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Search results (157)

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Future-proofing tuberculosis therapy: framework for concurrent drug and resistance testing development

Saluzzo F. et al, (2026), The Lancet Infectious Diseases, 26, e248 - e256

Transmission of rifampicin-resistant tuberculosis in Ho Chi Minh City, Viet Nam: a prospective genomic epidemiology study

Spies R. et al, (2026), The Lancet Regional Health - Western Pacific, 71, 101906 - 101906

Undetected isoniazid resistance leads to rifampicin-resistant tuberculosis: a prospective observational study and transmission modelling analysis

Spies R. et al, (2026)

Long-read sequencing of Mycobacterial tuberculosis is comparable to short-read sequencing for antimicrobial resistance prediction and epidemiological studies

Colpus M. et al, (2026)

Interferon-gamma release assay positivity in populations at high risk of TB infection

Dagnew AF. et al, (2026), IJTLD Open, 3, 232 - 240

Transmission of rifampicin-resistant tuberculosis in Ho Chi Minh City, Viet Nam: a prospective genomic epidemiology study

Spies R. et al, (2026)

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study

Spies R. et al, (2025), The Lancet Microbe, 6, 101210 - 101210

Rapidly and reproducibly building a comprehensive catalogue of resistance-associated variants for M. tuberculosis

Adlard D. et al, (2025)

Tuberculosis preventive therapy: scientific and ethical considerations for trials of ultra-short regimens

Walker TM. et al, (2025), The Lancet Infectious Diseases, 25, e432 - e438

All parts of the WHO Mycobacterium tuberculosis mutation catalog need to be applied when evaluating its performance

Laurent S. et al, (2025), Microbiology Spectrum, 13

Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis

Kulkarni SG. et al, (2025), Nature Communications, 16

A modified decontamination and storage method for sputum from patients with tuberculosis

Le Quang N. et al, (2025), Wellcome Open Research, 8, 166 - 166

Deep Learning-based Framework for Mycobacterium Tuberculosis Bacterial Growth Detection for Antimicrobial Susceptibility Testing

Vo H-AT. et al, (2025)

Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing

Vo H-AT. et al, (2025), Computational and Structural Biotechnology Journal, 27, 2208 - 2218

The catalogue of Mycobacterium tuberculosis mutations associated with drug resistance to 12 drugs in China from a nationwide survey: a genomic analysis

Pei S. et al, (2024), The Lancet Microbe, 5, 100899 - 100899

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