Carmen Socaciu’s research while affiliated with University of Agricultural Sciences and Veterinary Medicine and other places

Sea buckthorn (Hippophae rhamnoides L.) (SB) is increasingly consumed worldwide as a food and food supplement. The remarkable richness in biologically active phytochemicals (polyphenols, carotenoids, sterols, vitamins) is responsible for its purported nutritional and health-promoting effects. Despite the considerable interest and high market demand for SB-based supplements, a limited number of studies report on the authentication of such commercially available products. Herein, untargeted metabolomics based on ultra-high-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UHPLC-QTOF-ESI+MS) were able to compare the phytochemical fingerprint of leaves, berries, and various categories of SB-berry herbal supplements (teas, capsules, tablets, liquids). By untargeted metabolomics, a multivariate discrimination analysis and a univariate approach (t-test and ANOVA) showed some putative authentication biomarkers for berries, e.g., xylitol, violaxanthin, tryptophan, quinic acid, quercetin-3-rutinoside. Significant dominant molecules were found for leaves: luteolin-5-glucoside, arginine, isorhamnetin 3-rutinoside, serotonin, and tocopherol. The univariate analysis showed discriminations between the different classes of food supplements using similar algorithms. Finally, eight molecules were selected and considered significant putative authentication biomarkers. Further studies will be focused on quantitative evaluation.

Acute pancreatitis (AP) remains a challenging medical condition, where a deeper metabolic insight could pave the way for innovative treatments. This research harnessed serum metabolomics to discern potential diagnostic markers for AP and distinguish between its biliary (BAP) and alcohol-induced (AAP) forms. Leveraging high-performance liquid chromatography coupled with mass spectrometry, the metabolic signatures of 34 AP patients were contrasted against 26 healthy participants, and then between different etiologies of AP. The results identified metabolites primarily from glycerophospholipids, glycerolipids, fatty acyls, sterol lipids, and pteridines and derivative classes, with the Human Metabolome Database aiding in classification. Notably, these metabolites differentiated AP from healthy states with high AUROC values above 0.8. Another set of metabolites revealed differences between BAP and AAP, but these results were not as marked as the former. This lipidomic analysis provides an introduction to the metabolic landscape of acute pancreatitis, revealing changes in multiple lipid classes and metabolites and identifying these metabolites. Future research could add and discover new diagnostic biomarkers and therapeutic strategies enhancing the management of acute pancreatitis.

Background Milk thistle is one of the most popular hepatoprotectants, and is often sold in combination with other ingredients. Botanical supplements are known to be vulnerable to contamination and adulteration, and emerging technologies show promise to improve their quality control. Methods Untargeted and semi-targeted metabolomics based on UHPLC-QTOF-ESI⁺MS techniques, UV spectrometry, and DNA metabarcoding using Illumina MiSeq were used to authenticate eighteen milk thistle botanical formulations (teas, capsules, tablets, emulsion). Results Untargeted metabolomics separated 217 molecules and by multivariate analysis the discrimination between the different preparations was established. The semi-targeted metabolomics focused on 63 phytochemicals, mainly silymarin flavonolignans and flavonoids, that may be considered as putative biomarkers of authenticity. All formulations contained molecules from silymarin complexes at different levels. The quantitative evaluation of silybins was done using in parallel UV spectrometry and UHPLC-QTOF-ESI⁺MS and their correlations were compared. DNA metabarcoding detected milk thistle in eleven out of sixteen retained preparations, whereas two others had incomplete evidence of milk thistle despite metabolomics validating specific metabolites, e.g., silymarin complex, identified and quantified in all samples. Meanwhile, the DNA metabarcoding provided insights into the total species composition allowing the interpretation of the results in a broad context. Conclusion Our study emphasizes that combining spectroscopic, chromatographic, and genetic techniques bring complementary information to guarantee the quality of the botanical formulations.

Milk thistle (Silybum marianum (L.) Gaertn.) is among the top-selling botanicals used as a supportive treatment for liver diseases. Silymarin, a mixture of unique flavonolignan metabolites, is the main bioactive component of milk thistle. The biological activities of silymarin have been well described in the literature, and its use is considered safe and well-tolerated in appropriate doses. However, commercial preparations do not always contain the recommended concentrations of silymarin, failing to provide the expected therapeutic effect. While the poor quality of raw material may explain the low concentrations of silymarin, its deliberate removal is suspected to be an adulteration. Toxic contaminants and foreign matters were also detected in milk thistle preparations, raising serious health concerns. Standard methods for determination of silymarin components include thin-layer chromatography (TLC), high-performance thin-layer chromatography (HPTLC), and high-performance liquid chromatography (HPLC) with various detectors, but nuclear magnetic resonance (NMR) and ultra-high-performance liquid chromatography (UHPLC) have also been applied. This review surveys the extraction techniques of main milk thistle metabolites and the quality, efficacy, and safety of the derived food supplements. Advanced analytical authentication approaches are discussed with a focus on DNA barcoding and metabarcoding to complement orthogonal chemical characterization and fingerprinting of herbal products.

Background and aim: Osteoarthritis (OA) is the most common joint condition and the leading cause of pain and disability in elderly patients. Currently, there is no biomarker available for the early diagnosis of OA, and limited data is available regarding the molecular basis of progression for OA. For this reason, this study aimed to identify the metabolomic profile of early and late OA using high-performance liquid chromatography coupled with untargeted mass spectrometry (LC-MS). Methods: 31 patients with knee OA and joint effusion were enrolled. Based on Kellgren/Laurence scale, 12 patients were classified as early OA (eOA) and 19 as late OA (lOA). The synovial fluid (SF) was collected and characterized by untargeted LC-MS. Only the metabolites identified in more than 25% of each group were kept for further analysis. Principal component analysis (PCA) enabled the unsupervised clustering of the eOA and lOA groups. Further, for classification, the best three principal components (PCs) were used as input for two machine learning algorithms (random forest and naïve Bayes), which were trained to discriminate between the eOA and lOA groups. Results: 43 metabolites were identified in both eOA and lOA, but after selecting the metabolites present in at least 25% of the patients in each group, the metabolomics analysis yielded a panel of only nine metabolites: four metabolites related to phospholipids (phosphatidylcholine 20:0/18:2 and 18:0/20:2, sphingomyelin, and ceramide), three metabolites belonging to purine metabolites (inosine 5'-phosphate, adenosine thiamine diphosphate, and diadenosine 5',5'-diphosphate), one metabolite was a gonadal steroid hormone (estrone 3-sulfate), and one metabolite represented by heme, with all but ceramide (d18:1/20:0) being enriched in the lOA group. By using as features the best three PCs (PC2, PC8 and PC9), random forest and naïve Bayes machine learning algorithms yielded a classification accuracy of 0.81 and 0.78, respectively. Conclusion: Our LC-MS analysis of SF from patients with eOA and lOA indicates stage-dependent differences, lOA being associated with a perturbed metabolome of phospholipids, purine metabolites, gonadal steroid hormones (estrone 3-sulfate) and a heme molecule. Specific questions need to be answered regarding the biosynthesis and function of these metabolites in osteoarthritic joints, with the aim of developing new relevant biomarkers and therapeutic strategies.

The scientific interest in natural food flavors is growing considering concerns of the population related to food safety. Aromatic plants and their concentrated forms (essential oils and phenolic extracts) are highly considered for health benefits, mainly due to antioxidant and antibacterial properties. Meanwhile the authenticity and safety of essential oils is a strong concern. Comparative signatures of six genuine, essential oils (Thyme, Juniperus, Oregano, Tea tree, Clove and Cinnamon) was obtained by Gas chromatography coupled with Mass Spectrometry, using a metabolomic approach, by an updated statistical tool available online Metaboanalyst 5.0. The key-molecules of each oil were identified and the multivariate analysis combined with correlation heatmaps reflected the predictability of around 15 putative biomarkers, such as thymol and p-cymene for Thyme, α-pinene, β-myrcene and sabinene for Juniperus, carvacrol for Oregano, terpinene derivatives for Tea tree, eugenol, eugenol acetate for Clove, cinnamaldehyde for Cinnamon. Since these oils are used frequently as ingredients in food supplements and food flavors, this study offers an accurate evaluation and interpretation of the authenticity of these oils based on biomarker identification, easy to be done also from food matrices. The adulteration of similar commercial oils, of synthetic or degraded specimens is also possible using this model.

Chronic kidney disease (CKD) affects around 13% of the adult population, has become a considerable concern worldwide, and is characterized by inadequate renal clearance, resulting in the accumulation of various potential toxic compounds. Metabolomics, one of the many important parts of “omics” science, refers to the systematic study of metabolites in a living system and their changes because of pathophysiological and genetic modifications. The use of metabolomics in the nephrology field of research has offered a better understanding of the pathomechanisms of CKD. The most recent technologies used for the evaluation of plasma and urinary metabolites are nuclear magnetic resonance (NMR) and mass spectroscopy (MS). A major research direction of modern medicine is to develop new therapies and new biomarkers for the early diagnosis of patients with CKD. Experimental studies of renal metabolism unequivocally demonstrated that kidney function has a huge impact on several circulating metabolites. Moreover, metabolites themselves appear to have an essential role in CKD pathogenesis/complications, being recognized as potential biomarkers with prognostic, diagnostic, and therapeutic value for the disease. The present paper provides a bird’s eye view on metabolomics and a summary of the most recent studies of metabolomics carried out in patients with CKD.

Microalgae (green or blue-green ones) are among the most important organisms on the world, with a versatile and adaptive metabolism. They are able to synthesize bioactive molecules (mainly secondary metabolites such as unsaturated fatty acids, pigments, amino acids) with biomedical applications, enhancement of the nutritional value of food, animal feed/aquaculture, as well with impact on the environmental protection ( as raw materials for biofuels). Last decade, by a targeted selection of wild microalgae strains, their cultivation in farms developed in parallel with the bioreactors’products. There are nowadays cultivated at industrial scale especially Dunaliella salina p., Spirulina platensis, Hematococcus pluvialis or Chlorella vulgaris as valuable resources of polyunsaturated lipids and sterols, proteins, polysaccharides, carotenoid pigments, vitamins, minerals with antioxidant, antibacterial or antiviral effects. This review presents a systematic approach on the recent literature data collected the last years, underlying their morphologic and biochemical potential, the advanced technologies to use the bioactive components of different microalgae, new formulations which incorporate, stabilize and store their bioactivity and increase the bioavailability of their components in food and feed. Although their morphologic and biochemical potential is well described, there are presented new data on their bioactive components and formulations using emerging technologies for new application approaches which aims their use as ingredients in added value products for food, cosmetics and feed industry, to be exploited for commercial use. This review updated the last findings in these areas, underlined the reason for the scientific and technological advances, due to their huge potential, not only in environment, energy, but more and more as ingredients for food and feed/ aquaculture products, in the future.