Evaluation of applied biosystems MicroSEQ real-time PCR system for detection of Salmonella spp. in food

Real-time PCR methods for detecting foodborne pathogens offer the advantages of simplicity and quick time-to-results compared to traditional culture methods. In this study, the MicroSEQ real-time PCR system was evaluated for detection of Salmonella spp. in 10 different food matrixes following the AOAC Research Institute's Performance Tested Method validation program. In addition, the performance of the MicroSEQ system was evaluated for the detection of Salmonella in peanut butter as a part of the Emergency Response Validation Program sponsored by the AOAC Research Institute. The system was compared to the ISO 6579 reference method using a paired-study design for detecting Salmonella spp. in raw ground beef, raw chicken, raw shrimp, Brie cheese, shell eggs, cantaloupe, chocolate, black pepper, dry infant formula, and dry pet food. For the peanut butter study, the system was compared to the U.S. Food and Drug Administration's Bacteriological Analytical Manual procedures using an unpaired-study design. No significant difference in performance was observed between the MicroSEQ Salmonella spp. detection system and the corresponding reference methods for all 11 food matrixes. The MicroSEQ system detected all Salmonella strains tested, while showing good discrimination against detection of an exclusivity panel of 30 strains, with high accuracy.     

Evaluation of applied biosystems MicroSeq real-time PCR system for detection of Listeria monocytogenes in food. Performance Tested Method 011002

Increasingly, more food companies are relying on molecular methods, such as PCR, for pathogen detection due to their improved simplicity, sensitivity, and rapid time to results. This report describes the validation of a new Real-Time PCR method to detect Listeria monocytogenes in nine different food matrixes. The complete system consists of the MicroSEQ L. monocytogenes Detection Kit, sample preparation, the Applied Biosystems 7500 Fast Real-Time PCR instrument, and RapidFinder Express software. Two sample preparation methods were validated: the PrepSEQ Nucleic Acid extraction kit and the PrepSEQ Rapid Spin sample preparation kit. The test method was compared to the ISO 11290-1 reference method using an unpaired-study design to detect L. monocytogenes in roast beef, cured bacon, lox (smoked salmon), lettuce, whole cow's milk, dry infant formula, ice cream, salad dressing, and mayonnaise. The MicroSEQ L. monocytogenes Detection Kit and the ISO 11290-1 reference method showed equivalent detection based on Chi-square analysis for all food matrixes when the samples were prepared using either of the two sample preparation methods. An independent validation confirmed these findings on smoked salmon and whole cow's milk. The MicroSEQ kit detected all 50 L. monocytogenes strains tested, and none of the 30 nontargeted bacteria strains.     

Lattice gauge fields and noncommutative geometry

Conventional approaches to lattice gauge theories do not properly consider the topology of spacetime or of its fields. In this paper, we develop a formulation which tries to remedy this defect. It starts from a cubical decomposition of the supporting manifold (compactified space-time or spatial slice) interpreting it as a finite topological approximation in the sense of Sorkin. This finite space is entirely described by the algebra of cochains with the cup product. The methods of Connes and Lott are then used to develop gauge theories on this algebra and to derive Wilson's actions for the gauge and Dirac fields therefrom which can now be given geometrical meaning. We also describe very natural candidates for the QCD θ-term and Chern-Simons action suggested by this algebraic formulation. Some of these formulations are simpler than currently available alternatives. The paper treats both the functional integral and Hamiltonian approaches.     

Expected escape times from attractor basins due to low intensity noise

In this paper, a numerical approach is described to estimate escape times from attractor basins when a dynamical system is subjected to noise or stochastic perturbations. Noise can affect nonlinear system response by driving solution trajectories to different attractors. The changes in physical behavior can be observed as amplitude and phase change of periodic oscillations, initiation or annihilation of chaotic motion, phase synchronization, and so on. Estimating probability of transitions from one attractor to another, and predicting escape times are essential for quantifying the effects of noise on the system response. In this paper, a numerical approach is outlined where probability transition maps are generated between grids. Then, these maps are iterated to find the probability distribution after long durations, wherein, a constant escape rate can be observed between basins. The constant escape rate is then used to estimate the average escape times. The approach is applicable to systems subjected to low-intensity stochastic disturbances and with long escape times, where Monte Carlo simulations are impractical. Escape times up to \(10^{13}\) periods are estimated without relying on computationally expensive computations.