Citations

Abstract Background Estimating bacterial load in clinical samples has important applications in tuberculosis (TB) management, including assessment of disease severity, treatment response, and baseline genome copies required for sequencing. However, rapid and affordable tools for quantifying Mycobacterium tuberculosis ( M. tuberculosis ) remain limited. Methods We developed a high-resolution melt (HRM) based quantitative PCR assay using molecular beacon chemistry targeting the single-copy RD9 region of M. tuberculosis . Analytical performance was assessed using 10-fold serial dilutions of H37Rv DNA. Clinical validation included DNA from 100 M. tuberculosis culture isolates and 40 sputum samples from Xpert MTB/RIF- and culture-positive pulmonary TB patients. To evaluate specificity, we tested 30 non-tuberculous mycobacterium (NTM) culture isolates from patients infected with Mycobacterium abscessus (n=25) and Mycobacterium fortuitum (n=5) and DNA from saliva samples of 10 healthy controls. Results The HRM-qPCR assay showed a linear dynamic range from 10 1 to 10 6 genome copies per reaction, with a lower limit of detection of 10 copies. Standardized melt-curve analysis yielded a single target-specific peak at 73.7±0.12°C across dilutions, confirming specific amplification. Sensitivity for M. tuberculosis detection was 100% in culture isolates and 95.0% (38/40) in sputum, with no false positives among M. tuberculosis -negative controls. Assay specificity was 100% in both culture isolates and sputum, with no additional melt peaks. We did not observe any peaks indicative of non-specific binding in NTMs. Amplification was observed in two NTM samples whose Tm matched M. tuberculosis RD9 (median M. tuberculosis copies=678.5), suggesting possible co-infection or contamination. No amplification or specific melt peaks were observed in saliva samples, indicating high probe specificity. Conclusions Molecular beacon-based HRM-qPCR assay enables rapid, highly specific quantification of M. tuberculosis genome copies in clinical samples and has potential utility for treatment monitoring, triaging specimens for sequencing, and assessing transmission risk in high-burden settings.

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm—the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.