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Background/Objectives: Pentacyclic triterpenoids, as bioactive phytochemicals, have proven to exhibit significant bioactivity (antioxidant, anti-inflammatory, hypoglycemic, and anticancer) and low cytotoxicity. This study developed convenient methods for extracting and characterizing a birch bark extract enriched in pentacyclic triterpenoids (betulin, betulinic acid, and lupeol) and entrapped in two bioavailable nanoformulations. The performance of ATR-FTIR spectroscopy as a cost-effective and non-destructive method was evaluated comparatively with accurate HPLC-based methods. Methods: The bark extract and pure betulin or betulinic acid were used to obtain PEGylated liposomes and nano lipid carriers (NLCs). Their size was characterized by light scattering diffraction. UV–Vis spectrometry was applied as a preliminary evaluation (1), as well as UHPLC-QTOF-ESI+-MS for structure identification (2), ATR-FTIR spectroscopy (for semi-quantitative evaluation) (3), and HPLC-DAD for an accurate quantification of each component, either in the organic solvents or in the nanoformulations (4). Results: The PEGylated liposomes had smaller sizes, and higher entrapment efficiency, significantly correlated between the three analytical methods. The performance of ATR-FTIR spectroscopy was positively correlated with HPLC-DAD data and confirmed the potential of this cheaper and reliable semi-quantitative method to evaluate the entrapment efficiency of TTs in liposome and NLC nanoformulations. Conclusions: The results recommend using liposomal nanoformulations for the entrapment of bioactive terpenoids and their characterization by ATR-FTIR after validation by HPLC-DAD. The ATR-FTIR spectroscopy also offers the possibility of screening in a short time different recipes of nanoformulations as well as their stability and bioavailability, which is useful for investigations in vitro and in vivo, which may confirm their efficacy as therapeutic agents. [ABSTRACT FROM AUTHOR]

Background/Objectives: Pentacyclic triterpenoids are increasingly studied as anticancer agents with many advantages compared to synthetic chemotherapeutics. The aim of this study was to prepare liposomal and nanostructured lipid formulations including a standardized extract of silver birch (Betula pendula) outer bark (TTs) and to evaluate their potential as anticancer agents in vitro, using Melanoma B16-F10 and Walker carcinoma cells. Methods: Appropriate solvents were selected for efficient TTs extraction, and original recipes were used to obtain Pegylated liposomes and nanolipid complexes with entrapped TTs, comparative to pure standards (betulinic acid and doxorubicin) in similar conditions. The composition, morphology, and sizes of all nanoformulations were checked by high-performance liquid chromatography/mass spectrometry, Transmission Electronic Microscopy, and Diffraction Light Scattering. The entrapment efficiency and its impact on cell viability, cell cycle arrest, and apoptosis by flow cytometry was also measured on both cancer cell lines. Conclusions: The standardized TTs, including betulin, lupeol, and betulinic acid, showed good stability and superior activity compared to pure betulinic acid. According to experimental data, TTs showed good entrapment in liposomal and NLC nanoformulations, both delivery systems including natural, biodegradable ingredients and enhanced bioavailability. The apoptosis and necrosis effects were more pronounced for TTs liposomal formulations in both types of cancer cells, with lower cytotoxicity compared to Doxorubicin, and can be correlated with their increased bioavailability. [ABSTRACT FROM AUTHOR]

Background: Identification of specific urine metabolic profiles for patients diagnosed with papillary thyroid carcinoma (TC) vs. benign nodules (B) to identify specific biomarkers and altered pathways compared to those of healthy controls (C). Methods: Patient urine samples were collected, before surgery and after a histological confirmation of TC (n = 30) and B (n = 30), in parallel with sample collection from healthy controls (n = 20). The untargeted and semi-targeted metabolomic protocols were applied using UPLC-QTOF-ESI+-MS analysis, and the statistical analysis was performed using the Metaboanalyst 6.0 platform. The results for the blood biomarkers, previously published, were compared with the data obtained from urine sampling using the Venny algorithm and multivariate statistics. Results: Partial least squares discrimination, including VIP values, random forest graphs, and heatmaps (p < 0.05), together with biomarker analysis (AUROC ranking) and pathway analysis, suggested a specific model for the urinary metabolic profile and pathway alterations in TC and B vs. C, based on 190 identified metabolites in urine that were compared with the serum metabolites. By semi-targeted metabolomics, 10 classes of metabolites, considered putative biomarkers, were found to be responsible for specific alterations in the metabolic pathways, from polar molecules to lipids. Specific biomarkers for discrimination were identified in each class of metabolites that were either upregulated or downregulated when compared to those of the controls. Conclusions: The lipidomic window was the most relevant for identifying biomarkers related to thyroid cancer and benign conditions, since this study detected a stronger involvement of lipids and selenium-related molecules for metabolic discrimination. [ABSTRACT FROM AUTHOR]

In this study, serum metabolic profiling of patients diagnosed with papillary thyroid carcinoma (PTC) and benign thyroid pathologies (BT) aimed to identify specific biomarkers and altered pathways when compared with healthy controls (C). The blood was collected after a histological confirmation from PTC (n = 24) and BT patients (n = 31) in parallel with healthy controls (n = 81). The untargeted metabolomics protocol was applied by UHPLC-QTOF-ESI+-MS analysis and the statistical analysis was performed using the MetaboAnalyst 5.0 platform. The partial least squares-discrimination analysis, including VIP values, random forest graphs, and heatmaps (p < 0.05), was complemented with biomarker analysis (with AUROC ranking) and pathway analysis, suggesting a model for abnormal metabolic pathways in PTC and BT based on 166 identified metabolites. There were 11 classes of putative biomarkers selected that were involved in altered metabolic pathways, e.g., polar molecules (amino acids and glycolysis metabolites, purines and pyrimidines, and selenium complexes) and lipids including free fatty acids, bile acids, acylated carnitines, corticosteroids, prostaglandins, and phospholipids. Specific biomarkers of discrimination were identified in each class of metabolites and upregulated or downregulated comparative to controls, PTC group, and BT group. The lipidomic window was revealed to be more relevant for finding biomarkers related to thyroid carcinoma or benign thyroid nodules, since our study reflected a stronger involvement of lipids and selenium-related molecules in metabolic discrimination. [ABSTRACT FROM AUTHOR]

This study aimed to find alternative, cheap and fast procedures to incorporate Doxorubicin in small unilamellar nanoliposomes made of Dipalmitoyl Phosphatidyl Choline and Cholesterol. It was compared the entrapment efficiency of doxorubicin in "home-made" liposomes (1) and in ImmunoSOME liposomes (2), a commercial, expensive formulation. It was obtained an entrapment efficiency of 27.6 % vs 12.1% for formulatios (1) vs (2). The liposomes' size and zeta-potential of formulation (1) ranged from 116 and 120 nm, being smaller than in formulation (2). The zeta potential was negative for both formulations and showed a better stability and monodispersibility also for formulation (1). This fast procedure is convenient and assure efficient doxorubicin entrapment in the monodisperse nanoliposomes. Such simple formulations, easier to be obtained, can offer also good quality/price ratios and can be produced at larger scale, with higher incorporation efficiency for experimental in vivo studies which aims the targeted delivery of Doxorubicin to cancer tumors in animals. [ABSTRACT FROM AUTHOR]