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Mary Cloud B. Ammons, PhD

MaryCloud.AmmonsAnderson@va.gov

Faculty Positions

  • Associate Research Scientist
  • Idaho Veterans Research & Education Foundation
  • Boise VA Medical Center
  • Idaho State University Department of Biomedical and Pharmaceutical Sciences – Affiliate Faculty
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Education

  • B.A. Biology – University of Colorado Boulder
  • Ph.D. Molecular Biology – Montana State University Bozeman

Bibliography

A list of peer-reviewed publications can be found at:

https://www.ncbi.nlm.nih.gov

Research

Research in the Ammons Lab is focused on understanding the mechanisms and clinical outcomes of how metabolism drives macrophage functional plasticity in non-healing wounds. Utilizing a complex systems biology approach, the Ammons Lab investigates genomic, transcriptomic, proteomic, and metabolomic biomarkers to characterize cellular mechanisms of metabolic immunomodulation and facilitate discovery of novel diagnostic and therapeutic targets for non-healing wounds.

In addition, the Ammons Lab has expanded into SARS-CoV-2 research, including genetic epidemiology of viral emergence, social and geographical determinants of variant emergence, host immunity of COVID-19, and characterization of Long/Post-COVID Syndrome. The Ammons Lab runs the VA Sequencing Consortium United for Research and Epidemiology (VA SeqCURE) and VA Science and Health Initiative to combat Infectious Diseases and other Emerging Life-threatening Diseases (VA SHIELD), the national VA initiatives for infectious disease research and biorepository. Through these initiatives the Boise VA has access to a national biospecimen and data repository for emerging infectious disease research.

Current Projects

  • Ex vivo macrophage functional phenotyping and metabotype characterization.
  • Impact of diabetes on macrophage polarization.
  • Host-pathogen interaction between macrophage functional phenotypes and pathogenic bacterial biofilms.
  • In situ characterization of microbiome, metabolic landscape, and innate immune cell profiles in non-healing wounds.
  • Applying machine learning and predictive modeling approaches to discover novel diagnostic and therapeutic biomarkers of correlated with clinical care.
  • Co-morbidities and clinical biomarkers predictive of Long-COVID endotypes.
  • Genetic epidemiology of SARS-CoV-2 emergence and spread in Idaho.
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