Sphingomyelin is involved in regulating UCP1-mediated nonshivering thermogenesis.

Adipogenesis is one of the major mechanisms for adipose tissue expansion, during which spindle-shaped mesenchymal stem cells commit to the fate of adipocyte precursors and differentiate into round-shaped fat-laden adipocytes. Here, we investigated the lipidomic profile dynamics of ex vivo-differentiated brown and white adipocytes derived from the stromal vascular fractions of interscapular brown (iBAT) and inguinal white adipose tissues. We showed that sphingomyelin was specifically enriched in terminally differentiated brown adipocytes, but not white adipocytes. In line with this, freshly isolated adipocytes of iBAT showed higher sphingomyelin content than those of inguinal white adipose tissue. Upon cold exposure, sphingomyelin abundance in iBAT gradually decreased in parallel with reduced sphingomyelin synthase 1 protein levels. Cold-exposed animals treated with an inhibitor of sphingomyelin hydrolases failed to maintain core body temperature and showed reduced oxygen consumption and iBAT UCP1 levels. Conversely, blockade of sphingomyelin synthetic enzymes resulted in enhanced nonshivering thermogenesis, reflected by elevated body temperature and UCP1 levels. Taken together, our results uncovered a relation between sphingomyelin abundance and fine-tuning of UCP1-mediated nonshivering thermogenesis.

Mass spectrometry-based methods for the advanced characterization and structural analysis of lignin: A review.

Lignin is currently one of the most promising biologically derived resources, due to its abundance and application in biofuels, materials and conversion to value aromatic chemicals. The need to better characterize and understand this complex biopolymer has led to the development of many different analytical approaches, several of which involve mass spectrometry and subsequent data analysis. This review surveys the most important analytical methods for lignin involving mass spectrometry, first looking at methods involving gas chromatography, liquid chromatography and then continuing with more contemporary methods such as matrix assisted laser desorption ionization and time-of-flight-secondary ion mass spectrometry. Following that will be techniques that directly ionize lignin mixtures-without chromatographic separation-using softer atmospheric ionization techniques that leave the lignin oligomers intact. Finally, ultra-high resolution mass analyzers such as FT-ICR have enabled lignin analysis without major sample preparation and chromatography steps. Concurrent with an increase in the resolution of mass spectrometers, there have been a wealth of complementary data analyses and visualization methods that have allowed researchers to probe deeper into the "lignome" than ever before. These approaches extract trends such as compound series and even important analytical information about lignin substructures without performing lignin degradation either chemically or during MS analysis. These innovative methods are paving the way for a more comprehensive understanding of this important biopolymer, as we seek more sustainable solutions for our human species' energy and materials needs.

Analysis of vitamin D metabolic markers by mass spectrometry: Recent progress regarding the "gold standard" method and integration into clinical practice.

Liquid chromatography/tandem mass spectrometry is firmly established today as the gold standard technique for analysis of vitamin D, both for vitamin D status assessments as well as for measuring complex and intricate vitamin D metabolic fingerprints. While the actual mass spectrometry technology has seen only incremental performance increases in recent years, there have been major, very impactful changes in the front- and back-end of MS-based vitamin D assays; for example, the extension to new types of biological sample matrices analyzed for an increasing number of different vitamin D metabolites, novel sample preparation techniques, new powerful chemical derivatization reagents, as well the continued integration of high resolution mass spectrometers into clinical laboratories, replacing established triple-quadrupole instruments. At the same time, the sustainability of mass spectrometry operation in the vitamin D field is now firmly established through proven analytical harmonization and standardization programs. The present review summarizes the most important of these recent developments.

Comparison of reversed-phase, hydrophilic interaction, and porous graphitic carbon chromatography columns for an untargeted toxicometabolomics study in pooled human liver microsomes, rat urine, and rat plasma.

INTRODUCTION: Untargeted metabolomics studies are expected to cover a wide range of compound classes with high chemical diversity and complexity. Thus, optimizing (pre-)analytical parameters such as the analytical liquid chromatography (LC) column is crucial and the selection of the column depends primarily on the study purpose. OBJECTIVES: The current investigation aimed to compare six different analytical columns. First, by comparing the chromatographic resolution of selected compounds. Second, on the outcome of an untargeted toxicometabolomics study using pooled human liver microsomes (pHLM), rat plasma, and rat urine as matrices. METHODS: Separation and analysis were performed using three different reversed-phase (Phenyl-Hexyl, BEH C18, and Gold C18), two hydrophilic interaction chromatography (HILIC) (ammonium-sulfonic acid and sulfobetaine), and one porous graphitic carbon (PGC) columns coupled to high-resolution mass spectrometry (HRMS). Their impact was evaluated based on the column performance and the size of feature count, amongst others. RESULTS: All three reversed-phase columns showed a similar performance, whereas the PGC column was superior to both HILIC columns at least for polar compounds. Comparing the size of feature count across all datasets, most features were detected using the Phenyl-Hexyl or sulfobetaine column. Considering the matrices, most significant features were detected in urine and pHLM after using the sulfobetaine and in plasma after using the ammonium-sulfonic acid column. CONCLUSION: The results underline that the outcome of this untargeted toxicometabolomic study LC-HRMS metabolomic study was highly influenced by the analytical column, with the Phenyl-Hexyl or sulfobetaine column being the most suitable. However, column selection may also depend on the investigated compounds as well as on the investigated matrix.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics.

INTRODUCTION: Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population. OBJECTIVES: This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs). METHODS: We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers. RESULTS: The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer.

BACKGROUND: Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum. METHODS: Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards. RESULTS: Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00). CONCLUSIONS: To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Implementation of a LC-MS based multi-attribute method (MAM) and intact multi-attribute method (iMAM) workflow for the characterisation of a GLP-Fc fusion protein.

Over the past few years, the implementation of mass spectrometry (MS) in QC laboratories has become a more common occurrence. The multi-attribute method (MAM), and emerging intact multi-attribute method (iMAM), are powerful analytical tools utilising liquid chromatography-mass spectrometry (LC-MS) methods that enable the monitoring of critical quality attributes (CQAs) in biotherapeutic proteins in compliant settings. Both MAM and iMAM are intended to replace or supplement several conventional assays with a single LC-MS method utilising MS data in combination with robust, semi-automated data processing workflows. MAM and iMAM workflows can also be implemented into current Good Manufacturing Practices environments due to the availability of CFR 11 compliant chromatography data system software. In this study, MAM and iMAM are employed for the analysis of 4 batches of a glucagon-like peptide-Fc fusion protein. MAM approach involved a first the discovery phase for the identification of CQAs and second, the target monitoring phase of the selected CQAs in other samples. New peak detection was performed on the data set to determine the appearance, absence or change of any peak. For native iMAM workflow both size exclusion and strong cation exchange chromatography were optimized for the identification and monitoring of CQAs at the intact level.

Qualification of a LC-HRMS platform method for biosimilar development using NISTmab as a model.

Biosimilars are a cost-effective alternative to biopharmaceuticals, necessitating rigorous analytical methods for consistency and compliance. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is a versatile tool for assessing key attributes, encompassing molecular mass, primary structure, and post-translational modifications (PTMs). Adhering to ICH Q2R1, we validated an LC-HRMS based peptide mapping method using NISTmab as a reference. The method validation parameters, covering system suitability, specificity, accuracy, precision, robustness, and carryover, were comprehensively assessed. The method effectively differentiated the NISTmab from similar counterparts as well as from artificially introduced spiked conditions. Notably, the accuracy of mass error for NISTmab specific complementarity determining region peptides was within a maximum of 2.42 parts per million (ppm) from theoretical and the highest percent relative standard deviation (%RSD) observed for precision was 0.000219 %. It demonstrates precision in sequence coverage and PTM detection, with a visual inspection of total ion chromatogram approach for variability assessment. The method maintains robustness when subjected to diverse storage conditions, encompassing variations in column temperature and mobile phase composition. Negligible carryover was noted during the carryover analysis. In summary, this method serves as a versatile platform for multiple biosimilar development by effectively characterizing and identifying monoclonal antibodies, ultimately ensuring product quality.

Unveiling the bioactive potential of Actinomycetota from the Tagus River estuary.

The increase in global travel and the incorrect and excessive use of antibiotics has led to an unprecedented rise in antibiotic resistance in bacterial and fungal populations. To overcome these problems, novel bioactive natural products must be discovered, which may be found in underexplored environments, such as estuarine habitats. In the present work, estuarine actinomycetotal strains were isolated with conventional and iChip techniques from the Tagus estuary in Alcochete, Portugal, and analysed for different antimicrobial bioactivities. Extracts were produced from the isolated cultures and tested for bioactivity against Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 25922, Aspergillus fumigatus ATCC 240305, Candida albicans ATCC 10231 and Trichophyton rubrum FF5. Furthermore, bioactive extracts were subjected to dereplication by high-performance liquid chromatography (HPLC) and high-resolution mass spectrometry (HRMS) to putatively identify their chemical components. In total, 105 isolates belonging to 3 genera were obtained. One which was isolated, MTZ3.1 T, represents a described novel taxon for which the name Streptomyces meridianus was proposed. Regarding the bioactivity testing, extracts from 12 strains proved to be active against S. aureus, 2 against E. coli, 4 against A. fumigatus, 3 against C. albicans and 10 against T. rubrum. Dereplication of bioactive extracts showed the presence of 28 known bioactive molecules, 35 hits have one or more possible matches in the DNP and 18 undescribed ones. These results showed that the isolated bacteria might be the source of new bioactive natural products.

Synthesis and Characterization of Organic Peroxides from Monoterpene-Derived Criegee Intermediates in Secondary Organic Aerosol.

Ozonolysis of alkenes is known to produce reactive intermediates─stabilized Criegee intermediates (SCIs), and their subsequent bimolecular reactions with various carboxylic acids can form α-acyloxyalkyl hydroperoxides (AAHPs), which is considered a major class of organic peroxides in secondary organic aerosol (SOA). Despite their atmospheric and health importance, the molecular-level identification of organic peroxides in atmospheric aerosols is highly challenging, preventing further assessment of their environmental fate. Here, we synthesize 20 atmospherically relevant AAHPs through liquid-phase ozonolysis, in which two types of monoterpene-derived SCIs from either α-pinene or 3-carene are scavenged by 10 different carboxylic acids to form AAHPs with diverse structures. These AAHPs are identified individually by liquid chromatography coupled with high-resolution mass spectrometry. AAHPs were previously thought to decompose quickly in an aqueous environment such as cloud droplets, but we demonstrate here that AAHPs hydrolysis rates are highly compound-dependent with rate constants differing by 2 orders of magnitude. In contrast, the aqueous-phase formation rate constants between SCI and various carboxylic acids vary only within a factor of 2-3. Finally, we identified two of the 20 synthesized AAHPs in α-pinene SOA and two in 3-carene SOA, contributing ∼0.3% to the total SOA mass. Our results improve the current molecular-level understanding of organic peroxides and are useful for a more accurate assessment of their environmental fate and health impact.

Hydrolysis of Antimicrobial Peptides by Extracellular Peptidases in Wastewater.

Several antimicrobial peptides (AMPs) are emerging as promising novel antibiotics. When released into wastewater streams after use, AMPs might be hydrolyzed and inactivated by wastewater peptidases─resulting in a reduced release of active antimicrobials into wastewater-receiving environments. A key step towards a better understanding of the fate of AMPs in wastewater systems is to investigate the activity and specificity of wastewater peptidases. Here, we quantified peptidase activity in extracellular extracts from different stages throughout the wastewater treatment process. For all four tested municipal wastewater treatment plants, we detected highest activity in raw wastewater. Complementarily, we assessed the potential of enzymes in raw wastewater extracts to biotransform 10 selected AMPs. We found large variations in the susceptibility of AMPs to enzymatic transformation, indicating substantial substrate specificity of extracted enzymes. To obtain insights into peptidase specificities, we searched for hydrolysis products of rapidly biotransformed AMPs and quantified selected products using synthetic standards. We found that hydrolysis occurred at specific sites and that these sites were remarkably conserved across the four tested wastewaters. Together, these findings provide insights into the fate of AMPs in wastewater systems and can inform the selection and design of peptide-based antibiotics that are hydrolyzable by wastewater peptidases.

Nontarget Identification of Novel Organophosphorus Flame Retardants and Plasticizers in Indoor Air and Dust from Multiple Microenvironments in China.

The indoor environment is a typical source for organophosphorus flame retardants and plasticizers (OPFRs), yet the source characteristics of OPFRs in different microenvironments remain less clear. This study collected 109 indoor air samples and 34 paired indoor dust samples from 4 typical microenvironments within a university in Tianjin, China, including the dormitory, office, library, and information center. 29 target OPFRs were analyzed, and novel organophosphorus compounds (NOPs) were identified by fragment-based nontarget analysis. Target OPFRs exhibited the highest air and dust concentrations of 46.2-234 ng/m3 and 20.4-76.0 µg/g, respectively, in the information center, where chlorinated OPFRs were dominant. Triphenyl phosphate (TPHP) was the primary OPFR in office air, while tris(2-chloroethyl) phosphate dominated in the dust. TPHP was predominant in the library. Triethyl phosphate (TEP) was ubiquitous in the dormitory, and tris(2-butoxyethyl) phosphate was particularly high in the dust. 9 of 25 NOPs were identified for the first time, mainly from the information center and office, such as bis(chloropropyl) 2,3-dichloropropyl phosphate. Diphenyl phosphinic acid, two hydroxylated and methylated metabolites of tris(2,4-ditert-butylphenyl) phosphite (AO168), and a dimer phosphate were newly reported in the indoor environment. NOPs were widely associated with target OPFRs, and their human exposure risk and environmental behaviors warrant further study.

Quantitative Non-targeted Screening to Profile Micropollutants in Sewage Sludge Used for Agricultural Field Amendments.

A considerable number of micropollutants from human activities enter the wastewater network for removal. However, at the wastewater treatment plant (WWTP), some proportion of these compounds is retained in the sewage sludge (biosolids), and due to its high content of nutrients, sludge is widely applied as an agricultural fertilizer and becomes a means for the micropollutants to be introduced to the environment. Accordingly, a holistic semiquantitative nontarget screening was performed on sewage sludges from five different WWTPs using nanoflow liquid chromatography coupled to high-resolution Orbitrap mass spectrometry. Sixty-one inorganic elements were measured using inductively coupled plasma mass spectrometry. Across all sludges, the nontarget analysis workflow annotated >21,000 features with chemical structures, and after strict prioritization and filtering, 120 organic micropollutants with diverse chemical structures and applications such as pharmaceuticals, pesticides, flame retardants, and industrial and natural compounds were identified. None of the tested sludges were free from organic micropollutants. Pharmaceuticals contributed the largest share followed by pesticides and natural products. The predicted concentration of identified contaminants ranged between 0.2 and 10,881 ng/g dry matter. Through quantitative nontarget analysis, this study comprehensively demonstrated the occurrence of cocktails of micropollutants in sewage sludges.

Application of Nontarget High-Resolution Mass Spectrometry Fingerprints for Qualitative and Quantitative Source Apportionment: A Real Case Study.

High-resolution mass spectrometry (HRMS) provides extensive chemical data, facilitating the differentiation and quantification of contaminants of emerging concerns (CECs) in aquatic environments. This study utilizes liquid chromatography-HRMS for source apportionment in Chebei Stream, an urban water stream in Guangzhou, South China. Initially, 254 features were identified as potential CECs by the nontarget screening (NTS) method. We then established 1689, 1317, and 15,759 source-specific HRMS fingerprints for three distinct sources, the mainstream (C3), the tributary (T2), and the rain runoff (R1), qualitatively assessing the contribution from each source downstream. Subsequently, 32, 55, and 3142 quantitative fingerprints were isolated for sites C3, T2, and R1, respectively, employing dilution curve screening for source attribution. The final contribution estimates downstream from sites C3, T2, and R1 span 32-96, 12-23, and 8-23%, respectively. Cumulative contributions from these sources accurately mirrored actual conditions, fluctuating between 103 and 114% across C6 to C8 sites. Yet, with further tributary integration, the overall source contribution dipped to 52%. The findings from this research present a pioneering instance of applying HRMS fingerprints for qualitative and quantitative source tracking in real-world scenarios, which empowers the development of more effective strategies for environmental protection.

Identification of Emerging Per- and Polyfluoroalkyl Substances (PFAS) in E-waste Recycling Practices and New Precursors for Trifluoroacetic Acid.

Electronic waste is an emerging source of per- and polyfluoroalkyl substance (PFAS) emissions to the environment, yet the contribution from hazardous recycling practices in the South Asian region remains unclear. This study detected 41 PFAS in soil samples from e-waste recycling sites in Pakistan and the total concentrations were 7.43-367 ng/g dry weight (dw) (median: 37.7 ng/g dw). Trifluoroacetic acid (TFA) and 6:2 fluorotelomer sulfonic acid emerged as the dominant PFAS, constituting 49% and 13% of the total PFAS concentrations, respectively. Notably, nine CF3-containing emerging PFAS were identified by the high-resolution mass spectrometry (HRMS)-based screening. Specifically, hexafluoroisopropanol and bistriflimide (NTf2) were consistently identified across all the samples, with quantified concentrations reaching up to 854 and 90 ng/g dw, respectively. This suggests their potential association with electronic manufacturing and recycling processes. Furthermore, except for NTf2, all the identified emerging PFAS were confirmed as precursors of TFA with molar yields of 8.87-40.0% by the TOP assay validation in Milli-Q water. Overall, this study reveals significant emission of PFAS from hazardous e-waste recycling practices and emphasizes the identification of emerging sources of TFA from precursor transformation, which are essential for PFAS risk assessment.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review.

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments.

Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typically rely on an apical and/or single endpoint, providing limited diagnostic potential to guide chemical prioritization. We proposed an event-driven taxonomy framework for mixture risk assessment that relied on high-throughput screening bioassays and toxicant identification integrated by deep learning. In this work, the framework was evaluated using chemical mixtures in sediments eliciting aryl-hydrocarbon receptor activation and oxidative stress response. Mixture prediction using target analysis explained <10% of observed sediment bioactivity. To identify additional contaminants, two deep learning models were developed to predict fingerprints of a pool of bioactive substances (event driver fingerprint, EDFP) and convert these candidates to MS-readable information (event driver ion, EDION) for nontarget analysis. Two libraries with 121 and 118 fingerprints were established, and 247 bioactive compounds were identified at confidence level 2 or 3 in sediment extract using GC-qToF-MS. Among them, 12 toxicants were analytically confirmed using reference standards. Collectively, we present a "bioactivity-signature-toxicant" strategy to deconvolute mixtures and to connect patchy data sets and guide nontarget analysis for diverse chemicals that elicit the same bioactivity.

A comprehensive study on the identification and characterization of major degradation products of synthetic liraglutide using liquid chromatography-high resolution mass spectrometry.

Liraglutide (LGT) is a synthetic glucagon-like peptide-1 analogue mainly used for the treatment of type-2 diabetes or obesity. Comprehensive stability testing is essential in the development and routine quality control of synthetic therapeutic peptide pharmaceuticals. The GLP-1 peptide drugs are usually formulated in aqueous-base solution, which can generate stability issues during manufacturing, storage or shipment. The current study endeavors to observe the chemical stability behavior of LGT by exposing the drug substance to oxidative and hydrolytic stress conditions. A simple liquid chromatography (LC) method was developed where sufficient resolution between LGT and the generated degradation products was achieved. In total, 19 degradation products (DPs) were separated under acidic, basic and oxidative stress conditions. Using LC-HRMS, MS/MS studies, the generated degradation products were identified and characterized. The mechanistic fragmentation pathway for all generated DPs were established and the plausible chemical structure for the identified DPs was predicted based on MS/MS data. The results strongly suggest that LGT is highly susceptible to degrade under oxidative and hydrolytic conditions. Furthermore, this study provides insights into the hydrolytic and oxidative stability of LGT, which can be implied during generic and novel formulation drug development and discovery in synthesizing relatively stable GLP-1 analogues.

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances.

Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration "surrogates," which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from "global" chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using "global" surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using "expert-selected" surrogates (n = 3) instead of "global" surrogates (n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases.

Suspect screening for chemical residues in aquacultured shrimp and fish using liquid chromatography-high resolution mass spectrometry: comparison of data evaluation approaches.

High-resolution mass spectrometry (HRMS) has become an important tool for monitoring chemical residues in food, but the time and effort required to evaluate the large amount of data generated by HRMS can be a limiting factor in the widespread application of this tool. Suspect screening, i.e., searching HRMS data against large compound databases or mass lists, represents a practical compromise between using HRMS data to only look for target compounds and performing full non-target analysis. Several different approaches for suspect screening using HRMS data were tested using data from shrimp and eel spiked with veterinary drugs and pesticides as well as from imported aquaculture samples. Most of the analytes (>70%) in the spiked samples were detected and identified by searching against compound databases. To query larger databases and on-line resources such as mzCloud, it was necessary to use software capable of differential analysis and selective filtering, such as Compound Discoverer. Using selective filtering, the number of compounds detected in fish sample extracts could be reduced from tens of thousands to a few hundred by subtracting method blanks and comparing to matrix blank extracts. This smaller list of potential compounds could be further evaluated and compared to available databases and libraries. Analysis of imported aquaculture samples resulted in detection of unexpected contaminants including the dewormer levamisole, the insecticide buprofezin, and potentially the plant alkaloid ricinine.