Non-invasive diagnostic method to objectively measure olfaction and diagnose smell disorders by molecularly targeted fluorescent imaging agent

  1. Dauren Adilbay
  2. Junior Gonzales
  3. Marianna Zazhytska
  4. Paula Demetrio de Souza Franca
  5. Sheryl Roberts
  6. Tara Viray
  7. Raik Artschwager
  8. Snehal Patel
  9. Albana Kodra
  10. Jonathan B. Overdevest
  11. Chun Yuen Chow
  12. Glenn F. King
  13. Sanjay K. Jain
  14. Alvaro A. Ordonez
  15. Laurence S. Carroll
  16. Thomas Reiner
  17. Nagavarakishore Pillarsetty

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Abstract

The sense of smell (olfaction) is one of the most important senses for animals including humans. Despite significant advances in the understanding mechanism of olfaction, currently, there are no objective non-invasive methods that can identify loss of smell. Covid-19-related loss of smell has highlighted the need to develop methods that can identify loss of olfaction. Voltage-gated sodium channel 1.7 (Na V 1.7) plays a critical role in olfaction by aiding the signal propagation to the olfactory bulb. We have identified several conditions such as chronic inflammation and viral infections such as Covid-19 that lead to loss of smell correlate with downregulation of Na V 1.7 expression at transcript and protein levels in the olfactory epithelium. Leveraging this knowledge, we have developed a novel fluorescent probe Tsp1a-IR800 that targets Na V 1.7. Using fluorescence imaging we can objectively measure the loss of sense of smell in live animals non-invasively. We also demonstrate that our non-invasive method is semiquantitative because the loss of fluorescence intensity correlates with the level of smell loss. Our results indicate, that our probe Tsp1a-IR800, can objectively diagnose anosmia in animal and human subjects using infrared fluorescence. We believe this method to non-invasively diagnose loss of smell objectively is a significant advancement in relation to current methods that rely on highly subjective behavioral studies and can aid in studying olfaction loss and the development of therapeutic interventions.

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  1. ScreenIT

    SciScore for 10.1101/2021.10.07.463532: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIACUC: Animal works: All animal care and procedures were approved by the Animal Care and Use Committees (IACUC) of Memorial Sloan-Kettering Cancer Center.
    Sex as a biological variableHsd:athymic female mice Nude-Foxn1nu (6–8 weeks old) were used in the study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    We used an anti-NaV1.7 antibody [N68/6] (NeuroMab) that binds to both human and mouse NaV1.7 (0.5 μg/mL).
    anti-NaV1.7
    suggested: (UC Davis/NIH NeuroMab Facility Cat# N68/6, RRID:AB_2877500)
    Experimental Models: Organisms/Strains
    SentencesResources
    Nine athymic nude mice were divided into three groups.
    athymic nude
    suggested: RRID:RGD_5508395)
    Software and Algorithms
    SentencesResources
    The threshold for signal intensity in the DAB (brown) and H&E (blue, representing all tissue area) channels was determined via an automated script using ImageJ analysis software.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistical analysis: Statistical analysis of NaV1.7 expression was performed using R v3.6.3 (R Core Team - 2020, R Foundation for Statistical Computing, Vienna, Austria) and GraphPad Prism 9 (GraphPad Software, San Diego, CA).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.10.07.463532 on bioRxiv