Evidence Hub

Current progress of functional nanobiosensors for potential tuberculosis diagnosis: The novel way for TB control?

Yang X, Fan S, Ma Y, Chen H, Xu JF, Pi J, Wang W, Chen G

Frontiers in bioengineering and biotechnology, 2022

9 citations

Abstract

Tuberculosis (TB), induced by the foxy Mycobacterium tuberculosis (Mtb), is still one of the top killers worldwide among infectious diseases. Although several antibiotics have been developed to significantly relieve the tuberculosis epidemics worldwide, there are still several important scientific challenges for tuberculosis. As one of the most critical issues for tuberculosis control, the accurate and timely diagnosis of tuberculosis is critical for the following therapy of tuberculosis and thus responsible for the effective control of drug-resistant tuberculosis. Current tuberculosis diagnostic methods in clinic are still facing the difficulties that they can't provide the rapid diagnostic results with high sensitivity and accuracy, which therefore requires the development of more effective novel diagnostic strategies. In recent decades, nanomaterials have been proved to show promising potentials for novel nanobiosensor construction based on their outstanding physical, chemical and biological properties. Taking these promising advantages, nanomaterial-based biosensors show the potential to allow the rapid, sensitive and accurate tuberculosis diagnosis. Here, aiming to increase the development of more effective tuberculosis diagnostic strategy, we summarized the current progress of nanobiosensors for potential tuberculosis diagnosis application. We discussed the different kind diagnostic targets for tuberculosis diagnosis based on nanobiosensors, ranging from the detection…

How strong is the evidence?

Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free