structures and gas-liquid chromatographic retention indices of amines

Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.