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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

  • Rotem Vishinkin
  • , Rami Busool
  • , Elias Mansour
  • , Falk Fish
  • , Ali Esmail
  • , Parveen Kumar
  • , Alaa Gharaa
  • , John C. Cancilla
  • , Jose S. Torrecilla
  • , Ģirts Šķenders
  • , Mārcis Leja
  • , Keertan Dheda
  • , Sarman Singh
  • , Hossam Haick
  • Institute of Clinical and Preventive Medicine
  • Technion-Israel Institute of Technology
  • Complutense University
  • Riga East University Hospital
  • London School of Hygiene and Tropical Medicine

Research output: Contribution to journal › Article › peer-review

61 Citations (Scopus)

Abstract

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test.

Original languageEnglish
Article number2100235
JournalAdvanced Science
Volume8
Issue number15
DOIs
Publication statusPublished - 4 Aug 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

OECD Field of Science

  • 3. Medical and Health Sciences

Keywords

  • diagnosis
  • noninvasive approach
  • point-of-care test
  • sensor
  • skin
  • tuberculosis
  • wearable device

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