Automated Segmented-Flow Analysis - NMR with a Novel Fluoropolymer Flow Cell for High-Throughput Screening.

High-throughput analysis in fields such as industrial biotechnology, combinatorial chemistry, and life sciences is becoming increasingly important. Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique providing exhaustive molecular information on complex samples. Flow NMR in particular is a cost- and time-efficient method for large screenings. In this study, we have developed a novel 3.0 mm inner diameter polychlorotrifluoroethylene (PCTFE) flow cell for a segmented-flow analysis (SFA) - NMR automated platform. The platform uses FC-72 fluorinated oil and fluoropolymer components to achieve a fully fluorinated flow path. Samples were repeatably transferred from 96-deepwell plates to the flow cell by displacing a fixed volume of oil, with a transfer time of 42 s. 1H spectra were acquired fully automated with 500 and 600 MHz NMR spectrometers. The spectral performance of the novel PCTFE cell was equal to that of commercial glass cells. Peak area repeatability was excellent with a relative standard deviation of 0.1-0.5% for standard samples, and carryover was below 0.2% without intermediate washing. The sample temperature was conditioned by using a thermostated transfer line in order to reduce the equilibration time in the probe and increase the throughput. Finally, analysis of urine samples demonstrated the applicability of this platform for screening complex matrices.

Subexponential-Time Algorithms for Finding Large Induced Sparse Subgraphs.

Let C and D be hereditary graph classes. Consider the following problem: given a graph G ∈ D , find a largest, in terms of the number of vertices, induced subgraph of G that belongs to C . We prove that it can be solved in 2 o ( n ) time, where n is the number of vertices of G, if the following conditions are satisfied:the graphs in C are sparse, i.e., they have linearly many edges in terms of the number of vertices;the graphs in D admit balanced separators of size governed by their density, e.g., O ( Δ ) or O ( m ) , where Δ and m denote the maximum degree and the number of edges, respectively; andthe considered problem admits a single-exponential fixed-parameter algorithm when parameterized by the treewidth of the input graph. This leads, for example, to the following corollaries for specific classes C and D :a largest induced forest in a P t -free graph can be found in 2 O ~ ( n 2 / 3 ) time, for every fixed t; anda largest induced planar graph in a string graph can be found in 2 O ~ ( n 2 / 3 ) time.