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Redox disbalance in placental cells leads to the hyperproduction of reactive oxygen species (ROS), it mediates the dysregulation of the maternal immune tolerance to a semi-allogenic fetus, inducing pro-inflammatory reactions, and it plays a central role in perinatal complications and neonatal disease programming. Microvesicles, which provide transplacental communication between a mother and fetus, contain microRNAs (miRNAs) that are sensitive to oxidative stress (OS) mediators and can control the balance of ROS production and utilization in target cells. In the context of this paradigm, we evaluated the markers of redox balance—MDA and 4-HNE for OS and GPx, and SOD, CAT, and GSH for the antioxidant system in the cord blood plasma of newborns diagnosed with fetal growth restriction (FGR)—by using polarography, spectrophotometry, and Western blotting. The expression of miRNAs associated with OS, immune and inflammatory responses in the blood plasma of newborns with intrauterine pneumonia (IP), neonatal sepsis (NS) and respiratory distress syndrome (RDS) was evaluated by a quantitative RT-PCR. Significant differences in the MDA level and reduced GPx and CAT activity were co-found for early-onset FGR (i.e., <34 gestational age). Significant correlations were found with a low birth weight by Apgar scores with reduced levels of antioxidant enzymes. Indeed, the level of OS markers increased in early-onset FGR in newborns with an extremely low body weight and high echogenicity of the periventricular zones, and reduced in late-onset FGR in newborns with IP, hyperbilirubinemia, intraventricular hemorrhage (IVH) and cerebral cysts. A prognostic model (AUC = 1; cutoff—0.5) was developed to assess the risk of IVH in newborns diagnosed with FGR based on the assessment of the OS markers (i.e., MDA + 4 HNE + CAT + GSH). A significant increase in the miR-127-3p expression was found in the plasma of newborns with NS (<32 GA; p ≤ 0.03 and >32 GA; p ≤ 0.009), IP (>32 GA; p ≤ 0.0001), and RDS (>32 GA; p ≤ 0.03). At the same time, the expression of miR-25-3p (p ≤ 0.03) was increased only in newborns with NS (>32 GA; p ≤ 0.03). The risk of developing IVH for premature newborns with IP (AUC = 0.8; cutoff—0.6) and NS (AUC = 0.68; cutoff—0.49) was assessed based on the miR-25-3p and miR-127-3p expression. Several key transcription factors were identified as the targets of studied miRNA since they are involved in the regulation of OS (NRF2), signaling and activation of the immune response (PRDM1, CCL26) and, also, inflammatory responses (NFKB1). The study of these miRNAs showed that they are involved in the modulation of processes leading to perinatal complications. Moreover, miR-127-3p is related to pro-inflammatory reactions and the formation of the macrophage phenotype in newborns with IP, NS, and RDS, while miR-25-3p is associated with an inhibition of macrophage migration and activation of antioxidant enzymes, which may prevent the development of oxidative damage in newborns with NS. [ABSTRACT FROM AUTHOR]

Knowledge about the chemical composition of floral volatile organic compounds (VOCs) is valuable in biological studies as well as for the flavor, cosmetic, and fragrance industries. The flowers of Chinese chestnut (Castanea mollissima) emit a distinctive semen-like odor; however, the chemical composition and biological role for the semen-like odor of chestnut flowers remain scarcely studied. Herein, we report the floral VOCs and the pollinators of chestnut flowers. A fast method based on a neutral desorption (ND) device coupled to extractive atmospheric pressure chemical ionization mass spectrometry (EAPCI-MS) was developed for the rapid identification of VOCs from freshly collected chestnut flowers without any chemical pretreatment. Chemical identification was performed using high-resolution MS analysis in combination with tandem MS analysis and whenever possible was confirmed by the analysis of standard reference compounds. Twenty volatiles were identified, most of which are nitrogen-containing. Out of the identified volatiles, 1-pyrroline is known to have a semen-like odor and is probably also responsible for the semen-like odor of the chestnut flowers. Four nitrogenous VOCs of chestnut flowers, including 1-pyrroline, 1-piperideine, 2-pyrrolidone, and phenethylamine, were also common in other semen-like odor flowers such as Photinia serrulata, Castanopsis sclerophylla, and Stemona japonica, suggesting similar chemical origin. The main visitors of chestnut flowers were dipteran species, such as Eristalis tenax, Eristalis arvorum, Episyrphus balteatus, Lucilia sericata, Chrysomya megacephala, Chrysochus asclepiadeus, and Adalia bipunctata. Our results suggest that the chestnut flowers and other semen-like odor flowers may present a new type of sapromyophily. This study also indicates that ND-EAPCI-MS provides more sensitive and simpler detection of many VOCs (particularly nitrogen-containing VOCs) than GC-MS and therefore can be used to complement traditional approaches for the higher chemical coverage of VOCs analysis. [ABSTRACT FROM AUTHOR]

The mass spectrometry‐based molecular profiling can be used for better differentiation between normal and cancer tissues and for the detection of neoplastic transformation, which is of great importance for diagnostics of a pathology, prognosis of its evolution trend, and development of a treatment strategy. The aim of the present study is the evaluation of tissue classification approaches based on various data sets derived from the molecular profile of the organic solvent extracts of a tissue. A set of possibilities are considered for the orthogonal projections to latent structures discriminant analysis: all mass spectrometric peaks over 300 counts threshold, subset of peaks selected by ranking with support vector machine algorithm, peaks selected by random forest algorithm, peaks with the statistically significant difference of the intensity determined by the Mann‐Whitney U test, peaks identified as lipids, and both identified and significantly different peaks. The best predictive potential is obtained for OPLS‐DA model built on nonpolar glycerolipids (Q2 = 0.64, area under curve [AUC] = 0.95); the second one is OPLS‐DA model with lipid peaks selected by random forest algorithm (Q2 = 0.58, AUC = 0.87). Moreover, models based on particular molecular classes are more preferable from biological point of view, resulting in new explanatory mechanisms of pathophysiology and providing a pathway analysis. Another promising features for OPLS‐DA modeling are phosphatidylethanolamines (Q2 = 0.48, AUC = 0.86). [ABSTRACT FROM AUTHOR]

Urine is a sample of choice for noninvasive biomarkers search because it is easily available in large amounts and its molecular composition provides information on processes in the organism. The high potential of urine peptidomics has been demonstrated for clinical purpose. Several mass spectrometry based approaches have been successfully applied for urine peptidome analysis and potential biomarkers search. Summarizing literature data and our own experience we developed a protocol for comprehensive urine peptidome analysis. The technology includes several stages and consists of urine sample preparation by size exclusion chromatography and identification of featured peptides by nano-HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry, semiquantitative and statistical data analysis.