Articlenpj antimicrobials and resistance2024
Assessment of tuberculosis drug efficacy using preclinical animal models and in vitro predictive techniques.
Article in npj antimicrobials and resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Evaluating novel antibodies for cytokine profiling in the guinea pig model.ImmunoHorizons · 2026Article
- Mycobacterium tuberculosis-induced PCBP1 degradation drives macrophage ferroptosis to promote infection: a lung-macrophage-targeted RNAa nanotherapy.Journal of nanobiotechnology · 2026Article
- Evaluation of clofazimine-bedaquiline combination as a candidate regimen for macrolide-resistantAntimicrobial agents and chemotherapy · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Tuberculosis (TB) killed approximately 1.3 million people in 2022 and remains a leading cause of death from the bacteria Mycobacterium tuberculosis (M.tb); this number of deaths was surpassed only by COVID-19, caused by the SARS-CoV-2 virus. The alarming emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) M.tb strains presents an urgent need for effective new treatments. Our study aimed to determine the synergistic effects of antibiotic combinations against M.tb. Using a high-throughput in vitro checkerboard assay, we evaluated the interactions of Bedaquiline (BDQ) and other antibiotics including Capreomycin (CAP), Linezolid (LIN), and Sutezolid (SUT) against M.tb H37Rv. BDQ and CAP demonstrated in vitro enhanced effect, which prompted further investigation in vivo using the murine low dose aerosol (LDA) model. After aerosol challenge with M.tb, C57BL/6 mice were treated with BDQ, CAP, or their combination, starting 28 days post-infection. The antimicrobial treatment lasted four weeks, and the bacterial burden in lung and spleen tissues was assessed at the end of treatment. At 4 weeks post-treatment, a significant reduction in bacterial load was observed within the lungs and spleens of mice given BDQ alone or given as a BDQ/CAP combination compared to the untreated group. In contrast, CAP monotherapy led to an increase in bacterial load within the lung and no significant difference in bacterial burden in the spleen in comparison to the untreated mice. These results were confirmed in the guinea pig model of TB, where both BDQ and the BDQ/CAP combination treatment led to a decrease in bacterial burden in the lung and spleen, whereas CAP had no significant effect on bacterial burden at the 4-week post treatment timepoint. We next determined whether there may be differences in vitro with the BDQ/CAP combination against M.tb lineages 1, 2 and 4. We determined that in vitro enhanced effect was not observed in some representative strains of M.tb lineage 4, indicating variability in drug effectiveness across M.tb lineages. This research underscores the complexity of TB treatment and the critical need for innovative approaches to combat this global health threat.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.