Schizophrenia is a widespread mental disorder that leads to significant functional impairments and premature death. The state of the art indicates gaps in the understanding and diagnosis of this disease, but also the need for personalized and precise approaches to patients through customized medical treatment and reliable monitoring of treatment response. In order to fulfill existing gaps, the establishment of a universal set of disorder biomarkers is a necessary step. Metabolomic investigations of serum samples of Serbian patients with schizophrenia (51) and healthy controls (39), based on NMR analyses associated with chemometrics, led to the identification of 26 metabolites/biomarkers for this disorder. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models with prediction accuracies of 0.9718 and higher were accomplished during chemometric analysis. The established biomarker set includes aspartate/aspartic acid, lysine, 2-hydroxybutyric acid, and acylglycerols, which are identified for the first time in schizophrenia serum samples by NMR experiments. The other 22 identified metabolites in the Serbian samples are in accordance with the previously established NMR-based serum biomarker sets of Brazilian and/or Chinese patient samples. Thirteen metabolites (lactate/lactic acid, threonine, leucine, isoleucine, valine, glutamine, asparagine, alanine, gamma-aminobutyric acid, choline, glucose, glycine and tyrosine) that are common for three different ethnic and geographic origins (Serbia, Brazil and China) could be a good start point for the setup of a universal NMR serum biomarker set for schizophrenia.
We give a survey of graph spectral techniques used in computer sciences. The survey consists of a description of particular topics from the theory of graph spectra independently of the areas of Computer science in which they are used. We have described the applications of some important graph eigenvalues (spectral radius, algebraic connectivity, the least eigenvalue etc.), eigenvectors (principal eigenvector, Fiedler eigenvector and other), spectral reconstruction problems, spectra of random graphs, Hoffman polynomial, integral graphs etc. However, for each described spectral technique we indicate the fields in which it is used (e.g. in modelling and searching Internet, in computer vision, pattern recognition, data mining, multiprocessor systems, statistical databases, and in several other areas). We present some novel mathematical results (related to clustering and the Hoffman polynomial) as well.
Marrubium vulgare is a cosmopolitan medicinal plant from the Lamiaceae family, which produces structurally highly diverse groups of secondary metabolites. A total of 160 compounds were determined in the volatiles from Serbia during two investigated years (2019 and 2020). The main components were E-caryophyllene, followed by germacrene D, α-humulene and α-copaene. All these compounds are from sesquiterpene hydrocarbons class which was dominant in both investigated years. This variation in volatiles composition could be a consequence of weather conditions, as in the case of other aromatic plants. According to the unrooted cluster tree with 37 samples of Marrubium sp. volatiles from literature and average values from this study, it could be said that there are several chemotypes: E-caryophyllene, β-bisabolene, α-pinene, β-farnesene, E-caryophyllene + caryophyllene oxide chemotype, and diverse (unclassified) chemotypes. However, occurring polymorphism could be consequence of adaptation to grow in different environment, especially ecological conditions such as humidity, temperature and altitude, as well as hybridization strongly affected the chemotypes. In addition, this paper aimed to obtain validated models for prediction of retention indices (RIs) of compounds isolated from M. vulgare volatiles. A total of 160 experimentally obtained RIs of volatile compounds was used to build the prediction models. The coefficients of determination were 0.956 and 0.964, demonstrating that these models could be used for predicting RIs, due to low prediction error and high r2.
Essential oil (EO) obtained by hydrodistillation in a Clevenger-type apparatus from aerial parts of Nepeta cataria L. var. citriodora (Becker), cultivated in Serbia was subjected to gas chromatography-mass spectroscopy (GC-MS) to determine the composition. Furthermore, N. cataria var. citriodora essential oil wastested to determine its antimicrobial, antioxidant, antihyperglycemic and anti-inflammatory activities in vitro.The antimicrobial activity was tested by broth microdilution method against 16 bacterial strains from American Type Culture Collection (ATCC). Four common tests for measuring in vitro antioxidant activity were used: 2, 2-diphenyl-1-picrylhydrazyl assay (DPPH), reducing power (RP), 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and β-carotene bleaching assay (BCB). Antihyperglycemic activity was examined by using α-glucosidase inhibitory potential (AHgA), while anti-inflammatory activity (AIA) was determined by protein denaturation bioassay, using egg albumin. In total, 36 compounds were isolated and detected by GC-MS technique in N. cataria var. citriodora EO. The EO is mainly comprised of oxygenated monoterpenes (93.1%), and the main compounds were two monoterpenoid alcohols, nerol (38.5%) and geraniol (24.9%), followed by two aliphatic aldehyde, geranial (14.6%) and neral (11.0%). Antimicrobial activity of this EO shows growth inhibition of all tested bacteria strains, and exhibited good antioxidant, antihyperglycemic and anti-inflammatory activities. The EO obtained from N. cataria var. citriodora grown in Serbia shows valuable biological activity, indicating its potential for use as a supplement in everyday diet and as a natural preservative in food industry.
Plum brandy (Slivovitz (en); Šljivovica(sr)) is an alcoholic beverage that is increasingly consumed all over the world. Its quality assessment has become of great importance. In our study, the main volatiles and aroma compounds of 108 non-aged plum brandies originating from three plum cultivars, and fermented using different conditions, were investigated. The chemical profiles obtained after two-step GC-FID-MS analysis were subjected to multivariate data analysis to reveal the peculiarity in different cultivars and fermentation process. Correlation of plum brandy chemical composition with its sensory characteristics obtained by expert commission was also performed. The utilization of PCA and OPLS-DA multivariate analysis methods on GC-FID-MS, enabled discrimination of brandy samples based on differences in plum varieties, pH of plum mash, and addition of selected yeast or enzymes during fermentation. The correlation of brandy GC-FID-MS profiles with their sensory properties was achieved by OPLS multivariate analysis. Proposed workflow confirmed the potential of GC-FID-MS in combination with multivariate data analysis that can be applied to assess the plum brandy quality.
Let C(2m, k) be the set of all cactuses on 2m vertices, k cycles, and with perfect matchings. In this paper, we identify in C(2m, k) the unique graph with the largest spectral radius.2000 Mathematics Subject Classification. 05C50.
Introduction Ramonda serbica and R. nathaliae are resurrection plants that have the remarkable ability to survive the complete desiccation of their vegetative organs (i.e. leaves, stem, roots) during periods of drought and rapidly revive when rewatered and rehydrated. Objective To investigate metabolic changes in R. serbica and R. nathaliae during their desiccation and recovery process Methods Proton nuclear magnetic resonance (1H‐NMR) and gas chromatography–mass spectrometry (GC–MS)‐based metabolomics approach coupled with multivariate data analysis was utilised to identify the metabolomes of the plants from 90 biological replicates. Results Sucrose and the polyphenolic glycoside myconoside were predominant in almost equal amounts in all samples studied, regardless of their water content at sampling. During the dehydration process, a decrease in the relative content of fructose, galactose, and galactinol was observed while the contents of those metabolites were preserved in the partially rehydrated plants. Raffinose and myo‐inositol were accumulated in dry samples. Conclusion Using 1H‐NMR and GC–MS as two complementary analytical platforms provided a more complete picture of the metabolite composition for investigation of the desiccation and recovery process in resurrection plants.
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