Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Effects of Acidified Yeast and Whey Powder on Performance, Organ Weights, Intestinal Microflora, and Gut Morphology of Male Broilers

ABSTRACT In the present study, we investigated the effects of acidified dried whey and acidified yeast product and their combination on broiler growth characteristics, intestinal microflora and gut morphology. Seven hundred and fifty day-old Ross 308 male broilers were fed one of 10 dietary treatments with 5 replicates in a randomized design. A corn-soybean meal based diet (control group) was supplemented with 3 levels (0.15, 0.30 and 0.45%) of acidified whey powder (AW), acidified yeast product (AY), and acidified whey powder and yeast product (AWY). Acidified yeast product improved ADG and FCR at d 42, but the effects of additives on productive performance were not significant across the entire rearing period. The highest level of AY increased the population of Lactobacillus spp., decreased that of E. coli and did not affect the bacterial total count at d 42. Birds fed 0.45% AY showed higher villus height and better gut morphology compared to control birds. In conclusion, acidified yeast product increased the population of Lactobacillus, inhibited the growth of E. coli and improved gut morphology and structure, but did not affect growth performance and relative organ weight