Untargeted Lipidomics Method for the Discrimination of Five Crab Species by Ultra-High-Performance Liquid Chromatography High-Resolution Mass Spectrometry Combined with Chemometrics.

In this study, ultra-high-performance liquid chromatography high-resolution accurate mass-mass spectrometry (UHPLC-HRAM/MS) was applied to characterize the lipid profiles of five crab species. A total of 203 lipid molecular species in muscle tissue and 176 in edible viscera were quantified. The results indicate that Cancer pagurus contained high levels of lipids with a docosahexaenoic acid (DHA) and eicosapntemacnioc acid (EPA) structure in the muscle tissue and edible viscera. A partial least squares discriminant analysis (PLS-DA) showed that PE 16:0/22:6, PE P-18:0/20:5, PA 16:0/22:6 and PC 16:0/16:1 could be used as potential biomarkers to discriminate the five kinds of crabs. In addition, some lipids, such as PE 18:0/20:5, PC 16:0/16:1, PE P-18:0/22:6 and SM 12:1;2O/20:0, could be used as characteristic molecules to distinguish between Cancer magister and Cancer pagurus, which are similar in appearance. This study provides a new perspective on discriminating crab species from MS-based lipidomics.

Urinary metabolomics using gas chromatography-mass spectrometry: potential biomarkers for autism spectrum disorder.

BACKGROUND: Diagnosis of autism spectrum disorder (ASD) is generally made phenotypically and the hunt for ASD-biomarkers continues. The purpose of this study was to compare urine organic acids profiles of ASD versus typically developing (TD) children to identify potential biomarkers for diagnosis and exploration of ASD etiology. METHODS: This case control study was performed in the Department of Pathology and Laboratory Medicine in collaboration with the Department of Pediatrics and Child Health, Aga Khan University, Pakistan. Midstream urine was collected in the first half of the day time before noon from the children with ASD diagnosed by a pediatric neurologist based on DSM-5 criteria and TD healthy controls from August 2019 to June 2021. The urine organic acids were analyzed by Gas Chromatography-Mass Spectrometry. To identify potential biomarkers for ASD canonical linear discriminant analysis was carried out for the organic acids, quantified in comparison to an internal standard. RESULTS: A total of 85 subjects were enrolled in the current study. The mean age of the ASD (n = 65) and TD groups (n = 20) was 4.5 ± 2.3 and 6.4 ± 2.2 years respectively with 72.3% males in the ASD group and 50% males in the TD group. Parental consanguinity was 47.7 and 30% in ASD and TD groups, respectively. The common clinical signs noted in children with ASD were developmental delay (70.8%), delayed language skills (66.2%), and inability to articulate sentences (56.9%). Discriminant analysis showed that 3-hydroxyisovalericc, homovanillic acid, adipic acid, suberic acid, and indole acetic were significantly different between ASD and TD groups. The biochemical classification results reveal that 88.2% of cases were classified correctly into ASD& TD groups based on the urine organic acid profiles. CONCLUSION: 3-hydroxy isovaleric acid, homovanillic acid, adipic acid, suberic acid, and indole acetic were good discriminators between the two groups. The discovered potential biomarkers could be valuable for future research in children with ASD.

Single-Molecule Detection of Nucleic Acids via Liposome Signal Amplification in Mass Spectrometry.

A single-molecule detection method was developed for nucleic acids based on mass spectrometry counting single liposome particles. Before the appearance of symptoms, a negligible amount of nucleic acids and biomarkers for the clinical diagnosis of the disease were already present. However, it is difficult to detect extremely low concentrations of nucleic acids using the current methods. Hence, the establishment of an ultra-sensitive nucleic acid detection technique is urgently needed. Herein, magnetic beads were used to capture target nucleic acids, and liposome particles were employed as mass tags for single-particle measurements. Liposomes were released from magnetic beads via photocatalytic cleavage. Hence, one DNA molecule corresponded to one liposome particle, which could be counted using mass spectrometric measurement. The ultrasensitive detection of DNA (10-18 M) was achieved using this method.

Bound Electron Enhanced Radiosensitisation of Nimorazole upon Charge Transfer.

This novel work reports nimorazole (NIMO) radiosensitizer reduction upon electron transfer in collisions with neutral potassium (K) atoms in the lab frame energy range of 10-400 eV. The negative ions formed in this energy range were time-of-flight mass analyzed and branching ratios were obtained. Assignment of different anions showed that more than 80% was due to the formation of the non-dissociated parent anion NIMO•- at 226 u and nitrogen dioxide anion NO2- at 46 u. The rich fragmentation pattern revealed that significant collision induced the decomposition of the 4-nitroimidazole ring, as well as other complex internal reactions within the temporary negative ion formed after electron transfer to neutral NIMO. Other fragment anions were only responsible for less than 20% of the total ion yield. Additional information on the electronic state spectroscopy of nimorazole was obtained by recording a K+ energy loss spectrum in the forward scattering direction (θ ≈ 0°), allowing us to determine the most accessible electronic states within the temporary negative ion. Quantum chemical calculations on the electronic structure of NIMO in the presence of a potassium atom were performed to help assign the most significant lowest unoccupied molecular orbitals participating in the collision process. Electron transfer was shown to be a relevant process for nimorazole radiosensitisation through efficient and prevalent non-dissociated parent anion formation.

Fragment Mass Spectrum Prediction Facilitates Site Localization of Phosphorylation.

Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been the most widely used technology for phosphoproteomics studies. As an alternative to database searching and probability-based phosphorylation site localization approaches, spectral library searching has been proved to be effective in the identification of phosphopeptides. However, incompletion of experimental spectral libraries limits the identification capability. Herein, we utilize MS/MS spectrum prediction coupled with spectral matching for site localization of phosphopeptides. In silico MS/MS spectra are generated from peptide sequences by deep learning/machine learning models trained with nonphosphopeptides. Then, mass shift according to phosphorylation sites, phosphoric acid neutral loss, and a "budding" strategy are adopted to adjust the in silico mass spectra. In silico MS/MS spectra can also be generated in one step for phosphopeptides using models trained with phosphopeptides. The method is benchmarked on data sets of synthetic phosphopeptides and is used to process real biological samples. It is demonstrated to be a method requiring only computational resources that supplements the probability-based approaches for phosphorylation site localization of singly and multiply phosphorylated peptides.

Discovery and validation of PZP as a novel serum biomarker for screening lung adenocarcinoma in type 2 diabetes mellitus patients.

BACKGROUND: Patients with type 2 diabetes mellitus (T2DM) have an increased risk of suffering from various malignancies. This study aimed to identify specific biomarkers that can detect lung adenocarcinoma (LAC) in T2DM patients for the early diagnosis of LAC. METHODS: The clinical information of hospitalized T2DM patients diagnosed with various cancers was collected by reviewing medical records in Wuxi People's Hospital Affiliated to Nanjing Medical University from January 1, 2015, to June 30, 2020. To discover diagnostic biomarkers for early-stage LAC in the T2DM population, 20 samples obtained from 5 healthy controls, 5 T2DM patients, 5 LAC patients and 5 T2DM patients with LAC (T2DM + LAC) were subjected to sequential windowed acquisition of all theoretical fragment ion mass spectrum (SWATH-MS) analysis to identify specific differentially-expressed proteins (DEPs) for LAC in patients with T2DM. Then, these results were validated by parallel reaction monitoring MS (PRM-MS) and ELISA analyses. RESULTS: Lung cancer was the most common malignant tumor in patients with T2DM, and LAC accounted for the majority of cases. Using SWATH-MS analysis, we found 13 proteins to be unique in T2DM patients with early LAC. Two serum proteins were further validated by PRM-MS analysis, namely, pregnancy-zone protein (PZP) and insulin-like growth factor binding protein 3 (IGFBP3). Furthermore, the diagnostic values of these proteins were validated by ELISA, and PZP was validated as a novel serum biomarker for screening LAC in T2DM patients. CONCLUSIONS: Our findings indicated that PZP could be used as a novel serum biomarker for the identification of LAC in T2DM patients, which will enhance auxiliary diagnosis and assist in the selection of surgical treatment at an early stage.

Discrimination of Ignitable Liquid Residues in Burned Petroleum-Derived Substrates by Using HS-MS eNose and Chemometrics.

Interpretation of data from fire debris is considered as one of the most challenging steps in fire investigation. Forensic analysts are tasked to identify the presence or absence of ignitable liquid residues (ILRs) which may indicate whether a fire was started deliberately. So far, data analysis is subjected to human interpretation following the American Society for Testing and Materials' guidelines (ASTM E1618) based on gas chromatography-mass spectrometry data. However, different factors such as interfering pyrolysis compounds may hinder the interpretation of data. Some substrates release compounds that are in the range of common ignitable liquids, which interferes with accurate determination of ILRs. The aim of the current research is to investigate whether headspace-mass spectroscopy electronic nose (HS-MS eNose) combined with pattern recognition can be used to classify different ILRs from fire debris samples that contain a complex matrix (petroleum-based substrates or synthetic fibers carpet) that can strongly interfere with their identification. Six different substrates-four petroleum-derived substrates (vinyl, linoleum, polyester, and polyamide carpet), as well as two different materials for comparison purposes (cotton and cork) were used to investigate background interferences. Gasoline, diesel, ethanol, and charcoal starter with kerosene were used as ignitable liquids. In addition, fire debris samples were taken after different elapsed times. A total of 360 fire debris samples were analyzed. The obtained total ion mass spectrum was combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) as well as supervised linear discriminant analysis (LDA). The results from HCA show a strong tendency to group the samples according to the ILs and substrate used, and LDA allowed for a full identification and discrimination of every ILR regardless of the substrate.

Five Surfactin Isomers Produced during Cheonggukjang Fermentation by Bacillus pumilus HY1 and Their Properties.

The cyclic lipopeptide produced from Bacillus pumilus strain HY1 was isolated from Korean soybean sauce cheonggukjang. The chemical structures of the surfactin isomers were analyzed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and electrospray ionization tandem mass spectrometry (ESI-MS/MS). The five potential surfactin isoforms were detected with protonated masses of m/z 994.7, 1008.7, 1022.7, 1036.7, and 1050.7 and different structures in combination with Na+, K+, and Ca2+ ions. ESI-MS/MS analysis revealed that the isolated surfactin possessed the precise amino acid sequence LLVDLL and hydroxyl fatty acids with 12 to 16 carbons. The surfactin content during cheonggukjang fermentation increased from 0.3 to 51.2 mg/kg over 60 h of fermentation. The mixture of five surfactin isoforms of cheonggukjang inhibited the growth of two cancer cell lines. The growth of both MCF-7 and Caco-2 cells was strongly inhibited with 100 µg/µL of surfactin. This study is the first-time report of five surfactin isomers of Bacillus pumilus strain HY1 during Korean soybean sauce cheonggukjang fermentation, which has cytotoxic properties.

A Fast and Memory-Efficient Spectral Library Search Algorithm Using Locality-Sensitive Hashing.

With the accumulation of MS/MS spectra collected in spectral libraries, the spectral library searching approach emerges as an important approach for peptide identification in proteomics, complementary to the commonly used protein database searching approach, in particular for the proteomic analyses of well-studied model organisms, such as human. Existing spectral library searching algorithms compare a query MS/MS spectrum with each spectrum in the library with matched precursor mass and charge state, which may become computationally intensive with the rapidly growing library size. Here, the software msSLASH, which implements a fast spectral library searching algorithm based on the Locality-Sensitive Hashing (LSH) technique, is presented. The algorithm first converts the library and query spectra into bit-strings using LSH functions, and then computes the similarity between the spectra with highly similar bit-string. Using the spectral library searching of large real-world MS/MS spectra datasets, it is demonstrated that the algorithm significantly reduced the number of spectral comparisons, and as a result, achieved 2-9X speedup in comparison with existing spectral library searching algorithm SpectraST. The spectral searching algorithm is implemented in C/C++, and is ready to be used in proteomic data analyses.

Identification of dissociation factors in pancreatic Cancer using a mass spectrometry-based proteomic approach.

BACKGROUD: Pancreatic cancer is a highly malignant tumor of the digestive system. This secretome of pancreatic cancer is key to its progression and metastasis. But different methods of protein extraction affect the final results. In other words, the real secretion of proteins in cancer cells has been changed. Based on mass spectrometry, we analyze the secretome from the serum-containing and serum-free medium, using different protein pretreatment methods. This study aims to identify dissociation factors in pancreatic cancer. METHODS: In this study, pancreatic cancer cells were cultured in serum-containing or serum-free medium, and the corresponding supernatants were extracted as samples. Subsequently, the above samples were separated by size exclusion chromatography (SEC), and peptide segments were identified by LC-MS/MS. The final results were identified via the hamster secreted protein database and a public database. RESULTS: Although the number of identified proteins in the serum-free medium group was high, the real secretion of proteins in pancreatic cancer cells was changed. There were six significant secreted proteins in the serum-containing medium group. Survival analysis via the TCGA database suggested that patients with higher expression levels of YWHAG showed a worse overall survival rate than those with lower YWHAG expression. CONCLUSIONS: Our study demonstrated the results in the serum-containing medium group were more similar to the real secretome of pancreatic cancer cells. YWHAG could be used as a prognostic indicator for pancreatic cancer.

Vinblastine production by the endophytic fungus Curvularia verruculosa from the leaves of Catharanthus roseus and its in vitro cytotoxicity against HeLa cell line.

The current study was to isolate endophytic fungi producing high yields of indole alkaloids such as vinblastine analogous to their host Cathranthus roseus. Endophytic fungi were isolated from the leaves of C. roseus, identified as Curvularia verruculosa by molecular techniques, and the sequence was deposited in NCBI (MK995628). Vinblastine producing endophytic fungus was grown in 1L Vinca medium for 21 days. The extract was examined for vinblastine by chromatographic techniques. TLC plates showed purple colour spot co-migrated with authentic vinblastine and Rf was calculated by HPTLC (Vin 1 vinblastine -0.75; authentic vinblastine-0.78), these results confirmed vinblastine presence in the Vin1 extract. Further, the TLC purified fungal extract was examined by LC-MS, which revealed the exact mass of vinblastine ([M + H]+m/z 811.51). The most important of the study is high yield production of vinblastine; hence, the extract analysed by HPLC revealed 182 µg/L vinblastine. The TLC purified fungal vinblastine was analysed for the cytotoxicity effect on HeLa cell line and it depicted a higher activity with IC50-8.5 µg/mL and apoptotic morphological changes were analysed. All the results revealed that the endophytic fungus Curvularia verruculosa produced vinblastine and for the first time in a surplus amount compared to other fungi.

Identification of intracellular peptides associated with thermogenesis in human brown adipocytes.

OBJECTIVES: Currently, brown adipose tissue (BAT) is a therapeutic target in obesity and diabetes, but the mechanism of BAT activation remains unclear. Because increasing emphasis has been placed on the role of intracellular peptides in biological processes, we conducted a study to gain insight into the mechanism of BAT activation by using a peptidomic approach and then attempted to identify peptides that are capable of activating BAT. METHODS: In the present study, we generated the peptidomic profile of the intracellular peptides in brown adipocytes treated with forskolin (FSK) using a peptidomic approach. Then, the differentially expressed peptides were evaluated via Gene Ontology (GO) enrichment, KEGG pathway, and protein-protein interaction (PPI) network analysis. Finally, we selected candidate peptides for further validation via assessing the expression levels of UCP-1 and PGC-1α in brown adipocytes exposed to the peptides. RESULTS: A total of 4,370 peptides were identified, of which 951 were upregulated and 379 were downregulated after FSK treatment. Bioinformatic analysis demonstrated that the ECM-receptor interaction GO term was the most enriched and that collagen alpha-related proteins exhibited the highest degree of PPI. Four peptides separately derived from TSC22 domain family protein 1 (T22D1), bromodomain and WD repeat-containing protein 1 (BRWD1), protein piccolo (PCLO), and collagen alpha-1 (III) chain (CO3A1) increased the expression levels of UCP-1 and PGC-1α. CONCLUSIONS: ECM-receptor interaction may play an important role in the process of FSK-stimulated BAT activation, and the pT22D1tide, pBRWD1tide, pPCLOtide, and pCO3A1tide peptides potentially promote BAT thermogenesis.

MS2CNN: predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks.

BACKGROUND: Tandem mass spectrometry allows biologists to identify and quantify protein samples in the form of digested peptide sequences. When performing peptide identification, spectral library search is more sensitive than traditional database search but is limited to peptides that have been previously identified. An accurate tandem mass spectrum prediction tool is thus crucial in expanding the peptide space and increasing the coverage of spectral library search. RESULTS: We propose MS2CNN, a non-linear regression model based on deep convolutional neural networks, a deep learning algorithm. The features for our model are amino acid composition, predicted secondary structure, and physical-chemical features such as isoelectric point, aromaticity, helicity, hydrophobicity, and basicity. MS2CNN was trained with five-fold cross validation on a three-way data split on the large-scale human HCD MS2 dataset of Orbitrap LC-MS/MS downloaded from the National Institute of Standards and Technology. It was then evaluated on a publicly available independent test dataset of human HeLa cell lysate from LC-MS experiments. On average, our model shows better cosine similarity and Pearson correlation coefficient (0.690 and 0.632) than MS2PIP (0.647 and 0.601) and is comparable with pDeep (0.692 and 0.642). Notably, for the more complex MS2 spectra of 3+ peptides, MS2PIP is significantly better than both MS2PIP and pDeep. CONCLUSIONS: We showed that MS2CNN outperforms MS2PIP for 2+ and 3+ peptides and pDeep for 3+ peptides. This implies that MS2CNN, the proposed convolutional neural network model, generates highly accurate MS2 spectra for LC-MS/MS experiments using Orbitrap machines, which can be of great help in protein and peptide identifications. The results suggest that incorporating more data for deep learning model may improve performance.

Degradation of the phenolic ß-ether lignin model dimer and dyes by dye-decolorizing peroxidase from Bacillus amyloliquefaciens.

OBJECTIVE: The dye-decolorizing peroxidase from Bacillus amyloliquefaciens, BaDyP, was identified to be an efficient catalyst for the degradation of phenolic ß-ether lignin model dimer guaiacylglycerol-ß-guaiacyl ether (GGE) and dyes. RESULTS: Efeb gene encoding BaDyP from B. amyloliquefaciens MN-13 consisted of 1257 bp and the open reading frame encoded 418 amino acids. The efeb gene was expressed in Escherichia coli BL21 and a recombinant BaDyP of 50 kDa was achieved. The BaDyP exhibited activity in oxidizing GGE and decolorizing azo and triphenylmethane dyes. At pH 4.5 and 30 °C the BaDyP not only completely degraded GGE by the cleavage of ß-O-4 ether bond and Cα-Cß bond, and Cα oxidation without any oxidative mediator, but also decolorized four synthetic dyes, including congo red, bromine cresol green, eriochrome black T and crystal violet. This was achieved with decolorization rates of 65.7%, 70.62%, 80.06% and 62.09%, respectively, after 72 h of incubation. CONCLUSIONS: BaDyP was identified as a bacteria peroxidase with great potential for the degradation of lignin and bioremediation of dye-contamination.

Enhancing Element Identification by Expectation-Maximization Method in Atom Probe Tomography.

This paper describes an alternative way to assign elemental identity to atoms collected by atom probe tomography (APT). This method is based on Bayesian assignation of label through the expectation-maximization method (well known in data analysis). Assuming the correct shape of mass over charge peaks in mass spectra, the probability of each atom to be labeled as a given element is determined, and is used to enhance data visualization and composition mapping in APT analyses. The method is particularly efficient for small count experiments with a low signal to noise ratio, and can be used on small subsets of analyzed volumes, and is complementary to single-ion decomposition methods. Based on the selected model and experimental examples, it is shown that the method enhances our ability to observe and extract information from the raw dataset. The experimental case of the superimposition of the Si peak and N peak in a steel is presented.

Quantifying Uncertainty from Mass-Peak Overlaps in Atom Probe Microscopy.

There are many sources of random and systematic error in composition quantification by atom probe microscopy, often, however, only statistical error is reported. Significantly larger errors can occur from the misidentification of ions and overlaps or interferences of peaks in the mass spectrum. These overlaps can be solved using maximum likelihood estimation (MLE), improving the accuracy of the result, but with an unknown effect on the precision. An analytical expression for the uncertainty of the MLE solution is presented and it is demonstrated to be much more accurate than the existing methods. In one example, the commonly used error estimate was five times too small.Literature results containing overlaps most likely underestimate composition uncertainty because of the complexity of correctly dealing with stochastic effects and error propagation. The uncertainty depends on the amount of overlapped intensity, for example being ten times worse for the CO/Fe overlap than the Cr/Fe overlap. Using the methods described here, accurate estimation of error, and the minimization of this could be achieved, providing a key milestone in quantitative atom probe. Accurate estimation of the composition uncertainty in the presence of overlaps is crucial for planning experiments and scientific interpretation of the measurements.

Benzenedicarboxylic acid upregulates O48814 and Q9FJQ8 for improved nutritional contents of tomato and low risk of fungal attack.

BACKGROUND: Tomato is an important food item and a cocktail of phytonutrients. In the current study, metabolites from a non-pathogenic fungal species Penicillium oxalicum have been exploited to obtain nutritionally augmented tomato fruits from the plants to better withstand against Alternaria alternata infection. RESULTS: Initially, bioactivity-guided assay and chromatographic analyses identified the bioactive metabolites of P. oxalicum [benzenedicarboxylic acid (BDA) and benzimidazole]. Then, ≥3 times elevated quantities of vitamins and other nutritional elements (protein, fat, fibers, and carbohydrates) were achieved by the foliar application of BDA. The maximum increase (625.81%) was recorded in riboflavin contents; however, thiamine showed the second highest enhancement (542.86%). Plant metabolites analysis revealed that jasmonic acid contents were boosted 121.53% to significantly enhance guaiacyl lignin defenses along with the reduction in coumarin contents. The protein profile analysis explored three most actively responding protein species toward BDA applications, (i) palmitoyltransferase protein Q9FLM3; (ii) serine/threonine-protein kinase O48814; and (iii) E3 ubiquitin-protein ligase Q9FJQ8. The O48814 improved plant defenses; whereas, Q9FJQ8 protein was negatively regulating cysteine-type endopeptidase activity and assisted plant to resist schedule alterations. Tomato cultivar with more active innate metabolism was found to be more responsive toward BDA. Furthermore, the bioactive compounds were enriched by using the two-step extraction method of ethyl acetate and chloroform, respectively. CONCLUSION: Penicillium oxalicum a non-pathogenic fungal species, produced BDA, induced nutritional contents in tomato and protected it against Alternaria alternata. The current study is the first report on the bioactivity of BDA and benzimidazole concerning the nutritional enhancement and plant defense improvement. © 2019 Society of Chemical Industry.

Identification of proteins differentially expressed in the gills of grass carp (Ctenopharyngodon idella) after hypoxic stress by two-dimensional gel electrophoresis analysis.

Two-dimensional gel electrophoresis (2-DE) was combined with liquid chromatography-mass spectrometry (LC-MS/MS) to identify the differential proteomics of grass carp gills after hypoxic stress to better understand the roles of proteins in the hypoxic response and to explore the possible molecular mechanisms. Protein spots were obtained from a hypoxia-stressed group (372 ± 11 individuals) and a control group (406 ± 14 individuals) using the lmage Master 2D Platinum 7.0 analysis software. Fifteen protein spots were expressed differentially in the hypoxia-stressed group and varied significantly after exposure to the hypoxic conditions. In addition, these differential proteins were identified by mass spectrometry and then searched in a database. We found the expression and upregulation of the toll-like receptor 4, ephx1 protein, isocitrate dehydrogenase, L-lactate dehydrogenase, GTP-binding nuclear protein Ran, and glyceraldehyde-3-phosphate dehydrogenase; however, the expression of the keratin type II cytoskeletal 8, type I cytokeratin, ARP3 actin-related protein 3 homolog, thyroid hormone receptor alpha-A, ATP synthase subunit beta, citrate synthase, tropomyosin 2, and tropomyosin 3 were downregulated. Six proteins were found in the hypoxia-inducible factor-1 (HIF-1) signaling pathway. We concluded that the grass carp gill is involved in response processes, including energy generation, metabolic processes, cellular structure, antioxidation, immunity, and signal transduction, to hypoxic stress. To our knowledge, this is the first study to conduct a proteomics analysis of expressed proteins in the gills of grass carp, and this study will help increase the understanding of the molecular mechanisms involved in hypoxic stress responses in fish at the protein level.

Qualitative analysis of flavors and fragrances added to tea by using GC-MS.

A precise identification method was developed to identify the flavors and fragrances added to tea matrix artificially using gas chromatography with mass spectrometry and gas chromatography with quadrupole time-of-flight mass spectrometry. The proposed method was based on the corresponding "three-column retention indices, two exact mass numbers, one mass spectrum matching degree" database of 40 kinds of common flavors and fragrances. The intraday and the interday relative standard deviation of the retention indices were less than 0.048 and 0.093%, respectively. The accuracy of exact mass was between 0.15 and 6.22 ppm. And the validation of the created database was performed by analyzing the tea samples. Thus, the proposed method is suitable for the precise identification of the flavors and fragrances added to tea matrix artificially without standard substances as a reference.

Development of an on-line measurement system for water-soluble organic matter in PM2.5 and its application in China.

Water-soluble organic matter (WSOM) represents a critical fraction of fine particles (PM2.5) in the air, but its changing behaviors and formation mechanisms are not well understood yet, partly due to the lack of fast techniques for the ambient measurements. In this study, a novel system for the on-line measurement of water-soluble components in PM2.5, the particle-into-liquid sampler (PILS)-Nebulizer-aerosol chemical speciation monitor (ACSM), was developed by combining a PILS, a nebulizer, and an ACSM. High time resolution concentrations of WSOM, sulfate, nitrate, ammonium, and chloride, as well as mass spectra, can be obtained with satisfied quality control results. The system was firstly applied in China for field measurement of WSOM. The mass spectrum of WSOM was found to resemble that of oxygenated organic aerosol, and WSOM agreed well with secondary inorganic ions. All evidence collected in the field campaign demonstrated that WSOM could be a good surrogate of secondary organic aerosol (SOA). The PILS-Nebulizer-ACSM system can thus be a useful tool for intensive study of WSOM and SOA in PM2.5.