1H nuclear magnetic resonance-based metabolic profiling of cerebrospinal fluid to identify metabolic features and markers for tuberculosis meningitis

BackgroundTuberculosis meningitis (TBM) is the most severe form of tuberculosis, and currently lacks efficient diagnostic approaches. Metabolomics has the potential to differentiate patients with TBM from those with other forms of meningitis and meningitis-negative individuals. However, no systemic metabolomics research has compared the cerebrospinal fluid (CSF) of these patients.Methods¹H nuclear magnetic resonance (NMR) was used for CSF metabolic profiling. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OPLS-DA) were used to screen for important variables. The Human Metabolome Database was used to identify metabolites, and MetaboAnalyst 4.0 was used for pathway analysis and over-representation analysis.ResultsOPLS-DA modeling could distinguish TBM from other forms of meningitis, and several significantly changed metabolites were identified. Additionally, 23, 6, and 21 metabolites were able to differentiate TBM from viral meningitis, bacterial meningitis, and meningitis-negative groups, respectively. Pathway analysis indicated that these metabolites were mainly involved in carbohydrate and amino acid metabolism, and over-representation analysis indicated that some of these pathways were over-represented.ConclusionsThe metabolites identified have the potential to serve as biomarkers for TBM diagnosis, and carbohydrate and amino acid metabolism are perturbed in the CSF of patents with TBM. Metabolomics is a valuable approach for screening TBM biomarkers. With further investigation, the metabolites identified in this study could aid in TBM diagnosis.     

Understanding the Influence of Nanocarrier-Mediated Brain Delivery on Therapeutic Performance Through Pharmacokinetic-Pharmacodynamic Modeling

This study aimed at evaluating how encapsulation in a regular nanocarrier (NC) (providing extended circulation time) or in a brain-targeting NC (providing prolonged circulation time and increased brain uptake) may influence the therapeutic index compared with the unformulated drug and to explore the key parameters affecting therapeutic performance using a model-based approach. Pharmacokinetic (PK) models were built with chosen PK parameters. For a scenario where central effect depends on area under the unbound brain concentration curve and peripheral toxicity relates to peak unbound plasma concentration, dose-effect and drug-side effect curves were constructed, and the therapeutic index was evaluated. Regular NC improved the therapeutic index compared with the unformulated drug due to reduced peripheral toxicity, while brain-targeting NC enhanced the therapeutic index by lowering peripheral toxicity and increasing central effect. Decreasing drug release rate or systemic clearance of NC with drug still encapsulated could increase the therapeutic index. Also, a drug with shorter half-life would therapeutically benefit more from a NC encapsulation. This work provides insights into how a NC for brain delivery should be optimized to maximize the therapeutic performance and is helpful to predict if and to what extent a drug with certain PK properties would obtain therapeutic benefit from nanoencapsulation.     

Prognostic and clinicopathological utility of programmed death-ligand 1 in malignant pleural mesothelioma: A meta-analysis

ObjectiveProgrammed death ligand 1 (PD-L1) has been reported to be connected to prognosis in individuals with malignant pleural mesothelioma (MPM), although there is no consensus based on data from previous studies. Accordingly, this quantitative meta-analysis investigated prognostic and clinicopathological utility of PD-L1 in patients with MPM.MethodsA comprehensive search of the PubMed, Web of Science, Embase, and Cochrane Library databases for articles published up to October 4, 2019 was performed. Studies using immunohistochemical techniques to detect/quantify the expression of PD-L1 in MPM tissue were enrolled in the analysis. The combined hazard ratio (HR) and corresponding 95% confidence interval (CI) was applied to assess the association between PD-L1 expression and overall survival (OS).ResultsA total of 11 studies comprising 1606 patients was included in the present meta-analysis. For OS, pooled data revealed an HR of 1.50 (95% CI 1.32–1.70; p < 0.001), suggesting that patients with PD-L1 overexpression experience inferior OS. Subgroup analysis revealed that elevated PD-L1 remained a significant prognostic indicator for worse OS, irrespective of sample size, cut-off value, ethnicity, and Newcastle-Ottawa Scale score. Moreover, PD-L1 overexpression was associated with non-epithelioid histology (odds ratio 4.30 [95% CI 1.89–9.74]; p < 0.001).ConclusionsResults of this meta-analysis show that elevated expression of PD-L1 could be a factor predicting poorer survival in patients with MPM.