Increased Peak Capacity Research Articles

Increasing throughput and information content for in vitro drug metabolism experiments using ultra‐performance liquid chromatography coupled to a quadrupole time‐of‐flight mass spectrometer

The field of drug metabolism has been revolutionized by liquid chromatography/mass spectrometry (LC/MS) applications with new technologies such as triple quadrupoles, ion traps and time-of-flight (ToF) instrumentation. Over the years, these developments have often relied on the improvements to the mass spectrometer hardware and software, which has allowed users to benefit from lower levels of detection and ease-of-use. One area in which the development pace has been slower is in high-performance liquid chromatography (HPLC). In the case of metabolite identification, where there are many challenges due to the complex nature of the biological matrices and the diversity of the metabolites produced, there is a need to obtain the most accurate data possible. Reactive or toxic metabolites need to be detected and identified as early as possible in the drug discovery process, in order to reduce the very costly attrition of compounds in late-phase development. High-resolution, exact mass measurement plays a very important role in metabolite identification because it allows the elimination of false positives and the determination of non-trivial metabolites in a much faster throughput environment than any other standard current methodology available to this field. By improving the chromatographic resolution, increased peak capacity can be achieved with a reduction in the number of co-eluting species leading to superior separations. The overall enhancement in the chromatographic resolution and peak capacity is transferred into a net reduction in ion suppression leading to an improvement in the MS sensitivity. To investigate this, a number of in vitro samples were analyzed using an ultra-performance liquid chromatography (UPLC) system, with columns packed with porous 1.7 mum particles, coupled to a hybrid quadrupole time-of-flight (ToF) mass spectrometer. This technique showed very clear examples for fundamental gains in sensitivity, chromatographic resolution and speed of analysis, which are all important factors for the demands of today's HTS in discovery.

Quantification of naphthalenes in jet fuel with GC x GC/Tri-PLS and windowed rank minimization retention time alignment.

Comprehensive, two-dimensional gas chromatography (GC x GC) is used in conjunction with trilinear partial least squares (Tri-PLS) to quantify the percent weight of naphthalenes (two-ring aromatic compounds) in jet fuel samples. The increased peak capacity and selectivity of GC x GC makes the technique attractive for the rapid, and possibly less tedious analysis of jet fuel. The analysis of complex mixtures by GC x GC is further enhanced through the use of chemometric techniques, including those designed for use on 2-D data such as Tri-PLS. Unfortunately, retention time variation, unless corrected, can be an impediment to chemometric analysis. Previous work has demonstrated that the effects of retention time variation can be mitigated in sub-regions of GC x GC chromatograms through the application of an objective retention time alignment algorithm based on rank minimization. Building upon this previous work, it is demonstrated here that the effects of retention time variation can be mitigated throughout an entire GC x GC chromatogram with an objective retention time alignment algorithm based on windowed rank minimization alignment. A significant decrease in calibration error is observed when the algorithm is applied to chromatograms prior to construction of Tri-PLS models. Fourteen jet fuel samples with known weight percentages of naphthalenes (ASTM D1840) were obtained. Each sample was subjected to five replicate five-minute GC x GC separations over a period of two days. A subset of nine samples spanning the range of weight percentages of naphthalenes was chosen as a calibration set and Tri-PLS calibration models were subsequently developed in order to predict the naphthalene content of the samples from the GC x GC chromatograms of the remaining five samples. Calibration models constructed from GC x GC chromatograms that were retention time corrected are shown to exhibit a root mean square error of prediction of roughly half that of calibration models constructed from uncorrected chromatograms. The error of prediction is lowered further to a value that nearly matches the uncertainty in the standard percent weight values (ca. 1% of the median percent volume value) when the aligned chromatograms are truncated to include only regions of the chromatogram populated by naphthalenes and compounds of similar polarity and boiling point.

Coadunation of Technologies: Cogeneration and Thermal Energy Storage

Thermal energy storage can help cogeneration meet the energy generation challenges of the 21st century by increasing the flexibility and performance of cogeneration facilities. Thermal energy storage (TES) allows a cogeneration facility to: (1) provide dispatchable electric power while providing a constant thermal load, and (2) increase peak capacity by providing economical cooling of the combustion turbine inlet air. The particular systems that are considered in this paper are high-temperature diurnal TES, and TES for cooling the combustion turbine inlet air. The paper provides a complete assessment of the design, engineering, and economic benefits of combining TES technology with new or existing cogeneration systems, while also addressing some of the issues involved.

Sample dimensionality: A predictor of order-disorder in component peak distribution in multidimensional separation

While the use of multiple dimensions in separation systems can create very high peak capacities, the effectiveness of the enhanced peak capacity in resolving large numbers of components depends strongly on whether the distribution of component peaks is ordered or disordered. Peak overlap is common in disordered distributions, even with a very high peak capacity. It is therefore of great importance to understand the origin of peak order/disorder in multidimensional separations and to address the question of whether any control can be exerted over observed levels of order and disorder and thus separation efficacy. It is postulated here that the underlying difference between ordered and disordered distributions of component peaks in separation systems is related to sample complexity as measured by a newly defined parameter, the sample dimensionality s, and by the derivative dimensionality s′. It is concluded that the type and degree of order and disorder is determined by the relationship of s (or s′) to the dimensionality n of the separation system employed. Thus for some relatively simple samples (defined as having small s values), increased order and a consequent enhancement of resolution can be realized by increasing n. The resolution enhancement is in addition to the normal gain in resolving power resulting from the increased peak capacity of multidimensional systems. However, for other samples (having even smaller s values), an increase in n provides no additional benefit in enhancing component separability.