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Inorganic Complexes and Metal-Based Nanomaterials for Infectious Disease Diagnostics

[Image: see text] Infectious diseases claim millions of lives each year. Robust and accurate diagnostics are essential tools for identifying those who are at risk and in need of treatment in low-resource settings. Inorganic complexes and metal-based nanomaterials continue to drive the development of...

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Detalles Bibliográficos
Autores principales: Markwalter, Christine F., Kantor, Andrew G., Moore, Carson P., Richardson, Kelly A., Wright, David W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6348445/
https://www.ncbi.nlm.nih.gov/pubmed/30511833
http://dx.doi.org/10.1021/acs.chemrev.8b00136
Descripción
Sumario:[Image: see text] Infectious diseases claim millions of lives each year. Robust and accurate diagnostics are essential tools for identifying those who are at risk and in need of treatment in low-resource settings. Inorganic complexes and metal-based nanomaterials continue to drive the development of diagnostic platforms and strategies that enable infectious disease detection in low-resource settings. In this review, we highlight works from the past 20 years in which inorganic chemistry and nanotechnology were implemented in each of the core components that make up a diagnostic test. First, we present how inorganic biomarkers and their properties are leveraged for infectious disease detection. In the following section, we detail metal-based technologies that have been employed for sample preparation and biomarker isolation from sample matrices. We then describe how inorganic- and nanomaterial-based probes have been utilized in point-of-care diagnostics for signal generation. The following section discusses instrumentation for signal readout in resource-limited settings. Next, we highlight the detection of nucleic acids at the point of care as an emerging application of inorganic chemistry. Lastly, we consider the challenges that remain for translation of the aforementioned diagnostic platforms to low-resource settings.