Multicenter evaluation of the Selux Next-Generation Phenotyping antimicrobial susceptibility testing system.

The Selux Next-Generation Phenotyping (NGP) system (Charlestown, MA) is a new antimicrobial susceptibility testing system that utilizes two sequential assays performed on all wells of doubling dilution series to determine MICs. A multicenter evaluation of the performance of the Selux NGP system compared with reference broth microdilution was conducted following FDA recommendations and using FDA-defined breakpoints. A total of 2,488 clinical and challenge isolates were included; gram-negative isolates were tested against 24 antimicrobials, and gram-positive isolates were tested against 15 antimicrobials. Data is provided for all organism-antimicrobial combinations evaluated, including those that did and did not meet FDA performance requirements. Overall very major error and major error rates were less than 1% (31/3,805 and 107/15,606, respectively), essential agreement and categorical agreement were >95%, reproducibility was ≥95%, and the average time-to-result (from time of assay start to time of MIC result) was 5.65 hours.

Improved method for kinetic studies in microreactors using flow manipulation and noninvasive Raman spectrometry.

A novel method has been devised to derive kinetic information about reactions in microfluidic systems. Advantages have been demonstrated over conventional procedures for a Knoevenagel condensation reaction in terms of the time required to obtain the data (fivefold reduction) and the efficient use of reagents (tenfold reduction). The procedure is based on a step change from a low (e.g., 0.6 µL min(-1)) to a high (e.g., 14 µL min(-1)) flow rate and real-time noninvasive Raman measurements at the end of the flow line, which allows location-specific information to be obtained without the need to move the measurement probe along the microreactor channel. To validate the method, values of the effective reaction order n were obtained employing two different experimental methodologies. Using these values of n, rate constants k were calculated and compared. The values of k derived from the proposed method at 10 and 40 °C were 0.0356 ± 0.0008 mol(-0.3) dm(0.9) s(-1) (n = 1.3) and 0.24 ± 0.018 mol(-0.1) dm(0.3) s(-1) (n = 1.1), respectively, whereas the values obtained using a more laborious conventional methodology were 0.0335 ± 0.0032 mol(-0.4) dm(1.2) s(-1) (n = 1.4) at 10 °C and 0.244 ± 0.032 mol(-0.3) dm(0.9) s(-1) (n = 1.3) at 40 °C. The new approach is not limited to analysis by Raman spectrometry and can be used with different techniques that can be incorporated into the end of the flow path to provide rapid measurements.

Non-invasive analysis in micro-reactors using Raman spectrometry with a specially designed probe.

An optical interface has been designed to maximise the sensitivity and spatial resolution required when Raman spectrometry is used to monitor a reaction in a micro-reactor, revealing advantages over a conventional commercial probe. A miniature aspheric lens was shown to be better than microscope objectives to focus the probing laser beam onto the sample. The diameters of the exciting and collection optical fibres were also shown to have a significant influence on sensitivity and the signal-to-background ratio, with 62.5 microm diameter 0.28 numerical aperture (NA) fibres found to be best for analysis of liquids in the 150 microm deep channel in the micro-reactor used. With a spectral measurement time of 2 s, it was shown that the probe could monitor the progress of an esterification reaction in real time and quickly optimise the reagent flow rates. The fast response time revealed features related to short-term pump instabilities and micro-reactor rheology effects that would not have been identified without rapid real-time measurements.

Automated cosmic spike filter optimized for process Raman spectroscopy.

Despite the existence of various methods to remove cosmic spikes from Raman data, only a few of them are suitable for process Raman spectroscopy. The disadvantages of these algorithms include increased analysis time, low accuracy of spike detection, or reliance on variable parameters that must be chosen by trial and error in each case. We demonstrate a novel approach to detecting cosmic spikes in process Raman data and validate it using a wide range of experimental data. This new method features a multistage spike recognition algorithm that is based on tracking sharp changes of intensity in the time domain. The algorithm effectively distinguishes cosmic spikes from random spectral noise and abrupt variations of Raman peaks, allowing accurate detection of both high and low intensity cosmic spikes. The procedure is free from variable user-defined parameters and operates reliably in a fully automated manner with a wide range of time-series process Raman data sets containing more than 40 to 50 spectra.