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Considering the high biodiversity of microalgae and their important impact on economy and ecological balance, new screening techniques are needed for their phenotypic characterization and efficient valorization of bioactive components. This represents one the key purpose of the emerging bioeconomy concept, involving new biorefinery technologies coupled with advanced analytical tools. The article presents an overview of the recent extraction and chemical techniques used to recover, separate and characterize the main bioactive molecules (lipids and fatty acids, carbohydrates, proteins and mycosporine-like amino acids chlorophylls and carotenoid pigments) syntesized by microalgae, considering their interesting applications in food, pharmaceutical and cosmetic industries. Special focuses will be directed towards the cell disintegration and extraction procedures, identification and quantification of main metabolites by advanced analytical techniques. [ABSTRACT FROM AUTHOR]

Introduction: Although obesity and its biomarkers have been intensively studied, little is known about the metabolomic signature of visceral adiposity independent of insulin resistance that frequently accompanies increased levels of visceral fat. Our study aimed to investigate specific changes in amino acid (AA) levels as biomarkers of increased visceral adiposity independent of insulin resistance, in healthy subjects.

The aim of the present study was to create a functional, enriched in polyphenols and free of alcohol product obtained by acetic fermentation of beer. Beer and vinegar were tested first for their phenolic content and antioxidant activity, by the Folin Ciocalteu and the free radical scavenging activity by the 1,1-diphenyl-2-picrylhydrazyl free-radical scavenging assay, respectively. Then, the separation and identification of the 30 phenolic compounds was realized by high-performance liquid chromatography coupled with positive electrospray ionisation and diode array detection (HPLC-DAD–ESI(+)-MS) analysis. Identification of the phenolic compounds data was realized based on the UV spectra of each compound. Based on a calibration curve (R2 = 0.9985), the amounts of the phenolic compounds, expressed as mg cathechin equivalents (CE)/L, were calculated. The total phenolic content of the beer and vinegar samples determined using Folin–Ciocalteu reagent were of 428.9±1.58 and 661.5±7.69 mg GAE L-1, respectively, which contributed to the high antioxidant activity in the vinegar sample of 82.18 %. Statistically significant differences were observed after acetic fermentation between each parameter (p < 0.05). Brown beer vinegar represents a rich source of polyphenols and phenolic derivatives, compared to beer. By its increased phenolic content and antioxidant activity, brown beer vinegar could be considered another source of valuable compounds to beer, which could also be of interest in special diets.

This work examines the release rates in different solvents (polar and non-polar) of seabuckthorn oil encapsulated in different natural biopolymers (alginate, k-carrageenan and chitosan). The sea buckthorn oil was encapsulated using the ionotropically crosslinked gelation technique, and spherical orange beads with diameters ranging from 2 to 3 cm were obtained. The free and encapsulated seabuckthorn oil beads were characterized by Fourier transformed infrared (FTIR) spectroscopy. Determination of release rates of seabuckthorn oil (in hexane and methanol) was monitored by UV-Vis spectroscopy. Our experimental data indicated that release rates are determined by the diffusivity in the biopolymer matrices, and the solvent type, which influences the swelling of the beads. [ABSTRACT FROM AUTHOR]

Presently, in Romania, the cultivated area with plants for biofuel production represents 1,6% of the arable surface of the country, about 150 000 ha (in 2008). With an adequate promotion of the production technologies and usage of biofliel, at farm level, Romania could cover up to 8 % of the European need. Although there is an arable potential, and also there are the crops suitable for it (rape, soybean, sunflower, corn) Romania produces much less under the energetic potential it has. Regarding the future of biofuel there are investments in the domain, in the phase of project. [ABSTRACT FROM AUTHOR]

Vegetables comprise a significant portion of our daily diet with their high content in nutrients including fiber, vitamins, minerals, as well as phenolic compounds. Vegetable consumption has been shown to be positively associated with the prevention of several degenerative diseases thanks to their bioactive compounds. Accordingly, five selected vegetables, namely, red chicory, red onion, eggplant, purple sweet potato, and black carrot were thoroughly assessed for their phenolic content in this study. For this purpose, the total phenolic and flavonoid content of these five vegetables and their antioxidant activities that are based on three common methods ABTS radical cation decolorization assay (ABTS), Cupric Ion Reducing Antioxidant Capacity (CUPRAC), and DPPH scavenging activity assay were determined. Additionally, HPLC-PDA/Electrospray ionization coupled with mass spectrometry (HPLC-PDA/-ESI+-MS)-based identification and quantification of the members belonging to polyphenols present in each vegetable were determined. Statistical correlations between antioxidant activities and the specific type of phenolic compounds, such as anthocyanins, flavonoids, anthocyanins, and phenolic acids were further elucidated. Phenolic acids (chlorogenic and syringic acids) were found to be the most abundant compounds that are present in all samples. Among the anthocyanins, cyaniding derivatives were present in all vegetables. In terms of their antioxidant activities, the analyzed vegetables were ranked as red chicory > purple sweet potato > black carrot > eggplant > red onion, in descending order. Superior antioxidant activities exhibited by red chicory and purple sweet potato were attributed to the high content of phenolic compounds, especially flavonols (quercetin-3,4-O-diglucoside) in red chicory and anthocyanins (peonidin-3-caffeoyl p-hydroxybenzoylsophoroside-5-glucoside) in purple sweet potato.

Pesticide residues and microbial load on the surface of fresh fruits and vegetables becomes a major concern due to the safety and quality of these products for consumer.In order to minimize these risk factors (pesticide residues and microbial load), were achieved labels for fruits and vegetables that are consumed with shell which disintegrates under the influence of water jet and thus reduce the amount of these contaminants. Were elaborated labels based on polymer (chitosan) at a concentration of 2%, which incorporate bioactive compounds from green tea with potential decontaminant of the peel of this products. Green tea extract was obtained by infusing 1 g of dried green tea in 100 ml water at 80° C for 10 minutes. The extract was filtered and then mixed with 2 g chitosan acidified with 0.7% glacial acetic acid and dilute to the mark with distilled water. Were identified bioactive compounds from green tea, using UV-VIS and HPLC. Then were elaborated the labels. These tags were used on pepper, tomato, apple and nectarine. Were quantified the microbial load and the pesticide residues on their surface unwashed, washed only with water and were monitored the influence of labels on these factors. Identified pesticides were mefenoxan and thiamethoxam, which were quantified by HPLC. In what it concerns the influence, were founded the absence of germs at pepper and a significant decrease at the other. In terms of the potential of reducing pesticide, the experimental results have indicated that the label can prove its effectiveness.

Abstract Background The well–known prebiotics are carbohydrates but their effects may not always be beneficial, as they can also encourage the growth of non-probiotic bacteria such as Eubacterium biforme and Clostridium perfringens. Therefore, new alternatives such as non-carbohydrate sources to stimulate the growth of probiotics are needed. The aim of this work was to evaluate (I) the green tea polyphenols by HPLC-LC/MS and (II) the protective effect of green tea extract on viability and stability of B. infantis ATCC 15697 and B. breve ATCC 15700 microencapsulated in chitosan coated alginate microcapsules during exposure to simulated gastrointestinal conditions and refrigerated storage. Results The major compound identified by HPLC-LC/MS in green tea was epigallocatechin gallate followed by caffeine and epigallocatechin. The survival yield of probiotic bacteria in microcapsules with 10% GT during storage at 4°C, demonstrated significantly (P B.infantis and B. breve with 5% and 10% GT showed a significantly (P Conclusions The results of this study suggest that green tea coencapsulated with B. infantis or B. breve exert a protective effect of bacteria during exposure to gastrointestinal conditions and refrigerated storage. For a health perspective, the results confirm the growing interest probiotic bacteria and the perceived benefit of increasing their numbers in the gastrointestinal tract by microencapsulation.

Background: Pregnancy induces significant physiological and metabolic changes in the mother to support fetal growth and prepare for childbirth. These adaptations impact various systems, including immune tolerance, metabolism, and endocrine function. While metabolomics has been utilized to study pregnancy-related metabolic changes, comprehensive comparisons between pregnant and non-pregnant states, particularly using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS), remain limited., Methods: This study aimed to explore the dynamic, longitudinal metabolic shifts during pregnancy by profiling plasma samples from 65 pregnant women across three time points (6-14 weeks, 14-22 weeks, and >24 weeks) and 42 postpartum women. Lipidomics was prioritized, and a solvent mixture was employed to enhance lipid extraction, using UHPLC-QTOF-ESI + -MS., Results: A total of 290 metabolites were identified and analyzed. Our results revealed significant metabolic differences between pregnant and postpartum women, with lipid molecules such as estrogen derivatives, fatty acids, and ceramides showing strong potential as biomarkers. Further biomarker analysis highlighted distinct metabolic signatures between early and late pregnancy stages, particularly in lipid metabolism (with AUC values > 0.8)., Conclusions: These findings contribute to a deeper understanding of pregnancy-related metabolic changes and may offer insights into maternal and neonatal health outcomes.

Background and Aim: Tacrolimus, a widely used immunosuppressive drug in kidney transplant recipients, exhibits a narrow therapeutic window necessitating careful monitoring of its concentration to balance efficacy and minimize dose-related toxic effects. Although essential, this approach is not optimal, and tacrolinemia, even in the therapeutic interval, might be associated with toxicity and rejection within range. This study aimed to identify specific urinary metabolites associated with tacrolimus levels in kidney transplant patients using a combination of serum high-precision liquid chromatography-mass spectrometry (HPLC-MS) and machine learning algorithms., Methods: A cohort of 42 kidney transplant patients, comprising 19 individuals with high tacrolimus levels (>8 ng/mL) and 23 individuals with low tacrolimus levels (<5 ng/mL), were included in the analysis. Urinary samples were subjected to HPLC-MS analysis, enabling comprehensive metabolite profiling across the study cohort. Additionally, tacrolimus concentrations were quantified using established clinical assays., Results: Through an extensive analysis of the HPLC-MS data, a panel of five metabolites were identified that exhibited a significant correlation with tacrolimus levels (Valeryl carnitine, Glycyl-tyrosine, Adrenosterone, LPC 18:3 and 6-methylprednisolone). Machine learning algorithms were then employed to develop a predictive model utilizing the identified metabolites as features. The logistic regression model achieved an area under the curve of 0.810, indicating good discriminatory power and classification accuracy of 0.690., Conclusions: This study demonstrates the potential of integrating HPLC-MS metabolomics with machine learning algorithms to identify urinary metabolites associated with tacrolimus levels. The identified metabolites are promising biomarkers for monitoring tacrolimus therapy, aiding in dose optimization and personalized treatment approaches.