Improving acid-fast fluorescent staining for the detection of mycobacteria using a new nucleic acid staining approach

Ryan, Gavin J.; Shapiro, Howard M.; Lenaerts, Anne J.

doi:10.1016/j.tube.2014.07.004

Cited by 41 publications

(33 citation statements)

References 43 publications

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“…Thus, the combination of a histologic diagnosis, acid-fast staining, and the detection of M. tuberculosis DNA would ensure an accurate diagnosis. [32][33][34] When patients are diagnosed with TB in the oral cavity, personalized treatments should be planned on the basis of clinical examination results. The most popular anti-TB drugs include isoniazid, rifampicin, pyrazinamide, ethambutol, and streptomycin.…”

Section: Discussionmentioning

confidence: 99%

Clinical and pathologic analyses of tuberculosis in the oral cavity: report of 11 cases

Yong

Liu

et al. 2018

Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology

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Section: Discussionmentioning

confidence: 99%

Clinical and pathologic analyses of tuberculosis in the oral cavity: report of 11 cases

Yong

Liu

et al. 2018

Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology

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“…Of particular interest in TB drug and vaccine development is to include the mycobacterial quantification metrics of each individual lesion. The goal would be to integrate precise measurements on bacterial numbers after fluorescent staining 21,66 , as well as bacterial aggregation sizes, level of fluorescence, and the average number of bacteria as a metric of area. With the availability of matrix assisted laser desorption ionization (MALDI) imaging to assess drug levels across pulmonary lesions 67,68 , one can envision the development of a model that would integrate data sets from digital lesion pathology with bacterial metrics as well as drug exposure.…”

Section: Discussionmentioning

confidence: 99%

Digital Image Analysis of Heterogeneous Tuberculosis Pulmonary Pathology in Non-Clinical Animal Models using Deep Convolutional Neural Networks

Asay

Edwards

Andrews

et al. 2020

Sci Rep

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Efforts to develop effective and safe drugs for treatment of tuberculosis require preclinical evaluation in animal models. Alongside efficacy testing of novel therapies, effects on pulmonary pathology and disease progression are monitored by using histopathology images from these infected animals. to compare the severity of disease across treatment cohorts, pathologists have historically assigned a semi-quantitative histopathology score that may be subjective in terms of their training, experience, and personal bias. Manual histopathology therefore has limitations regarding reproducibility between studies and pathologists, potentially masking successful treatments. This report describes a pathologist-assistive software tool that reduces these user limitations, while providing a rapid, quantitative scoring system for digital histopathology image analysis. The software, called 'Lesion Image Recognition and Analysis' (LIRA), employs convolutional neural networks to classify seven different pathology features, including three different lesion types from pulmonary tissues of the C3HeB/FeJ tuberculosis mouse model. LIRA was developed to improve the efficiency of histopathology analysis for mouse tuberculosis infection models, this approach has also broader applications to other disease models and tissues. the full source code and documentation is available from https://Github. com/TB-imaging/LIRA.

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“…; Ryan et al . ). This method is especially justified in high‐demand laboratories (Slim‐Saidi et al .…”

Section: Current Pulmonary Tuberculosis Diagnostic Testsmentioning

confidence: 97%

Mass spectrometry applied to the identification ofMycobacterium tuberculosisand biomarker discovery

et al. 2016

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Summary An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species.

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Improving acid-fast fluorescent staining for the detection of mycobacteria using a new nucleic acid staining approach

Cited by 41 publications

References 43 publications

Clinical and pathologic analyses of tuberculosis in the oral cavity: report of 11 cases

Clinical and pathologic analyses of tuberculosis in the oral cavity: report of 11 cases

Digital Image Analysis of Heterogeneous Tuberculosis Pulmonary Pathology in Non-Clinical Animal Models using Deep Convolutional Neural Networks

Mass spectrometry applied to the identification ofMycobacterium tuberculosisand biomarker discovery

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