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Bruker Contributes to Major Breakthrough in Understanding and Predicting Long COVID - In a major breakthrough in Long COVID research the University of Cambridge (UK) and the Australian National Phenome Center (ANPC) have been using Bruker’s 600 MHz Avance III HD NMR spectrometer (IVDr) to gain new insights into the risk and progression
Bruker Contributes to Major Breakthrough in Understanding and Predicting Long COVID

 

NewswireTODAY - /newswire/ - Billerica, CA, United States, 2023/02/02 - In a major breakthrough in Long COVID research the University of Cambridge (UK) and the Australian National Phenome Center (ANPC) have been using Bruker’s 600 MHz Avance III HD NMR spectrometer (IVDr) to gain new insights into the risk and progression. NASDAQ: BRKR

   
 
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In a major breakthrough in Long COVID research the University of Cambridge (UK) and the Australian National Phenome Center (ANPC) have been using Bruker’s 600 MHz Avance III HD NMR spectrometer (IVDr) to gain new insights into the risk and progression of Long COVID. Recently published research1 in Nature Immunology reveals distinct systemic recovery profiles over several months after infection with SARS-CoV-2. The paper also presents a new online predictive model that can determine the likelihood of individual patient disease courses and recovery.

Prof. Jeremy Nicholson, Pro-Vice Chancellor for Health Services at Murdoch University, Perth, Australia, and Fellow of the UK Academy of Medical Science

Since the outset of the pandemic, we have conducted research into the effects of the virus to understand its impact. Working with our strategic partner, Bruker, we have previously investigated metabolic and lipidomic markers to predict phenotypic recovery, developing modeling tools to eludicate the molecular pathways associated with metabolic abnormalities.2 In this next stage of our research, we have built upon this bank of knowledge to initiate the development a predictive model based on cellular and molecular parameters that can rapidly provide a composite signature predictive of systemic recovery, measured soon after disease onset.

References

Helene Ruffieux, Aimee L. Hanson, Samantha Lodge, Nathan G. Lawler, Luke Whiley, Nicola Gray, Tui Nolan1, Laura Bergamaschi, Federica Mescia, Lorinda Turner, Aloka De Sa, Prasanti Kotagiri, Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID BioResource Collaboration, Nathalie Kingston, John R. Bradley, Elaine Holmes, Julien Wist, Jeremy K. Nicholson, Paul A. Lyons, Kenneth G.C. Smith, Sylvia Richardson, Glenn Bantug, Christoph Hess: A patient-centric modelling framework captures recovery from SARS-CoV-2 infection, Nature Immunology 2023. doi.org/10.1038/s41590-022-01380-2
Holmes, E., Wist, J., Masuda, R., et al. “Incomplete Systemic Recovery and Metabolic Phenoreversion in Post-Acute-Phase Nonhospitalized COVID-19 Patients: Implications for Assessment of Post-Acute COVID-19 Syndrome,” J Proteome Res, 2021; 20: 3315-3329.

About Bruker Corporation

Bruker (bruker.com) is enabling scientists to make breakthrough discoveries and develop new applications that improve the quality of human life. Bruker’s high performance scientific instruments and high value analytical and diagnostic solutions enable scientists to explore life and materials at molecular, cellular and microscopic levels. In close cooperation with our customers, Bruker is enabling innovation, improved productivity and customer success in life science molecular and cell biology research, in applied and pharma applications, in microscopy and nanoanalysis, as well as in industrial applications. Bruker offers differentiated, high-value life science and diagnostics systems and solutions in preclinical imaging, clinical phenomics research, proteomics and multiomics, spatial and single-cell biology, functional structural and condensate biology, as well as in clinical microbiology and molecular diagnostics. For more information, please visit: bruker.com.

 
 
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Bruker Contributes to Major Breakthrough in Understanding and Predicting Long COVID

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