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Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis
Tuberculosis produces two clinical manifestations: active and latent (non-apparent) disease. The latter is estimated to affect one-third of the world population and constitutes a source of continued transmission should the disease emerge from its hidden state (reactivation). Methods to diagnose late...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Shared Science Publishers OG
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695853/ https://www.ncbi.nlm.nih.gov/pubmed/29167798 http://dx.doi.org/10.15698/mic2017.11.596 |
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author | Flores-Valdez, Mario Alberto |
author_facet | Flores-Valdez, Mario Alberto |
author_sort | Flores-Valdez, Mario Alberto |
collection | PubMed |
description | Tuberculosis produces two clinical manifestations: active and latent (non-apparent) disease. The latter is estimated to affect one-third of the world population and constitutes a source of continued transmission should the disease emerge from its hidden state (reactivation). Methods to diagnose latent TB have been evolving and aim to detect the disease in people who are truly infected with M. tuberculosis, versus those where other mycobacteria, or even other pathologies not related to TB, are present. The current use of proteomic and transcriptomic approaches may lead to improved detection methods in the coming years. |
format | Online Article Text |
id | pubmed-5695853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Shared Science Publishers OG |
record_format | MEDLINE/PubMed |
spelling | pubmed-56958532017-11-22 Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis Flores-Valdez, Mario Alberto Microb Cell Microbiology Tuberculosis produces two clinical manifestations: active and latent (non-apparent) disease. The latter is estimated to affect one-third of the world population and constitutes a source of continued transmission should the disease emerge from its hidden state (reactivation). Methods to diagnose latent TB have been evolving and aim to detect the disease in people who are truly infected with M. tuberculosis, versus those where other mycobacteria, or even other pathologies not related to TB, are present. The current use of proteomic and transcriptomic approaches may lead to improved detection methods in the coming years. Shared Science Publishers OG 2017-10-24 /pmc/articles/PMC5695853/ /pubmed/29167798 http://dx.doi.org/10.15698/mic2017.11.596 Text en https://creativecommons.org/licenses/by/4.0/ This is an open-access article released under the terms of the Creative Commons Attribution (CC BY) license, which allows the unrestricted use, distribution, and reproduction in any medium, provided the original author and source are acknowledged. |
spellingShingle | Microbiology Flores-Valdez, Mario Alberto Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title | Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title_full | Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title_fullStr | Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title_full_unstemmed | Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title_short | Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
title_sort | uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695853/ https://www.ncbi.nlm.nih.gov/pubmed/29167798 http://dx.doi.org/10.15698/mic2017.11.596 |
work_keys_str_mv | AT floresvaldezmarioalberto uncoveringthehiddencomplexityandstrategiesfordiagnosinglatenttuberculosis |