PodcastSepsis

Science Translational Medicine Podcast: 24 July 2013

See allHide authors and affiliations

Science Translational Medicine  24 Jul 2013:
Vol. 5, Issue 195, pp. 195pc4
DOI: 10.1126/scitranslmed.3007122

Additional Files

  • Science Translational Medicine Podcast: 24 July 2013

    Participants: Raymond J. Langley and Orla Smith

    In this podcast, Raymond J. Langley explains how a new molecular signature can help to identify patients with sepsis who are at greatest risk of dying.

    Highlighted article:

    R. J. Langley, E. L. Tsalik, J. C. v. Velkinburgh, S. W. Glickman, B. J. Rice, C. Wang, B. Chen, L. Carin, A. Suarez, R. P. Mohney, D. H. Freeman, M. Wang, J. You, J. Wulff, J. W. Thompson, M. A. Moseley, S. Reisinger, B. T. Edmonds, B. Grinnell, D. R. Nelson, D. L. Dinwiddie, N. A. Miller, C. J. Saunders, S. S. Soden, A. J. Rogers, L. Gazourian, L. E. Fredenburgh, A. F. Massaro, R. M. Baron, A. M. K. Choi, G. R. Corey, G. S. Ginsburg, C. B. Cairns, R. M. Otero, V. G. Fowler, E. P. Rivers, C. W. Woods, S. F. Kingsmore, An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis. Sci. Transl. Med. 5, 195ra95 (2013).

    Length: 8.52 min

    File size: 5.2 MB

    Listen to Podcast | Download the Transcript | Featured Research Article

Stay Connected to Science Translational Medicine