Library Matching Research Articles

Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching

The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral imaging system. Compressed sensing technology is one of the important ways to solve this problem. Distributed compressed sensing was proposed to exploit both intra- and inter-correlation structures of hyperspectral images. However, the implementation method of distributed compressed sampling has not been reported, and the joint sparsity reconstruction algorithm cannot achieve excellent image reconstruction performance. In this paper, a distributed compressed sampling strategy inspired by distributed compressed video sensing and optical implementation model are proposed to collect compressed hyperspectral data. In the image reconstruction process, we discard the direct application of the joint sparsity constraint on the data itself. Instead, we explore the estimation method of abundance and endmember with the help of the existing spectral library. Then, the images are recovered by applying the linear mixing model of hyperspectral. The comparison experiments of various schemes show that the proposed compressed sensing scheme has an obvious advantage in reconstruction performance under the low sampling rate. The proposed compressed sensing scheme has great potential in a high-compression ratio onboard hyperspectral imaging system.

Metabolite Profiling of Alangium salviifolium Bark Using Advanced LC/MS and GC/Q-TOFTechnology.

There is an urge for traditional herbal remedies as an alternative to modern medicine in treating several ailments. Alangium salviifolium is one such plant, used traditionally to treat several diseases. In several reports, there are findings related to the use of this plant extract that demonstrate its therapeutic value. However, very few attempts have been made to identify the extensive metabolite composition of this plant. Here, we performed metabolite profiling and identification from the bark of A. salviifolium by extracting the sample in organic and aqueous solvents. The organic and aqueous extracts were fraction-collected using the Agilent 1260 Analytical Scale Fraction Collection System. Each of the fractions was analyzed on Liquid Chromatogaphy/Quadrupole Time-of-Flight LC/Q-TOF and Gas Chromatography/Quadrupole Time-of-Flight GC/instruments. The Liquid Chromatography/Mass Spectrometry (LC/MS) analyses were performed using Hydrophilic Ineraction Liquid Chromatography (HILIC), as well as reversed-phase chromatography using three separate, orthogonal reverse phase columns. Samples were analyzed using an Agilent Jet Stream (AJS) source in both positive and negative ionization modes. The compounds found were flavonoids, fatty acids, sugars, and terpenes. Eighty-one secondary metabolites were identified as having therapeutic potential. The data produced was against the METLIN database using accurate mass and/or MS/MS library matching. Compounds from Alangium that could not be identified by database or library matching were subsequently searched against the ChemSpider) database of over 30 million structures using MSMS data and Agilent MSC software.In order to identify compounds generated by GC/MS, the data were searched against the AgilentFiehn GCMS Metabolomics Library as well as the Wiley/NIST libraries.

Teaching Graduate Students GC-QTOF-MS Operation and Application via an Analytical Chemistry Experiment

This experiment combines analytical techniques of solid-phase extraction (SPE) and gas chromatography quadrupole time-of-flight mass spectrometry (GC-QTOF-MS) to determine organochlorine pesticides (OCPs) in river water as a means to develop and improve student understanding of the use of GC-QTOF-MS for qualitative and quantitative analysis. In the classroom, students are presented with the principles and instrumentation of SPE, GC, and QTOF-MS via conventional lectures and question–answer sessions. In the laboratory, they are introduced to the procedure for tuning GC-QTOF-MS and developing a new method, analyzing OCPs in standard solutions to obtain retention times and characteristic ions, employing the mass spectrometry data to conduct library matching, and completing the identification and quantification of OCPs in the river. Additionally, students learn how to deduce the chemical formula of an “unknown” eluent compound by relying on high-resolution mass measurements and isotopic distributions. This method could be applied in the courses of instrumental analysis or environmental analysis. It could be readily adapted to other analytes such as the presence of steroids or other pharmaceuticals.

Suspect and non-target screening of reuse water by large-volume injection liquid chromatography and quadrupole time-of-flight mass spectrometry

Eight samples were obtained to characterize the chemical loads in water recycled for reuse applications. The sources included stormwater, rooftop runoff, wastewater, mixed water, and drinking water as a comparison. The water was reused for irrigation, cleaning, toilet flushing, and cooling purposes. Large-volume injection (650 μL) high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry were employed to separate and detect features by suspect and non-target screening. The instrumental method had the advantage that no sample extractions were required prior to analysis. Two chromatographic methods were developed to separate positive- and negative-ionizing compounds and retention time models were developed for both. Retention time models provide an additional measure of confidence for probable and tentative identifications. The two models had predictive R2—which indicates how well the models predicts new observations—of 0.87. After data-reduction, the number of features detected in the samples ranged from 304 to 1513. Feature metrics such as the average response-per-feature provided a simple method to characterize similarities and differences between samples. Additionally, a statistical comparison was performed by principal component analysis. Of the 97 suspect-screening compounds, 20 were positively identified. Benzotriazole/benzothiazole-derivatives and per- and poly-fluoroalkyl substances were the most frequently detectedcompounds during suspect screening. Other compounds detected included pharmaceuticals, drug metabolites, and sucralose. Features were prioritized for non-target analysis based on in-house library matches, magnitude of response, and frequency of occurrence. Fifty-five unique compounds were positively identified via non-target analysis. The identified compounds included 17 pharmaceuticals, 17 pesticides, 13 industrial compounds, four personal-use compounds, and four biological compounds.

Low Molecular Weight Volatile Organic Compounds Indicate Grazing by the Marine Rotifer Brachionus plicatilis on the Microalgae Microchloropsis salina.

Microalgae produce specific chemicals indicative of stress and/or death. The aim of this study was to perform non-destructive monitoring of algal culture systems, in the presence and absence of grazers, to identify potential biomarkers of incipient pond crashes. Here, we report ten volatile organic compounds (VOCs) that are robustly generated by the marine alga, Microchloropsis salina, in the presence and/or absence of the marine grazer, Brachionus plicatilis. We cultured M. salina with and without B. plicatilis and collected in situ volatile headspace samples using thermal desorption tubes over the course of several days. Data from four experiments were aggregated, deconvoluted, and chromatographically aligned to determine VOCs with tentative identifications made via mass spectral library matching. VOCs generated by algae in the presence of actively grazing rotifers were confirmed via pure analytical standards to be pentane, 3-pentanone, 3-methylhexane, and 2-methylfuran. Six other VOCs were less specifically associated with grazing but were still commonly observed between the four replicate experiments. Through this work, we identified four biomarkers of rotifer grazing that indicate algal stress/death. This will aid machine learning algorithms to chemically define and diagnose algal mass production cultures and save algae cultures from imminent crash to make biofuel an alternative energy possibility.

Using GC-MS for natural product analysis in Nigeria: Problems and prospects

The absence or idle state of analytical equipment such as nuclear magnetic resonance spectroscopy, mass spectrometers and chromatographic techniques has constrained natural products research in Nigeria. Presently, gas chromatography-mass spectrometry has become the more easily available method in Nigeria for the identification of natural products in extracts. This method is sometimes fraught with non-reproducible results and the identification of non-natural or biosynthesized compounds. Several of the extracts analyzed are not volatile, some of the analysts are not competent and certified reference standards are hardly used. These coupled with poor library or database matches and data processing among others lead to the identification of compounds not recognizable from the extract or plants materials under study. This review discusses some of the problems involved in the use of this method for dereplication studies of plant extracts in Nigeria and makes some suggestions for improvement.

Untargeted GC-MS investigation of serum metabolomics of coronary artery disease patients.

Recent advances in metabolomics provide tools to investigate human metabolome in order to establish new parameters to study different approaches towards diagnostics, diseases and their treatment. The present study focused on the untargeted identification of metabolites in serum of patients with coronary artery disease who were under treatment at the time of sample collection. AUCs (Area Under the Curves) from different peaks were considered for the analysis and comparison purposes. The metabolome was studied using GC–MS (Gas Chromatography Mass Spectrometry) and the metabolites were identified with NIST (The National Institute of Standards and Technology) and Wiley library matches. A total of 17 metabolites were identified and focused on to compare with the metabolome of healthy individuals. T test analysis found significant differences in alanine, malonic acid, ribitol, D-glucose, mannose (P < 0.001), acetohydroxamic acid, N-carboxyglycine, and aminobutyrate (P < 0.05). Principal Component Analysis of serum metabolites data found three components out of 17 metabolites; RC1 (Acetohydroxamic acid, alanine, D-glucose, malonic acid, mannose, N-carboxy glycine and ribitol), RC2 (Heptadecanoic acid, hexadecanoic acid, octadecanoic acid and Trans-9-octadecanoic acid), RC3 (Aminobutyrate, D-sorbit, gamma lactone, valine, benzene propanoic acid and lactic acid). No correlation was found among the components.

Towards automatic classification of diffuse reflectance image cubes from paintings collected with hyperspectral cameras

Knowledge of pigments and their distribution in paintings can inform conservators and scholars to better understand, and conserve these objects. In recent years, a variety of macro-scale non-contact imaging modalities have been applied to paintings to create classification/material maps. One modality, reflectance imaging spectroscopy (RIS) captures the diffuse reflectance spectral signatures of the artists’ materials present in the objects which can be used for classification (by defining regions of the image cube that have the same spectral reflectance signature). In Cultural Heritage Science the ENVI spectral hourglass wizard (ENVI-SHW) has been used to create classification maps from RIS. This method is slow and requires an expert user input during the processing in order to find the reflectance spectra that define the spectral classes (spectral endmembers or exemplars). The pigments are then deduced from spectral features in endmember spectra and from other non-invasive analytical chemical analysis of sites defined by the RIS maps. This paper explores the potential of more automated algorithms, such as maximum distance (MaxD), that are based on the theory of convex hulls for doing these classifications as well as spectral matching algorithms to an optimal spectral library. While all of these algorithms were developed for Remote Sensing community, MaxD and the library matching examine all the spectra in the reflectance image cube, require little user input, and are reproducible and fast. The results from the analysis of reflectance image cubes (400 to 950 nm) of three paintings with MaxD and a spectral library matching algorithm are presented and compared to those obtained with the ENVI-SHW algorithm. The three paintings analyzed are the central panels from illuminated leafs, two from the Laudario of Sant’Agnese (c. 1340) painted by the Master of the Dominican Effigies, namely The Nativity with the Annunciation to the Shepherds and, Christ and the Virgin Enthroned with Forty Saints, and one cutting from a leaf from a Choir book, Saint Francis Receiving the Stigmata, painted by Cosmè Tura (c. 1470s). Specifically, the results include the spectral endmembers recovered from each method as well as the associated classification maps. The findings from this study show that the MaxD algorithm was able to find the majority of the reflectance spectral endmembers with little user input.

Bland-Altman Statistical Analysis and Mean Concentration Ratio for the Determination of Amphetamine-type Stimulants-related Drugs in Dried Blood Stain (DBS) Versus Whole Blood Sample (WBS) by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) Application to Forensic Toxicology Cases in Malaysia

The performance of dried blood stain (DBS) versus whole blood sample (WBS) methods were evaluated using Bland-Altman analysis and mean concentration ratio for forensic toxicology cases in Malaysia. Common amphetamine-type stimulants related drugs of ephedrine, pseudoephedrine, amphetamine, methamphetamine, MDMA (3,4- Methylenedioxymethamphetamine), MDA (3,4-Methylenedioxyamphetamine), MDEA (3,4- Methylenedioxy-N-ethylamphetamine) and phentermine were investigated using DBS and WBS methods. The analysis was performed utilizing novel protocol consists of mass spectrometry detection technique based on a multiperiod and multi-experiment (MRM-EPI- MRM3) with library matching post liquid-liquid extraction of whole blood and corresponding DBS samples from spiked samples. The analysis was applied to 20 whole blood samples submitted for forensic and medico-legal analysis which were reported positive for the presence of the drugs. Results for both DBS and WBS were compared using Bland-Altman mean difference plots and mean concentration ratio for degree of agreement. The results showed good degree of agreements indicating no significant differences in results obtaining from DBS and WBS methods, allowing both methods to be used interchangeably. The study also demonstrated the advantage of the DBS method as an inexpensive alternative to WBS in the forensic toxicology field.

Metabolomics Benefits from Orbitrap GC-MS-Comparison of Low- and High-Resolution GC-MS.

The development of improved mass spectrometers and supporting computational tools is expected to enable the rapid annotation of whole metabolomes. Essential for the progress is the identification of strengths and weaknesses of novel instrumentation in direct comparison to previous instruments. Orbitrap liquid chromatography (LC)–mass spectrometry (MS) technology is now widely in use, while Orbitrap gas chromatography (GC)–MS introduced in 2015 has remained fairly unexplored in its potential for metabolomics research. This study aims to evaluate the additional knowledge gained in a metabolomics experiment when using the high-resolution Orbitrap GC–MS in comparison to a commonly used unit-mass resolution single-quadrupole GC–MS. Samples from an osmotic stress treatment of a non-model organism, the microalga Skeletonema costatum, were investigated using comparative metabolomics with low- and high-resolution methods. Resulting datasets were compared on a statistical level and on the level of individual compound annotation. Both MS approaches resulted in successful classification of stressed vs. non-stressed microalgae but did so using different sets of significantly dysregulated metabolites. High-resolution data only slightly improved conventional library matching but enabled the correct annotation of an unknown. While computational support that utilizes high-resolution GC–MS data is still underdeveloped, clear benefits in terms of sensitivity, metabolic coverage, and support in structure elucidation of the Orbitrap GC–MS technology for metabolomics studies are shown here.

Retrospective screening of synthetic cannabinoids, synthetic opioids and designer benzodiazepines in data files from forensic post mortem samples analysed by UHPLC-QTOF-MS from 2014 to 2018

The introduction of new psychoactive substances (NPS) on the illicit drug market has led to major challenges for the analytical laboratories. Keeping screening methods up to date with all relevant drugs is hard to achieve and the risk of missing important findings in biological samples is a matter of concern. Aiming for an extended retrospective data analysis, diagnostic fragment ions from synthetic cannabinoids (n=251), synthetic opioids (n=88) and designer benzodiazepines (n=26) not included in our original analytical method were obtained from the crowdsourced database HighResNPS.com and converted to a personalized library in a format compatible with the analytical instrumentation. Data files from the analysis of 1314 forensic post mortem samples with an Agilent 6540 ultra high pressure liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) performed in our laboratory from January 2014 to December 2018 were retrieved and retrospectively processed with the new personalized library. Potentially positive findings were grouped in two: The most confident findings contained MS/MS data for library match (category 1) whereas the less confident findings lacked such data (category 2). Five new category 1 findings were identified: Flubromazepam in two data files from 2015 and 2016, respectively, phenibut (4-amino-3-phenylbutyric acid) in one data file from 2015, fluorofentanyl in one data file from 2016 and cyclopropylfentanyl in one data file from 2018. Retention time matches with reference standards further strengthened these findings. A list of 35 presumably positive category 2 findings was generated. Of these, only one finding of phenibut was considered plausible after checking retention times and signal-to-noise ratios. This study shows that new compounds can be detected retrospectively in data files from QTOF-MS using an updated library containing diagnostic fragment ions. Automatic screening procedures can be useful, but a manual re-evaluation of positive findings will always be necessary.

A Method for Identifying Defects on Highly Reflective Roller Surface Based on Image Library Matching

Identification of the highly reflective surface defects on roller parts is a requirement to assure high quality of parts. However, the highly reflective roller surface has the reflection characteristics, which easily lead to the missed detection or wrong detection of defect targets in the visual recognition process. For this problem, a new identification method based on image library matching is proposed. First, to protect the edge information of the defect target while eliminating noise, preprocessing of the measured initial images can be accomplished by using the accelerated optimized bilateral filtering. Second, the entropy and grid gray gradient are used to achieve rough segmentation of highly reflective surface defects on roller parts. Finally, a defect fine identification method based on the Hu invariant moment matching integrated with morphological classification is proposed for achieving image library matching and further quickly removing the pseudodefects. Experimental tests were conducted to verify the effectiveness of the proposed method in achieving accurate identification of highly reflective surface defects on roller parts. The proposed method has an accuracy of 98.2%, and the running time can basically meet the requirements of real-time performance.

Assessing specialized metabolite diversity of Alnus species by a digitized LC–MS/MS data analysis workflow

Alnus spp. (Betulaceae) have been used for treatments of hemorrhage, burn injuries, antipyretic fever, diarrhea, and alcoholism in traditional medicines. In this study, a digitized LC–MS/MS data analysis workflow was applied to provide an overview on chemical diversity of 15 Alnus extracts prepared from bark, twigs, leaves, and fruits of A. japonica, A. firma, A. hirsuta, and A. hirsuta var. sibirica. Most of the MS/MS spectra could be putatively annotated based on library matching, in silico fragmentation, and substructural topic modeling. The putative annotation allowed us to discriminate the extracts into three chemotypes based on dominant chemical scaffolds: diarylheptanoids, flavonoids or tannins. This high-throughput chemical annotation was correlated with α-glucosidase inhibition data of extracts, and it allowed us to identify gallic acid as the major active compound of A. firma.

The identification of chemical attribution signatures of stored VX nerve agents using NMR, GC-MS, and LC-HRMS

The organophosphorous nerve agent VX is classified by the Chemical Warfare Convention (CWC) as a Schedule 1 chemical; namely a substance that is highly toxic with no use that is of benefit to society. Even with this classification, the nefarious use of the Schedule 1 chemical VX has been observed, as demonstrated in 2017 in Malaysia. Therefore, undertaking chemical analysis on samples of VX to identify chemical attribution signatures (CAS) for chemical forensics is required. To further understand the chemical profile of VX, and to aid in the identification of potential CAS, three in house synthesised stocks of VX were investigated. The three VX stocks analysed were synthesised in 2014, 2017 and 2018 using the same method, allowing for a comparison of data between each of the stocks at different stages of storage. As opposed to a majority of literature reports, these agent stocks were not stabilised, nor were they subjected to forced degradation. Using NMR, high resolution (HR) LC-HRMS, GC-(EI)MS and GC-(CI)MS to gain a full insight into the CAS profile, a total of 44 compounds were identified. Of these compounds, 30 were readily identified through accurate mass measurement and NIST library matches. A further seven were identified through extensive LC-HRMS/MS studies, with seven remaining unresolved. Several compounds, identified in minor amounts, were able to be traced back to impurities in the precursor compounds used in the synthesis of VX, and hence may be useful as CAS for source attribution.

Comparing mass, retention time and tandem mass spectra as criteria for the automated screening of small molecules in aqueous environmental samples analyzed by liquid chromatography/quadrupole time-of-flight tandem mass spectrometry.

The adoption of database screening using high-resolution liquid chromatography/mass spectrometry data is promising as a river water monitoring and surveillance tool but depends on the ability to perform reliable data processing on a large number of samples in a unified workflow. Strategies to minimize errors have been proposed but automated procedures are rare. High-resolution LC/ESI-QTOFMS/MS in data-dependent MS2 acquisition mode was performed for the analysis of surface water samples by direct injection. Data processing was achieved with software tools written in R. A database containing MS2 spectra of 693 compounds formed the basis of the workflow. Standard mixes and a time series of 361 samples of river water were analyzed and processed with the optimized workflow. Using the database and a mix of 70 standards for testing, it was found that an identification strategy including (i) mass, (ii) retention time, and (iii) MS2 spectral matching achieved a two- to three-fold improvement in the fraction of false positives compared with using only two criteria, while the number of false negatives remained low. The optimized workflow was applied to the sample series of river water. In total, 135 compounds were identified by a library match. The developed automated database screening approach minimizes the proportion of false positives, while still allowing for the screening of hundreds of water samples for hundreds of compounds in a single run.

Multiclass Multipesticide Residue Analysis in Fish Matrix by a Modified QuEChERS Method Using Gas Chromatography with Mass Spectrometric Determination.

Pesticide residue in fish is a global food safety concern. However, very few validated methods are available targeting simultaneous analysis of multiple classes of pesticides. The aim of this study was to validate a quick, easy, cheap, effective, rugged, and safe workflow-based method for the quantitative determination of multiclass pesticides in fish matrix using GC-MS determination. The sample was extracted with acetonitrile, and the cleanup method involved dispersive solid-phase extraction with C-18 sorbent, which effectively scavenged the coextracted matrix components and removed those from the extract. The data on recovery and precision of the method satisfied the criteria of SANTE/11813/2017 guidelines. Average recoveries of pesticides were in the range of 80-120% with precision RSDs ≤20%. The LOD and LOQ were in the ranges of 0.001-0.029 and 0.005-0.125 µg/mL, respectively, for all pesticides. The expanded uncertainty was in the range of 14-20%, based on the single-laboratory validation data (coverage factor, k = 2, confidence level, 95%). The validation data prove that the method is convenient and acceptable for the routine analysis of multiclass pesticide residues in fish matrices for regulatory compliance. The study achieves multiresidue analysis of pesticides in fish matrix with MS-based confirmation. The method combines the advantages of nontarget analysis based on National Institute of Standards and Technology library matching in full scan mode with selected-ion monitoring-based sensitivity.

Qualitative terpene profiling of Cannabis varieties cultivated for medical purposes

Abstract With the upcoming medical Cannabis regulation, quality control methods on raw material will be required. Besides testing for contaminants and potency, there are also pharmaceutical and forensic interests in the determination of the terpene profile in different strains of Cannabis as complementary identification methods. A simple non-destructive HS-SPME GC-MS method was used to identify the terpene content in twelve Cannabis samples, four of them were of the hemp type (Harle-tsu), seven from various marihuana types and one of the intermediate type. They all were previously analyzed by HPLC to determine the potency (THC and CBD content). Spectral library matching was used to identify the terpenes compounds. Thirty terpenes compounds were detected, nine of them were present in all Cannabis samples and used to find their terpene profile: α-pinene, β-pinene, β-myrcene, D-limonene, terpinolene, linalool, caryophyllene, α-bergamotene and humulene. Three of them, caryophyllene, α-pinene and β-myrcene were found as larger components in most of samples. A principal components analyses (PCA) was performed. The four hemp type samples showed two different profiles, two samples showed caryophyllene as main component and the others two with β-myrcene as such. The marihuana type samples showed wider profiles with no clear patterns at all, which is not surprising because of the low number of samples. The simple methodology shows viable to set the terpenes profile for analyses of raw Cannabis material. Suitability for differentiation between different sorts of types needs more studies, with increasing numbers of samples.

Analysis of heterocyclic aromatic amine profiles in Chinese traditional bacon and sausage based on ultrahigh-performance liquid chromatography–quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC–Q-Orbitrap-HRMS)

Ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC–Q-Orbitrap-HRMS) was used for the screening and determination of 14 heterocyclic aromatic amines (HAAs) in Chinese traditional bacon and sausage. HAAs were extracted from samples using sodium hydroxide solution with acetonitrile, and purified by solid-phase extraction. UHPLC–Q-Orbitrap-HRMS acquired full MS data for quantification, and UHPLC–Q-Orbitrap-Full MS/dd-MS2 (i.e., data-dependent scan mode) obtained product ion spectra for identification. Quantification was achieved using matrix-matched standard calibration curves along with the use of isotope labeled standards as internal standards. Linearity was observed in the range of 0.2–500 μg/L for 14 HAAs, with determination coefficients (R2) greater than 0.997. Limits of detection and limits of quantification were in the ranges of 0.1–0.8 μg/kg and 0.3–2.5 μg/kg, respectively. UHPLC–Q-Orbitrap-HRMS demonstrated acceptable performance for quantification and confirmation of HAAs, while UHPLC–Q-Orbitrap-Full MS/dd-MS2 along with library matching showed great potential for screening and confirmation of unknown HAAs in meat products.

Statistical approach to determining the cut-off value in the algorithms of substance identification in Fourier transform infrared spectroscopy

The purpose of the paper was to find the approach to determining the cut-off value in the spectral library matching identification algorithm. We used Pearson correlation coefficient as a similarity measure between the spectra, and according to its value between the reference spectra we divided the spectral library into classes. We considered a situation when one of the investigated spectra had an additive narrowband white noise component with a Gaussian distribution. We examined the impact of the cut-off value on the possibility of calculating the probability of right identification in a single identification experiment by means of probability distribution function, when the signal-to-noise ratio is known a priori. The signal-to-noise ratio was taken from the value area where analytical expressions were unknown. In the research we applied numerical methods. The algorithm of determining the cut-off value based on the fundamental principles of the ROC-curves analysis was proposed. The cut-off value was obtained where possible, and the situation for every class was analysed. Maximal probabilities of right identification were obtained.

Major AhR-active chemicals in sediments of Lake Sihwa, South Korea: Application of effect-directed analysis combined with full-scan screening analysis

This study utilized effect-directed analysis (EDA) combined with full-scan screening analysis (FSA) to identify aryl hydrocarbon receptor (AhR)-active compounds in sediments of inland creeks flowing into Lake Sihwa, South Korea. The specific objectives were to (i) investigate the major AhR-active fractions of organic extracts of sediments by using H4IIE-luc in vitro bioassay (4 h and 72 h exposures), (ii) quantify known AhR agonists, such as polycyclic aromatic hydrocarbons (PAHs) and styrene oligomers (SOs), (iii) identify unknown AhR agonists by use of gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOFMS), and (iv) determine contributions of AhR agonists to total potencies measured by use of the bioassay. FSA was conducted on fractions F2.6 and F2.7 (aromatics with log Kow 5–7) in extracts of sediment from Siheung Creek (industrial area). Those fractions exhibited significant AhR-mediated potency as well as relatively great concentrations of PAHs and SOs. FSA detected 461 and 449 compounds in F2.6 and F2.7, respectively. Of these, five tentative candidates of AhR agonist were selected based on NIST library matching, aromatic structures and numbers of rings, and available standards. Benz[b]anthracene, 11H-benzo[a]fluorene, and 4,5-methanochrysene exhibited significant AhR-mediated potency in the H4IIE-luc bioassay, and relative potencies of these compounds were determined. Potency balance analysis demonstrated that these three newly identified AhR agonists explained 1.1% to 67% of total induced AhR-mediated potencies of samples, which were particularly great for industrial sediments. Follow-up studies on sources and ecotoxicological effects of these compounds in coastal environments would be required.