Waters Honors University of Minnesota's Joseph Dalluge and Department of Chemistry Mass Spectrometry Laboratory with Center of Innovation Recognition
Waters Corporation (Milford, Massachusetts) recently welcomed the University of Minnesota?s (Minneapolis, Minnesota) Mass Spectrometry Laboratory into its Centers of Innovation Program. Waters honored the Mass Spectrometry Laboratory under the direction of Joseph Dalluge for his research in diagnostic marker assay development relevant to cystic fibrosis and other diseases.
Waters Corporation (Milford, Massachusetts) recently welcomed the University of Minnesota’s (Minneapolis, Minnesota) Mass Spectrometry Laboratory into its Centers of Innovation Program. Waters honored the Mass Spectrometry Laboratory under the direction of Joseph Dalluge for his research in diagnostic marker assay development relevant to cystic fibrosis and other diseases. Dalluge also was honored for his research as a collaborating member of the university’s newly created Center for Bioanalysis of Molecular Signaling. The Dalluge mass spectrometry laboratory is part of the Department of Chemistry within the University’s College of Science and Engineering.
Dalluge’s research is focused on the use of leading edge liquid chromatograpy–mass spectrometry (LC–MS) instrumentation for metabolite profiling, biomarker discovery, and advanced assay development, as well as the detailed chemical characterization of biological systems as it relates to function.
Waters Centers of Innovation Program recognizes and supports the efforts of scientists facilitating breakthroughs in health and life science research, food safety, environmental protection, sports medicine, and other areas.
“I am honored to be a part of the Centers of Innovation Program and for what it means to us as we conduct leading-edge research. I regard Waters as more than just an instrument vendor of choice. They are a research partner,” said Dalluge.
Dalluge is one of 13 researchers recognized by Waters Centers of Innovation Program. Others include Jeremy Nicholson, Imperial College (London, England); John Engen, Northeastern University, (Boston, Massachusetts); James Scrivens, University of Warwick (Coventry, UK); David Cowan, Kings College (London, England); Arthur Moseley, Duke University (Durham, North Carolina); Julie Leary, University of California (Davis, California); Albert J. Fornace, Jr., Georgetown Lombardi Comprehensive Cancer Center (Washington, D.C.); Marcos Eberlin, University of Campinas (São Paulo, Brazil); Chang Hsu, Future Fuels Institute (Tallahassee, Florida); Ganesh Anund, National University of Singapore; Konstantinos Petritis, Translational Genomics Research Institute (Phoenix, Arizona); and Vladimir Shulaev, University of North Texas Department of Biological Sciences (Denton, Texas).
AI and Dual-Sensor Spectroscopy Supercharge Antibiotic Fermentation
June 30th 2025Researchers from Chinese universities have developed an AI-powered platform that combines near-infrared (NIR) and Raman spectroscopy for real-time monitoring and control of antibiotic production, boosting efficiency by over 30%.
Toward a Generalizable Model of Diffuse Reflectance in Particulate Systems
June 30th 2025This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.
