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Fold recognition force fields based on statistics from native structures have become commonplace. New, nonphysical force fields based on optimizing parameters rather than reflecting Boltzmann statistics may offer improvement in force-field performance for threading and other applications. Improvements in sequence-to-structure alignments will also be essential for improved fold recognition.
Quantitative analysis of [(18)F]-fluoro-deoxyglucose (FDG) uptake is important in oncologic positron emission tomography (PET) studies to be able to set an objective threshold in determining if a tissue is malignant or benign, in assessing response to therapy, and in attempting to predict the aggressiveness of an individual tumor. The most common method used today for simple, clinical quantitation is standardized uptake value (SUV). SUV is normalized for body weight. Other potential normalization factors are lean body mass (LBM) or body surface area (BSA). More complex quantitation schemes include simplified kinetic analysis (SKA), Patlak graphical analysis (PGA), and parameter optimization of the complete kinetic model to determine FDG metabolic rate (FDGMR). These various methods were compared in a group of 40 patients with colon cancer metastatic to the liver. The methods were assessed by (1) correlation with FDGMR, (2) ability to predict survival using Kaplan-Meier plots, and (3) area under receiver operating characteristic (ROC) curves for distinguishing between tumor and normal liver. The best normalization scheme appears to be BSA with minor differences depending on the specific formula used to calculate BSA. Overall, PGA is the best predictor of outcome and best discriminator between normal tissue and tumor. SKA is almost as good. In conventional PET imaging it is worthwhile to normalize SUV using BSA. If a single blood sample is available, it is possible to use the SKA method, which is distinctly better. If more than one image is available, along with at least one blood sample, PGA is feasible and should produce the most accurate results.
RATIONALE AND OBJECTIVES: We sought to induce large zones of coagulation necrosis using radiofrequency (RF) with perfusion electrodes and to define optimal parameters for this system. METHODS: We developed RF electrodes with internal cannulas to enable tip perfusion. Lesions were created with monopolar RF in ex vivo and in vivo liver and muscle tissue with and without perfusion of the electrode tip using 0 degree C saline. In separate experiments, wattage, current, procedure duration, tip exposure, and perfused tip temperatures were studied. RESULTS: In ex vivo liver tissue, a maximum lesion diameter of 3.1 cm without charring occurred with perfusion at 12 min and 50 W. In in vivo liver tissue with perfusion (tip temperature = 25-35 degrees C) and a 3-cm tip exposure, 80 W were deposited in muscle tissue and 65 W in liver tissue for 12 min without inducing charring. Lesion diameters were 4.5 cm and 2.4 cm, respectively. By comparison, without perfusion a maximum of 20 W could be deposited into either tissue type, resulting in 1.8-cm muscle lesions and 1.2-cm liver lesions. Tip temperatures between 45 degrees C and 55 degrees C resulted in charring. Smaller but predictable lesion diameters were created with a lower power, a shorter tip exposure, or both. Of all the parameters, diameter correlated best with the current applied. CONCLUSION: Perfusion of RF electrodes with chilled saline allows for increased power deposition without tissue charring, increasing the volume of coagulation necrosis created with a single electrode insertion. Perfusion electrodes therefore might decrease the number of probe insertions required for percutaneous tumor ablation therapy or allow for the treatment of larger lesions.
Hepatocyte transplantation (HTx) is technically feasible and can be clinically beneficial. Current research focuses on optimizing parameters which relate to the outcome of HTx, including site of transplantation, cell number and, most notably, the preferred cell type to be transplanted (differentiated adult vs. fetal hepatocytes vs. putative progenitor or precursor cells). However, the single major impediment towards the clinical effectiveness of HTx is the limited expansion of donor cells in the recipient liver. To this end, a relative growth advantage must be present or is to be imposed on transplanted hepatocytes versus resident cells. Possible strategies are presented and discussed.
A sensitive method for determining ultratrace volatile Se species produced from Brassica juncea seedlings is described. The use of a new commercially available GC/ ICPMS interface in conjunction with solid-phase micro-extraction is a promising way to perform these studies. The addition of optional gases (O2 and N2) to the argon discharge proved to increase the sensitivity for Se and S as well as for Xe, which as a trace contaminant gas, was used for ICPMS optimization studies. However, the optimization parameters differ when an optional gas is added. In the best conditions, limits of detection ranging from 1 to 10 ppt can be obtained depending on the Se compound and 30 to 300 ppt for the volatile S species. The use of GC/MS with similar sample introduction permits the characterization of several unknown species produced as artifacts from the standards. The method allows the virtually simultaneous monitoring of S and Se species from the headspace of several plants (e.g., onions, garlic, etc.) although the present work is focused on the B. juncea seedlings grown in closed vials and treated with Se. Dimethyl selenide and dimethyl diselenide were detected as the primary volatile Se components in the headspace. Sulfur species also were present as allyl (2-propenyl) isothiocyanate and 3-butenyl isothiocyanate as characterized by GC/MS.
Due to growing problems with new emerging pathogens, cost-effective and manageable methods for their accurate identification in routine diagnostics are urgently required. Of particular importance is the genus Mycobacterium with its more than 100 species. Identification of these species is hampered by their slow growth in the laboratory and by the obligate need for DNA sequence analysis. To provide a fast and reliable diagnostic tool, we developed a novel approach using fluorescently labeled DNA hairpin structures (smart probes) for selective and sensitive detection of mycobacterial 16S rDNA PCR amplicons in homogeneous and heterogeneous assays. Smart probes are singly labeled hairpin-shaped oligonucleotides bearing a fluorescent dye at the 5'-end, which is quenched by guanosine residues in the complementary stem. Upon hybridization to target sequences, a conformational change occurs reflected in an increase in fluorescence intensity. Using optimized parameters for hybridization experiments we established a reliable method for the specific detection of Mycobacterium tuberculosis (M. tuberculosis complex) and Mycobacterium xenopi (member of the atypical mycobacteria) with a detection sensitivity of approximately 2 x 10(-8) M in homogeneous solution. The specificity of the smart probes designed is demonstrated by discrimination of M. tuberculosis and M. xenopi against 15 of the most frequently isolated mycobacterial species in a single assay. In combination with a microsphere-based heterogeneous assay format, the technique opens new avenues for the detection of pathogen-specific DNA sequences with hitherto unsurpassed sensitivity.
A novel method of sample introduction into an isotope ratio mass spectrometer (IRMS) is described. The technique uses the chemical reaction interface (CRI) to convert samples coming from a gas chromatograph (GC) or high-performance liquid chromatograph (HPLC) into CO2 using a microwave-induced helium plasma. Optimization parameters for both GC/CRI/IRMS and HPLC/CRI/IRMS are described. In both modes of operation, it was possible to obtain 13CO2/12CO2 ratios with standard deviations less than 1%. Investigation of HPLC/CRI/IRMS performance at low and high concentrations (0.5-10 micrograms) resulted in no significant deviations of the isotope ratios. The ability to differentiate samples of different biological origins was illustrated using chlorophyll a from spinach and algae, where a large difference was observed but good precision was maintained (SD < 0.60%).
Solid-phase microextraction (SPME), capillary column gas chromatography, and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of gas chromatograms from 180 neat jet fuel samples representing common aviation turbine fuels found in the United States (JP-4, Jet-A, JP-7, JPTS, JP-5, JP-8). SPME sampling of the fuel's headspace afforded well-resolved reproducible profiles, which were standardized using special peak-matching software. The peak-matching procedure yielded 84 standardized retention time windows, though not all peaks were present in all gas chromatograms. A genetic algorithm (GA) was employed to identify features (in the standardized chromatograms of the neat jet fuels) suitable for pattern recognition analysis. The GA selected peaks, whose two largest principal components showed clustering of the chromatograms on the basis of fuel type. The principal component analysis routine in the fitness function of the GA acted as an information filter, significantly reducing the size of the search space, since it restricted the search to feature subsets whose variance is primarily about differences between the various fuel types in the training set. In addition, the GA focused on those classes and/or samples that were difficult to classify as it trained using a form of boosting. Samples that consistently classify correctly were not as heavily weighted as samples that were difficult to classify. Over time, the GA learned its optimal parameters in a manner similar to a perceptron. The pattern recognition GA integrated aspects of strong and weak learning to yield a "smart" one-pass procedure for feature selection.
Cell cultures of Taxus canadensis were subjected to exogenously applied ethylene (ET) hormone and methyl jasmonate (MJ) elicitation in factorial design experiments. Levels of extracellular taxanes, including paclitaxel, were used with principal component analysis for fault detection and real-coded genetic algorithms for parameter optimization to construct a culture sub-population induction model. Culture sub-populations were identified by the model as (1) uninduced, (2) induced to unilateral function of the ET-signaling pathway, and (3) induced to cooperation between jasmonic acid (JA)- and ET-signaling pathways. Comprehensive model results suggested greater rates of cellular induction (resulting in exogenous taxane production) by ET gas as opposed to MJ elicitation. However, cellular induction of ET-signaling pathway genes increased the rate of induction of JA-signaling pathway genes by orders of magnitude. In addition, model results showed that induction of genes leading to extracellular production of the simple taxane 10-deacetylbaccatin III was regulated by the unilateral ET-signaling pathway. However, it was suggested that further processing of this simple taxane to complex taxane structures, such as paclitaxel, required further gene induction by the JA-signaling pathway. Thus, production rate constants of exogenous complex taxanes were predicted to be an order of magnitude lower than that for the simple taxane 10-deacetylbaccatin III. The fraction of the cell culture sub-population displaying unilateral ET-signaling pathway gene induction was found inversely proportional to levels of MJ elicitation. When coupled with simple non-growth product models, levels of all extracellular taxanes were effectively predicted using the culture sub-population induction model.
This paper explores the utility of data mining and machine learning algorithms for the induction of mutagenicity structure-activity relationships (SARs) from noncongeneric data sets. We compare (i) a newly developed algorithm (MOLFEA) for the generation of descriptors (molecular fragments) for noncongeneric compounds with traditional SAR approaches (molecular properties) and (ii) different machine learning algorithms for the induction of SARs from these descriptors. In addition we investigate the optimal parameter settings for these programs and give an exemplary interpretation of the derived models. The predictive accuracies of models using MOLFEA derived descriptors is approximately 10-15%age points higher than those using molecular properties alone. Using both types of descriptors together does not improve the derived models. From the applied machine learning techniques the rule learner PART and support vector machines gave the best results, although the differences between the learning algorithms are only marginal. We were able to achieve predictive accuracies up to 78% for 10-fold cross-validation. The resulting models are relatively easy to interpret and usable for predictive as well as for explanatory purposes.
Weighted least-squares spline functions are discussed and applied for calibration processes in analytical chemistry. Different weighting techniques are also considered, and for the evaluation of the results some quality coefficients are proposed. Depending upon the structure of the data, some weighting procedures may improve the results dramatically. Considering the results obtained in the case of TLC densitometry, it seems that nonlinear weighting procedures based upon the distance to the function are the best ones, with a plus for the y-distance type. It is difficult to give general rules regarding the optimal parameters of the weighted calibration splines-function order (m), number (N) and distribution of knots, and weighting technique. These depend upon the structure of the data. However, higher order splines are not recommended since the result might become extremely unstable. The example used to illustrate the performances of the procedures discussed here involved only a single independent variable. The method is general and extends practically to any number of variables, thus resulting in a multivariate approach.
The coagulation-flocculation process incorporated with membrane separation technology will become a new approach for palm oil mill effluent (POME) treatment as well as water reclamation and reuse. In our current research, a membrane pilot plant has been used for POME treatment where the coagulation-flocculation process plays an important role as a pretreatment process for the mitigation of membrane fouling problems. The pretreated POME with low turbidity values and high water recovery are the main objectives to be achieved through the coagulation-flocculation process. Therefore, treatment optimization to serve these purposes was performed using jar tests and applying a response surface methodology (RSM) to the results. A 2(3) full-factorial central composite design (CCD) was chosen to explain the effect and interaction of three factors: coagulant dosage, flocculent dosage, and pH. The CCD is successfully demonstrated to efficiently determine the optimized parameters, where 78% of water recovery with a 20 NTU turbidity value can be obtained at the optimum value of coagulant dosage, flocculent dosage, and pH at 15 000 mg/L, 300 mg/L, and 6, respectively.
Fourier transform infrared spectroscopy is a popular method for the experimental investigation of hydrogen-bonded aggregates, but linking spectral information to microscopic information on aggregate size distribution and aggregate architecture is an arduous task. Static electronic structure calculations with an implicit solvent model, Car-Parrinello molecular dynamics (CPMD) using the Becke-Lee-Yang-Parr (BLYP) exchange and correlation energy functionals and classical molecular dynamics simulations for the all-atom version of the optimized parameters for liquid simulations (OPLS-AA) force field were carried out for an ensemble of 1-hexanol aggregates solvated in n-hexane. The initial configurations for these calculations were size-selected from a distribution of aggregates obtained from a large-scale Monte Carlo simulation. The vibrational spectra computed from the static electronic structure calculations for monomers and dimers and from the CPMD simulations for aggregates up to pentamers demonstrate the extent of the contribution of dangling or nondonating hydroxyl groups found in linear and branched aggregates to the "monomeric" peak. Furthermore, the computed spectra show that there is no simple relationship between peak shift and aggregate size nor architecture, but the effect of hydrogen-bond cooperativity is shown to differentiate polymer-like (cooperative) and dimer-like (noncooperative) hydrogen bonds in the vibrational spectrum. In contrast to the static electronic structure calculations and the CPMD simulations, the classical molecular dynamics simulations greatly underestimate the vibrational peak shift due to hydrogen bonding.
Extrusion cooking processing followed by air-drying has been applied to obtain low-fat potato snacks. Optimal parameters were developed for a dough recipe. Dough contained apart from potato granules 7% of canola oil, 1% of salt, 1% of baking powder, 5% of maltodextrin, and 15% of wheat flour. After the extrusion process, snacks were dried at 85 degrees C for 15 min followed by 130 degrees C for 45 min. The potent odorants of extruded potato snacks were identified using aroma extract dilution analysis and gas chromatography-olfactometry. Among the characteristic compounds, methional with boiled potato flavor, benzenemethanethiol with pepper-seed flavor, 2-acetyl-1-pyrroline with popcorn flavor, benzacetaldehyde with strong flowery flavor, butanal with rancid flavor, and 2-acetylpyrazine with roasty flavor were considered to be the main contributors to the aroma of extruded potato snacks. Several compounds were concluded to be developed during extrusion cooking, such as ethanol, 3-methylbutanal, (Z)-1,5-octadien-3-one with geranium flavor, and unknown ones with the flavor of boiled potato, cumin, candy, or parsley root. Compounds such as methanethiol, 2,3-pentanedione, limonene, 2-acetylpyrazine, 2-ethyl-3,5-dimethylpyrazine, 4-hydroxy-2,5-dimethyl-3(2H)-furanone, 3-hydroxy-4,5-dimethyl-2(5H)-furanone, 2-methyl-3,5-diethylpyrazine, 5-methyl-2,3-diethylpyrazine, and (E)-beta-damascenone were probably developed during air-drying of the potato extrudate.
When stabilized BH(3-)THF (BTHF) was added to a mixture of ketone and tetrahydro-1-methyl-3,3-diphenyl-1H,3H-pyrrolo[1,2-c][1,3,2]oxazaborole (MeCBS-ozaxaborolidine, MeCBS) catalyst 1, low enantioselectivities resulted. Several relative rate experiments showed that a borohydride species in BTHF catalyzed the nonselective borane reduction of ketones, effectively competing with enantioselective MeCBS reduction of ketones, lowering the overall selectivity of the reaction. Improved enantioselectivities in the reaction are obtained by reversing the mode of addition (ketone to BTHF and catalyst), lowering the concentration of NaBH(4) stabilizer in the BTHF solution (87-95% ee) and increasing the concentration or addition rate of BTHF. Decreased reaction temperature and increased catalyst loading only slightly improved the selectivity of the reaction. Upon reaction parameter optimization, simultaneous addition of substrate and BTHF to MeCBS catalyst stabilizer resulted in the highest overall enantioselectivities (96% ee) and diminished the effect of the borohydride. Alternatively, the addition of Lewis acids such as BF(3-)THF to the reaction mixture effectively destroyed the NaBH(4) stabilizer in BTHF solutions, restoring the enantioselectivity to acceptable levels.
Multiwalled carbon nanotubes (MWCNTs) were grown by chemical vapor deposition by applying C(2)H(2) fluxed over Fe(1)(-x)Co(x) catalyst supported by alkaline earth carbonate. Detailed investigations of the chemical process occurring prior and during the growth allowed us a significant improvement of the nanotube production rate and quality. We observed a strong influence of the catalyst stoichiometry on the carbon deposition rate and the nanotube characteristics. We also found evidence for the active role of the support in the growth process, which is explained by the decomposition of the carbonate at the growth temperature. Using the optimized parameters obtained from our study performed in a fixed bed furnace, we could improve the production rate to about 500 g/day of purified MWCNTs in our large-scale rotary tube furnace.
The molecular geometries, conformational energies, and zero-point energies of di(trimethylsilylene)methylene have been determined from high-level quantum chemistry calculations. The results are further used in the parametrization of a classical potential energy function suitable for performing simulations of the corresponding polymer, namely, poly(dimethylsilylenemethylene). Di(trimethylsilylene)methylene geometrical parameter optimizations for a proper location of the global minimum and other local minima, constrained at certain dihedral and bond angles, were performed at both the B3LYP/6-311G and MP2(full)/6-311G levels of theory. The global minimum configuration is slightly displaced from a perfectly staggered geometry, approximately by 16.0 degrees, at both levels of theory. Molecular mechanics and Monte Carlo calculations for isolated polymer chains together with molecular dynamics runs for the modeled dimer provide very good results in terms of conformational and thermodynamic properties.
The radical reaction mechanism of FCO + NO on the ground electronic state energy surface has been studied at the G2M level of theory based on the geometric parameters optimized at the B3LYP/6-311+G(d) level of theory. The two kinds of reaction pathways include the direct fluorine abstraction channel producing CO + FNO and the association channel forming the FC(O)NO complex. The former has a distinct barrier of 8.9 kcal mol(-1), while the latter is a barrierless association process. The rate constant of this reaction system in the temperature range 200-3000 K has been calculated by the microcanonical VTST/RRKM theory. The theoretical result shows that the predicted total rate constants exhibit a negative-temperature dependence and positive-pressure effect at lower temperatures. Under the experimental conditions, the predicted values are in good agreement with the experimental results. In addition, the predicted branching ratios clearly indicate that the dominant product channel is the formation of FC(O)NO at low temperatures and FNO + CO at high temperatures (>500 K).