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Description
The optimization of a blood-based assay for diagnosing tuberculosis which has been developed and validated in Dr. Hu’s lab, at Arizona State University, is important for ensuring its successful translation to a resource-limited setting of the developing world. Tuberculosis is

The optimization of a blood-based assay for diagnosing tuberculosis which has been developed and validated in Dr. Hu’s lab, at Arizona State University, is important for ensuring its successful translation to a resource-limited setting of the developing world. Tuberculosis is most prevalent in the developing world with Sub-Saharan Africa having the highest cases of HIV/TB coinfections. The implementation of a blood-based assay for diagnosing Tuberculosis in the sub-Saharan would significantly improve the diagnosis and treatment monitoring of tuberculosis thereby managing or eliminating the pandemic altogether. The World Health Organization has called for robust diagnostic technologies that would resolve the shortfalls of the current technologies which include GeneXpert, X-ray, and smear microscopy. The blood-based diagnostic methodology heavily relies on Mass-spectrometry, a technology which could be entirely novel and expensive to implement in most laboratories in the Sub-Saharan. Despite virtual challenges in implementing the technology, the assay has demonstrated high specificity and sensitivity to HIV/TB coinfected patients and children in comparison to the available TB diagnostic assays. This study endorses the Blood-based Mass Spectrometry assay as one of the promising technologies to effectively improve the diagnosis of TB. The performance of the assay on detecting TB antigens was tested using different methods and materials. In the end, the use of DBS and miniaturized mass spectrometers have been discussed as possible routes for translating the assay to the developing world
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Details

Title
  • Optimization of a Blood-Based Tuberculosis Diagnostic Assay for the Developing World-with a focus on Sub-Saharan Africa
Contributors
Date Created
2019-05
Resource Type
  • Text
  • Machine-readable links