A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis.

Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects. Metabolomic profiling was conducted, involving the quantitative analysis of 87 endogenous metabolites in plasma. A novel regression method of age-adjustment correction of metabolomics data was developed. We identified 36 significantly changed metabolites which included increased cystathionine and dimethylglycine and the decreased ADMA and arginine. Tryptophan catabolism pathways showed significant alterations with increased levels of serotonin, intermediates of the kynurenine pathway and decreased intermediates of indole pathway. Amino acid profiles indicated elevated branched-chain amino acids and increased amino acid ratios. Short-chain acylcarnitines were reduced, while long-chain acylcarnitines were elevated. Based on these metabolites data, machine learning algorithms: logistic regression, support vector machine, decision trees, random forest, and gradient boosting, were used for IHD diagnostic models. Random forest demonstrated the highest accuracy with an AUC of 0.98. The metabolites Norepinephrine; Xanthurenic acid; Anthranilic acid; Serotonin; C6-DC; C14-OH; C16; C16-OH; GSG; Phenylalanine and Methionine were found to be significant and may serve as a novel preliminary panel for IHD diagnostics. Further studies are needed to confirm these findings.

A dual-vector phospholipid nanosystem of doxorubicin: accumulation and cytotoxic effect in breast cancer cells in vitro.

Various chemotherapeutic agents are used to treat breast cancer (BC); one of them is the anthracycline antibiotic doxorubicin (Dox), which, in addition to its cytostatic effect, has serious side effects. In order to reduce its negative impact on healthy organs and tissues and to increase its accumulation in tumors, Dox was incorporated into phospholipid nanoparticles. The additional use of vector molecules for targeted delivery to specific targets can increase the effectiveness of Dox due to higher accumulation of the active substance in the tumor tissue. The integrin αvß3, which plays an important role in cancer angiogenesis, and the folic acid receptor, which is responsible for cell differentiation and proliferation, have been considered in this study as targets for such vector molecules. Thus, a phospholipid composition of Dox containing two vector ligands, cRGD peptide and folic acid (NPh-Dox-cRGD-Fol(3,4)), was prepared. Study of the physical properties of the developed composition NPh-Dox-cRGD-Fol(3,4) showed that the average particle size was 39.62±4.61 nm, the ζ-potential value was 4.17±0.83 mV. Almost all Dox molecules were incorporated into phospholipid nanoparticles (99.85±0.21%). The simultaneous use of two vectors in the composition led to an increase in the Dox accumulation in MDA-MB-231 BC cells by almost 20% as compared to compositions containing each vector separately (folic acid or the cRGD peptide). Moreover, the degree of Dox internalization was 22% and 24% higher than in the case of separate use of folic acid and cRGD peptide, respectively. The cytotoxic effect on MDA-MB-231 cells was higher during incubations with the compositions containing folic acid as a single vector (NPh-Dox-Fol(3,4)) and together with the RGD peptide (NPh-Dox-cRGD-Fol(3,4)). Experiments on the Wi-38 diploid fibroblast cell line have shown a significantly lower degree of cytotoxic effect of the phospholipid composition, regardless of the presence of the vector molecules in it, as compared to free Dox. The results obtained indicate the potential of using two vectors in one phospholipid composition for targeted delivery of Dox.