The comparison of pleural fluid TNF-α levels in tuberculous and nontuberculous pleural effusion

Effect of saffron, black seed, and their main constituents on inflammatory cytokine response (mainly TNF-α) and oxidative stress status: an aspect on pharmacological insights

Tumor necrosis factor-α (TNF-α), an inflammatory cytokine, is produced by monocytes and macrophages. It is known as a 'double-edged sword' because it is responsible for advantageous and disadvantageous events in the body system. The unfavorable incident includes inflammation, which induces some diseases such as rheumatoid arthritis, obesity, cancer, and diabetes. Many medicinal plants have been found to prevent inflammation, such as saffron (Crocus sativus L.) and black seed (Nigella sativa). Therefore, the purpose of this review was to assess the pharmacological effects of saffron and black seed on TNF-α and diseases related to its imbalance. Different databases without time limitations were investigated up to 2022, including PubMed, Scopus, Medline, and Web of Science. All the original articles (in vitro, in vivo, and clinical studies) were collected on the effects of black seed and saffron on TNF-α. Black seed and saffron have therapeutic effects against many disorders, such as hepatotoxicity, cancer, ischemia, and non-alcoholic fatty liver, by decreasing TNF-α levels based on their anti-inflammatory, anticancer, and antioxidant properties. Saffron and black seed can treat a variety of diseases by suppressing TNF-α and exhibiting a variety of activities such as neuroprotective, gastroprotective, immunomodulatory, antimicrobial, analgesic, antitussive, bronchodilator, antidiabetic activity, anticancer, and antioxidant effects. To uncover the beneficial underlying mechanisms of black seed and saffron, more clinical trials and phytochemical research are required. Also, these two plants affect other inflammatory cytokines, hormones, and enzymes, implying that they could be used to treat a variety of diseases.

Pleural fluid tumor necrosis factor for diagnosis of pleural tuberculosis: A systematic review and meta-analysis

OBJECTIVE

Tumor necrosis factor (TNF) is an important local host response mediator in tuberculous pleural effusion (TPE) and is proposed as a potential biomarker for diagnosing TPE. We assessed the performance of pleural fluid TNF in the diagnosis of TPE, and evaluated its ability to distinguish TPE from parapneumonic or malignant effusions.

METHODS

We queried the PubMed and Embase databases for studies indexed till August 2020. We included studies that (a) provided data on sensitivity and specificity of pleural fluid TNF for the diagnosis of TPE, or (b) compared pleural fluid TNF levels between TPE and malignant or parapneumonic effusions. We used a hierarchical summary receiver operating characteristic plot to model summary sensitivity and specificity. A random effects model was used to pool standardized mean differences (SMD) across studies comparing TPE and other effusions. We explored heterogeneity using subgroup analysis. We also performed meta-regression to identify factors significantly influencing results.

RESULTS

We retrieved 1090 citations, and included 38 publications, in our review. The summary estimates for sensitivity, specificity, and diagnostic odds ratio were 0.79 (95% CI 0.72-0.84), 0.82 (95% CI 0.76-0.87), and 16.84 (95% CI 9.47-29.95) respectively. Pleural fluid TNF levels were significantly higher in TPE than in malignant effusions (summary SMD 1.50, 95% CI 1.13-1.87), but not parapneumonic effusions (summary SMD 0.61, 95% CI -0.14 to 1.35). None of the prespecified subgroup variables significantly influenced summary estimates.

CONCLUSION

Pleural fluid TNF has poor diagnostic accuracy for diagnosing TPE and imperfectly discriminates TPE from parapneumonic pleural effusions.

A bioinformatics analysis to identify novel biomarkers for prognosis of pulmonary tuberculosis

Background

Due to the fact that pulmonary tuberculosis (PTB) is a highly infectious respiratory disease characterized by high herd susceptibility and hard to be treated, this study aimed to search novel effective biomarkers to improve the prognosis and treatment of PTB patients.

Methods

Firstly, bioinformatics analysis was performed to identify PTB-related differentially expressed genes (DEGs) from GEO database, which were then subjected to GO annotation and KEGG pathway enrichment analysis to initially describe their functions. Afterwards, clustering analysis was conducted to identify PTB-related gene clusters and relevant PPI networks were established using the STRING database.

Results

Based on the further differential and clustering analyses, 10 DEGs decreased during PTB development were identified and considered as candidate hub genes. Besides, we retrospectively analyzed some relevant studies and found that 7 genes (CCL20, PTGS2, ICAM1, TIMP1, MMP9, CXCL8 and IL6) presented an intimate correlation with PTB development and had the potential serving as biomarkers.

Conclusions

Overall, this study provides a theoretical basis for research on novel biomarkers of PTB, and helps to estimate PTB prognosis as well as probe into targeted molecular treatment.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12890-020-01316-2.