PolyMatch: Novel Libraries, Algorithms, and Visualizations for Discovering Polymers and Chemical Series.

Polymers are integral components of everyday products, ranging from plastics and emulsifiers to lubricants and detergents. Characterization of these materials at the molecular level is essential to understanding their physicochemical properties and potential health impacts, considering factors such as the number of repeating units, chemical moieties, functional groups, and degree of unsaturation. This study introduces a free open-source vendor neutral software, PolyMatch, designed to annotate polysorbates, polysorbides, polyethylene glycols (PEGs), fatty acid esterified species, and related chemical species based on mass spectral and chromatographic patterns inherent in the repeating nature of chemical moieties. PolyMatch facilitates the generation of MS/MS libraries for polymeric chemical species characterization (with over 800 000 structures with associated fragment masses already built in) and covers the entire liquid chromatography-high-resolution mass spectrometry (LC-HRMS/MS) data-processing workflow. PolyMatch covers peak picking, blank filtering, annotation, data visualization, and sharing of interactive data sets via an HTML link to the community. The software was applied to a Tween 80 mixture, using LC-HRMS/MS on an Agilent 6546 Q-TOF instrument with iterative exclusion for comprehensive fragmentation coverage. PolyMatch automatically assigned 86 features with high confidence at the species level, 362 based on PEG containing fragments and accurate mass matching to a simulated polymer database, and over 10 000 based on being a member of a homologous series (three or more) with CH2CH2O repeating units. The ease of use of PolyMatch and comprehensive coverage with species level assignment is expected to contribute to the advancement of materials science, health research, and product development.

Assessment of wood smoke induced pulmonary toxicity in normal- and chronic bronchitis-like bronchial and alveolar lung mucosa models at air-liquid interface.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) has the highest increased risk due to household air pollution arising from biomass fuel burning. However, knowledge on COPD patho-mechanisms is mainly limited to tobacco smoke exposure. In this study, a repeated direct wood smoke (WS) exposure was performed using normal- (bro-ALI) and chronic bronchitis-like bronchial (bro-ALI-CB), and alveolar (alv-ALI) lung mucosa models at air-liquid interface (ALI) to assess broad toxicological end points. METHODS: The bro-ALI and bro-ALI-CB models were developed using human primary bronchial epithelial cells and the alv-ALI model was developed using a representative type-II pneumocyte cell line. The lung models were exposed to WS (10 min/exposure; 5-exposures over 3-days; n = 6-7 independent experiments). Sham exposed samples served as control. WS composition was analyzed following passive sampling. Cytotoxicity, total cellular reactive oxygen species (ROS) and stress responsive NFkB were assessed by flow cytometry. WS exposure induced changes in gene expression were evaluated by RNA-seq (p ≤ 0.01) followed by pathway enrichment analysis. Secreted levels of proinflammatory cytokines were assessed in the basal media. Non-parametric statistical analysis was performed. RESULTS: 147 unique compounds were annotated in WS of which 42 compounds have inhalation toxicity (9 very high). WS exposure resulted in significantly increased ROS in bro-ALI (11.2%) and bro-ALI-CB (25.7%) along with correspondingly increased NFkB levels (bro-ALI: 35.6%; bro-ALI-CB: 18.1%). A total of 1262 (817-up and 445-down), 329 (141-up and 188-down), and 102 (33-up and 69-down) genes were differentially regulated in the WS-exposed bro-ALI, bro-ALI-CB, and alv-ALI models respectively. The enriched pathways included the terms acute phase response, mitochondrial dysfunction, inflammation, oxidative stress, NFkB, ROS, xenobiotic metabolism of AHR, and chronic respiratory disorder. The enrichment of the 'cilium' related genes was predominant in the WS-exposed bro-ALI (180-up and 7-down). The pathways primary ciliary dyskinesia, ciliopathy, and ciliary movement were enriched in both WS-exposed bro-ALI and bro-ALI-CB. Interleukin-6 and tumor necrosis factor-α were reduced (p < 0.05) in WS-exposed bro-ALI and bro-ALI-CB. CONCLUSION: Findings of this study indicate differential response to WS-exposure in different lung regions and in chronic bronchitis, a condition commonly associated with COPD. Further, the data suggests ciliopathy as a candidate pathway in relation to WS-exposure.

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon.

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor-fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome.

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Novel perfluoroalkyl substances (PFAS) discovered in whole blood using automated non-targeted analysis of dried blood spots.

A small subset of per- and polyfluoroalkyl substances (PFAS) are routinely screened in human blood. These compounds generally explain <50 % of the total PFAS in human blood. The percentage of known PFAS in human blood has been decreasing as replacement PFAS and more complex PFAS chemistries are introduced to the market. Most of these novel PFAS have not been previously identified. Non-targeted methods are required to characterize this "dark matter" PFAS. Our objective was to apply non-targeted PFAS analysis to human blood to gain an understanding about the sources, concentrations, and toxicity of these compounds. A high-resolution tandem mass spectrometry (HRMS) and software workflow for PFAS characterization in dried blood spots is reported. Dried blood spots are a less invasive collection technique compared to venous blood draws, allowing collection from vulnerable populations. Biorepositories of archived dried blood spots are available internationally from newborns and present opportunities to study prenatal exposure to PFAS. In this study, dried blood spot cards were analyzed using iterative MS/MS by liquid chromatography HRMS. Data processing was conducted using FluoroMatch Suite including a visualizer tool that presents homologous series, retention time vs m/z plots, MS/MS spectra, feature tables, annotations, and fragments for fragment screening. The researcher performing data-processing and annotation was blinded to the fact that standards were spiked in, and was able to annotate 95 % of standards spiked on dried blood spot samples, signifying a low false negative rate using FluoroMatch Suite. A total of 28 PFAS (20 standards and 4 exogenous compounds) were detected across five homologous series with Schymanski Level 2 confidence. Of these 4, 3 were perfluoroalkyl ether carboxylic acids (PFECA), a chemical class of PFAS which is increasingly being detected in environmental and biological matrices but is not currently screened in most targeted analysese. A further 86 potential PFAS were detected using fragment screening. PFAS are extremely persistent and widespread yet remain largely unregulated. Our findings will contribute to an improved an understanding of exposures. Application of these methods in environmental epidemiology studies have the potential to inform policy with regards to PFAS monitoring, regulation, and individual-level mitigation strategies.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions.

PURPOSE OF REVIEW: We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale. RECENT FINDINGS: Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Characterizing the external exposome using passive samplers-comparative assessment of chemical exposures using different wearable form factors.

BACKGROUND: Organic contaminants are released into the air from building materials/furnishings, personal care, and household products. Wearable passive samplers have emerged as tools to characterize personal chemical exposures. The optimal placement of these samplers on an individual to best capture airborne exposures has yet to be evaluated. OBJECTIVE: To compare personal exposure to airborne contaminants detected using wearable passive air samplers placed at different positions on the body. METHODS: Participants (n = 32) simultaneously wore four passive Fresh Air samplers, on their head, chest, wrist, and foot for 24 hours. Exposure to 56 airborne organic contaminants was evaluated using thermal desorption gas chromatography high resolution mass spectrometry with a targeted data analysis approach. RESULTS: Distinct exposure patterns were detected by samplers positioned on different parts of the body. Chest and wrist samplers were the most similar with correlations identified for 20% of chemical exposures (Spearman's Rho > 0.8, p < 0.05). In contrast, the greatest differences were found for head and foot samplers with the weakest correlations across evaluated exposures (8% compounds, Spearman's Rho > 0.8, p < 0.05). SIGNIFICANCE: The placement of wearable passive air samplers influences the exposures captured and should be considered in future exposure and epidemiological studies. IMPACT STATEMENT: Traditional approaches for assessing personal exposure to airborne contaminants with active samplers presents challenges due to their cost, size, and weight. Wearable passive samplers have recently emerged as a non-invasive, lower cost tool for measuring environmental exposures. While these samplers can be worn on different parts of the body, their position can influence the type of exposure that is captured. This study comprehensively evaluates the exposure to airborne chemical contaminants measured at different passive sampler positions worn on the head, chest, wrist, and foot. Findings provide guidance on sampler placement based on chemicals and emission sources of interest.

An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry.

Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.

Personal air pollutant exposure monitoring in South African children in the VHEMBE birth cohort.

The burden of disease associated with environmental exposures disproportionately impacts residents of low- and middle-income countries. Children living in rural regions of these countries may experience higher exposure to insecticides from indoor residual spraying used for malaria control and household air pollution. This study evaluated environmental exposures of children living in a rural region of South Africa. Quantifying exposure levels and identifying characteristics that are associated with exposure in this geographic region has been challenging due to limitations with available monitoring techniques. Wearable passive samplers have recently been shown to be a convenient and reliable tool for assessing personal exposures. In this study, a passive sampler wristband, known as Fresh Air wristband, was worn by 49 children (five-years of age) residing in the Limpopo province of South Africa. The study leveraged ongoing research within the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE) birth cohort. A wide range of chemicals (35 in total) were detected using the wristbands, including polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides, phthalates, and organophosphate esters (OPEs) flame retardants. Higher concentrations of PAHs were observed among children from households that fell below the food poverty threshold, did not have access to electric cookstoves/burners, or reported longer times of cooking or burning materials during the sampling period. Concentrations of p,p'-DDD and p,p'-DDT were also found to be elevated for children from households falling below the food poverty threshold as well as for children whose households were sprayed for malaria control within the previous 1.5 years. This study demonstrates the feasibility of using passive sampler wristbands as a non-invasive method for personal exposure assessment of children in rural regions of South Africa to complex mixtures environmental contaminants derived from a combination of sources. Future studies are needed to further identify and understand the effects of airborne environmental contaminants on childhood development and strategies to mitigate exposures.

Occurrence and contamination profile of legacy and emerging per- and polyfluoroalkyl substances (PFAS) in Belgian wastewater using target, suspect and non-target screening approaches.

With the growing concern regarding the health risks of per- and polyfluoroalkyl substances (PFAS), there is an increasing demand for the identification of emerging PFAS. This study provides a comprehensive investigation of legacy and emerging PFAS in 16 wastewater treatment plants (WWTPs) in Belgium using target, suspect, and non-target screening methods. Perfluorobutanoic acid (PFBA) and perfluoropentanoic acid (PFPeA) were the dominant compounds in most locations, whereas perfluorooctanoic acid (PFOA) was the most predominant PFAS in WWTP Deurne (Antwerp region). Using a suspect screening approach, 14 PFAS were annotated as confidence level (CL) of 4 or higher and 4 PFAS were annotated as CL 2a and 2b, including aqueous film forming foam (AFFF)-derived PFAS. The compound group of n:3 unsaturated fluorotelomer carboxylic acid was found using non-target screening in the wastewater from WWTP Deurne. Population exposure in a catchment area estimated using population-normalized mass loads (PNML) showed the highest value in the catchment area of WWTP Deurne, implying a potentially higher exposure to PFAS in this community.

Assessing the External Exposome Using Wearable Passive Samplers and High-Resolution Mass Spectrometry among South African Children Participating in the VHEMBE Study.

Children in low- and middle-income countries are often exposed to higher levels of chemicals and are more vulnerable to the health effects of air pollution. Little is known about the diversity, toxicity, and dynamics of airborne chemical exposures at the molecular level. We developed a workflow employing state-of-the-art wearable passive sampling technology coupled with high-resolution mass spectrometry to comprehensively measure 147 children's personal exposures to airborne chemicals in Limpopo, South Africa, as part of the Venda Health Examination of Mothers, Babies, and Their Environment (VHEMBE). 637 environmental exposures were detected, many of which have never been measured in this population; of these 50 airborne chemical exposures of concern were detected, including pesticides, plasticizers, organophosphates, dyes, combustion products, and perfumes. Biocides detected in wristbands included p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), propoxur, piperonyl butoxide, and triclosan. Exposures differed across the assessment period with 27% of detected chemicals observed to be either higher or lower in the wet or dry seasons.

Changes in Sewage Sludge Chemical Signatures During a COVID-19 Community Lockdown, Part 1: Traffic, Drugs, Mental Health, and Disinfectants.

The early months of the COVID-19 pandemic and the associated shutdowns disrupted many aspects of daily life and thus caused changes in the use and disposal of many types of chemicals. While records of sales, prescriptions, drug overdoses, and so forth provide data about specific chemical uses during this time, wastewater and sewage sludge analysis can provide a more comprehensive overview of chemical changes within a region. We analyzed primary sludge from a wastewater-treatment plant in Connecticut, USA, collected March 19 to June 30, 2020. This time period encompassed the first wave of the pandemic, the initial statewide stay at home order, and the first phase of reopening. We used liquid chromatography-high-resolution mass spectrometry and targeted and suspect screening strategies to identify 78 chemicals of interest, which included pharmaceuticals, illicit drugs, disinfectants, ultraviolet (UV) filters, and others. We analyzed trends over time for the identified chemicals using linear trend analyses and multivariate comparisons (p < 0.05). We found trends related directly to the pandemic (e.g., hydroxychloroquine, a drug publicized for its potential to treat COVID-19, had elevated concentrations in the week following the implementation of the US Emergency Use Authorization), as well as evidence for seasonal changes in chemical use (e.g., increases for three UV-filter compounds). Though wastewater surveillance during the pandemic has largely focused on measuring severe acute respiratory syndrome-coronavirus-2 RNA concentrations, chemical analysis can also show trends that are important for revealing the public and environmental health effects of the pandemic. Environ Toxicol Chem 2022;41:1179-1192. © 2021 SETAC.

FluoroMatch 2.0-making automated and comprehensive non-targeted PFAS annotation a reality.

Because of the pervasiveness, persistence, and toxicity of per- and polyfluoroalkyl substances (PFAS), there is growing concern over PFAS contamination, exposures, and health effects. The diversity of potential PFAS is astounding, with nearly 10,000 PFAS catalogued in databases to date (and growing). The ability to detect the thousands of known PFAS, and discover previously uncatalogued PFAS, is necessary to understand the scope of PFAS contamination and to identify appropriate remediation and regulatory solutions. Current non-targeted methods for PFAS analysis require manual curation and are time-consuming, prone to error, and not comprehensive. FluoroMatch Flow 2.0 is the first software to cover all steps of data processing for PFAS discovery in liquid chromatography-high-resolution tandem mass spectrometry samples. These steps include feature detection, feature blank filtering, exact mass matching to catalogued PFAS, mass defect filtering, homologous series detection, retention time pattern analysis, class-based MS/MS screening, fragment screening, and predicted MS/MS from SMILES structures. In addition, a comprehensive confidence level criterion is implemented to help users understand annotation certainty and integrate various layers of evidence to reduce overreporting. Applying the software to aqueous film forming foam analysis, we discovered over one thousand likely PFAS including previously unreported species. Furthermore, we were able to filter out 96% of features which were likely not PFAS. FluoroMatch Flow 2 increased coverage of likely PFAS by over tenfold compared to the previous release. This software will enable researchers to better characterize PFAS in the environment and in biological systems.

Lipidomics and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage.

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

Optimization of a liquid chromatography-ion mobility-high resolution mass spectrometry platform for untargeted lipidomics and application to HepaRG cell extracts.

Analytical methods to evaluate the lipidome of biological samples need to provide high data quality to ensure comprehensive profiling and reliable structural elucidation. In this perspective, liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art technique for lipidomic analysis of biological samples. There are thousands of lipids in most biological samples, and therefore separation methods before introduction to the mass spectrometer is key for relative quantitation and identification. Chromatographic methods differ across laboratories, without any consensus on the best methodologies. Therefore, we designed an experiment to determine the optimal LC methodology, and assessed the value of ion mobility for an additional dimension of separation. To apply an untargeted method for hypothesis generation focused on lipidomics, LC-HRMS parameters were optimized based on the measurement of 50 panel lipids covering key human metabolic pathways. Reversed-phase liquid chromatography columns were compared based on a quality scoring system considering the signal-to-noise ratio, peak shape, and retention factor. Furthermore, drift tube ion mobility spectrometry (DTIMS) was implemented to increase peak capacity and confidence during annotation by providing collision cross section (CCS) values for the analytes under investigation. However, hyphenating DTIMS to LC-HRMS may result in a reduced sensitivity due to impaired duty cycles. To increase the signal intensity, a Box-Behnken design (BBD) was used to optimize four key factors, i.e. drift entrance voltage, drift exit voltage, rear funnel entrance, and rear funnel exit voltages. Application of a maximized desirability function provided voltages for the above-mentioned parameters resulting in higher signal intensity compared to each combination of parameters used during the BBD. In addition, the influence of single pulse and Hadamard 4-bit multiplexed modes on signal intensity was explored and different trap filling and release times of ions were evaluated. The optimized LC-DTIM-HRMS platform was applied to extracts from HepaRG cells and resulted in 3912 high-quality features (<30% median relative standard deviation; n = 6, t = 24 h). From these features, 436 lipid species could be annotated (i.e., matching based on accurate mass <5 ppm, isotopic pattern, in-silico MS/MS fragmentation, and in-silico CCS database matching <3%). The application of LC-DTIM-HRMS for untargeted analysis workflows is growing and the platform optimization, as described here, can be used to guide the method development and CCS database comparison for high confidence lipid annotation.

Exploring personal chemical exposures in China with wearable air pollutant monitors: A repeated-measure study in healthy older adults in Jinan, China.

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p < 0.05). Specifically, dimethyl phthalate (rs = 0.31) decreased as temperatures declined, while nitrobenzene (rs = -0.35) and naphthalene (rs = -0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p < 0.05) and hexachlorobutadiene was lower across participants (p < 0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements.

A Novel Technique for Redox Lipidomics Using Mass Spectrometry: Application on Vegetable Oils Used to Fry Potatoes.

Vegetables oils, rich in polyunsaturated fatty acids, are vulnerable to oxidation during manufacturing, processing, and food preparation. Currently, individual oxidation products are not well characterized, and hence, the health impacts of these unique lipid species remain unknown. Here, we introduce an extensive oxidized lipidomics in silico tandem mass spectrometry library and integrate these libraries within a user-friendly software covering a comprehensive redox lipidomics workflow. We apply this workflow to olive, soy, and walnut cooking oil; comparing unheated oil, oil after deep frying potatoes, and oil after oven frying potatoes. We annotated over a thousand oxidized triglycerides across 273 features (many coeluted). This software was validated against traditional chemical assays of oxidation, known oxidized lipids in castor oil, synthesized standards, and an alternate software LPPtiger. Development of these new software programs for redox lipidomics opens the door to characterize health implications of individual oxidation products.

Evolution of the liver biopsy and its future.

Liver biopsies are commonly used to evaluate a wide variety of medical disorders, including neoplasms and post-transplant complications. However, its use is being impacted by improved clinical diagnosis of disorders, and non-invasive methods for evaluating liver tissue and as a result the indications of a liver biopsy have undergone major changes in the last decade. The evolution of highly effective treatments for some of the common indications for liver biopsy in the last decade (e.g., viral hepatitis B and C) has led to a decline in the number of liver biopsies in recent years. At the same time, the emergence of better technologies for histologic evaluation, tissue content analysis and genomics are among the many new and exciting developments in the field that hold great promise for the future and are going to shape the indications for a liver biopsy in the future. Recent advances in slide scanners now allow creation of "digital/virtual" slides that have image of the entire tissue section present in a slide [whole slide imaging (WSI)]. WSI can now be done very rapidly and at very high resolution, allowing its use in routine clinical practice. In addition, a variety of technologies have been developed in recent years that use different light sources and/or microscopes allowing visualization of tissues in a completely different way. One such technique that is applicable to liver specimens combines multiphoton microscopy (MPM) with advanced clearing and fluorescent stains known as Clearing Histology with MultiPhoton Microscopy (CHiMP). Although it has not yet been extensively validated, the technique has the potential to decrease inefficiency, reduce artifacts, and increase data while being readily integrable into clinical workflows. Another technology that can provide rapid and in-depth characterization of thousands of molecules in a tissue sample, including liver tissues, is matrix assisted laser desorption/ionization (MALDI) mass spectrometry. MALDI has already been applied in a clinical research setting with promising diagnostic and prognostic capabilities, as well as being able to elucidate mechanisms of liver diseases that may be targeted for the development of new therapies. The logical next step in huge data sets obtained from such advanced analysis of liver tissues is the application of machine learning (ML) algorithms and application of artificial intelligence (AI), for automated generation of diagnoses and prognoses. This review discusses the evolving role of liver biopsies in clinical practice over the decades, and describes newer technologies that are likely to have a significant impact on how they will be used in the future.