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.

Prioritization of the Secondary Metabolites for the Rapid Annotation Based on Liquid Chromatography-High Resolution Mass Spectrometry Assessment: Varanasine and Schroffanone from Murraya paniculata and Cytotoxic Evaluation.

The liquid chromatography-high resolution mass spectrometry (LC-HRMS) technique enables the detection of phytochemicals present in the extracts. LC-HRMS-generated mass list showed abundant compounds of interest, artifacts, and primary metabolites. The identification of a secondary metabolite of interest within the extract is very challenging. We hypothesized that identifying the "new metabolite" in the whole metabolome is more challenging than identifying it within the class of metabolites. The proposed prioritization strategy focused on the elimination of unknown and prioritizing the known class of secondary metabolites to identify new metabolites. The prioritization strategy demonstrated on Murraya paniculata for the identification of new metabolites. LC-HRMS-generated information is used as a filter to target the secondary metabolite and the new metabolites. This strategy successfully annotated the new coumarin and coumarin alkaloids from the mass list of 1448 metabolites. Varanasine (3), schroffanone (4), schroffanene (5), and O-methylmurraol (9) are new compounds, and coumarin (1, 2, and 6-8) are known. Varanasine (3) is the first naturally occurring 7-aminocoumarin with additional N-formyl functionality. The isolates were screened for cytotoxicity against the panel of cancer cell lines. Varanasine (3) and minumicrollin (6) showed significant cytotoxicity and apoptosis-inducing potential. The immunoblot analysis confirmed inhibition of apoptotic protein PARP-1 and caspase-3 expression by 3 and 6.

Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues.

Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.

Anti-inflammatory potential of aspergillus unguis SP51-EGY: TLR4-dependent effects & chemical diversity via Q-TOF LC-HRMS.

Inflammation serves as an intricate defense mechanism for tissue repair. However, overactivation of TLR4-mediated inflammation by lipopolysaccharide (LPS) can lead to detrimental outcomes such as sepsis, acute lung injury, and chronic inflammation, often associated with cancer and autoimmune diseases. This study delves into the anti-inflammatory properties of "Aspergillus unguis isolate SP51-EGY" on LPS-stimulated RAW 264.7 macrophages. Through real-time qPCR, we assessed the expression levels of pivotal inflammatory genes, including iNOS, COX-2, TNF-α, and IL-6. Remarkably, our fungal extracts significantly diminished NO production and showed noteworthy reductions in the mRNA expression levels of the aforementioned genes. Furthermore, while Nrf2 is typically associated with modulating inflammatory responses, our findings indicate that the anti-inflammatory effects of our extracts are not Nrf2-dependent. Moreover, the chemical diversity of the potent extract (B Sh F) was elucidated using Q-TOF LC-HRMS, identifying 54 compounds, some of which played vital roles in suppressing inflammation. Most notably, compounds like granisetron, fenofibrate, and umbelliprenin were found to downregulate TNF-α, IL-1ß, and IL-6 through the NF-κB signaling pathway. In conclusion, "Aspergillus unguis isolate SP51-EGY", isolated from the Red Sea, Egypt, has been unveiled as a promising TLR4 inhibitor with significant anti-inflammatory potentials, presenting novel insights for their potential therapeutic use in inflammation.

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.

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.

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.

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.

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.

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.

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.

Molecular Insights into Gas-Particle Partitioning and Viscosity of Atmospheric Brown Carbon.

Biomass burning organic aerosol (BBOA), containing brown carbon chromophores, plays a critical role in atmospheric chemistry and climate forcing. However, the effects of evaporation on BBOA volatility and viscosity under different environmental conditions remain poorly understood. This study focuses on the molecular characterization of laboratory-generated BBOA proxies from wood pyrolysis emissions. The initial mixture, "pyrolysis oil (PO1)", was progressively evaporated to produce more concentrated mixtures (PO1.33, PO2, and PO3) with volume reduction factors of 1.33, 2, and 3, respectively. Chemical speciation and volatility were investigated using temperature-programmed desorption combined with direct analysis in real-time ionization and high-resolution mass spectrometry (TPD-DART-HRMS). This novel approach quantified saturation vapor pressures and enthalpies of individual species, enabling the construction of volatility basis set distributions and the quantification of gas-particle partitioning. Viscosity estimates, validated by poke-flow experiments, showed a significant increase with evaporation, slowing particle-phase diffusion and extending equilibration times. These findings suggest that highly viscous tar ball particles in aged biomass burning emissions form as semivolatile components evaporate. The study highlights the importance of evaporation processes in shaping BBOA properties, underscoring the need to incorporate these factors into atmospheric models for better predictions of BBOA aging and its environmental impact.

Evaluation of Nontargeted Mass Spectral Data Acquisition Strategies for Water Analysis and Toxicity-Based Feature Prioritization by MS2Tox.

The machine-learning tool MS2Tox can prioritize hazardous nontargeted molecular features in environmental waters, by predicting acute fish lethality of unknown molecules based on their MS2 spectra, prior to structural annotation. It has yet to be investigated how the extent of molecular coverage, MS2 spectra quality, and toxicity prediction confidence depend on sample complexity and MS2 data acquisition strategies. We compared two common nontargeted MS2 acquisition strategies with liquid chromatography high-resolution mass spectrometry for structural annotation accuracy by SIRIUS+CSI:FingerID and MS2Tox toxicity prediction of 191 reference chemicals spiked to LC-MS water, groundwater, surface water, and wastewater. Data-dependent acquisition (DDA) resulted in higher rates (19-62%) of correct structural annotations among reference chemicals in all matrices except wastewaters, compared to data-independent acquisition (DIA, 19-50%). However, DIA resulted in higher MS2 detection rates (59-84% DIA, 37-82% DDA), leading to higher true positive rates for spectral library matching, 40-73% compared to 34-72%. DDA resulted in higher MS2Tox toxicity prediction accuracy than DIA, with root-mean-square errors of 0.62 and 0.71 log-mM, respectively. Given the importance of MS2 spectral quality, we introduce a "CombinedConfidence" score to convey relative confidence in MS2Tox predictions and apply this approach to prioritize potentially ecotoxic nontargeted features in environmental waters.