Polyphenols-Enrichment of Vienna Sausages Using Microcapsules Containing Acidic Aqueous Extract of Boletus edulis Mushrooms.

Polyphenols are ubiquitous by-products in many plant foods. Their intake has been linked to health benefits like the reduced incidence of cardiovascular disease, diabetes, and cancer. These bioactive compounds can be successfully extracted from Boletus edulis mushrooms with acidic water. However, such extract could influence the sensory or textural properties of the product to be enriched; this inconvenience can be avoided by microencapsulating it using spray drying. In this study, the Vienna sausages were reformulated by replacing 2% of the cured meat with microcapsules containing an acidic aqueous extract of Boletus edulis mushrooms and by replacing ice flakes, an ingredient that represents 22.9% of the manufacturing recipe, with ice cubes from the same extract aiming to obtain a polyphenol enriched product. The results showed a higher content of polyphenols in sausages with extract (VSe; 568.92 µg/g) and microcapsules (VSm; 523.03 µg/g) than in the control ones (455.41 µg/g), with significant differences for 2,4-dihydroxybenzoic acid, protocatechuic acid, and 1-O-galloyl-ß-D-glucose. However, because of the oxidative stress caused to the microcapsules by the extract's spray drying, VSm had the highest oxidation state. PV and TBARS levels varied with storage time in all formulations, but given the short period tested, they were well below the allowed/recommended limit. The extract, as such, negatively affected the appearance, odor, and taste of Vienna sausages. The microcapsules, instead, determined an increase in their acceptance rate among consumers; they also prevented moisture loss and color changes during storage. In conclusion, microcapsules are more suitable for use as a polyphenol enrichment ingredient in Vienna sausages than the extract.

Metabolic Profiles and Blood Biomarkers to Discriminate between Benign Thyroid Nodules and Papillary Carcinoma, Based on UHPLC-QTOF-ESI+-MS Analysis.

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.

Characterization of the Chemical Composition and Biological Activities of Bog Bilberry (Vaccinium uliginosum L.) Leaf Extracts Obtained via Various Extraction Techniques.

This investigation aimed to assess the chemical composition and biological activities of bog bilberry (Vaccinium uliginosum L.) leaves. Hydroethanolic extracts were obtained using four extraction techniques: one conventional (CE) and three alternative methods; ultrasound (UAE), microwave (MAE) and high-pressure (HPE) extractions. Spectrophotometric analysis was conducted to determine their chemical content, including the total phenolic content (TPC) and total flavonoid content (TFC). Furthermore, their antioxidative and antimicrobial properties were evaluated. HPLC (high performance liquid chromatography) analysis identified and quantified 17 phenolic compounds, with chlorogenic acid being the predominant compound, with the lowest level (37.36 ± 0.06 mg/g) for the bog bilberry leaf extract obtained by CE and the highest levels (e.g., HPE = 44.47 ± 0.08 mg/g) for the bog bilberry leaf extracts obtained by the alternative methods. Extracts obtained by HPE, UAE and MAE presented TPC values (135.75 ± 2.86 mg GAE/g; 130.52 ± 1.99 mg GAE/g; 119.23 ± 1.79 mg GAE/g) higher than those obtained by the CE method (113.07 ± 0.98 mg GAE/g). Regarding the TFC values, similar to TPC, the highest levels were registered in the extracts obtained by alternative methods (HPE = 43.16 ± 0.12 mg QE/g; MAE = 39.79 ± 0.41 mg QE/g and UAE = 33.89 ± 0.35 mg QE/g), while the CE extract registered the lowest level, 31.47 ± 0.28 mg QE/g. In the case of DPPH (1,1-diphenyl-2-picrylhydrazyl) antioxidant activity, the extracts from HPE, UAE and MAE exhibited the strongest radical scavenging capacities of 71.14%, 63.13% and 60.84%, respectively, whereas the CE extract registered only 55.37%. According to Microbiology Reader LogPhase 600 (BioTek), a common MIC value of 8.88 mg/mL was registered for all types of extracts against Staphylococcus aureus (Gram-positive bacteria) and Salmonella enterica (Gram-negative bacteria). Moreover, the alternative extraction methods (UAE, HPE) effectively inhibited the growth of Candida parapsilosis, in comparison to the lack of inhibition from the CE method. This study provides valuable insights into bog bilberry leaf extracts, reporting a comprehensive evaluation of their chemical composition and associated biological activities, with alternative extraction methods presenting greater potential for the recovery of phenolic compounds with increased biological activities than the conventional method.

In Search of Authenticity Biomarkers in Food Supplements Containing Sea Buckthorn: A Metabolomics Approach.

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.

Effect of Bioactive Compounds from Pumpkin Powder on the Quality and Textural Properties of Shortbread Cookies.

The problem of food with functional ingredients, characterized by low energy intake and a variety of phytonutrients with biological activity, is one of the concerns of the population. The objectives of this study were to investigate the effect of pumpkin powder and its bioactive components on the quality, color and textural properties of shortbread cookies. In the drying process of pumpkin powder (Cucurbita moschata) at 60 ± 2 °C, the physicochemical parameters did not change significantly in relation to fresh pulp. The chromatic parameters L*, a* and b* showed that the pumpkin powder was brighter than the pulp, with a greater presence of yellow pigments. Pumpkin powder presented a rich source of bioactive compounds (polyphenols flavonoids, carotenoids) with an antioxidant potential of 161.52 mmol TE/100 g DW and 558.71 mg GAE/100 g DW. Antimicrobial activity against Gram-positive (Staphylococcus aureus, Bacillus cereus), Gram-negative (Escherichia coli, Salmonella Abony and Pseudomonas aeruginosa) bacteria and high antifungal activity against Candida albicans were attested. The sensory, physicochemical, texture parameters and color indicators of shortbread cookies with yellow pumpkin powder (YPP) added in a proportion of 5-20% were analyzed. The optimal score was given to the sample of 15% YPP. The use of 15-20% YPP contributed to improved consistency due to the formation of complexes between starch and protein.

Unraveling the Metabolic Changes in Acute Pancreatitis: A Metabolomics-Based Approach for Etiological Differentiation and Acute Biomarker Discovery.

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.

Metabolites Potentially Derived from Gut Microbiota Associated with Podocyte, Proximal Tubule, and Renal and Cerebrovascular Endothelial Damage in Early Diabetic Kidney Disease in T2DM Patients.

Complications due to type 2 diabetes mellitus (T2DM) such as diabetic kidney disease (DKD) and cerebral small vessel disease (CSVD) have a powerful impact on mortality and morbidity. Our current diagnostic markers have become outdated as T2DM-related complications continue to develop. The aim of the investigation was to point out the relationship between previously selected metabolites which are potentially derived from gut microbiota and indicators of endothelial, proximal tubule (PT), and podocyte dysfunction, and neurosonological indices. The study participants were 20 healthy controls and 90 T2DM patients divided into three stages: normoalbuminuria, microalbuminuria, and macroalbuminuria. Serum and urine metabolites were determined by untargeted and targeted metabolomic techniques. The markers of endothelial, PT and podocyte dysfunction were assessed by ELISA technique, and the neurosonological indices were provided by an ultrasound device with high resolution (MYLAB 8-ESAOTE Italy). The descriptive statistical analysis was followed by univariable and multivariable linear regression analyses. In conclusion, in serum, arginine (sArg), butenoylcarnitine (sBCA), and indoxyl sulfate (sIS) expressed a biomarker potential in terms of renal endothelial dysfunction and carotid atherosclerosis, whereas sorbitol (sSorb) may be a potential biomarker of blood-brain barrier (BBB) dysfunction. In urine, BCA and IS were associated with markers of podocyte damage, whereas PCS correlated with markers of PT dysfunction.

Pentacyclic Triterpenoid Phytochemicals with Anticancer Activity: Updated Studies on Mechanisms and Targeted Delivery.

Pentacyclic triterpenoids (TTs) represent a unique family of phytochemicals with interesting properties and pharmacological effects, with some representatives, such as betulinic acid (BA) and betulin (B), being mainly investigated as potential anticancer molecules. Considering the recent scientific and preclinical investigations, a review of their anticancer mechanisms, structure-related activity, and efficiency improved by their insertion in nanolipid vehicles for targeted delivery is presented. A systematic literature study about their effects on tumor cells in vitro and in vivo, as free molecules or encapsulated in liposomes or nanolipids, is discussed. A special approach is given to liposome-TTs and nanolipid-TTs complexes to be linked to microbubbles, known as contrast agents in ultrasonography. The production of such supramolecular conjugates to deliver the drugs to target cells via sonoporation represents a new scientific and applicative direction to improve TT efficiency, considering that they have limited availability as lipophilic molecules. Relevant and recent examples of in vitro and in vivo studies, as well as the challenges for the next steps towards the application of these complex delivery systems to tumor cells, are discussed, as are the challenges for the next steps towards the application of targeted delivery to tumor cells, opening new directions for innovative nanotechnological solutions.

Authentication of milk thistle commercial products using UHPLC-QTOF-ESI + MS metabolomics and DNA metabarcoding.

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.

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques, such as the following: arginine, dimethylarginine, hippuric acid, indoxyl sulfate, p-cresyl sulfate, L-acetylcarnitine, butenoylcarnitine and sorbitol. The study concept was based on the targeted analysis of selected metabolites, using the serum and urine of 20 healthy subjects and 90 T2DM patients with DKD in different stages (normoalbuminuria-uACR < 30 mg/g; microalbuminuria-uACR 30-300 mg/g; macroalbuminuria-uACR > 300 mg/g). The quantitative evaluation of metabolites was performed with pure standards, followed by the validation methods such as the limit of detection (LOD) and the limit of quantification (LOQ). The following metabolites from this study resulted as possible biomarkers of early DKD: in serum-arginine, dimethylarginine, hippuric acid, indoxyl sulfate, butenoylcarnitine and sorbitol and in urine-p-cresyl sulfate.

Metabolomic Investigation of Blood and Urinary Amino Acids and Derivatives in Patients with Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease; however, few biomarkers of its early identification are available. The aim of the study was to assess new biomarkers in the early stages of DKD in type 2 diabetes mellitus (DM) patients. This cross-sectional pilot study performed an integrated metabolomic profiling of blood and urine in 90 patients with type 2 DM, classified into three subgroups according to albuminuria stage from P1 to P3 (30 normo-, 30 micro-, and 30 macroalbuminuric) and 20 healthy controls using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI* MS). From a large cohort of separated and identified molecules, 33 and 39 amino acids and derivatives from serum and urine, respectively, were selected for statistical analysis using Metaboanalyst 5.0. online software. The multivariate and univariate algorithms confirmed the relevance of some amino acids and derivatives as biomarkers that are responsible for the discrimination between healthy controls and DKD patients. Serum molecules such as tiglylglycine, methoxytryptophan, serotonin sulfate, 5-hydroxy lysine, taurine, kynurenic acid, and tyrosine were found to be more significant in the discrimination between group C and subgroups P1-P2-P3. In urine, o-phosphothreonine, aspartic acid, 5-hydroxy lysine, uric acid, methoxytryptophan, were among the most relevant metabolites in the discrimination between group C and DKD group, as well between subgroups P1-P2-P3. The identification of these potential biomarkers may indicate their involvement in the early DKD and 2DM progression, reflecting kidney injury at specific sites along the nephron, even in the early stages of DKD.

Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling.

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.

Untargeted Metabolomics by Ultra-High-Performance Liquid Chromatography Coupled with Electrospray Ionization-Quadrupole-Time of Flight-Mass Spectrometry Analysis Identifies a Specific Metabolomic Profile in Patients with Early Chronic Kidney Disease.

Chronic kidney disease (CKD) has emerged as one of the most progressive diseases with increased mortality and morbidity. Metabolomics offers new insights into CKD pathogenesis and the discovery of new biomarkers for the early diagnosis of CKD. The aim of this cross-sectional study was to assess metabolomic profiling of serum and urine samples obtained from CKD patients. Untargeted metabolomics followed by multivariate and univariate analysis of blood and urine samples from 88 patients with CKD, staged by estimated glomerular filtration rate (eGFR), and 20 healthy control subjects was performed using ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry. Serum levels of Oleoyl glycine, alpha-lipoic acid, Propylthiouracil, and L-cysteine correlated directly with eGFR. Negative correlations were observed between serum 5-Hydroxyindoleacetic acid, Phenylalanine, Pyridoxamine, Cysteinyl glycine, Propenoylcarnitine, Uridine, and All-trans retinoic acid levels and eGFR. In urine samples, the majority of molecules were increased in patients with advanced CKD as compared with early CKD patients and controls. Amino acids, antioxidants, uremic toxins, acylcarnitines, and tryptophane metabolites were found in all CKD stages. Their dual variations in serum and urine may explain their impact on both glomerular and tubular structures, even in the early stages of CKD. Patients with CKD display a specific metabolomic profile. Since this paper represents a pilot study, future research is needed to confirm our findings that metabolites can serve as indicators of early CKD.

Enhanced diagnosis and prognosis of severe alcoholic hepatitis using novel metabolomic biomarkers.

AIM: Differentiating alcoholic hepatitis (AH) from acute decompensation of alcoholic cirrhosis (DC) is challenging, as the presentation and biochemistry are similar. We aimed to identify potential metabolomic biomarkers to differentiate between AH and DC, and to predict short-term mortality. METHODS: We included consecutive biopsy proven AH and DC patients, which were managed according to current guidelines and followed up until the end of the study. Untargeted metabolomics was assessed in all patients at baseline. Specific analyses were successively performed to identify potential biomarkers, which were further semi-quantitatively analysed against relevant clinical endpoints. RESULTS: Thirty-four patients with AH and 37 with DC were included. UHPLC-MS analysis identified 83 molecules potentially differentiating between AH and DC. C16-Sphinganine-1P (S1P) was the most increased, whereas Prostaglandin E2 (PGE2) was the most decreased. The PGE2/S1P ratio < 1.03 excellently discriminates between AH and DC: AUC 0.965 (p < 0.001), Se 90%, Sp 100%, PPV 0.91, NPV 1, and diagnostic accuracy 95%. This ratio is not influenced by the presence of infection (AUC 0.967 vs. 0.962), correlates with the Lille score at 7 days (r = -0.60; P = 0.022) and tends to be lower in corticosteroid non-responders as compared with patients who responded [0.85(±0.02) vs. 0.89(±0.05), P = 0.069]. Additionally, decreased ursodeoxycholic acid levels are correlated with MELD and Maddrey scores and predict mortality with a 77.27% accuracy (NPV = 100%). CONCLUSION: This study suggests the PGE2 (decreased)/S1P (increased) ratio as a biomarker to differentiate AH from DC. The study also finds that low levels of ursodeoxycholic acid could predict increased mortality in AH.

Stabilization of Sunflower Oil with Biologically Active Compounds from Berries.

Sunflower oil (Helianthus annuus) contains a rich concentration of polyunsaturated fatty acids, which are susceptible to rapid oxidative processes. The aim of this study was to evaluate the stabilizing effect of lipophilic extracts from two types of berries, sea buckthorn and rose hips, on sunflower oil. This research included the analysis of sunflower oil oxidation products and mechanisms, including the determination of chemical changes occurring in the lipid oxidation process via LC-MS/MS using electrospray ionization in negative and positive mode. Pentanal, hexanal, heptanal, octanal, and nonanal were identified as key compounds formed during oxidation. The individual profiles of the carotenoids from sea buckthorn berries were determined using RP-HPLC. The influence of the carotenoid extraction parameters ascertained from the berries on the oxidative stability of sunflower oil was analyzed. The dynamics of the accumulation of the primary and secondary products of lipid oxidation and the variation of the carotenoid pigment content in the lipophilic extracts of sea buckthorn and rose hips during storage demonstrated good stability at 4 °C in the absence of light for 12 months. The experimental results were applied to mathematical modeling using fuzzy sets and mutual information analysis, which allowed for the prediction of the oxidation of sunflower oil.

Metabolite Profiling of the Gut-Renal-Cerebral Axis Reveals a Particular Pattern in Early Diabetic Kidney Disease in T2DM Patients.

Type 2 diabetes mellitus (T2DM) represents an important microvascular disease concerning the kidney and the brain. Gut dysbiosis and microbiota-derived metabolites may be in relation with early pathophysiological changes in diabetic kidney disease (DKD). The aim of the study was to find new potential gut-derived biomarkers involved in the pathogenesis of early DKD, with a focus on the complex interconnection of these biomarkers with podocyte injury, proximal tubule dysfunction, renal and cerebrovascular endothelial dysfunction. The study design consisted of metabolite profiling of serum and urine of 90 T2DM patients (subgroups P1-normoalbuminuria, P2-microalbuminuria, P3-macroalbuminuria) and 20 healthy controls (group C), based on ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry analysis (UHPLC-QTOF-ESI+-MS). By multivariate and univariate analyses of serum and urine, which included Partial Least Squares Discriminant Analysis (PLSDA), Variable Importance Plots (VIP), Random Forest scores, One Way ANOVA and Biomarker analysis, there were discovered metabolites belonging to nitrogen metabolic pathway and retinoic acid signaling pathway which differentiate P1 group from P2, P3, C groups. Tyrosine, phenylalanine, indoxyl sulfate, serotonin sulfate, and all-trans retinoic acid express the metabolic fingerprint of P1 group vs. P2, P3, C groups, revealing a particular pattern in early DKD in T2DM patients.

Detecting and Profiling of Milk Thistle Metabolites in Food Supplements: A Safety-Oriented Approach by Advanced Analytics.

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.

Stage related metabolic profile of the synovial fluid in patients with acute flares of knee osteoarthritis.

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.

Anthocyanins as Key Phytochemicals Acting for the Prevention of Metabolic Diseases: An Overview.

Anthocyanins are water-soluble pigments present in fruits and vegetables, which render them an extensive range of colors. They have a wide distribution in the human diet, are innocuous, and, based on numerous studies, have supposed preventive and therapeutical benefits against chronic affections such as inflammatory, neurological, cardiovascular, digestive disorders, diabetes, and cancer, mostly due to their antioxidant action. Despite their great potential as pharmaceutical applications, they have a rather limited use because of their rather low stability to environmental variations. Their absorption was noticed to occur best in the stomach and small intestine, but the pH fluctuation of the digestive system impacts their rapid degradation. Urine excretion and tissue distribution also occur at low rates. The aim of this review is to highlight the chemical characteristics of anthocyanins and emphasize their weaknesses regarding bioavailability. It also targets to deliver an update on the recent advances in the involvement of anthocyanins in different pathologies with a focus on in vivo, in vitro, animal, and human clinical trials.

The Use of Machine Learning Algorithms and the Mass Spectrometry Lipidomic Profile of Serum for the Evaluation of Tacrolimus Exposure and Toxicity in Kidney Transplant Recipients.

Tacrolimus has a narrow therapeutic window; a whole-blood trough target concentration of between 5 and 8 ng/mL is considered a safe level for stable kidney transplant recipients. Tacrolimus serum levels must be closely monitored to obtain a balance between maximizing efficacy and minimizing dose-related toxic effects. Currently, there is no specific tacrolimus toxicity biomarker except a graft biopsy. Our study aimed to identify specific serum metabolites correlated with tacrolinemia levels using serum high-precision liquid chromatography-mass spectrometry and standard laboratory evaluation. Three machine learning algorithms were used (Naïve Bayes, logistic regression, and Random Forest) in 19 patients with high tacrolinemia (8 ng/mL) and 23 patients with low tacrolinemia (5 ng/mL). Using a selected panel of five lipid metabolites (phosphatidylserine, phosphatidylglycerol, phosphatidylethanolamine, arachidyl palmitoleate, and ceramide), Mg2+, and uric acid, all three machine learning algorithms yielded excellent classification accuracies between the two groups. The highest classification accuracy was obtained by Naïve Bayes, with an area under the curve of 0.799 and a classification accuracy of 0.756. Our results show that using our identified five lipid metabolites combined with Mg2+ and uric acid serum levels may provide a novel tool for diagnosing tacrolimus toxicity in kidney transplant recipients. Further validation with targeted MS and biopsy-proven TAC toxicity is needed.