In a new study, scientists at the University of Warwick (Coventry, UK) present the results of the analysis of petroleum and protein samples to demonstrate the applicability of the absorption-mode in Fourier Transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to routine experiments.
In a new study, scientists at the University of Warwick (Coventry, UK) present the results of the analysis of petroleum and protein samples to demonstrate the applicability of the absorption-mode in Fourier Transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to routine experiments.
The new study follows two papers published last year by the same team, led by Professor Peter B. O’Conner. Those papers explained that the resolving power of FT-ICR-MS could be enhanced up to a factor of two by phasing the raw data accurately and plotting them in the pure absorption mode, which had been a long-standing problem for almost 40 years.
Through the analysis of crude oil and top-down protein spectra, the new study provides empirical evidence confirming that the absorption mode, in addition to improving the resolving power compared to the conventional magnitude mode, improves the signal-to-noise ratio of a spectrum by 1.4-fold and can improve the mass accuracy up to 2-fold, throughout the entire m/z range, without any additional cost in instrumentation.
The paper, “Absorption-Mode: The Next Generation of Fourier-Transform Mass Spectra,” was published on February 17 in the journal Analytical Chemistry.
An Interview with AES Mid-Career Award Recipient Jason Dwyer
July 25th 2024Jason Dwyer of the University of Rhode Island has been named the recipient of the American Electrophoresis Society’s Mid-Career Award, which honors exceptional contributions to the field of electrophoresis, microfluidics, and related areas by an individual who is currently in the middle of their career.
Glucose's Impact on Brain Cancer Cells Unveiled Through Raman Imaging
July 25th 2024Researchers have used Raman spectroscopy and chemometric methods to reveal how glucose affects normal and cancerous brain cell metabolism. Their findings highlight specific biomarkers that can distinguish metabolic changes, potentially aiding in cancer research and treatment.