Selected article for: "false positive true positive and true positive"
Author: Allgoewer, Kristina; Maity, Shuvadeep; Zhao, Alice; Lashua, Lauren; Ramgopal, Moti; Balkaran, Beni N.; Liu, Liyun; Purushwani, Savita; Arévalo, Maria T.; Ross, Ted M.; Choi, Hyungwon; Ghedin, Elodie; Vogel, Christine
Title: New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
  • Cord-id: 0y6zdfw2
  • Document date: 2021_2_12
    • ID: 0y6zdfw2
    Snippet: Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection an
    Document: Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ∼70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections.

    Search related documents:
    Co phrase search for related documents
    • absence presence and acid amplification test: 1
    • absence presence and acute illness: 1, 2, 3, 4, 5, 6
    • absence presence and acute infection: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
    • absence presence and acute phase: 1, 2, 3, 4, 5, 6, 7, 8
    • absence presence and acute phase infection: 1, 2
    • absence presence and acute symptom: 1
    • absence presence and additional factor: 1
    • absence presence and additional role: 1, 2
    • absence presence and additional testing: 1
    • absence presence and liver injury: 1, 2, 3, 4, 5, 6
    • absence presence and loading control: 1, 2, 3
    • absence presence and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63
    • absence presence and low expression: 1, 2, 3
    • absence presence and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
    • absence presence and machine learning approach: 1