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Updated: Jul 12, 2026

Quantitative Optical Microscopy: Measurement of Cellular Biophysical Features with a Standard Optical Microscope
Published on: April 7, 2014
2D HSQC-derived "dark forest" image with enhanced local resolution via first derivative processing-logarithmic cosine
Xiaohui Xing1, Jeffrey P Tingley2, Barinder Bajwa1
1Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, Alberta, T1J 4B1, Canada.
Abstract:
Solution-state two-dimensional (2D) 1H-13C HSQC NMR is a powerful tool for polysaccharide structure elucidation but often suffers from limited sensitivity and broad peaks due to the low natural abundance of 13C and poor digital resolution of the indirect dimension, respectively, as well as the typically low concentration and high viscosity of polysaccharide solutions. It is therefore pivotal to improve the resolution of 2D 1H-13C HSQC spectra for accurate peak picking and assignment, particularly in the indirect 13C dimension. In this study, we developed an algorithm that combines first derivative processing with a novel logarithmic cosine transformation (FDP-LCT) to convert 2D 1H-13C HSQC spectra into local-resolution-enhanced images resembling a dark forest of straight, densely standing trees. These images revealed sharpened spectral features and enabled extraction of precise 1H and 13C chemical shifts, as demonstrated using per-O-ethylated kappa- and iota-carrageenans, two sulfated galactans differing only by a single substitution at the O-2 position of anhydrogalactose. In conclusion, this approach provides an effective post-acquisition strategy for enhancing digital resolution in 2D HSQC spectra and improving the structural analysis of closely related complex polysaccharides.
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