Topic Editors
Discriminating Tuberculosis Infection States: Immunological Signatures and Emerging Diagnostics
Topic Information
Dear Colleagues,
Tuberculosis (TB) manifests across a spectrum, from asymptomatic infection to progressive disease. Precise discrimination between these infection states is essential for targeted therapy, transmission control, and effective public health interventions. This Topic examines the immunological signatures that distinguish TB states, including immune cell dynamics and multiplexed molecular profiles. It highlights novel biomarkers and emerging diagnostic technologies—such as single-cell sequencing, high-dimensional immunological assays, and machine learning approaches—designed to enhance the accuracy and efficiency of TB diagnosis. Advances in these areas promise to enable timely, personalized interventions and bolster global efforts to control and eliminate TB.
Dr. Ying Luo
Dr. Ying Xue
Topic Editors
Keywords
- tuberculosis
- infection states
- immunological signatures
- biomarkers
- single-cell sequencing
- immune profiling
- machine learning
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
|---|---|---|---|---|---|---|
Biomedicines
|
4.5 | 7.8 | 2013 | 18.2 Days | CHF 2600 | Submit |
Diagnostics
|
3.8 | 6.9 | 2011 | 20.4 Days | CHF 2600 | Submit |
International Journal of Molecular Sciences
|
5.6 | 10.0 | 2000 | 17.5 Days | CHF 2900 | Submit |
Journal of Respiration
|
- | - | 2021 | 44.4 Days | CHF 1000 | Submit |
Pathogens
|
3.8 | 6.7 | 2012 | 12.5 Days | CHF 2400 | Submit |
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