Mass filtering combined with photochemical derivatization enables high throughput mass spectrometric analysis of unsaturated phosphatidylcholine isomers.

Phosphatidylcholines (PCs) are closely related to coronary heart disease, such as myocardial infarction. The analysis of the deep structure of PCs is of great significance for exploring the effects of exercise rehabilitation and lipid metabolism. Here, we present a mass filtering combined with photochemical derivatization method for rapid screening and accurate identification of the CC position and sn-location isomer of PCs. This method is simple to execute and easily implementable for routine analysis. The accurate qualitative and quantitative analysis of PCs and isomers facilitates the discovery of biomarkers for exercise rehabilitation of patients with myocardial infarction.

Engineering an Antifouling Electrochemical Sensing Platform Based on an All-in-One Peptide and a Hierarchical ß-Bi2O3-Au Microsphere for Vancomycin Detection in Food.

Challenges associated with interference aroused by nonspecific attachment of foulants in the food matrix steered the development of sensor surfaces capable of antifouling capacity. In this study, an antifouling electrochemical sensing platform based on an all-in-one peptide (DOPA3-PPPPEKDQDKKaa) with anchoring, antifouling, and recognition functions and a hierarchical ß-Bi2O3-Au microsphere was proposed for vancomycin (Van) detection in food. The ß-Bi2O3-Au with excellent conductivity was synthesized and introduced as an electrode modifier to accelerate electron transfer on the sensor surface, enhancing sensing response. Mussel organism-inspired oligo DOPA, that is, oligo 3,4-dihydroxyphenylalanine, was employed as the anchoring segment of the all-in-one peptide, which is versatile for surfaces with different materials. PPPPEKDQDK and Kaa as antifouling and recognition segments confer abilities to resist nonspecific adsorption of foulants and specifically bind Van on the sensor surface, respectively. Notably, the excellent antifouling performance of the proposed sensor has been verified in protein solutions, carbohydrate solutions, and even in diluted milk and honey. Molecular dynamics simulation was carried out to explain the antifouling mechanism of the all-in-one peptide. The proposed sensor can detect Van sensitively and selectively with a relatively wide linear range (0.1-100 ng mL-1) and a limit of detection (LOD) as low as 0.038 ng mL-1 and support the quantification of Van in milk, milk powder, and honey samples with satisfactory recoveries within 105.3-110.8%. This antifouling electrochemical sensing platform offers a feasible strategy to reduce matrix interference, which guarantees the accurate detection of Van in food samples.

Nontargeted screening of aldehydes and ketones by chemical isotope labeling combined with ultra-high performance liquid chromatography-high resolution mass spectrometry followed by hybrid filtering of features.

Aldehydes and ketones are important carbonyl compounds that are widely present in foodstuffs, biological organisms and human living environment. However, it is still challenging to comprehensively detect and capture them using liquid chromatography - mass spectrometry. In this work, a chemical isotope labeling (CIL) coupled with ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC-HRMS) strategy was developed for the capture and detection of this class of compounds. 2,4-Dinitrophenylhydrazine (DNPH) and isotope-labeled DNPH (DNPH-d3) were utilized to selectively label the target analytes. To address the difficulties in processing UHPLC-HRMS data, a post-acquisition data processing method called MSFilter was proposed to facilitate the screening and identification aldehydes and ketones in complex matrices. The MSFilter consists of four independent filters, namely statistical characteristic-based filtering, mass defect filtering, CIL paired peaks filtering, and diagnostic fragmentation ion filtering. These filters can be used individually or in combination to eliminate unrelated interfering MS features and efficiently detect DNPH-labeled aldehydes and ketones. The results of a mixture containing 48 model compounds showed that although all individual filtering methods could significantly reduce more than 95% of the raw MS features with acceptable recall rates above 85%, but they had relatively high false positive ratios of over 90%. In comparison, the hybrid filtering method combining four filters is able to eliminate massive interfering features (> 99.5%) with a high recall rate of 81.25% and a much lower false positive ratio of 15.22%. By implementing the hybrid filtering method in MSFilter, a total of 154 features were identified as potential signals of CCs from the original 45,961 features of real tobacco samples, of which 70 were annotated. We believe that the proposed strategy is promising to analyze the potential CCs in complex samples by UHPLC-HRMS.

Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and odor activity value (OAV) to reveal the flavor characteristics of ripened Pu-erh tea by co-fermentation.

Introduction: Pu-erh tea is a geographical indication product of China. The characteristic flavor compounds produced during the fermentation of ripened Pu-erh tea have an important impact on its quality. Methods: Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and odor activity value (OAV) is used for flavor analysis. Results: A total of 135 volatile compounds were annotated, of which the highest content was alcohols (54.26%), followed by esters (16.73%), and methoxybenzenes (12.69%). Alcohols in ripened Pu-erh tea mainly contribute flower and fruit sweet flavors, while methoxybenzenes mainly contribute musty and stale flavors. The ripened Pu-erh tea fermented by Saccharomyces: Rhizopus: Aspergillus niger mixed in the ratio of 1:1:1 presented the remarkable flavor characteristics of flower and fruit sweet flavor, and having better coordination with musty and stale flavor. Discussion: This study demonstrated the content changes of ripened Pu-erh tea's flavor compounds in the fermentation process, and revealed the optimal fermentation time. This will be helpful to further understand the formation mechanism of the characteristic flavor of ripened Pu-erh tea and guide the optimization of the fermentation process of ripened Pu-erh tea.

[Comprehensive analysis of chemical constituents of tea flowers by ultra-performance liquid chromatography-high resolution mass spectrometry combined with integrated filtering strategy].

Tea flowers and fresh tea leaves are biological products of tea, but tea flower is often regarded as waste during tea production, resulting in notable waste of tea flower resources. At present, analysis of the chemical components in tea flowers focuses on single types of chemical components such as amino acids and tea polyphenols, and there are only a few reports on the simultaneous analysis of numerous chemical components in tea flowers. Researchers are not completely clear about the types and amounts of the chemical components in tea flowers; this has hindered the in-depth development and effective utilization of tea flowers. In this study, ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was used to detect the chemical constituents of tea flowers. This technique was combined with the integrated filtering strategy (IFS) of nitrogen rule filtering (NRF), mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) for screening the characteristic mass spectra of the target chemical components. Furthermore, the chemical constituents of tea flowers were annotated with information about the retention time, MS fragmentation, and MS/MS fragmentation. All the qualitative chemical components were divided into six categories with a total of 137 chemical constituents, including 3 alkaloids, 38 flavonoids, 31 phenolic acids and their derivatives, 37 catechins and their derivatives, 18 amino acids, and 10 other components. The internal standard method was used to quantify all the qualitative chemical components. The quantitative results showed that the amounts of the six kinds of chemical components in tea flowers were as follows: amino acids, 9371.42 µg/g; catechins and their derivatives, 9068.43 µg/g; phenolic acids and their derivatives, 8696.92 µg/g; alkaloids, 4392.52 µg/g; flavonoids, 1192.88 µg/g; and others, 139.94 µg/g. Quality control samples were used to evaluate the stability of the instrument and the repeatability of the tested data. Nine representative chemical components with high, medium, and low contents in tea were selected, and the relative standard deviation (RSD) of the results was used to evaluate the repeatability of the data. These nine chemical constituents are selected from amino acids, alkaloids, flavonoids, phenolic acids and their derivatives, catechins and their derivatives, and other components, and the response intensities were different. The relative standard deviations of the nine chemical components were in the range of 2.11% to 12.17%. The above results demonstrated the good stability of the instrument and excellent repeatability of the test data. Chlorogenic acid components (CGAs) and glycosylated quercetin components (GQs) were used as two representative components to explain the entire process of extracting the target compounds by IFS. CGAs comprise a class of special esters formed by the esterification of cinnamic acid derivatives with quinic acid as the parent structure. The most common cinnamic acid derivatives are p-coumaric acid, caffeic acid, and ferulic acid. On the one hand, according to the above information and the different positions and degree of quinic acid esterification, the CGAs were structurally classified as monosubstituted CGAs (Mono-CGAs), disubstituted CGAs (Di-CGAs), and trisubstituted CGAs (Tri-CGAs), and three different mass defect filtering windows were set. Therefore, 751 possible target components were selected from 3537 mass spectra in accordance with the nitrogen rule. On the other hand, 22 target components in accordance with the nitrogen rule were obtained by further screening the m/z 191.0551 ion as the diagnostic fragment ion of the CGAs. Combining the overall analytical data with the above mass defect filtering and diagnostic fragment ion filtering screening results, nine target CGAs were selected and characterized based on the MS information. This study reveals the types and amounts of the chemical components accumulated in tea flowers, thus providing valuable information and serving as data reference for the in-depth development and effective utilization of tea flowers.

Stability and antioxidant capacity of epigallocatechin gallate in Dulbecco's modified eagle medium.

Though the instability of polyphenols in cell culture experiment has been investigated previously, the underlying mechanism is not completely clear yet. Therefore, in this study, the stability of epigallocatechin gallate (EGCG) in cell culture medium DMEM was investigated at 4 °C and 37 °C via UPLC-MS-MS analysis followed by determination of the antioxidant capacity of EGCG. EGCG was instable in DMEM and formed various degradation products derived from its dimer with increasing incubation time with many isomers being formed at both temperatures. The dimer products were more stable at 4 °C than at 37 °C. The structure and formation mechanism of five products were analyzed with four unidentified. Ascorbic acid significantly improved the stability of EGCG by protecting EGCG from auto-oxidation in DMEM, particularly at 4 °C. The antioxidative activity of EGCG in DMEM was determined by DPPH, ABTS and FRAP assay. The antioxidative properties of EGCG continuously decreased over 8 h in DMEM, which was consistent with its course of degradation.

Metabolic Profiling by UPLC-Orbitrap-MS/MS of Liver from C57BL/6 Mice with DSS-Induced Inflammatory Bowel Disease.

Liver disorder often occurs in patients with inflammatory bowel disease (IBD); however, the changes in IBD-induced liver disorder at the intrinsic molecular level (chiefly metabolites) and therapeutic targets are still poorly characterized. First, a refined and translationally relevant model of DSS chronic colitis in C57BL/6 mice was established, and cecropin A and antibiotics were used as interventions. We found that the levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6 in the liver tissues of mice were highly increased in the context of DSS treatment but were lowered by cecropin A and antibiotics. Subsequently, an untargeted metabolomics analysis was performed by UPLC-Orbitrap-MS/MS to reveal the metabolic profile and attempt to find the potential therapeutic targets of the liver disorders that occur in IBD. Notably, 133 metabolites were identified by an integrated database. Metabolism network and pathway analyses demonstrated that the metabolic disturbance of the liver in IBD mice was mainly enriched in bile acid metabolism, arachidonic acid metabolism, amino acid metabolism, and steroid hormone biosynthesis, while those disturbances were regulated or reversed through cecropin A and antibiotic treatment. Furthermore, the top 20 metabolites, such as glutathione, maltose, arachidonic acid, and thiamine, were screened as biomarkers via one-way analysis of variance (one-way ANOVA, p < 0.05) coupled with variable importance for project values (VIP >1) of orthogonal partial least-squares discriminant analysis (OPLS-DA), which could be upregulated or downregulated with the cecropin A and antibiotics treatment. Spearman correlation analysis showed that the majority of the biomarkers have a significant correlation with cytokines (TNF-α, IL-1ß, IL-6, and IL-10), indicating that those biomarkers may act as potential targets to interact directly or indirectly with cecropin A and antibiotics to affect liver inflammation. Collectively, our results extend the understanding of the molecular alteration of liver disorders occurring in IBD and offer an opportunity for discovering potential therapeutic targets in the IBD process.

Establishment of a pattern recognition metabolomics model for the diagnosis of hepatocellular carcinoma.

BACKGROUND: Early diagnosis of hepatocellular carcinoma may help to ensure that patients have a chance for long-term survival; however, currently available biomarkers lack sensitivity and specificity. AIM: To characterize the serum metabolome of hepatocellular carcinoma in order to develop a new metabolomics diagnostic model and identifying novel biomarkers for screening hepatocellular carcinoma based on the pattern recognition method. METHODS: Ultra-performance liquid chromatography-mass spectroscopy was used to characterize the serum metabolome of hepatocellular carcinoma (n = 30) and cirrhosis (n = 29) patients, followed by sequential feature selection combined with linear discriminant analysis to process the multivariate data. RESULTS: The concentrations of most metabolites, including proline, were lower in patients with hepatocellular carcinoma, whereas the hydroxypurine levels were higher in these patients. As ordinary analysis models failed to discriminate hepatocellular carcinoma from cirrhosis, pattern recognition analysis was used to establish a pattern recognition model that included hydroxypurine and proline. The leave-one-out cross-validation accuracy and area under the receiver operating characteristic curve analysis were 95.00% and 0.90 [95% Confidence Interval (CI): 0.81-0.99] for the training set, respectively, and 78.95% and 0.84 (95%CI: 0.67-1.00) for the validation set, respectively. In contrast, for α-fetoprotein, the accuracy and area under the receiver operating characteristic curve were 65.00% and 0.69 (95%CI: 0.52-0.86) for the training set, respectively, and 68.42% and 0.68 (95%CI: 0.41-0.94) for the validation set, respectively. The Z test revealed that the area under the curve of the linear discriminant analysis model was significantly higher than the area under the curve of α-fetoprotein (P < 0.05) in both the training and validation sets. CONCLUSION: Hydroxypurine and proline might be novel biomarkers for hepatocellular carcinoma, and this disease could be diagnosed by the metabolomics model based on pattern recognition.

Chemical profiling and discrimination of green tea and Pu-erh raw tea based on UPLC-Q-Orbitrap-MS/MS and chemometrics.

To reveal the characteristic chemical profiles of Pu-erh raw tea (PRT) and traditional green tea (TGT), a high-throughput analytical method based on UPLC-Q-Orbitrap-MS/MS was proposed. 145 components were characterized with a three-level qualitative strategy and the integrated filtering strategy combining nitrogen rule, mass defect, and diagnostic ions information. 124 components were quantified using an internal standard method. The total contents of flavan-3-ols and derivatives, phenolic acids and derivatives were higher in PRT than TGT, while flavonoids were reversed. Furthermore, partial least squares-discriminant analysis (PLS-DA) models were established to classify TGT and PRT. 23 characteristic components were revealed by variable importance in projection method. Their difference in content is between 1.5 and 7.3 times for PRT and TGT. The results showed the chemical characteristics of TGT and PRT clearly and comprehensively. The high-throughput method demonstrated considerable potential in the analysis of complex chemical system, such as food and herbs.

Directed self-assembly of herbal small molecules into sustained release hydrogels for treating neural inflammation.

Self-assembling natural drug hydrogels formed without structural modification and able to act as carriers are of interest for biomedical applications. A lack of knowledge about natural drug gels limits there current application. Here, we report on rhein, a herbal natural product, which is directly self-assembled into hydrogels through noncovalent interactions. This hydrogel shows excellent stability, sustained release and reversible stimuli-responses. The hydrogel consists of a three-dimensional nanofiber network that prevents premature degradation. Moreover, it easily enters cells and binds to toll-like receptor 4. This enables rhein hydrogels to significantly dephosphorylate IκBα, inhibiting the nuclear translocation of p65 at the NFκB signalling pathway in lipopolysaccharide-induced BV2 microglia. Subsequently, rhein hydrogels alleviate neuroinflammation with a long-lasting effect and little cytotoxicity compared to the equivalent free-drug in vitro. This study highlights a direct self-assembly hydrogel from natural small molecule as a promising neuroinflammatory therapy.

Tuning model parameters in class-imbalanced learning with precision-recall curve.

An issue for class-imbalanced learning is what assessment metric should be employed. So far, precision-recall curve (PRC) as a metric is rarely used in practice as compared with its alternative of receiver operating characteristic (ROC). This study investigates the performance of PRC as the evaluating criterion to address the class-imbalanced data and focuses on the comparison of PRC with ROC. The advantages of PRC over ROC on assessing class-imbalanced data are also investigated and tested on our proposed algorithm by tuning the whole model parameters in simulation studies and real data examples. The result shows that PRC is competitive with ROC as performance measurement for handling class-imbalanced data in tuning the model parameters. PRC can be considered as an alternative but effective assessment for preprocessing (such as variable selection) skewed data and building a classifier in class-imbalanced learning.

Hepatoprotective effects of raspberry (Rubus coreanus Miq.) seed oil and its major constituents.

Raspberry seed is a massive byproduct of raspberry juice and wine but usually discarded. The present study employed a microwave-assisted method for extraction of raspberry seed oil (RSO). The results revealed that omega-6 fatty acids (linoleic acid and γ-linolenic acid) were the major constituents in RSO. Cellular antioxidant enzyme activity such as superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT) were investigated in HepG2 cells treated with RSO. Induction of the synthesis of several antioxidants in H2O2-exposed HepG2 cells was found. RSO increased the enzyme activity of SOD, CAT, and GPx in H2O2-exposed HepG2. Furthermore, RSO inhibited the phosphorylation of upstream mitogen-activated protein kinases (MAPK) such as c-Jun N-terminal kinase (c-JNK) and extracellular signal-regulated kinase (ERK). Taken together, the possible mechanisms to increase antioxidant enzyme activities in HepG2 may through the suppression of ERK and JNK phosphorylation. Raspberry seed oil exhibited good effects on the activities of the intracellular antioxidant enzymes and seems to protect the liver from oxidative stress through the inhibition of MAPKs.

Comprehensive characterization and identification of antioxidants in Folium Artemisiae Argyi using high-resolution tandem mass spectrometry.

Antioxidants from natural sources, such as vegetables and fruits, are attracting more and more interest. In this work, we evaluated the antioxidant potential of Folium Artemisia Argyi, a traditional Chinese herb medicine and food supplement. The total phenolic content, total flavonoid content, and antioxidant ability of the crude extracts and fractions obtained from consecutively partition of n-hexane, ethyl acetate, and n-butanol were measured and compared. Ethyl acetate fraction shows the highest total phenolic and flavonoid contents and highest antioxidant capability with regard to DPPH, ABTS, superoxide anion free radical scavenging ability, and ferric-reducing antioxidant power. In addition, the potential antioxidant components were screened by DPPH-UHPLC-MS experiments and subsequently characterized by using high-resolution tandem mass spectrometry. This work finally identified 45 antioxidants, including organic acids, phenolic compounds, flavonoids, and methoxylated flavonoids. The results suggested that Folium Artemisiae Argyi is a potential inexpensive resource of natural antioxidants.

Discrimination of Acori Tatarinowii Rhizoma and Acori Calami Rhizoma based on quantitative gas chromatographic fingerprints and chemometric methods.

This study was conducted to investigate the chemical differences between Acori Tatarinowii Rhizoma and Acori Calami Rhizoma using gas chromatography with mass spectrometry and chemometric methods. Quantitative fingerprints were established. A total of 90 volatile compounds were identified and quantified using heuristic evolving latent projection and retention index. An efficient model based on partial least squares-discriminant analysis coupled with variable iterative space shrinkage approach was developed to distinguish Acori Tatarinowii Rhizoma from Acori Calami Rhizoma. The correct rate was 95.83%, and the area under the receiver operating characteristic curve was 100%. Finally, three volatiles, namely, camphor, longicyclene, and δ-cadinene, were selected as key discrimination factors between Acori Tatarinowii Rhizoma and Acori Calami Rhizoma. The proposed protocol can serve as a valid strategy for quality control and screening of potential bioactive components of herbal medicines.

Exploring metabolic syndrome serum profiling based on gas chromatography mass spectrometry and random forest models.

Metabolic syndrome (MetS) is a constellation of the most dangerous heart attack risk factors: diabetes and raised fasting plasma glucose, abdominal obesity, high cholesterol and high blood pressure. Analysis and representation of the variances of metabolic profiles is urgently needed for early diagnosis and treatment of MetS. In current study, we proposed a metabolomics approach for analyzing MetS based on GC-MS profiling and random forest models. The serum samples from healthy controls and MetS patients were characterized by GC-MS. Then, random forest (RF) models were used to visually discriminate the serum changes in MetS based on these GC-MS profiles. Simultaneously, some informative metabolites or potential biomarkers were successfully discovered by means of variable importance ranking in random forest models. The metabolites such as 2-hydroxybutyric acid, inositol and d-glucose, were defined as potential biomarkers to diagnose the MetS. These results obtained by proposed method showed that the combining GC-MS profiling with random forest models was a useful approach to analyze metabolites variances and further screen the potential biomarkers for MetS diagnosis.

Identification of integrin ß1 as a prognostic biomarker for human lung adenocarcinoma using 2D-LC-MS/MS combined with iTRAQ technology.

To discover novel lung adenocarcinoma (AdC) biomarkers, isobaric tags for relative and absolute quantitation (iTRAQ)-tagging combined with 2D-LC-MS/MS analysis was used to identify differentially expressed plasma membrane proteins in lung AdC and paired paraneoplastic normal lung tissues (PNLTs) adjacent to tumors. In this study, significant caveolin-1 downregulation and integrin ß1 upregulation was observed in primary lung AdC vs. PNLT. As there has been no report on the association of integrin ß1 with lung AdC, immunohistochemical staining was performed to detect the expression of integrin ß1 in an independent set of archival tissue specimens including 42 cases of PLNT, 46 cases of without lymph node metastasis primary AdC (non-LNM AdC) and 62 cases of LNM AdC; the correlation of their expression levels with clinicopathological characteristics and clinical outcomes were evaluated. Based on the data, upregulation of integrin ß1 was significantly correlated with advanced clinical stage and lymph node metastasis. Integrin ß1 overexpression was significantly associated with advanced clinical stage (P<0.05), lymph node metastasis (P<0.05), increased relapse rate (P<0.05) and decreased overall survival (P<0.05) in AdCs. Cox regression analysis indicated that integrin ß1 overexpression is an independent prognostic factor. The data suggest that integrin ß1 is a potential biomarker for LNM and prognosis of AdC and integrin ß1 upregulation may play an important role in the pathogenesis of AdC.

Investigation of scrambled ions in tandem mass spectra, part 2. On the influence of the ions on peptide identification.

A comprehensive investigation was performed to understand the influence of sequence scrambling in peptide ions on peptide identification results. To achieve this, four tandem mass spectrometry datasets with scrambled ions included and with them excluded were analyzed by Crux, X!Tandem, SpectraST, Lutefisk, and PepNovo. While the different algorithms differed in their performance, an increase in the number of correctly identified peptides was generally observed when removing scrambled ions, with the exception of the SpectraST algorithm. However, the variation of the match scores upon removal was unpredictable. Following these investigations, an interpretation was given on how the scrambled ions affect peptide identification. Lastly, a simulated theoretical mass spectral library derived from the NIST peptide Libraries was constructed and searched by SpectraST to study whether scrambled ions in predicted mass spectra could affect peptide identification. Consistent with the peptide library search results, no significant variations for dot product scores as well as peptide identification results were observed when these ions were included in the theoretical MS/MS spectra. From the five adopted algorithms, the SpectraST and Crux provided the most robust results, whereas X!Tandem, PepNovo, and Lutefisk were sensitive to the existence of the scrambled ions, especially the latter two de novo sequencing algorithms.

Comparative analysis of essential oil components in Pericarpium Citri Reticulatae Viride and Pericarpium Citri Reticulatae by GC-MS combined with chemometric resolution method.

The similarities and differences of essential oil components in Pericarpium Citri Reticulatae Viride (PCRV) and Pericarpium Citri Reticulatae (PCR) were investigated by GC-MS combined with a chemometric method, named alternative moving window factor analysis (AMWFA). Furthermore, temperature-programmed retention indices (PTRIs) were used together with mass spectra for identification of the essential oil components. A total of 61 and 59 compounds in the essential oils of PCRV and PCR from three Citrus species were identified, which represented 98.15-99.66% and 97.6-99.84% of their total relative contents, respectively. The essential oils from PCRV and PCR significantly differed both qualitatively and quantitatively. The main compound in the essential oils from PCRV and PCR was d-limonene accounting for 65.61-83.14%. The comparative analysis indicates that AMWFA greatly enhanced the accuracy of quantitative and qualitative results by utilizing information from chromatography and mass spectra. The results obtained may be helpful to find out the possibly bioactive compounds of PCRV and PCR.