IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0159001.html
   My bibliography  Save this article

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Author

Listed:
  • Michelle J Iandiorio
  • Jeanne M Fair
  • Stylianos Chatzipanagiotou
  • Anastasios Ioannidis
  • Eleftheria Trikka-Graphakos
  • Nikoletta Charalampaki
  • Christina Sereti
  • George P Tegos
  • Almira L Hoogesteijn
  • Ariel L Rivas

Abstract

Background: Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods: Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise-reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality-based) version. Results: In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions: Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

Suggested Citation

  • Michelle J Iandiorio & Jeanne M Fair & Stylianos Chatzipanagiotou & Anastasios Ioannidis & Eleftheria Trikka-Graphakos & Nikoletta Charalampaki & Christina Sereti & George P Tegos & Almira L Hoogestei, 2016. "Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-19, July.
    • Handle: RePEc:plo:pone00:0159001
    DOI: 10.1371/journal.pone.0159001
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0159001
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0159001&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0159001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ariel L Rivas & Mark D Jankowski & Renata Piccinini & Gabriel Leitner & Daniel Schwarz & Kevin L Anderson & Jeanne M Fair & Almira L Hoogesteijn & Wilfried Wolter & Marcelo Chaffer & Shlomo Blum & Tom, 2013. "Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-16, February.
    2. Thomas A. Wynn & Ajay Chawla & Jeffrey W. Pollard, 2013. "Macrophage biology in development, homeostasis and disease," Nature, Nature, vol. 496(7446), pages 445-455, April.
    3. Hutchinson, J Wesley & Kamakura, Wagner A & Lynch, John G, Jr, 2000. "Unobserved Heterogeneity as an Alternative Explanation for "Reversal" Effects in Behavioral Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(3), pages 324-344, December.
    4. Gabriel Leitner & Shlomo E Blum & Ariel L Rivas, 2015. "Visualizing the Indefinable: Three-Dimensional Complexity of ‘Infectious Diseases’," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-21, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Howard Kunreuther & Erwann Michel-Kerjan, 2015. "Demand for fixed-price multi-year contracts: Experimental evidence from insurance decisions," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 171-194, October.
    2. Donggen Wang & Jiukun Li & Harry Timmermans, 2004. "Measuring Bifurcation Points in Choice Behavior: Principles and Illustration," Environment and Planning A, , vol. 36(6), pages 1125-1138, June.
    3. Steven M. Shugan, 2002. "In Search of Data: An Editorial," Marketing Science, INFORMS, vol. 21(4), pages 369-377.
    4. Raphael Thomadsen & Robert P. Rooderkerk & On Amir & Neeraj Arora & Bryan Bollinger & Karsten Hansen & Leslie John & Wendy Liu & Aner Sela & Vishal Singh & K. Sudhir & Wendy Wood, 2018. "How Context Affects Choice," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 3-14, March.
    5. J. Wesley Hutchinson & Gal Zauberman & Robert Meyer, 2010. "—On the Interpretation of Temporal Inflation Parameters in Stochastic Models of Judgment and Choice," Marketing Science, INFORMS, vol. 29(1), pages 23-31, 01-02.
    6. Heewon Cho & Haw-Young Kwon & Amit Sharma & Sun Hyeok Lee & Xiao Liu & Naoki Miyamoto & Jong-Jin Kim & Sin-Hyeog Im & Nam-Young Kang & Young-Tae Chang, 2022. "Visualizing inflammation with an M1 macrophage selective probe via GLUT1 as the gating target," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    7. Evan Weingarten & Sudeep Bhatia & Barbara Mellers, 2019. "Multiple Goals as Reference Points: One Failure Makes Everything Else Feel Worse," Management Science, INFORMS, vol. 65(7), pages 3337-3352, July.
    8. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    9. Eisend, Martin, 2014. "Shelf space elasticity: A meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 168-181.
    10. Yao, Jun & Oppewal, Harmen, 2016. "Unit Pricing Increases Price Sensitivity Even When Products are of Identical Size," Journal of Retailing, Elsevier, vol. 92(1), pages 109-121.
    11. Elizabeth Wrigley-Field, 2020. "Multidimensional Mortality Selection: Why Individual Dimensions of Frailty Don’t Act Like Frailty," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 747-777, April.
    12. Jan-Michael Becker & Christian Ringle & Marko Sarstedt & Franziska Völckner, 2015. "How collinearity affects mixture regression results," Marketing Letters, Springer, vol. 26(4), pages 643-659, December.
    13. Grewal, Rajdeep & Chakravarty, Anindita & Ding, Min & Liechty, John, 2008. "Counting chickens before the eggs hatch: Associating new product development portfolios with shareholder expectations in the pharmaceutical sector," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 261-272.
    14. Xiaowei Gu & Anna Heinrich & Shu-Yun Li & Tony DeFalco, 2023. "Testicular macrophages are recruited during a narrow fetal time window and promote organ-specific developmental functions," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    15. Kai Cheng & Bo Liu & Xiao-Shuai Zhang & Ruo-Yun Zhang & Fang Zhang & Ghazal Ashraf & Guo-Qing Fan & Ming-Yu Tian & Xing Sun & Jing Yuan & Yuan-Di Zhao, 2022. "Biomimetic material degradation for synergistic enhanced therapy by regulating endogenous energy metabolism imaging under hypothermia," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    16. Ariel C. Vonk & Xiaofan Zhao & Zheyu Pan & Megan L. Hudnall & Conrad G. Oakes & Gabriela A. Lopez & Sarah C. Hasel-Kolossa & Alexander W. C. Kuncz & Sasha B. Sengelmann & Darian J. Gamble & Thomas P. , 2023. "Single-cell analysis of lizard blastema fibroblasts reveals phagocyte-dependent activation of Hedgehog-responsive chondrogenesis," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    17. Julian C. Bahr & Xiao-Yan Li & Tamar Y. Feinberg & Long Jiang & Stephen J. Weiss, 2022. "Divergent regulation of basement membrane trafficking by human macrophages and cancer cells," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    18. Fabian Gondorf & Afiat Berbudi & Benedikt C Buerfent & Jesuthas Ajendra & Dominique Bloemker & Sabine Specht & David Schmidt & Anna-Lena Neumann & Laura E Layland & Achim Hoerauf & Marc P Hübner, 2015. "Chronic Filarial Infection Provides Protection against Bacterial Sepsis by Functionally Reprogramming Macrophages," PLOS Pathogens, Public Library of Science, vol. 11(1), pages 1-27, January.
    19. Lin, Ying-Ching & Fang, Shiuan-Huei, 2013. "The face value of foreign currency on consumer price perception—The moderating effect of product substitution," Journal of Business Research, Elsevier, vol. 66(6), pages 745-751.
    20. Pravin Kesarwani & Shiva Kant & Yi Zhao & Antony Prabhu & Katie L. Buelow & C. Ryan Miller & Prakash Chinnaiyan, 2023. "Quinolinate promotes macrophage-induced immune tolerance in glioblastoma through the NMDAR/PPARγ signaling axis," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0159001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.