Proceedings of the Summer Institute on Symptoms and Omics

Burr, R. L., Gu, H., Cain, K., Djukovic, D., Zhang, X., Han, C., Callan, N., Raftery, D., Heitkemper, M. (2019). Tryptophan metabolites in irritable bowel syndrome: An overnight time-course study. Journal of Neurogastroenterology and Motility, 25(4), 551–562. https://doi.org/10.5056/jnm19042.
Google Scholar | Crossref | Medline Corwin, E. J., Brewster, G., Dunbar, S. B., Wells, J., Hertzberg, V., Holstad, M., Song, M.-K., Jones, D. (2021). The metabolomic underpinnings of symptom burden in patients with multiple chronic conditions. Biological Research for Nursing, 23(2), 270–279. https://doi.org/10.1177/1099800420958196.
Google Scholar | SAGE Journals Costedio, M. M., Hyman, N., Mawe, G. M. (2007). Serotonin and its role in colonic function and in gastrointestinal disorders. Diseases of the Colon & Rectum, 50(3), 376–388. https://doi.org/10.1007/s10350-006-0763-3.
Google Scholar | Crossref | Medline Harrigan, G. G., Goodacre, R. (2003). Metabolic profiling: It's role in biomarker discovery and gene function analysis. Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4615-0333-0.
Google Scholar | Crossref Khusial, R. D., Cioffi, C. E., Caltharp, S. A., Krasinskas, A. M., Alazraki, A., Knight‐Scott, J., Cleeton, R., Castillo‐Leon, E., Jones, D. P., Pierpont, B., Caprio, S., Santoro, N., Akil, A., Vos, M. B. (2019). Development of a plasma screening panel for pediatric nonalcoholic fatty liver disease using metabolomics. Hepatology Communications, 3(1), 1311–1321. https://doi.org/10.1002/hep4.1417.
Google Scholar | Crossref | Medline Kimble, L. P., Leslie, S., Carlson, N. (2020). Metabolomics research conducted by nurse scientists: A systematic scoping review. Biological Research for Nursing, 22(4), 436–448. https://doi.org/10.1177/1099800420940041.
Google Scholar | SAGE Journals | ISI Liang, D., Ladva, C. N., Golan, R., Yu, T., Walker, D. I., Sarnat, S. E., Greenwald, R., Uppal, K., Tran, V., Jones, D. P., Russell, A. G., Sarnat, J. A. (2019). Perturbations of the arginine metabolome following exposures to traffic-related air pollution in a panel of commuters with and without asthma. Environment International, 127, 503–513. https://doi.org/10.1016/j.envint.2019.04.003.
Google Scholar | Crossref | Medline Liang, D., Moutinho, J. L., Golan, R., Yu, T., Ladva, C. N., Niedzwiecki, M., Walker, D. I., Sarnat, S. E., Chang, H. H., Greenwald, R., Jones, D. P., Russell, A. G., Sarnat, J. A. (2018). Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution. Environment International, 120, 145–154. https://doi.org/10.1016/j.envint.2018.07.044.
Google Scholar | Crossref | Medline Li, Z., Liang, D., Ye, D., Chang, H. H., Ziegler, T. R., Jones, D. P., Ebelt, S. T. (2021). Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution. Environmental Research, 193, 110506. https://doi.org/10.1016/j.envres.2020.110506.
Google Scholar | Crossref | Medline

留言 (0)

沒有登入
gif