Increased Speed of Analysis and Sample Throughput with Kinetex Core-Shell Technology
The introduction of the new Kinetex core-shell technology provides a significant benefit to all separation scientists looking to increase sample throughput by reducing chromatographic analysis times while maintaining chromatographic resolution. This is especially important for QC labs, which typically have limited resources and can benefit the most from faster separations and higher sample throughput, allowing them to make the best use of their limited resources. However, the benefits derived from faster separations are equally important to discovery and method development departments as well.
How feasible is it to integrate this Bayesian graph-theory methodology into existing commercial chromatography software workflows for semi-automated data curation in routine analytical laboratories?
Gabriel Vivó-Truyols outlines the benefits and challenges of combining graph theory with Bayesian statistics to automate peak assignment and alignment.
This week, Chromatography Online’s coverage spanned lipidomics-based early cancer detection, career paths in separation science, machine learning and uncertainty-driven approaches to LC method development, new EU wastewater rules for pharmaceutical micropollutants, automated Separation Quality Factor (SQF) evaluation in chromatography data systems, and solutions to GLP-1 peptide analysis challenges.
Gabriel Vivó-Truyols from the Spanish Council for Scientific Research, Madrid, Spain. discusses his work on using graph theory and Bayesian statistics for peak assignment and chromatographic alignment.
Gas chromatography–mass spectrometry (GC–MS) and liquid chromatography-quadrupole time-of-flight mass spectrometry (LC–qTOF–MS) reveal metabolic shifts in tricuspid regurgitation.