Interleukin 32 as a Potential Marker for Diagnosis of Tuberculous Pleural Effusion

Enhanced differential evolution algorithm for feature selection in tuberculous pleural effusion clinical characteristics analysis

Tuberculous pleural effusion poses a significant threat to human health due to its potential for severe disease and mortality. Without timely treatment, it may lead to fatal consequences. Therefore, early identification and prompt treatment are crucial for preventing problems such as chronic lung disease, respiratory failure, and death. This study proposes an enhanced differential evolution algorithm based on colony predation and dispersed foraging strategies. A series of experiments conducted on the IEEE CEC 2017 competition dataset validated the global optimization capability of the method. Additionally, a binary version of the algorithm is introduced to assess the algorithm's ability to address feature selection problems. Comprehensive comparisons of the effectiveness of the proposed algorithm with 8 similar algorithms were conducted using public datasets with feature sizes ranging from 10 to 10,000. Experimental results demonstrate that the proposed method is an effective feature selection approach. Furthermore, a predictive model for tuberculous pleural effusion is established by integrating the proposed algorithm with support vector machines. The performance of the proposed model is validated using clinical records collected from 140 tuberculous pleural effusion patients, totaling 10,780 instances. Experimental results indicate that the proposed model can identify key correlated indicators such as pleural effusion adenosine deaminase, temperature, white blood cell count, and pleural effusion color, aiding in the clinical feature analysis of tuberculous pleural effusion and providing early warning for its treatment and prediction.

The regulation and potential role of interleukin-32 in tuberculous pleural effusion

The possible protective effect of interleukin-32 (IL-32) in Mycobacterium tuberculosis (Mtb) infection has been indicated. However, few studies have been focused on IL-32 in tuberculosis patients. Additionally, the regulation of IL-32 production has rarely been reported. In the present study, the production, regulation, and role of IL-32 in tuberculous pleurisy (TBP) were investigated. We found that the content of IL-32 in tuberculous pleural effusion (TPE) was higher than the level in the malignant pleural effusion and transudative pleural effusion. The level of IL-32 mRNA in pleural fluid mononuclear cells (PFMCs) was higher than that in peripheral blood mononuclear cells (PBMCs) of patients with TBP, and this difference was mainly reflected in the splice variants of IL-32α, IL-32β, and IL-32γ. Compared with the PBMCs, PFMCs featured higher IL-32β/IL-32γ and IL-32α/IL-32γ ratios. In addition, lipopolysaccharide (LPS), Bacillus Calmette-Guérin (BCG), and H37Ra stimulation could induce IL-32 production in the PFMCs. IL-32 production was positively correlated with the TNF-α, IFN-γ, and IL-1Ra levels in TPE, whereas IFN-γ, but not TNF-α or IL-1Ra, could induce the production of IL-32 in PFMCs. Furthermore, IL-32γ could induce the TNF-α production in PFMCs. Monocytes and macrophages were the main sources of IL-32 in PFMCs. Nevertheless, direct cell-cell contact between lymphocytes and monocytes/macrophages plays an important role in enhancing IL-32 production by monocyte/macrophage cells. Finally, compared with the non-tuberculous pleural effusion, the purified CD4+ and CD8+ T cells in TPE expressed higher levels of intracellular IL-32. Our results suggested that, as a potential biomarker, IL-32 may play an essential role in the protection against Mtb infection in patients with TBP. However, further studies need to be carried out to clarify the functions and mechanisms of the IFN-γ/IL-32/TNF-α axis in patients with TBP.

Interleukin-6 and -27 as potential novel biomarkers for human pleural tuberculosis regardless of the immunological status

Tuberculosis (TB) is the leading cause of pleural exudative effusions. Inflammatory markers, such as IFNγ and ADA, have been used as proxies for its diagnosis. We evaluated ex vivo levels of several cytokines in 83 pleural effusion specimens from patients with TB (including 10 with HIV co-infection) and 26 patients with other pleuritis using multiplex and ELISA assays. IL-6 and IL-27 levels were higher (p ≤ 0.04) in TB patients, regardless of the HIV status and the approach. IL-2, IL-4, IL-8, IFNγ, TNF and G-CSF showed variable results depending on the assay. This warranty these markers to be further validated.

Research progress of single-cell sequencing in tuberculosis

Tuberculosis is a major infectious disease caused by Mycobacterium tuberculosis infection. The pathogenesis and immune mechanism of tuberculosis are not clear, and it is urgent to find new drugs, diagnosis, and treatment targets. A useful tool in the quest to reveal the enigmas related to Mycobacterium tuberculosis infection and disease is the single-cell sequencing technique. By clarifying cell heterogeneity, identifying pathogenic cell groups, and finding key gene targets, the map at the single cell level enables people to better understand the cell diversity of complex organisms and the immune state of hosts during infection. Here, we briefly reviewed the development of single-cell sequencing, and emphasized the different applications and limitations of various technologies. Single-cell sequencing has been widely used in the study of the pathogenesis and immune response of tuberculosis. We review these works summarizing the most influential findings. Combined with the multi-molecular level and multi-dimensional analysis, we aim to deeply understand the blank and potential future development of the research on Mycobacterium tuberculosis infection using single-cell sequencing technology.

Hepatocyte growth factor combined with adenosine deaminase as biomarker for diagnosis of tuberculous pleural effusion

Background

The simple, rapid, and accurate diagnosis of tuberculous pleural effusion (TPE) remains difficult. This study aimed to determine the accuracy of hepatocyte growth factor (HGF) in the diagnosis of TPE.

Methods

We quantified the expression of HGF, adenosine deaminase (ADA), and interferon gamma (IFN-γ) in pleural effusion (PE) in 97 TPE subjects and 116 non-TPE subjects using an enzyme-linked immunosorbent assay (ELISA) or a fully automatic biochemical analyzer. The diagnostic performance of these three biomarkers was evaluated using a receiver operating characteristic (ROC) curve of subjects by age and gender.

Results

We discovered that the TPE group had much higher levels of HGF than the non-TPE group, regardless of age or gender, and that there was no statistically significant difference between the two groups' levels of HGF expression in peripheral plasma. In female TPE patients aged ≤65 years, the AUCs of TPE and non-TPE diagnosed by HGF, ADA or IFN-γ were 0.988, 0.964, and 0.827, respectively. HGF plus ADA had the highest diagnostic efficacy in female TPE patients aged ≤65 years. With HGF plus ADA having a cut-off value of 0.219 for distinguishing TPE from non-TPE, the area under the curve (AUC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), and negative predictive value (NPV) were, respectively, 0.998 (95% confidence interval [CI], 0.993-1.000), 100 (95% CI, 89.997-100.000), 96.667 (95% CI, 82.783-99.916), 97.222 (95% CI, 83.594-99.586), and 100.

Conclusion

This study confirmed that HGF plus ADA has high diagnostic efficacy in younger female TPE patients and has the potential to be an excellent biomarker.

Pleural fluid biochemical analysis: the past, present and future

Identifying the cause of pleural effusion is challenging for pulmonologists. Imaging, biopsy, microbiology and biochemical analyses are routinely used for diagnosing pleural effusion. Among these diagnostic tools, biochemical analyses are promising because they have the advantages of low cost, minimal invasiveness, observer independence and short turn-around time. Here, we reviewed the past, present and future of pleural fluid biochemical analysis. We reviewed the history of Light’s criteria and its modifications and the current status of biomarkers for heart failure, malignant pleural effusion, tuberculosis pleural effusion and parapneumonic pleural effusion. In addition, we anticipate the future of pleural fluid biochemical analysis, including the utility of machine learning, molecular diagnosis and high-throughput technologies. Clinical Chemistry and Laboratory Medicine (CCLM) should address the topic of pleural fluid biochemical analysis in the future to promote specific knowledge in the laboratory professional community.