Single-cell RNA sequencing in tuberculosis: Application and future perspectives.

ABSTRACT: Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.

Relationship between blood cadmium and abdominal aortic calcification: NHANES 2013-2014.

BACKGROUND: Cadmium is a common toxic heavy metal in the environment and can cause irreversible damage to the human body. It is well established that cadmium has direct cardiovascular toxicity, but the relationship between cadmium exposure and abdominal aortic calcification (AAC) is not clear. METHODS: This was a cross-sectional study that aimed to assess the relationship between blood cadmium (B-Cd) and AAC in U.S. adults ≥ 40 years old. We obtained data from the 2013-2014 National Health and Nutrition Examination Survey. The AAC score was quantified by the Kauppila score system, whereas severe AAC was defined as an AAC score ≥ 6. We performed multivariate regressions, correlated subgroup analyses, and interaction terms to evaluate the relationship between B-Cd and AAC score and severe AAC. RESULTS: For 1530 enrolled participants, the mean AAC score was 1.52 ± 3.32, and the prevalence of severe AAC was 8.95%. Participants with higher B-Cd levels showed higher AAC scores (ß = 0.36, 95% CI: 0.03, 0.70, P = 0.0323) and an increased risk of severe AAC (OR=1.61, 95% CI: 1.01, 2.56, P = 0.0432). However, these associations were weakened after adjusting for serum cotinine to define smoking exposure. Subgroup analyses and correlated interaction terms indicated that the relationship between B-Cd and AAC was generally similar in different population settings, except for males, nonsmokers, and participants with a normal body mass index (BMI). The interaction terms indicated that smoking exposure status defined by serum cotinine interacted with the relationship between B-Cd and AAC condition (P for interaction=0.0413). CONCLUSIONS: There might be positive associations between B-Cd levels and AAC scores and the risk of severe AAC, while these associations were partially explained by smoking exposure. However, more well-designed studies are still needed to validate this relationship.

Diagnostic Accuracy of the Artificial Intelligence Methods in Medical Imaging for Pulmonary Tuberculosis: A Systematic Review and Meta-Analysis.

Tuberculosis (TB) remains one of the leading causes of death among infectious diseases worldwide. Early screening and diagnosis of pulmonary tuberculosis (PTB) is crucial in TB control, and tend to benefit from artificial intelligence. Here, we aimed to evaluate the diagnostic efficacy of a variety of artificial intelligence methods in medical imaging for PTB. We searched MEDLINE and Embase with the OVID platform to identify trials published update to November 2022 that evaluated the effectiveness of artificial-intelligence-based software in medical imaging of patients with PTB. After data extraction, the quality of studies was assessed using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). Pooled sensitivity and specificity were estimated using a bivariate random-effects model. In total, 3987 references were initially identified and 61 studies were finally included, covering a wide range of 124,959 individuals. The pooled sensitivity and the specificity were 91% (95% confidence interval (CI), 89-93%) and 65% (54-75%), respectively, in clinical trials, and 94% (89-96%) and 95% (91-97%), respectively, in model-development studies. These findings have demonstrated that artificial-intelligence-based software could serve as an accurate tool to diagnose PTB in medical imaging. However, standardized reporting guidance regarding AI-specific trials and multicenter clinical trials is urgently needed to truly transform this cutting-edge technology into clinical practice.

Immune regulation and emerging roles of noncoding RNAs in Mycobacterium tuberculosis infection.

Tuberculosis, caused by Mycobacterium tuberculosis, engenders an onerous burden on public hygiene. Congenital and adaptive immunity in the human body act as robust defenses against the pathogens. However, in coevolution with humans, this microbe has gained multiple lines of mechanisms to circumvent the immune response to sustain its intracellular persistence and long-term survival inside a host. Moreover, emerging evidence has revealed that this stealthy bacterium can alter the expression of demic noncoding RNAs (ncRNAs), leading to dysregulated biological processes subsequently, which may be the rationale behind the pathogenesis of tuberculosis. Meanwhile, the differential accumulation in clinical samples endows them with the capacity to be indicators in the time of tuberculosis suffering. In this article, we reviewed the nearest insights into the impact of ncRNAs during Mycobacterium tuberculosis infection as realized via immune response modulation and their potential as biomarkers for the diagnosis, drug resistance identification, treatment evaluation, and adverse drug reaction prediction of tuberculosis, aiming to inspire novel and precise therapy development to combat this pathogen in the future.