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Background and ObjectivesPatients undergoing breast cancer surgery frequently experience chronic postoperative pain. The primary objective of this randomized study was to determine if thoracic paravertebral block (TPVB) reduced the incidence of chronic pain after a modified radical mastectomy (MRM) when compared with general anesthesia (GA).MethodsOne hundred eighty women undergoing MRM were randomized to 1 of 3 study groups: group 1: standardized GA, group 2: GA with a single-injection TPVB and placebo paravertebral infusion, and group 3: GA with a continuous TPVB. Outcomes assessed postoperatively included acute postoperative pain and analgesic consumption and, at 3 and 6 months, the incidence and severity of chronic pain and physical and mental health-related quality of life (HRQOL).ResultsThere was no significant difference in the incidence of chronic pain at 3 months (P = 0.13) and 6 months (P = 0.79) after the MRM between the study groups. The relative risk of developing chronic pain (P = 0.25) was also similar between the groups. There was no difference in acute pain (P = 0.22) or postoperative analgesic consumption (P = 0.67) between the groups. Nevertheless, differences were observed in chronic pain–related secondary outcome variables. The TPVB groups reported lower chronic pain scores (P < 0.05), exhibited fewer symptoms and signs of chronic pain (P ⩽ 0.01), and also experienced better physical and mental HRQOL than did the GA group. Chronic pain scores also decreased with time in all study groups (P < 0.05).ConclusionsThere is no significant difference in the incidence or relative risk of chronic pain at 3 and 6 months after an MRM when TPVB is used in conjunction with GA. Nevertheless, patients who receive a TPVB report less severe chronic pain, exhibit fewer symptoms and signs of chronic pain, and also experience better physical and mental HRQOL.

A rapid, sensitive and selective analysis method using Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) has been developed for the quantification of polyphenols in rosé wines. The compound detection being based on specific MS transitions in Multiple Reaction Monitoring (MRM) mode, the present method allows the selective quantification of up to 152 phenolic and two additional non-phenolic wine compounds in 30 min without sample purification or pre-concentration, even at low concentration levels. This method was repeatably applied to a set of 12 rosé wines and thus proved to be suitable for high-throughput and large-scale metabolomics studies.

Background: Pancreatic carcinoma (PC) is an aggressive malignancy that lacks strategies for early detection. This study aimed to develop a coherent, high-throughput and non-discriminatory pipeline for the novel clinical biomarker discovery of PC. Methods: We combined mass spectrometry (MS)-intensive methods such as isobaric tags for relative and absolute quantitation with two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS), 1D-targeted LC-MS/MS, prime MRM (P-MRM) and stable isotope dilution-based MRM (SID-MRM) to analyse serum samples from healthy people (normal control, NC), patients with benign diseases (BD) and PC patients to identify novel biomarkers of PC. Results: On the basis of the newly developed pipeline, we identified >1000 proteins, verified 142 differentially expressed proteins and finally targeted four proteins for absolute quantitation in 100 serum samples. The novel biomarker panel of apolipoprotein E (APOE), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), apolipoprotein A-I (APOA1), apolipoprotein L1 (APOL1), combining with CA19-9, statistically-significantly improved the sensitivity (95%) and specificity (94.1%), outperforming CA19-9 alone, for the diagnosis of PC. Conclusions: We developed a highly efficient pipeline for biomarker discovery, verification and validation, with each step systematically informing the next. A panel of proteins that might be clinically relevant biomarkers for PC was found.

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

Abstract Background Conventional HER2-targeting therapies improve outcomes for patients with HER2-positive breast cancer (BC), defined as tumors showing HER2 protein overexpression by immunohistochemistry and/or ERBB2 gene amplification determined by in situ hybridization (ISH). Emerging HER2-targeting compounds show benefit in some patients with neither HER2 protein overexpression nor ERBB2 gene amplification, creating a need for new assays to select HER2-low tumors for treatment with these compounds. We evaluated the analytical performance of a targeted mass spectrometry-based assay for quantifying HER2 protein in formalin-fixed paraffin-embedded (FFPE) and frozen BC biopsies. Methods We used immunoaffinity-enrichment coupled to multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) to quantify HER2 protein (as peptide GLQSLPTHDPSPLQR) in 96 frozen and 119 FFPE BC biopsies. We characterized linearity, lower limit of quantification (LLOQ), and intra- and inter-day variation of the assay in frozen and FFPE tissue matrices. We determined concordance between HER2 immuno-MRM-MS and predicate immunohistochemistry and ISH assays and examined the benefit of multiplexing the assay to include proteins expressed in tumor subcompartments (e.g., stroma, adipose, lymphocytes, epithelium) to account for tissue heterogeneity. Results HER2 immuno-MRM-MS assay linearity was ≥103, assay coefficient of variation was 7.8% (FFPE) and 5.9% (frozen) for spiked-in analyte, and 7.7% (FFPE) and 7.9% (frozen) for endogenous measurements. Immuno-MRM-MS-based HER2 measurements strongly correlated with predicate assay HER2 determinations, and concordance was improved by normalizing to glyceraldehyde-3-phosphate dehydrogenase. HER2 was quantified above the LLOQ in all tumors. Conclusions Immuno-MRM-MS can be used to quantify HER2 in FFPE and frozen BC biopsies, even at low HER2 expression levels.

Systems biology relies on data sets in which the same group of proteins is consistently identified and precisely quantified across multiple samples, a requirement that is only partially achieved by current proteomics approaches. Selected reaction monitoring (SRM)—also called multiple reaction monitoring—is emerging as a technology that ideally complements the discovery capabilities of shotgun strategies by its unique potential for reliable quantification of analytes of low abundance in complex mixtures. In an SRM experiment, a predefined precursor ion and one of its fragments are selected by the two mass filters of a triple quadrupole instrument and monitored over time for precise quantification. A series of transitions (precursor/fragment ion pairs) in combination with the retention time of the targeted peptide can constitute a definitive assay. Typically, a large number of peptides are quantified during a single LC‐MS experiment. This tutorial explains the application of SRM for quantitative proteomics, including the selection of proteotypic peptides and the optimization and validation of transitions. Furthermore, normalization and various factors affecting sensitivity and accuracy are discussed.

Red cabbage (Brassica oleracea L. var. capitata) continues to receive increasing attention on its health-promoting properties because of its high glucosinolate content. Glucosinolates are an unstable active substance; however, there are few studies on their changes in different cooking processes. In this study, we investigated the effects of processing methods (boiling, steaming, microwave heating, frying, stir-frying) and boiling time on glucosinolates in red cabbage. Ten glucosinolates, including 4-methoxyglucobrassicin, neoglucobrassicin, glucoalyssin, glucobrassicin, glucoraphanin, glucoiberin, progoitrin, gluconapin and sinigrin, in red cabbage were detected. Decreases of 32.36%, 24.83%, 25.27%, 81.11% and 84.29% for total glucosinolates were observed after boiling, microwaving, steaming, frying and stir-frying. Indole glucosinolates were more efficiently lost compared to aliphatic glucosinolates after boiling, while microwaving, steaming, frying and stir-frying also resulted in a greater reduction in indole glucosinolates than aliphatic glucosinolates. Glucoalyssin, glucoerucin and sinigrin were more thermal sensitive than other glucosinolates. It was confirmed that microwaving and steaming retained higher levels of glucosinolates than other methods and may be better for cooking red cabbage.

The color of rosé wines is extremely diverse and a key element in their marketing. It is due to the presence of anthocyanins and of additional pigments derived from them and from other wine constituents. To explore the pigment composition and determine its links with color, 268 commercial rosé wines were analysed. The concentration of 125 polyphenolic compounds was determined by a targeted metabolomics approach using ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode and the color characterised by spectrophotometry and CieLab parameters. Chemometrics analysis of the composition and color data showed that although color intensity is primarily determined by polyphenol extraction (especially anthocyanins and flavanols) from the grapes, different color styles correspond to different pigment compositions. The salmon shade of light rosé wines is mostly due to pyranoanthocyanin pigments, resulting from reactions of anthocyanins with phenolic acids and pyruvic acid, a yeast metabolite. Redness of intermediate color wines is related to anthocyanins and carboxypoyranoanthocyanins and that of dark rosé wines to products of anthocyanin reactions with flavanols while yellowness of these wines is associated to oxidation.

Multiple reaction monitoring (MRM)-based targeted metabolomics can simultaneously analyze up to hundreds of metabolites with high-throughput, good reproducibility, and wide dynamic range. However, when hundreds or thousands of MRM transitions are measured with tens to hundreds of biological samples, the complexity of MRM dataset acquired is no longer amenable to manual evaluation, and presents a challenge for targeted metabolomics. Here, we developed an R package, namely MRMAnalyzer, to process large set of MRM-based targeted metabolomics data automatically without any manual intervention. To demonstrate our MRMAnalyzer program, we first developed a targeted metabolomic method that simultaneously analyzes 182 metabolites in one 15-min LC run, and demonstrated the data processing procedures using MRMAnalyzer. The data processing steps include “pseudo” accurate m/z transformation, peak detection and alignment, metabolite identification, quality control check and statistical analysis. Finally, a targeted metabolomic assay was designed and integrated with MRMAnalyzer to profile the metabolic changes in Escherichia coli subjected to the protein expression. The generated MRM dataset consisting of more than 8000 MRM transitions were readily processed using MRMAnalyzer within 20 min without any manual intervention. Fourty seven out of 140 detected metabolites, enriched in six metabolic pathways, were found significantly affected in E. coli metabolome. In summary, a targeted metabolomic platform is developed for high-throughput metabolite profiling and automated data processing, and the MRMAnalyzer program is a high efficient informatics tool for large scale targeted metabolomics.

Starchy tubers of Solanum tuberosum are a staple crop and food in many countries. Among cultivated potato varieties a huge biodiversity exists, including an increasing number of red and purple colored cultivars. This coloration relates to the accumulation of anthocyanins and is supposed to offer nutritional benefits possibly associated with the antioxidative capacity of anthocyanins. However, the anthocyanin composition and its relation to the overall polyphenol constitution in colored potato tubers have not been investigated closely. This study focuses on the phytochemical characterization of the phenolic composition of a variety of colored potato tubers, both for peel and flesh tissues. First, liquid chromatography (LC) separation coupled to UV and mass spectrometry (MS) detection of polyphenolic compounds of potato tubers from 57 cultivars was used to assign groups of potato cultivars differing in their anthocyanin and polyphenol profiles. Tissues from 19 selected cultivars were then analyzed by LC separation coupled to multiple reaction monitoring (MRM) to detect quantitative differences in anthocyanin and polyphenol composition. The measured intensities of 21 anthocyanins present in the analyzed potato cultivars and tissues could be correlated with the specific tuber coloration. Besides secondary metabolites well-known for potato tubers, the metabolic profiling led to the detection of two anthocyanins not described for potato tuber previously, which we tentatively annotated as pelargonidin feruloyl-xylosyl-glucosyl-galactoside and cyanidin 3-p-coumaroylrutinoside-5-glucoside. We detected significant correlations between some of the measured metabolites, as for example the negative correlation between the main anthocyanins of red and blue potato cultivars. Mainly hydroxylation and methylation patterns of the B-ring of dihydroflavonols, leading to the formation of specific anthocyanidin backbones, can be assigned to a distinct coloring of the potato cultivars and tuber tissues. However, basically the same glycosylation and acylation reactions occur regardless of the main anthocyanidin precursor present in the respective red and blue/purple tissue. Thus, the different anthocyanin profiles in red and blue potato cultivars likely relate to superior regulation of the expression and activities of hydroxylases and methyltransferases rather than to differences for downstream glycosyl-and acyltransferases. In this regard, the characterized potato cultivars represent a valuable resource for the molecular analysis of the genetic background and the regulation of anthocyanin side chain modification.