Recent developments in environmental research have focused on the cumulative effects of the total environment on human metabolism and health state. The fundamental discipline, Exposure Science, is now being established as an academic specialty distinct from toxicology, epidemiology, and biology. (1) Exposure Science has been defined as studying “...human contact with chemical, physical, or biological agents occurring in their environments, (to) advance knowledge of the mechanisms and dynamics of events either causing or preventing adverse health outcomes...” and is considered the “...bedrock for protection of public health”. (2-4) In short, Exposure Science encompasses the study of the external environment’s contributions to the human system as well as the chemicals already present within human biological media; these are collectively referred to as the human exposome. (5, 6) The study of the human exposome is now gaining momentum; for example the European Helix Project is focusing on the “early-life exposome”, the U.S. National Institutes of Environmental Health Sciences (NIEHS) and U.S. Environmental Protection Agency (EPA) have jointly released a report entitled “Exposure Science in the 21st Century: A vision and strategy” for exploring the links between environment and disease, the NIEHS has established a Center for Exposure Biology at University of California, Berkeley, and the first U.S. Human Exposome Center has recently been funded at Emory University in Atlanta, Georgia. (7-10)

The general concept of the exposome considers all of the chemicals in the body representing environmental exposures received by an individual over a lifetime, as well as chemical metabolites, metabolic reaction products, byproducts of the microbiome, and systemic response molecules. In short, the exposome represents everything that is “not the genome” in human systems biology. (5, 11-13) However, in contrast to the genome, the exposome fluctuates throughout the human lifetime as it is constantly influenced by changes in the environment, human activities, and the individual’s current metabolism and health state at the molecular, cellular, and organ level of organization representing the overall concept of human systems biology. (14-16) So, why do we care about such a complicated and moving target?

We care because current research is showing that incidence of cancers as well as autoimmune, cardiovascular, pulmonary, and other chronic diseases are not just bad luck but that 70–90% of such human disease is attributable to environmental (human exposome) factors through the gene–environment interaction and the epigenome. (11, 17, 18) This has appeared as a bit of a surprise because the sequencing of the human genome, announced in 2000, and the subsequent associations of function with specific genes were thought to be the final explanation for human disease incidence. (19) Instead, the genome results and expected unambiguous linkages to disease have been elusive. (20-22)

To understand the underlying issue, consider familial relatives such as a grandfather and grandson pair (Figure 1); on average, they have a probability of sharing 25% of the same genetic traits. However, they have very little likelihood of sharing the same exposome because the grandfather has two generations of lifetime exposure head start. Furthermore, only when he and the grandson are collocated as in Figure 1, do they share the same short-term exposures, and even then, they are likely to absorb exogenous chemicals at different rates and process them with different efficiencies. In short, there is little expectation that their exposomes are as similar as their genomes over time and so their long-term health outcomes are much more likely to be different. In contrast, consider contemporary occupants of a locality or other kind of community that have grown-up and lived for a long time in the local environment. If long-term health outcome is indeed driven by the exposome as suggested by the research, then the long times spent in a common local environment should be much more important than whether or not the people are genetically related.

Figure 1. Relatives like the grandfather and grandson share genetic traits, but their environmental lifetime experiences result in very different personal exposomes despite sharing the same exposures for a short time on occasion. Photo Copyright: C. Maureen Pleil.

Targeted Biomarker Research

Click to copy section linkSection link copied!

This Feature is concerned with strategies for teasing out the constituents of the exposome that are significant for deducing the links between the environment, internal dose, and the apparently random outcomes in human health. The traditional approaches have centered on chemicals known to have engendered adverse health effects and studying linkages between environmental levels and internal doses; these are referred to as “knowledge driven investigations”. Some examples of such methods are the measurements of “benzene in the air vs benzene in the breath” or “chlorpyrifos pesticide in the food vs trichloropyridinol metabolite in the urine”. (23, 24) The gist of these contrasts is to estimate how much of a known hazardous environmental contaminant is getting into the human system, being distributed to target organs and subsequently metabolized, and then trying to use various calculations from animal and in vitro toxicological studies to assign health risk. This is called “targeted” or “bottom-up” research and has served us well in regulating chemicals known to affect public health. (17) The problem is that there are over 1 000 new chemicals introduced into the U.S. environment every year (from consumer products, industrial processes, farming operations, etc.) to join the more than 84 000 chemicals already listed in the Toxic Substances Control Act inventory. (25) Targeted research has only been performed for a few hundred of the presumed most toxic and/or prevalent of these chemicals; there are limited toxicity data of any kind for many of these compounds, and so the toxicological assessment system is becoming overwhelmed. (26-28)

Certainly, performing targeted in vivo research on all potentially toxic chemicals is not practical; the risk assessment community is exploring alternate paths especially for prioritizing chemicals for more detailed study. (29) The newer approaches implement in vitro (cellular/molecular level) and in silico (computational) methods for screening chemicals that promise high-throughput results on the order of thousands of chemicals per year. (30, 31) However, despite an increase in throughput, these methods still fall into the targeted category wherein in vivo experiments concerning systems biology, mode of action (MoA), adverse outcome pathways (AOP), and biochemical reactions are required. (32-34) In short, targeted assessments require prior knowledge which is best developed through discovery without preconceptions.

Discovery Biomarker Research

Click to copy section linkSection link copied!

Targeted toxicity testing is unquestionably valuable for delineating specific risks from specific compounds based on prior knowledge. The inverse procedure, wherein we try to discover which environmental chemicals, human metabolites, and endogenous biological compounds are related to preclinical and ultimately adverse effects, requires a different strategy. The study of “exposure biology” is part of the broader discipline of Exposure Science that encompasses the discovery aspects and has been described as follows:

“Epidemiologists wait for people to die or get sick before they can study them. Exposure biology connects exposures to hazardous chemicals with early effects of these exposures inside the body.” (Stephen Rappaport, Director, Center for Exposure Biology, University of California, Berkeley).

The immediacy of the preclinical effect reduces a great deal of uncertainty in making the connections to long-term latency disease occurrence. This prompts us to discover what biomarker patterns are prospective signs of disease and/or retrospective signs of exposure. In contrast to in vitro and in silico strategies, discovery generally requires samples from intact biological systems (human, mouse, rat, etc.). We are also working on discovery analyses using cultured bacteria representing the human microbiome which is technically in vitro; however, this still represents intact, albeit very small, organisms. We note that discovery methods do not necessarily preempt high-throughput analysis for different chemicals because we are looking at large groups of biological compounds simultaneously.

So, how does exposome discovery actually work? In Figure 2, we show a conceptual diagram contrasting the classical concept of targeted and discovery approaches to Exposure Science. In the targeted strategy, we start with a knowledge base of specific hazardous exogenous chemicals and then look for them in environmental media such as food, air, and water to determine what the potential of exposures could be. In the discovery approach, we start without preconceived notions about chemicals and just begin to analyze human biofluids (e.g., blood, breath, urine) for as many chemicals as we can. Unlike discovery within the genetics community where a single analytical platform such as a DNA microarray or “Affy chip” (Affymetrix, Santa Clara CA) exists that can give results from tens of thousands of probes for all specific sequences of interest simultaneously, (35) there is no single chemical analytical system (to date) that can analyze every kind of chemical at once.

Figure 2. The diagram shows the classical concepts of bottom-up, targeted analysis (left triangle) in contrast to top-down discovery analysis (right triangle) for assessing the effects on the human community or subpopulation (center). Center image photo credit: Shuttershock. Targeted analysis seeks out specific compounds of exposure in the environment from multiple sources (food, air, water, dust, etc.) whereas discovery analysis starts with human biological media (blood, breath, urine, etc.) to look for all possible compounds and then narrow them down to those with potential exposure to health linkages.

This classical concept described in Figure 2 is not necessarily practical or applicable in all cases. Most discovery experiments are targeted to some extent in that different compound types require different analytical approaches. Most targeted experiments fall partially into the discovery arena because when we target a group of compounds, we can subsequently “discover” that some turn out to be inconsequential for the particular hypothesis. Also, discovery and targeted analyses can be done within the same sample type; that is we can discover many compounds in exhaled breath and then subsequently target an important subset within breath samples without invoking the environment at all. Conversely, we can perform discovery experiments using environmental media samples to deduce what may be worthwhile targeting for assessing potential environmental toxicity in air, water, or food.

Exposome discovery requires a wide array of analytical techniques and sample processing methods to accommodate the different types and categories of biochemicals in the human body. We could not expect to measure small reactive compounds, nonpolar exogenous chemicals, endogenous polar compounds, and proteins all with the same methods. The best we can do is to pick our battles in a stratified fashion; gas chromatography/mass spectrometry (GC/MS) for volatiles, liquid chromatography mass–spectrometry (LC–MS) for larger polar molecules, immunochemistry for proteins, etc. with appropriate sample collection, storage, and preparation to accommodate the medium (blood, breath, or urine). Similarly, we have the same practical issues for environmental samples, and as such, the strict division between discovery and targeted analysis is always blurred to some extent.

Environment Wide Association Study (EWAS) and Case-Control Discovery

Click to copy section linkSection link copied!

The recent article by Patel et al. was heralded as a true exposome discovery experiment conducted using a genome-wide association study (GWAS) approach. (36) Dubbed “EWAS” wherein the word “environment” replaces “genome”, this style of research uses chemical and environmental biomarkers as the independent variables instead of the loci from sequenced genetic samples. (37) Patel et al. used 266 unique environmental factors from the National Health and Nutrition Examination Survey (NHANES) as potential associations with clinical status of diabetes mellitus as indicated by fasting blood sugar levels >126 mg/dL. They found significant positive associations with the pesticide derivative heptachlor epoxide, the vitamin γ-tocopherol, and polychlorinated biphenyls and protective factors associated with β-carotenes. As discussed above, this prototype exposome discovery experiment can also be considered to be targeted to some extent in that the 266 factors used were initially chosen by CDC to accommodate their sampling and analytical strategies and so do not represent all compounds available in the biological media. Regardless of these finer distinctions, such exposome discovery studies can be used to develop hypotheses as to the causes of different diseases and perhaps even provide preclinical evidence as to early stage susceptibility.

More prospective approaches have been performed on a smaller scale over the years under the umbrella of “case-control” studies. Herein, specific sets of compounds are chosen a priori based on available instrumentation and access to biological media, and then differences in their concentration patterns between a group of individuals with a diagnosed illness and a group of matched control subjects are investigated. For example, there have been a number of exhaled breath studies for trying to discern preclinical markers for lung cancer. This is of particular importance as early detection radically improves survival rate but symptoms are often mild or ambiguous during early stages of the cancer and so no specific imaging or biopsies are indicated. (38-41) For lung cancer especially, it seems that there would be some exhaled gas-phase chemicals that would give a clear early warning, but discovering what these chemicals could be is as yet difficult.

In both cases, the approaches have a discovery nature in that we do not make assumptions but rather let the chips (chemicals) fall where they may. The problem with such biomarker strategies is generalizability and repeatability. Often, an algorithm based on a pattern of biomarkers is able to separate the cases from the controls in the current experiment only to fail when the experiment is repeated with different subjects. This is often the case when there are confounding environmental factors or when the statistical approach is underpowered resulting in what is referred to as “voodoo correlations” wherein random chance yields a result that is not repeatable. (42, 43) The solution is to expand our horizons to as many different kinds of chemicals as possible, and then to do our statistical homework to make sure we get solid and repeatable results. In the remainder of this Feature, we focus on using exhaled breath, but the general approaches work just as well for other biological media such as blood and urine.

Biomarkers in Exhaled Breath Condensate (EBC) and Aerosols (EBA)

Click to copy section linkSection link copied!

The “Holy Grail” in preventative medicine is diagnosing early disease state before overt symptoms and irreversible effects of the disease occur. Similarly, figuring out which chemicals in the environment might be related to preclinical effects or perturbations in the human metabolism is the ultimate goal for exposure science. Exploiting breath as the biological fluid for analysis (rather than blood or urine) is attractive because sampling is noninvasive, can be repeated frequently, and there is essentially an unlimited supply. Basically, using breath biomarkers means no syringes full of blood, no containers of urine, no disposal of infectious wastes, just collecting a bit of gas and mist that otherwise get lost to the ambient air.

We have found that breath is not just for gas-phase compounds analysis; in addition to dissolved volatile organics, the small water droplets and mists we exhale also contain a myriad of interesting large molecules, proteins, bacteria, and viruses that cannot be measured with traditional gas chromatography (see Figure 3). (44) A great deal of the literature revolves around exhaled breath condensate (EBC) as an alternative to breath gas collection, primarily for measuring pH and inflammatory markers as indicators of asthma status for chronic obstructive pulmonary disease and for pulmonary infections. (45-49) EBC is also useful for interpreting the effects of recent exposures to environmental contaminants both for assessing exogenous chemicals and their metabolic responses. (49-51) It is notable that many factors can affect the composition of EBC including the pulmonary microbiome, specific pathologies, diet, epigenesis, and other individualized influences, but these are beyond the scope of this discussion.

Briefly, the exhaled breath is passed through a chilled tube and the pulmonary water vapor and aerosols condense on the surfaces. Typically, a subject breathes through the device for 10 minutes or so and about 1 mL of condensate is subsequently harvested from the tube. There are a variety of devices commercially available; in our laboratory we use the “R-Tube” (Respiratory Research, Austin, TX) modified for dry ice temperature collection. (52) The EBC fluid is a useful medium for a variety of polar volatile organic compounds, cytokines, and large molecules but tends to be very dilute as it is more than 99% water.

To collect just the aerosol fraction, we have been implementing a new technique wherein the subject blows through a filter at room temperature; we do not attempt to capture the water vapor or the more volatile fractions of breath. This is an attractive method for a qualitative study because it requires no infrastructure in the field besides disposable filters and sealable plastic bags. Furthermore, the filters collect exhaled pulmonary bacteria that stay alive at room temperature and can be cultured later in the laboratory. In addition to being able to identify strains via standard microbiological techniques, we also collect the headspace of the bacteria for subsequent organics analyses with GC/MS. In the long run, we hope to learn enough about individual bacteria “fingerprints” of gas-phase molecules that we can jump directly into exhaled breath analysis (without off-line bacterial cultures) to discern infection status of human subjects. The whole breath samples could also be collected directly onto adsorbent media (e.g., Tenax tubes) that can capture both aerosol and gas-phase constituents.

Comparisons of Discovery and Targeted Biomarker Data

Click to copy section linkSection link copied!

In the following discussion, we describe the difference between discovery and targeted biomarker research using GC/MS results from exhaled breath samples as an example. These samples are drawn from our archives from methods development projects using anonymous biological specimens. Different sampling and analytical schemes will have similar properties. This is to be considered the simplest of examples using conventional benchtop laboratory instrumentation available in many environmental and clinical laboratories (Ultra TD autosampler coupled with a Unity thermal desorber (Markes International, Ltd., Llantrisandt, U.K.), Agilent 6890N GC coupled with an Agilent 5973I MS (Agilent, Palo Alto, CA).

If we collect whole breath (e.g., onto adsorbent tubes) and run it through a GC/MS under “scan” mode, the instrument essentially looks for everything that can possibly pass through the column and can create an ion in the MS source (Figure 3). Typically, we scan from 33 m/z (mass to charge ratio) to 350 m/z in default 0.1 m/z increments resulting in large data files with reasonable sensitivity at any given m/z. We realize that this resolution does not add analytical advantage over the nominal single unit amu data, but we choose this default setting to draw more understandable graphics. After we run a sample, we can look for benzene, for example, by extracting the 78 m/z ion from all ions and locate that spot in time on the GC run; for ethanol, we look for 45 m/z, for 1-propanol we look for 59 m/z, for 2-methylbutanol we look for 55 m/z, for 1-butanol and hexanal we look for 56 m/z, for toluene we look for 91 m/z, for carbon tetrachloride we look for 117 m/z, etc. (52) By combining elution time from the column and the specific ions for a molecule, we can dig out peaks and values for most compounds that are present in the breath and can respond on the instrument without previous knowledge. This way, we can “discover” what volatile organic compounds are in a particular breath sample. Certainly we check to see if we are right by also analyzing true standards and matching time and complete mass spectra. We thus create a long list of compounds that potentially come from breath and begin to understand relative amounts, variability, and relationships depending on subject meta-data (gender, age, ethnicity, socio-economics, location, etc.).

Figure 3. Left side graphics are a depiction of a “whole breath” gas sample analyzed with GC/MS under full scan, or discovery mode (top), and with selected ion monitoring, or targeted mode (bottom). The right side graphics show only the extracted traces for specific ions, and a close-up for two specific compounds, 3-methylbutanol and benzene. Although the extractions of the discovery mode (top) show a “noisier” result than those of the targeted mode (bottom), the targeted mode is missing many ions that can be seen in discovery mode.

At some point, we no longer want every possible compound but would like to do a more specific and sensitive job for only a few compounds of exceedingly high interest. In this case, we go into selective ion monitoring (SIM) acquisition mode and only acquire the ions for specific molecules. In following the previous scan example, we would “SIM” for only preselected ions such as 45, 55, 56, 78, and 117 m/z and thus spend much more time looking for those by sacrificing all of the other ions between 33 and 350 m/z. (We point out that for routine analyses of actual samples, we always include confirmatory ions and test for ion ratios for each target analyte to ensure quality of results). SIM is a targeted approach resulting in a much lower background noise level and a higher (or cleaner) response for the chosen molecules. The figure above shows a series of GC/MS plots comparing Scan and SIM GC/MS runs from identical breath samples; we also show the respective extractions for each of the methods and compounds wherein we see that SIM gives better data, but many other compounds are completely gone. We use benzene (78 m/z) and 3-methylbutanol (55 m/z) as examples of ubiquitous exogenous and endogenous compounds, respectively, in breath and further extract the small portion of the chromatogram to highlight the improvement in analytical results going from discovery to targeted analysis.

This is only a simple example that contrasts discovery vs targeted analysis. There are many different analytical systems that can collect either or both types of modes. (53-55) For example, liquid chromatography tandem mass spectrometry (LC–MS/MS) is a powerful tool for making very exact measurements of larger molecules, but we can only take advantage of the instrument’s specificity by targeting analytes a priori and setting up their specific transitions for the linear quadrupoles. (56) In contrast, liquid chromatography time-of-flight mass spectrometry (LC–TOF) or LC-Orbitrap instrumentation can be used in discovery mode and the targeted features could be applied in data postprocessing. (57-59)

Summary of Discovery Approaches in Breath Biomarker Research

Click to copy section linkSection link copied!

The use of discovery approaches in all biomarker research (not just in breath) is extremely important in that it allows us to get an overall view of what is going on. Certainly not every compound is relevant for answering a particular question or testing a hypothesis. This requires many samples and analyses from different groups of subjects, and from multiple times from the same subject where we try to look for any changes between or within person that may mean something. From careful observation of such changes, we can build a more specific list of compounds that can help deduce the effects of exposures on the health state. There are, however, a number of precautions we need to take during the discovery phase of any study.

The first issue has been discussed above; by virtue of the broad nature of discovery analyses, any individual compound is not optimized for detection and so the data tend to be more qualitative. Also, the molecules with the highest concentrations and occurrence may not be the most important, and so we run the risk of missing something down in the “noise” that could tell a better story.

The second issue revolves around “test–retest” or “multiple hypothesis” statistics. The more compounds we are comparing the more likely we will have false positives (the aforementioned “voodoo correlation”); and the more we restrict the possibility of having excess false positives (e.g., Bonferroni correction), we increase the probability of false negatives. The statistics improve as we increase the number of independent samples and repeat the study with other groups of subjects. Other postprocessing methods including colinearity tests, nonparametric association tests, mixed models, and variable clustering can also reduce the occurrence of false positives but these methods may blur the impact of individual compounds and increase the chance of erroneously discarding an important probative compound. (60-62)

As such, the discovery approach is the first step. Without it, we would only be guessing as to what to look for with our specific targeted approaches. However, we cannot become complacent and assume that discovery is all-inclusive. We suggest that multiple discovery experiments with different biological media and analytical platforms are the ultimate solution for finding as many probative biochemicals as possible. Only then can we streamline the targeted approaches to achieve high-throughput sample processing. We conclude that exposure science is indeed evolving along a path blazed by the genomics community by embracing the broad discovery aspects of biomarker chemicals and defining the complex human exposome in a top down fashion, yet still recognizing the value of the targeted approaches that lead to exposure mitigation and regulation for protecting public health.

Author Information

Click to copy section linkSection link copied!

Corresponding Author
- Joachim D. Pleil - National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States; Email: [email protected]
Author
- Matthew A. Stiegel - Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, 27599, United States
Notes
The authors declare no competing financial interest.

Biography

Click to copy section linkSection link copied!

Download MS PowerPoint Slide

Joachim D. Pleil is principal investigator for systems biology approaches for exposure assessment for the U.S. EPA’s Office of Research and Development in Research Triangle Park, NC, and serves as adjunct Professor of Environmental Sciences and Engineering at the University of North Carolina School of Public Health in Chapel Hill, NC. He is a founding member of the International Association of Breath Research (IABR); he serves on the science advisory board of IABR and on the editorial boards of the Institute of Physics (IOP) Journal of Breath Research (JBR) and the InformaHealthCare journal Biomarkers.

Matthew A. Stiegel is an ORISE Research Fellow at U.S. EPA and a Ph.D. candidate in the Department of Environmental Sciences and Engineering at the University of North Carolina School of Public Health in Chapel Hill, NC.

Acknowledgment

Click to copy section linkSection link copied!

We are indebted to Terence Risby from Johns Hopkins University, Stephen Rappaport from University of California, Berkeley, and Stephen Edwards, Jon Sobus, Myriam Medina-Vera, Michael Madden, Andrew Ghio, and Linda Sheldon from U.S. EPA for invaluable insights and discussions over the past few years. We also thank our many colleagues in the exposure science and breath diagnostics/analysis communities who provide inspiration for continuing to develop the science for protecting human health. We especially thank C. Gaul and K. Tarpley from SRA International CreativeTeam for producing some of the artwork. This work was reviewed by the U.S. EPA and approved for publication. The views expressed in this article are those of the author(s) and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.

References

Click to copy section linkSection link copied!

This article references 62 other publications.

1
Pleil, J. D.; Blount, B. C.; Waidyanatha, S.; Harper, M. J. Exposure Sci. Environ. Epidemiol. 2012, 22, 317– 319
Google Scholar
1
Establishing exposure science as a distinct scientific discipline
Pleil Joachim D; Blount Benjamin C; Waidyanatha Suramya; Harper Martin
Journal of exposure science & environmental epidemiology (2012), 22 (4), 317-9 ISSN:.
There is no expanded citation for this reference.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38jjtFChtQ%253D%253D&md5=a520800c7dd7c6485b04e5b2afabfc8c
2
Barr, D. B. J. Exposure Sci. Environ. Epidemiol. 2006, 16
Google Scholar
There is no corresponding record for this reference.
3
Lioy, P. J. Environ. Health. Perspect. 2010, 118, 1081– 1090
Google Scholar
There is no corresponding record for this reference.
4
Cohen-Hubal, E. A.; Barr, D. B.; Koch, H. M.; Bahadori, T. J. J. Exposure Sci. Environ. Epidemiol. 2011, 21, 121– 122
Google Scholar
4
The promise of exposure science
Cohen Hubal Elaine A; Barr Dana B; Koch Holger M; Bahadori Tina
Journal of exposure science & environmental epidemiology (2011), 21 (2), 121-2 ISSN:.
There is no expanded citation for this reference.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3M7psFKisw%253D%253D&md5=6b4d5103bebbbf8e2d32faa45ee68c50
5
Wild, C. P. Cancer Epidemiol. Biomarkers Prev. 2005, 14, 1847– 1850
Google Scholar
There is no corresponding record for this reference.
6
Pleil, J. D.; Stiegel, M. A.; Madden, M. C.; Sobus, J. R. Chemosphere 2011, 84, 716– 23
Google Scholar
There is no corresponding record for this reference.
7
Helix Project: Building the Early-Life Exposome. http://www.projecthelix.eu/ (accessed September 10, 2013).
Google Scholar
There is no corresponding record for this reference.
8
National Research Council of The National Academies. The National Academies Press, Washington, DC, 2013.
Google Scholar
There is no corresponding record for this reference.
9
Berkeley Center for Exposure Biology: University of California, Berkeley. Biological Response Indicators of Environment Stress Centers. http://www.niehs.nih.gov/research/supported/dert/cris/programs/exposure/biological_response/berkeley/index.cfm (accessed September 10, 2013).
Google Scholar
There is no corresponding record for this reference.
10
Health and Exposome Research Center: Understanding Lifetime Exposures. http://news.emory.edu/stories/2013/05/hercules_esposome_grant_rollins/ (accessed September 10, 2013).
Google Scholar
There is no corresponding record for this reference.
11
Rappaport, S. M.; Smith, M. T. Science 2010, 330, 460– 461
Google Scholar
There is no corresponding record for this reference.
12
Pleil, J. D.; Sheldon, L. S. Biomarkers 2011, 16, 99– 105
Google Scholar
There is no corresponding record for this reference.
13
Pleil, J. D. J. Toxicol. Environ. Health, B: Crit. Rev. 2012, 15, 264– 80
Google Scholar
There is no corresponding record for this reference.
14
Paoloni-Giacobino, A. Swiss Med. Wkly. 2011, 141, w13321
Google Scholar
There is no corresponding record for this reference.
15
Klepeis, N. E.; Nelson, W. C.; Ott, W. R.; Robinson, J. P.; Tsang, A. M.; Switzer, P.; Behar, J. V.; Hern, S. C.; Engelmann, W. H. J. Exposure Anal. Environ. Epidemiol. 2001, 11, 231– 252
Google Scholar
15
The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants
Klepeis, Neil E.; Nelson, William C.; Ott, Wayne R.; Robinson, John P.; Tsang, Andy M.; Switzer, Paul; Behar, Joseph V.; Hern, Stephen C.; Engelmann, William H.
Journal of Exposure Analysis and Environmental Epidemiology (2001), 11 (3), 231-252CODEN: JEAEE9; ISSN:1053-4245. (Nature America Inc.)
Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey (NHAPS), a 2-yr probability-based telephone survey (n = 9386) of exposure-related human activities in the USA sponsored by the US Environmental Protection Agency (EPA). The primary purpose of the NHAPS was to provide comprehensive and current exposure information over broad geog. and temporal scales, particularly for use in probabilistic population exposure models. The NHAPS was conducted on a virtually daily basis from late Sept., 1992, through Sept., 1994, by the University of Maryland's Survey Research Center using a computer-assisted telephone interview instrument (CATI) to collect 24-h retrospective diaries and answers to a no. of personal and exposure-related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day (i.e., each microenvironment). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an av. of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly const. across the various regions of the USA and Canada and for the California population between the late 1980s, when the California Air Resources Board (CARB) sponsored a state-wide activity pattern study, and the mid-1990s, when the NHAPS was conducted. However, the no. of people exposed to environmental tobacco smoke (ETS) in California seems to have decreased over the same time period, where exposure is detd. by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXmtVSmsbs%253D&md5=6c8e00fa03e935e7abf4c454556c1b29
16
Zhang, L.; McHale, C. M.; Rothman, N.; Li, G.; Ji, Z.; Vermeulen, R.; Hubbard, A. E.; Ren, X.; Shen, M.; Rappaport, S. M.; North, M.; Skibola, C. F.; Yin, S.; Vulpe, C.; Chanock, S. J.; Smith, M. T.; Lan, Q. Chem. Biol. Interact. 2010, 184, 86– 93
Google Scholar
16
Systems biology of human benzene exposure
Zhang, Luoping; McHale, Cliona M.; Rothman, Nathaniel; Li, Guilan; Ji, Zhiying; Vermeulen, Roel; Hubbard, Alan E.; Ren, Xuefeng; Shen, Min; Rappaport, Stephen M.; North, Matthew; Skibola, Christine F.; Yin, Songnian; Vulpe, Christopher; Chanock, Stephen J.; Smith, Martyn T.; Lan, Qing
Chemico-Biological Interactions (2010), 184 (1-2), 86-93CODEN: CBINA8; ISSN:0009-2797. (Elsevier Ireland Ltd.)
A review. Toxicogenomic studies, including genome-wide analyses of susceptibility genes (genomics), gene expression (transcriptomics), protein expression (proteomics), and epigenetic modifications (epigenomics), of human populations exposed to benzene are crucial to understanding gene-environment interactions, providing the ability to develop biomarkers of exposure, early effect and susceptibility. Comprehensive anal. of these toxicogenomic and epigenomic profiles by bioinformatics in the context of phenotypic endpoints, comprises systems biol., which has the potential to comprehensively define the mechanisms by which benzene causes leukemia. We have applied this approach to a mol. epidemiol. study of workers exposed to benzene. Hematotoxicity, a significant decrease in almost all blood cell counts, was identified as a phenotypic effect of benzene that occurred even below 1 ppm benzene exposure. We found a significant decrease in the formation of progenitor colonies arising from bone marrow stem cells with increasing benzene exposure, showing that progenitor cells are more sensitive to the effects of benzene than mature blood cells, likely leading to the obsd. hematotoxicity. Anal. of transcriptomics by microarray in the peripheral blood mononuclear cells of exposed workers, identified genes and pathways (apoptosis, immune response, and inflammatory response) altered at high (>10 ppm) and low (<1 ppm) benzene levels. Serum proteomics by SELDI-TOF-MS revealed proteins consistently down-regulated in exposed workers. Preliminary epigenomics data showed effects of benzene on the DNA methylation of specific genes. Genomic screens for candidate genes involved in susceptibility to benzene toxicity are being undertaken in yeast, with subsequent confirmation by RNAi in human cells, to expand upon the findings from candidate gene analyses. Data on these and future biomarkers will be used to populate a large toxicogenomics database, to which we will apply bioinformatic approaches to understand the interactions among benzene toxicity, susceptibility genes, mRNA, and DNA methylation through a systems biol. approach.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXktVWqtro%253D&md5=8cfa665ab0aa2c430cba152f2bf7c63b
17
Rappaport, S. M. J. Exposure Sci. Environ. Epidemiol. 2011, 21, 5– 9
Google Scholar
17
Implications of the exposome for exposure science
Rappaport, Stephen M.
Journal of Exposure Science & Environmental Epidemiology (2011), 21 (1), 5-9CODEN: JESEBS; ISSN:1559-0631. (Nature Publishing Group)
A review. During the 1920s, the forerunners of exposure science collaborated with health professionals to investigate the causes of occupational diseases. With the birth of U.S. regulatory agencies in the 1970s, interest in the environmental origins of human diseases waned, and exposure scientists focused instead upon levels of selected contaminants in air and water. In fact, toxic chems. enter the body not only from exogenous sources (air, water, diet, drugs, and radiation) but also from endogenous processes, including inflammation, lipid peroxidn., oxidative stress, existing diseases, infections, and gut flora. Thus, even though current evidence suggests that non-genetic factors contribute about 90% of the risks of chronic diseases, we have not explored the vast majority of human exposures that might initiate disease processes. The concept of the exposome, representing the totality of exposures received by a person during life, encompasses all sources of toxicants and, therefore, offers scientists an agnostic approach for investigating the environmental causes of chronic diseases. In this context, it is appropriate to regard the "environment" as the body's internal chem. environment and to define "exposures" as levels of biol. active chems. in this internal environment. To explore the exposome, it makes sense to employ a top-down approach based upon biomonitoring (e.g. blood sampling) rather than a bottom-up approach that samples air, water, food, and so on. Because sources and levels of exposure change over time, exposomes can be constructed by analyzing toxicants in blood specimens obtained during crit. stages of life. Initial investigations could use archived blood from prospective cohort studies to measure important classes of toxic chems., notably, reactive electrophiles, metals, metabolic products, hormone-like substances, and persistent org. compds. The exposome offers health scientists an avenue for integrating research that is currently fractured along lines related to particular diseases and risk factors, and can thereby promote discovery of the key exposures responsible for chronic diseases. By embracing the exposome as its operational paradigm, exposure science can play a major role in discovering and mitigating these exposures.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFyku7nF&md5=dbc872e9f5a98a2f742b032c520e12c5
18
Liu, L.; Li, Y.; Tollefsbol, T. O. Curr. Issues. Mol. Biol. 2008, 10, 25– 36
Google Scholar
18
Gene-environment interactions and epigenetic basis of human diseases
Liu, Liang; Li, Yuanyuan; Tollefsbol, Trygve O.
Current Issues in Molecular Biology (2008), 10 (1 and 2), 25-36CODEN: CMBIF6; ISSN:1467-3037. (Horizon Scientific Press)
A review. Most human diseases are related in some way to the loss or gain in gene functions. Regulation of gene expression is a complex process. In addn. to genetic mechanisms, epigenetic causes are gaining new perspectives in human diseases related to gene deregulation. Most eukaryotic genes are packed into chromatin structures, which lead to high condensations of the genes that require dynamic chromatin remodeling processes to facilitate their transcription. DNA methylation and histone modifications represent two of the major chromatin remodeling processes. They also serve to integrate environmental signals for the cells to modulate the functional output of their genome. Complex human diseases such as cancer and type 2 diabetes are believed to have a strong environmental component in addn. to genetic causes. Aberrancies in chromatin remodeling are assocd. with both genetically and environmentally-related diseases. We will focus on recent findings of the epigenetic basis of human metabolic disorders to facilitate further exploration of epigenetic mechanisms and better understandings of the mol. cues underlying such complex diseases.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXos1Wju7g%253D&md5=0f033ba89b1e02b0b86bb25c6fd498d0
19
The White House, Office of the Press Secretary. President Clinton Announces the Completion of the First Survey of the Entire Human Genome, Hails Public and Private Efforts Leading to This Historic Achievement; http://web.ornl.gov/sci/techresources/Human_Genome/project/clinton1.shtml (accessed September 10, 2013).
Google Scholar
There is no corresponding record for this reference.
20
Wade, N. In New York Times; New York Times: New York, 2010.
Google Scholar
There is no corresponding record for this reference.
21
Hall, S. S. Sci. Am. 2010, 303, 60– 67
Google Scholar
21
Revolution postponed
Hall Stephen S
Scientific American (2010), 303 (4), 60-7 ISSN:0036-8733.
There is no expanded citation for this reference.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cfnsVOrsw%253D%253D&md5=a56bd07653d970e6d91cf63b7ea9629d
22
Kaiser, J. Science 2012, 338, 1016– 1017
Google Scholar
There is no corresponding record for this reference.
23
Egeghy, P. P.; Hauf-Cabalo, L.; Gibson, R.; Rappaport, S. M. Occup. Environ. Med. 2003, 60, 969– 976
Google Scholar
There is no corresponding record for this reference.
24
Rigas, M. L.; Okino, M. S.; Quackenboss, J. J. Toxicol. Sci. 2001, 61, 374– 381
Google Scholar
24
Use of a pharmacokinetic model to assess chlorpyrifos exposure and dose in children, based on urinary biomarker measurements
Rigas, Marc L.; Okino, Miles S.; Quackenboss, James J.
Toxicological Sciences (2001), 61 (2), 374-381CODEN: TOSCF2; ISSN:1096-6080. (Oxford University Press)
Chlorpyrifos is a common agricultural insecticide and has been used residentially in the United States until the year 2000 when this use was restricted by the U.S. Environmental Protection Agency (U.S. EPA). A chlorpyrifos metabolite, 3,5,6-trichloro-2-pyridinol (TCPy), has been found in urine samples collected during exposure field studies. In this work, the authors use urinary biomarker data and the inverse soln. of a simple pharmacokinetic (PK) model for chlorpyrifos to est. the magnitude and timing of doses. Three urine samples were collected on sep. days from each of 15 children (ages 3-12) who were participants in the Minnesota Children's Pesticide Exposure Study (MNCPES). The total vol. of urine was noted and samples analyzed for TCPy. The urinary data was used along with constraints imposed on dose timing, based on responses of the individuals to pesticide-use surveys. The authors predicted the time and magnitude of multiple event exposures characterized by short-term, relatively high doses superimposed over a continuous background exposure. The av. dose of chlorpyrifos predicted by the model was 1.61 μg/kg per reported event. Av. background dose rate for these children that reported exposure events was 0.0062 μg/kg/h, or 0.15 μg/kg/day. In addn. to predicting the total dose of chlorpyrifos received by an individual from urinary biomarker measurements, the model can then be run in a forward manner once the exposure regime is detd. This will allow the prediction of the total amt. of TCPy eliminated in the urine over any time period of interest.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXktVajt74%253D&md5=5633070a9c2ca9b7f2315feaf323db54
25
Toxic Substances Control Act. U.S. Code, Chapter 53, Title 15, pp 2601– 2629, 1976.
Google Scholar
There is no corresponding record for this reference.
26
U.S. Environmental Protection Agency. Framework for an EPA Chemical Safety for Sustainability Research Program; U.S. Government Printing Office: Washington, DC, 2011.
Google Scholar
There is no corresponding record for this reference.
27
Judson, R.; Richard, A.; Dix, D. J.; Houck, K.; Martin, M.; Kavlock, R.; Dellarco, V.; Henry, T.; Holderman, T.; Sayre, P.; Tan, S.; Carpenter, T.; Smith, E. Environ. Health Perspect. 2009, 117, 685– 695
Google Scholar
There is no corresponding record for this reference.
28
Sheldon, L. S.; Cohen Hubal, E. A. Environ. Health Perspect. 2009, 117, 119– 1194
Google Scholar
There is no corresponding record for this reference.
29
National Research Council of The National Academies. Toxicity Testing in the 21st Century: A Vision and a Strategy; 2007.
Google Scholar
There is no corresponding record for this reference.
30
Dix, D. J.; Houck, K. A.; Martin, M. T.; Richard, A. M.; Setzer, R. W.; Kavlock, R. Toxicol. Sci. 2007, 95, 5– 12
Google Scholar
30
The ToxCast Program for Prioritizing Toxicity Testing of Environmental Chemicals
Dix, David J.; Houck, Keith A.; Martin, Matthew T.; Richard, Ann M.; Setzer, R. Woodrow; Kavlock, Robert J.
Toxicological Sciences (2007), 95 (1), 5-12CODEN: TOSCF2; ISSN:1096-6080. (Oxford University Press)
A review. The U.S. Environmental Protection Agency (EPA) is developing methods for utilizing computational chem., high-throughput screening (HTS), and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources toward chems. that likely represent the greatest hazard to human health and the environment. This chem. prioritization research program, entitled "ToxCast," is being initiated with the purpose of developing the ability to forecast toxicity based on bioactivity profiling. The proof-of-concept phase of ToxCast will focus upon chems. with an existing, rich toxicol. database to provide an interpretive context for the ToxCast data. This set of several hundred ref. chems. will represent numerous structural classes and phenotypic outcomes, including tumorigens, developmental and reproductive toxicants, neurotoxicants, and immunotoxicants. The ToxCast program will evaluate chem. properties and bioactivity profiles across a broad spectrum of data domains: Phys.-chem., predicted biol. activities based on existing structure-activity models, biochem. properties based on HTS assays, cell-based phenotypic assays, and genomic and metabolomic analyses of cells. These data will be generated through a series of external contracts, along with collaborations across EPA, with the National Toxicol. Program, and with the National Institutes of Health Chem. Genomics center. The resulting multidimensional data set provides an informatics challenge requiring appropriate computational methods for integrating various chem., biol., and toxicol. data into profiles and models predicting toxicity.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtlChtLjK&md5=73fbf7b6fcaf532721dbe1584c6ee8f8
31
Knudsen, T.; Martin, M.; Chandler, K.; Kleinstreuer, N.; Judson, R.; Sipes, N. Methods Mol. Biol. 2013, 947, 343– 374
Google Scholar
31
Predictive models and computational toxicology
Knudsen, Thomas; Martin, Matthew; Chandler, Kelly; Kleinstreuer, Nicole; Judson, Richard; Sipes, Nisha
Methods in Molecular Biology (New York, NY, United States) (2013), 947 (Teratogenicity Testing), 343-374CODEN: MMBIED; ISSN:1064-3745. (Springer)
A review. Understanding the potential health risks posed by environmental chems. is a significant challenge elevated by the large no. of diverse chems. with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicol. research program was launched by EPA in 2007 and is part of the federal Tox21 consortium to develop a cost-effective approach for efficiently prioritizing the toxicity testing of thousands of chems. and the application of this information to assessing human toxicol. ToxCast addresses this problem through an integrated workflow using high-throughput screening (HTS) of chem. libraries across more than 650 in vitro assays including biochem. assays, human cells and cell lines, and alternative models such as mouse embryonic stem cells and zebrafish embryo development. The initial phase of ToxCast profiled a library of 309 environmental chems., mostly pesticidal actives having rich in vivo data from guideline studies that include chronic/cancer bioassays in mice and rats, multigenerational reproductive studies in rats, and prenatal developmental toxicity endpoints in rats and rabbits. The first phase of ToxCast was used to build models that aim to det. how well in vivo animal effects can be predicted solely from the in vitro data. Phase I is now complete and both the in vitro data (ToxCast) and anchoring in vivo database (ToxRefDB) have been made available to the public (http://actor.epa. gov/). As Phase II of ToxCast is now underway, the purpose of this chapter is to review progress to date with ToxCast predictive modeling, using specific examples on developmental and reproductive effects in rats and rabbits with lessons learned during Phase I.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXktlaqt78%253D&md5=46aeb3afb59ebfe6a48f3d779ba3321a
32
Bouhifd, M.; Hartung, T.; Hogberg, H. T.; Kleensang, A.; Zhao, L. J. Appl. Toxicol. 2013, DOI: 10.1002/jat.2874
Google Scholar
There is no corresponding record for this reference.
33
Pleil, J. D.; Williams, M. A.; Sobus, J. R. Toxicol. Lett. 2012, 215, 201– 207
Google Scholar
33
Chemical Safety for Sustainability (CSS): Human in vivo biomonitoring data for complementing results from in vitro toxicology-A commentary
Pleil, Joachim D.; Williams, Marc A.; Sobus, Jon R.
Toxicology Letters (2012), 215 (3), 201-207CODEN: TOLED5; ISSN:0378-4274. (Elsevier Ireland Ltd.)
A review. The U.S. Environmental Protection Agency (EPA) has instituted the Chem. Safety for Sustainability (CSS) research program for assessing the health and environmental impact of manufd. chems. This is a broad program wherein one of the tasks is to develop high throughput screening (HTS) methods and follow-up confirmation for toxicity at realistic environmental exposure levels. The main tools under this task are in vitro toxicity testing, in silico mol. modeling, and in vivo (systemic) measurements documentation. The in vivo research component is intended to support and corroborate in vitro chem. toxicity prioritization with observations of systemic perturbations and statistical parameters derived from intact (living) organisms. Based on EPA's Biomonitoring Framework for human health research, such observations are intended to link environmental exposures to a cascade of biomarker chems. to help identify and clarify adverse outcome pathways within the context of systems biol. This commentary discusses the issues regarding interpretation of in vitro changes from HTS as an adverse result, an adaptive (non-adverse) response, or a random/irrelevant occurrence. A second goal is to inform in vitro strategies as to relevant dosing (potency) levels at the cellular level that reflect realistic systemic exposures. Although the authors recognize the high value of in vivo animal toxicity testing, herein the authors focus on observational (minimally invasive) human biomonitoring methods and propose complementary in vivo testing that could help guide the design of high-throughput analyses and the ultimate interpretation of their outcomes.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhslKqtLnO&md5=558ef74730e1d618413066e0b29e0673
34
Ankley, G. T.; Bennett, R. S.; Erickson, R. J.; Hoff, D. J.; Hornung, M. W.; Johnson, R. D.; Mount, D. R.; Nichols, J. W.; Russom, C. L.; Schmieder, P. K.; Serrrano, J. A.; Tietge, J. E.; Villeneuve, D. L. Environ. Toxicol. Chem. 2010, 29, 730– 741
Google Scholar
There is no corresponding record for this reference.
35
Liu, H.; Bebu, I.; Li, X. Front. Biosci. 2010, 2, 325– 338
Google Scholar
35
Microarray probes and probe sets
Liu, Hongfang; Bebu, Ionut; Li, Xin
Frontiers in Bioscience, Elite Edition (2010), E2 (1), 325-338CODEN: FBEEAS; ISSN:1945-0508. (Frontiers in Bioscience)
A review. DNA microarrays have gained wide use in biomedical research by simultaneously monitoring the expression levels of a large no. of genes. The successful implementation of DNA microarray technologies requires the development of methods and techniques for the fabrication of microarrays, the selection of probes to represent genes, the quantification of hybridization, and data anal. In this paper, we conc. on probes that are either spotted or synthesized on the glass slides through several aspects: sources of probes, the criteria for selecting probes, tools available for probe selections, and probes used in com. microarray chips. We then provide a detailed review of one type of DNA microarray: Affymetrix GeneChips, discuss the need to re-annotate probes, review different methods for regrouping probes into probe sets, and compare various redefinitions through public available datasets.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXovFalsLs%253D&md5=ec191e5e945cf3a652e75ebd7a5c3148
36
Patel, C. J.; Bhattacharya, J.; Butte, A. J. PLoS One 2010, 5, e10746
Google Scholar
There is no corresponding record for this reference.
37
Rappaport, S. M. Biomarkers 2012, 17, 483– 489
Google Scholar
There is no corresponding record for this reference.
38
Amann, A.; Corradi, M.; Mazzone, P.; Mutti, A. Expert Rev. Mol. Diagn. 2011, 11, 202– 217
Google Scholar
There is no corresponding record for this reference.
39
Mazzone, P. J. J. Breath Res. 2012, 6, 027106
Google Scholar
There is no corresponding record for this reference.
40
Slatore, C. G.; Gould, M. K.; Au, D. H.; Deffebach, M. E.; White, E. BMC Cancer 2011, 11, 7
Google Scholar
There is no corresponding record for this reference.
41
Bunn, P. A. Arch. Pathol. Lab. Med. 2012, 136, 1478– 1481
Google Scholar
41
Worldwide overview of the current status of lung cancer diagnosis and treatment
Bunn Paul A Jr
Archives of pathology & laboratory medicine (2012), 136 (12), 1478-81 ISSN:.
Lung cancer is the leading worldwide cause of cancer deaths. Smoking is the dominant cause of lung cancer and smoking cessation is the established method to reduce lung cancer mortality. While lung cancer risk is reduced in former smokers, they have a lifelong increase in risk, compared to never-smokers. Novel chemoprevention strategies, such as oral or inhaled prostacyclin analogs, hold promise for these subjects. Low-dose spiral computed tomography screening reduced lung cancer mortality by 20% in high-risk heavy smokers older than 50 years. However, the high false-positive rate (96%) means that screened patients required controlled follow-up in experienced centers. An increasing percentage of patients with advanced lung cancer have molecular drivers in genes for which oral tyrosine kinase inhibitors have been developed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3s7nsVClsA%253D%253D&md5=f750891f4b27e02022112eddeafbffef
42
Pleil, J. D.; Stiegel, M. A.; Risby, T. H. J. Breath Res. 2013, 7, 017107
Google Scholar
There is no corresponding record for this reference.
43
Miekisch, W.; Herbig, J.; Schubert, J. K. J. Breath Res. 2012, 6, 036007
Google Scholar
There is no corresponding record for this reference.
44
Rosias, P. J. Breath Res. 2012, 6, 027102
Google Scholar
There is no corresponding record for this reference.
45
Loukides, S.; Kontogianni, K.; Hillas, G.; Horvath, I. Curr. Med. Chem. 2011, 18, 1432– 1443
Google Scholar
45
Exhaled breath condensate in asthma: from bench to bedside
Loukides, S.; Kontogianni, K.; Hillas, G.; Horvath, I.
Current Medicinal Chemistry (2011), 18 (10), 1432-1443CODEN: CMCHE7; ISSN:0929-8673. (Bentham Science Publishers Ltd.)
A review. The need for non-invasive assessment of airway inflammation is imperative, since inflammatory airway diseases, such as asthma and COPD, are characterized by variation in their clin. presentation throughout their course. Exhaled breath condensate (EBC) collection represents a rather appealing method that can be used to conveniently and noninvasively collect a wide range of volatile and non-volatile mols. from the respiratory tract, without affecting airway function or inflammation. Although promising, EBC is currently used only as a research tool, due to the lack of appropriate standardization and the absence of ref. values. A large no. of mediators of inflammation, oxidative and nitrosative stress, including adenosine, ammonia, hydrogen peroxide, isoprostanes, leukotrienes, prostanoids, nitrogen oxides, peptides and cytokines, were studied in EBC. This review focuses mainly on the presentation of the above biomarkers in asthma as well as on the effect of various factors on their concns. Concns. of such mediators have been shown to be related to the underlying asthma and its severity and to be modulated by therapeutic interventions. Despite the encouraging pos. results up-to-date, the introduction of EBC in everyday clin. practice requires the work-out of some methodol. pitfalls, the standardization of EBC collection, and finally the identification of a reliable biomarker which is reproducible, has normal values and provides information for the underlying inflammatory process and the response to treatment. So far none of the parameters studied in EBC fulfils the aforementioned requirements.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXpslOitrw%253D&md5=8646af52349f8cc18e4892411b0ddf30
46
Kazani, S.; Israel, E. J. Breath Res. 2010, 4, 047001
Google Scholar
There is no corresponding record for this reference.
47
Lee, W.; Thomas, P. S. Clin. Transl. Sci. 2009, 2, 150– 155
Google Scholar
47
Oxidative stress in COPD and its measurement through exhaled breath condensate
Lee, Wei; Thomas, Paul S.
Clinical and Translational Science (2009), 2 (2), 150-155CODEN: CTSLCA; ISSN:1752-8062. (Wiley-Blackwell)
A review. Oxidative stress and airway inflammation together form a vicious cycle, which is responsible for the disease progression in chronic pulmonary obstructive disease (COPD). The damaging effects of oxidative stress accumulate over the years, causing increased bronchial hyperresponsiveness and inflammation and destruction of airway epithelial cells and impairing the functions of antiproteases and surfactant. Although the lung expresses a no. of antioxidants, cigarette smoking and recurrent infections assocd. with this disease overwhelm this protective mechanism. Studies of antioxidants in COPD have yielded conflicting results, probably due to the compartmentalization of these mediators, and because of the fact that the lung is a difficult organ to sample. Chronic exposure to oxidants upregulates the prodn. of antioxidants, which become depleted during acute exacerbations. Future studies of the pathogenesis of COPD require a noninvasive yet accurate sampling procedure, of which exhaled breath condensate (EBC) is a good candidate. EBC samples the epithelial lining fluid, which contains the local oxidative stress markers in the lung. Oxidative stress markers such as hydrogen ions, hydrogen peroxide, 8-isoprostanes, thiobarbituric acid reactive products, nitrosothiols, and nitrite/nitrate have been identified in EBC of COPD patients, whereas many other markers of the oxidative-antioxidative balance have yet to be investigated.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXisVGktL0%253D&md5=2bc7e9b1b37393fc6f98a27e34352a66
48
Chambers, S. T.; Scott-Thomas, A.; Epton, M. Curr. Opin. Pulm. Med. 2012, 18, 228– 232
Google Scholar
48
Developments in novel breath tests for bacterial and fungal pulmonary infection
Chambers Stephen T; Scott-Thomas Amy; Epton Michael
Current opinion in pulmonary medicine (2012), 18 (3), 228-32 ISSN:.
PURPOSE OF REVIEW: Breath testing has developed over the last 20 years. New techniques that can identify fingerprints for specific diseases and specific markers of respiratory pathogens have been applied to breath analysis. This review discusses the recent advances in breath analysis for the diagnosis of bacterial and fungal lower respiratory tract infections. RECENT FINDINGS: The current techniques continue to develop rapidly, but preconcentration techniques are needed to analyse many target volatile organic compounds for most systems. Breath testing with an electronic nose is promising for the diagnosis of tuberculosis (TB), and specific volatiles identifiable by gas chromatography with mass spectrometry have been identified in breath for Mycobacterium tuberculosis, Pseudomonas aeruginosa and Aspergillus fumigatus, but are found at very low concentrations in breath. Contamination from the environment is an ongoing confounding influence. Exhaled breath condensate (EBC) is disappointing as a diagnostic sample. SUMMARY: Careful attention needs to be paid to the sensitivity and specificity of a technique and confounding from the environment. The role of technologies such as selected ion flow tube-mass spectrometry is emerging. The electronic nose requires further validation for TB. The identification of specific microbial biomarkers aids the quest for improved accuracy. EBC is currently of limited value.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38vktlGhtQ%253D%253D&md5=0d6bd7dae5aa07124669143e684cebf6
49
Zhang, J.; Zhu, T.; Kipen, H.; Wang, G.; Huang, W.; Rich, D.; Zhu, P.; Wang, Y.; Lu, S.-E.; Ohman-Strickland, P.; Diehl, S.; Hu, M.; Tong, J.; Gong, J.; Thomas, D.; H. E. I. H. R. Committee Res. Resp. Health Eff. Inst. 2013, 5– 174
Google Scholar
There is no corresponding record for this reference.
50
Hubbard, H. F.; Sobus, J. R.; Pleil, J. D.; Madden, M. C.; Tabucchi, S. J. Chromatogr., B: Anal. Technol. Biomed. Life Sci. 2009, 877, 3652– 3658
Google Scholar
50
Application of novel method to measure endogenous VOCs in exhaled breath condensate before and after exposure to diesel exhaust
Hubbard, H. F.; Sobus, J. R.; Pleil, J. D.; Madden, M. C.; Tabucchi, S.
Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences (2009), 877 (29), 3652-3658CODEN: JCBAAI; ISSN:1570-0232. (Elsevier B.V.)
Polar volatile org. compds. (PVOCs) such as aldehydes and alcs. are byproducts of normal human metab. and thus are found in blood and exhaled breath. Perturbation of the normal patterns of such metabolites may reflect exposures to environmental stressors, disease state, and human activity. Presented herein is a specific methodol. for assaying PVOC biomarkers in exhaled breath condensate (EBC) samples with application to a series of samples from a controlled chamber exposure to dil. diesel exhaust (DE) or to purified air. The collection/anal. method is based on condensation of normal (at rest) exhaled breaths for 10 min (resulting in 1-2 mL of liq.) with subsequent analyte adsorption onto Tenax cartridges followed by thermal desorption and anal. by gas chromatog./mass spectrometry (GC/MS). Anal. data have linearity of response (R2 > 0.98) across a range of 0-160 ng/mL with a detection limit ranging from 0.2 to 7 ng/mL depending on the compd. Statistical analyses of the results of the controlled exposure study indicate that metab., as reflected in simple breath-borne oxygenated species, is not affected by exposure to ambient airborne levels of DE. Linear mixed-effects models showed that PVOC biomarker levels are affected by gender and vary significantly among nominally healthy subjects. Differences among PVOCs analyzed in clinic air, purified chamber air, and chamber air contg. dil. DE confirm that most of the compds. are likely of endogenous origin as the exogenous exposure levels did not perturb the EBC measurements.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht1GksLbM&md5=3228e609899d64daa4bafd026a7a8187
51
Sawyer, K.; Samet, J. D.; Ghio, A. J.; Pleil, J. D.; Madden, M. C. J. Breath Res. 2009, 2, 037019
Google Scholar
There is no corresponding record for this reference.
52
Pleil, J. D.; Hubbard, H. F.; Sobus, J. R.; Sawyer, K.; Madden, M. C. J. Breath Res. 2008, 2, 026001
Google Scholar
There is no corresponding record for this reference.
53
Koester, C. J.; Moulik, A. Anal. Chem. 2005, 77, 3737– 3754
Google Scholar
There is no corresponding record for this reference.
54
Boja, E. S.; Rodriguez, H. Proteonomics 2012, 12, 1093– 1110
Google Scholar
54
Mass spectrometry-based targeted quantitative proteomics: Achieving sensitive and reproducible detection of proteins
Boja, Emily S.; Rodriguez, Henry
Proteomics (2012), 12 (8), 1093-1110CODEN: PROTC7; ISSN:1615-9853. (Wiley-VCH Verlag GmbH & Co. KGaA)
A review. Traditional shotgun proteomics used to detect a mixt. of hundreds to thousands of proteins through mass spectrometric anal., has been the std. approach in research to profile protein content in a biol. sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biol. conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biol. samples in the hope of elucidating the mol. mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, std. operating procedures, and well characterized reagents.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XmslKkt70%253D&md5=37fc2943ca29273badb4fa9bca24f483
55
Dasilva, N.; Díez, P.; Matarraz, S.; González-González, M.; Paradinas, S.; Orfao, A.; Fuentes, M. Sensors (Basel) 2012, 12, 2284– 2308
Google Scholar
55
Biomarker discovery by novel sensors based on nanoproteomics approaches
Dasilva Noelia; Diez Paula; Matarraz Sergio; Gonzalez-Gonzalez Maria; Paradinas Sara; Orfao Alberto; Fuentes Manuel
Sensors (Basel, Switzerland) (2012), 12 (2), 2284-308 ISSN:.
During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38vos1Slsw%253D%253D&md5=ef7668a264a0df9f70de970e1924c392
56
Grebe, S. K.; Singh, R. J. Clin. Biochem. Rev. 2011, 32, 5– 31
Google Scholar
56
LC-MS/MS in the Clinical Laboratory - Where to From Here?
Grebe Stefan Kg; Singh Ravinder J
The Clinical biochemist. Reviews (2011), 32 (1), 5-31 ISSN:.
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has seen enormous growth in clinical laboratories during the last 10-15 years. It offers analytical specificity superior to that of immunoassays or conventional high performance/pressure liquid chromatography (HPLC) for low molecular weight analytes and has higher throughput than gas chromatography-mass spectrometry (GC-MS). Drug/Toxicology and Biochemical Genetics/Newborn Screening laboratories were at the vanguard of clinical LC-MS/MS use, but have been eclipsed by Endocrine laboratories. In USA reference/referral laboratories, most steroids and biogenic amines are now assayed by LC-MS/MS, and the technology has started to penetrate into smaller laboratories. Assays for mineralo- and gluco-corticoids and their precursors, sex steroids, metanephrines and 25-hydroxy vitamin D highlight the advantages of LC-MS/MS.However, several limitations of LC-MS/MS have become apparent, centring on the interacting triangle of sensitivity - specificity - throughput. While sample throughput is higher than for conventional HPLC or GC-MS, it lags behind automated immunoassays. Techniques which improve throughput include direct sample injection, LC-multiplexing and samplemultiplexing. Measures to improve specificity and sensitivity include sample clean-up and optimising chromatography to avoid interferences and ion suppression due to sample-matrix components. Next generation instrumentation may offer additional benefits.The next challenge for clinical LC-MS/MS is peptide/protein analysis. The quest for multi-biomarker profiles for various diseases has largely failed, but targeted peptide and protein testing by LC-MS/MS, directed at analytical and clinical questions that need to be answered, is proving highly successful. We anticipate that this will result in similar growth of clinical protein/peptide LC-MS/MS as has been seen for low molecular weight applications.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3MzotFCgtg%253D%253D&md5=a26bc85caf25ed329080b925ab407562
57
Lacorte, S.; Fernandez-Alba, A. R. Mass Spectrom. Rev. 2006, 25, 866– 880
Google Scholar
57
Time of flight mass spectrometry applied to the liquid chromatographic analysis of pesticides in water and food
Lacorte, Silvia; Fernandez-Alba, Amadeo R.
Mass Spectrometry Reviews (2006), 25 (6), 866-880CODEN: MSRVD3; ISSN:0277-7037. (John Wiley & Sons, Inc.)
A review. Liq. chromatog. coupled to mass spectrometry (LC-MS) is an excellent technique to det. trace levels of polar and thermolabile pesticides and their degrdn. products in complex matrixes. LC-MS can be equipped with several mass analyzers, each of which provides unique features capable to identify, quantify, and resolve ambiguities by selecting appropriate ionization and acquisition parameters. The authors discuss in this review the use of LC coupled to (quadrupole) time-of-flight mass spectrometry (LC-(Q)ToF-MS) to det. the presence of target and non-target pesticides in water and food. This technique is characterized by operating at a resolving power of 10,000 or more. Therefore, it gives accurate masses for both parent and fragment ions and enables the measurement of the elemental formula of a compd. achieving compd. identification. In addn., the combination of quadrupole-ToF permits tandem mass spectrometry, provides more structural information, and enhances selectivity. The purpose of this article is to provide an overview on the state of the art and applicability of liq. chromatog. time-of-flight mass spectrometry (LC-ToF-MS), and liq. chromatog. quadrupole time-of-flight mass spectrometry (LC-QToF-MS) for the anal. of pesticides in environmental matrixes and food. The performance of such techniques is depicted in terms of accurate mass measurement, fragmentation, and selectivity. The final section is devoted to describing the applicability of LC-(Q)ToF-MS to routine anal. of pesticides in food matrixes, indicating those operational conditions and criteria used to screen, quantify, and identify target and suspected pesticides and their degrdn. products in water, fruits, and vegetables. The potential and future trends as well as limitations of LC-(Q)ToF-MS for pesticide monitoring are highlighted.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht1eiu7bE&md5=b0f6a6270bacfe3e5ccb1cca70e8e529
58
Ferrer, I.; Thurman, E. M.; Fernández-Alba, A. R. Anal. Chem. 2005, 77, 2818– 2825
Google Scholar
There is no corresponding record for this reference.
59
Zubarev, R. A.; Makarov, A. Anal. Chem. 2013, 85, 5288– 5296
Google Scholar
59
Orbitrap Mass Spectrometry
Zubarev, Roman A.; Makarov, Alexander
Analytical Chemistry (Washington, DC, United States) (2013), 85 (11), 5288-5296CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)
A review. Orbitrap is the newest addn. to the family of high-resoln. mass spectrometry analyzers. With its revolutionarily new, miniature design, Orbitrap combines high speed with excellent quantification properties, ranking favorably in many anal. applications.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXmtVyltro%253D&md5=3c3fdcddc24dd230f449b673e4c25cfa
60
Sobus, J. R.; Pleil, J. D.; McClean, M. D.; Herrick, R. F.; Rappaport, S. M. Toxicol. Lett. 2010, 199, 247– 253
Google Scholar
60
Biomarker variance component estimation for exposure surrogate selection and toxicokinetic inference
Sobus, Jon R.; Pleil, Joachim D.; McClean, Michael D.; Herrick, Robert F.; Rappaport, Stephen M.
Toxicology Letters (2010), 199 (3), 247-253CODEN: TOLED5; ISSN:0378-4274. (Elsevier Ireland Ltd.)
Biomarkers are useful exposure surrogates given their ability to integrate exposures through all routes and to reflect interindividual differences in toxicokinetic processes. Also, biomarker concns. tend to vary less than corresponding environmental measurements, making them less-biasing surrogates for exposure. In this article, urinary PAH biomarkers (namely, urinary naphthalene [U-Nap]; urinary phenanthrene [U-Phe]; 1-hydroxypyrene [1-OH-Pyr]; and 1-, (2+3)-, 4-, and 9-hydroxyphenanthrene [1-, (2+3)-, 4-, and 9-OH-Phe]) were evaluated as surrogates for exposure to hot asphalt emissions using data from 20 road-paving workers. Linear mixed-effects models were used to est. the within- and between-person components of variance for each urinary biomarker. The ratio of within- to between-person variance was then used to est. the biasing effects of each biomarker on a theor. exposure-response relationship. Mixed models were also used to est. the amts. of variation in Phe metab. to individual OH-Phe isomers that could be attributed to Phe exposure (as represented by U-Phe concns.) and covariates representing time, hydration level, smoking status, age, and body mass index. Results showed that 1-OH-Phe, (2+3)-OH-Phe, and 1-OH-Pyr were the least-biasing surrogates for exposure to hot asphalt emissions, and that effects of hydration level and sample collection time substantially inflated bias ests. for the urinary biomarkers. Mixed-model results for the individual OH-Phe isomers showed that between 63% and 82% of the obsd. biomarker variance was collectively explained by Phe exposure, the time and day of sample collection, and the hydration level, smoking status, body mass index, and age of each worker. By difference, the model results also showed that, depending on the OH-Phe isomer, a max. of 6-23% of the total biomarker variance was attributable to differences in unobserved toxicokinetic processes between the workers. Therefore, toxicokinetic processes are probably less influential on urinary biomarker variance than are exposures and observable covariate effects. The methods described in this anal. should be considered for the selection and interpretation of biomarkers as exposure surrogates in future exposure investigations.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVGnsL%252FO&md5=3f906a3477c45c8ac4c3ed50ad6660ce
61
Pleil, J. D.; Stiegel, M. A.; Sobus, J. R. J. Breath Res. 2011, 5, 046005
Google Scholar
There is no corresponding record for this reference.
62
Pleil, J. D.; Sobus, J. R.; Sheppard, P. R.; Ridenour, G.; Witten, M. L. Chem. Biol. Interact. 2012, 196, 68– 78
Google Scholar
62
Strategies for evaluating the environment-public health interaction of long-term latency disease: The quandary of the inconclusive case-control study
Pleil, Joachim D.; Sobus, Jon R.; Sheppard, Paul R.; Ridenour, Gary; Witten, Mark L.
Chemico-Biological Interactions (2012), 196 (3), 68-78CODEN: CBINA8; ISSN:0009-2797. (Elsevier Ireland Ltd.)
Environmental links to disease are difficult to uncover because environmental exposures are variable in time and space, contaminants occur in complex mixts., and many diseases have a long time delay between exposure and onset. Furthermore, individuals in a population have different activity patterns (e.g., hobbies, jobs, and interests), and different genetic susceptibilities to disease. As such, there are many potential confounding factors to obscure the reasons that one individual gets sick and another remains healthy. An important method for deducing environmental assocns. with disease outbreak is the retrospective case-control study wherein the affected and control subject cohorts are studied to see what is different about their previous exposure history. Despite success with infectious diseases (e.g., food poisoning, and flu), case-control studies of cancer clusters rarely have an unambiguous outcome. This is attributed to the complexity of disease progression and the long-term latency between exposure and disease onset. In this article, we consider strategies for investigating cancer clusters and make some observations for improving statistical power through broader non-parametric approaches wherein sub-populations (i.e., whole towns), rather than individuals, are treated as the cases and controls, and the assocd. cancer rates are treated as the dependent variable. We subsequently present some ecol. data for tungsten and cobalt from studies by University of Arizona researchers who document elevated levels of tungsten and cobalt in Fallon, NV. These results serve as candidates for future hybrid ecol. case-control investigations of childhood leukemia clusters.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xls1egsL0%253D&md5=082a94747b0b88286dce76c819237543

Cited By

Click to copy section linkSection link copied!

This article is cited by 55 publications.

Yan Wang, Jichun Jiang, Lei Hua, Keyong Hou, Yuanyuan Xie, Ping Chen, Wei Liu, Qingyun Li, Shuang Wang, and Haiyang Li . High-Pressure Photon Ionization Source for TOFMS and Its Application for Online Breath Analysis. Analytical Chemistry 2016, 88 (18) , 9047-9055. https://doi.org/10.1021/acs.analchem.6b01707
Sara El Fouikar, Nathalie Van Acker, Virginie Héliès, François-Xavier Frenois, Frank Giton, Véronique Gayrard, Yannick Dauwe, Laila Mselli-Lakhal, Delphine Rousseau-Ralliard, Natalie Fournier, Roger Léandri, Nicolas Gatimel. Folliculogenesis and steroidogenesis alterations after chronic exposure to a human-relevant mixture of environmental toxicants spare the ovarian reserve in the rabbit model. Journal of Ovarian Research 2024, 17 (1) https://doi.org/10.1186/s13048-024-01457-6
Hsuan Chou, Lucy Godbeer, Max Allsworth, Billy Boyle, Madeleine L. Ball. Progress and challenges of developing volatile metabolites from exhaled breath as a biomarker platform. Metabolomics 2024, 20 (4) https://doi.org/10.1007/s11306-024-02142-x
Yuanyuan SONG, Zenghua QI, Zongwei CAI. Application of multiomics mass spectrometry in the research of chemical exposome. Chinese Journal of Chromatography 2024, 42 (2) , 120-130. https://doi.org/10.3724/SP.J.1123.2023.10001
Pankaj Pankaj, Pramod Kumar, Aman Kapoor, Priyanka Priyanka, Puneet Kumar, Saweta Kumari. LC–Tof-Ms an Influential Hyphenated Technique and its Application. Asian Journal of Pharmaceutical Analysis 2023, , 35-41. https://doi.org/10.52711/2231-5675.2023.00006
. Appendix 1. 2023, e1-e52. https://doi.org/10.1016/B978-0-323-89873-7.00007-7
Shakiba Zeinali, Chiranjit Ghosh, Janusz Pawliszyn. Simultaneous determination of exhaled breath vapor and exhaled breath aerosol using filter-incorporated needle-trap devices: A comparison of gas-phase and droplet-bound components. Analytica Chimica Acta 2022, 1203 , 339671. https://doi.org/10.1016/j.aca.2022.339671
Joachim D Pleil, Charles N Lowe, M Ariel Geer Wallace, Antony J Williams. Using the US EPA CompTox Chemicals Dashboard to interpret targeted and non-targeted GC–MS analyses from human breath and other biological media. Journal of Breath Research 2021, 15 (2) , 025001. https://doi.org/10.1088/1752-7163/abdb03
Alexander J Schmidt, Eva Borras, Anh P Nguyen, Danny Yeap, Nicholas J Kenyon, Cristina E Davis. Portable exhaled breath condensate metabolomics for daily monitoring of adolescent asthma. Journal of Breath Research 2020, 14 (2) , 026001. https://doi.org/10.1088/1752-7163/ab35b5
Joachim D. Pleil, Matthew A. Stiegel, Jonathan D. Beauchamp. Breath biomarkers and the exposome. 2020, 3-21. https://doi.org/10.1016/B978-0-12-819967-1.00001-3
Joachim D Pleil, M Ariel Geer Wallace, James McCord, Michael C Madden, Jon Sobus, Glenn Ferguson. How do cancer-sniffing dogs sort biological samples? Exploring case-control samples with non-targeted LC-Orbitrap, GC-MS, and immunochemistry methods. Journal of Breath Research 2020, 14 (1) , 016006. https://doi.org/10.1088/1752-7163/ab433a
Shayma Alkobaisi, Wan D. Bae, Matthew Horak, Sada Narayanappa, Jongwon Lee, Eman AbuKhousa, Choon-Sik Park, Da Jung Bae. Predictive and exposome analytics: A case study of asthma exacerbation management. Journal of Ambient Intelligence and Smart Environments 2019, 11 (6) , 527-552. https://doi.org/10.3233/AIS-190540
Jingchuan Xue, Yunjia Lai, Chih-Wei Liu, Hongyu Ru. Towards Mass Spectrometry-Based Chemical Exposome: Current Approaches, Challenges, and Future Directions. Toxics 2019, 7 (3) , 41. https://doi.org/10.3390/toxics7030041
Wan D. Bae, Matthew Horak, Shayma Alkobaisi, Sehjeong Kim, Sada Narayanappa, Choon-Sik Park, Da Jeong Bae. A two-step approach to predictive modeling of individual-based environmental health risks. 2019, 729-738. https://doi.org/10.1145/3297280.3297350
Cassandra R. O’Lenick, Joachim D. Pleil, Matthew A. Stiegel, Jon R. Sobus, M. Ariel Geer Wallace. Detection and analysis of endogenous polar volatile organic compounds (PVOCs) in urine for human exposome research. Biomarkers 2019, 24 (3) , 240-248. https://doi.org/10.1080/1354750X.2018.1548031
M. Ariel Geer Wallace, Joachim D. Pleil, Karen D. Oliver, Donald A. Whitaker, Sibel Mentese, Kenneth W. Fent, Gavin P. Horn. Non-targeted GC/MS analysis of exhaled breath samples: Exploring human biomarkers of exogenous exposure and endogenous response from professional firefighting activity. Journal of Toxicology and Environmental Health, Part A 2019, 82 (4) , 244-260. https://doi.org/10.1080/15287394.2019.1587901
Xue Li, Dandan Huang, Jiafa Zeng, Chak Keung Chan, Zhen Zhou. Positive matrix factorization: A data preprocessing strategy for direct mass spectrometry-based breath analysis. Talanta 2019, 192 , 32-39. https://doi.org/10.1016/j.talanta.2018.09.020
Thomas Hector Chappuis, Bao An Pham Ho, Morgan Ceillier, Florence Ricoul, Manuel Alessio, Jean-Francois Beche, Christelle Corne, Gérard Besson, Jérôme Vial, Didier Thiébaut, Bertrand Bourlon. Miniaturization of breath sampling with silicon chip: application to volatile tobacco markers tracking. Journal of Breath Research 2018, 12 (4) , 046011. https://doi.org/10.1088/1752-7163/aad384
Jon R. Sobus, John F. Wambaugh, Kristin K. Isaacs, Antony J. Williams, Andrew D. McEachran, Ann M. Richard, Christopher M. Grulke, Elin M. Ulrich, Julia E. Rager, Mark J. Strynar, Seth R. Newton. Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA. Journal of Exposure Science & Environmental Epidemiology 2018, 28 (5) , 411-426. https://doi.org/10.1038/s41370-017-0012-y
Victor N Morozov, Andrey Y Mikheev, Yuri M Shlyapnikov, Alexander A Nikolaev, Irina V Lyadova. Non-invasive lung disease diagnostics from exhaled microdroplets of lung fluid: perspectives and technical challenges. Journal of Breath Research 2018, 12 (1) , 017103. https://doi.org/10.1088/1752-7163/aa88e4
Brett R Winters, Joachim D Pleil, Michelle M Angrish, Matthew A Stiegel, Terence H Risby, Michael C Madden. Standardization of the collection of exhaled breath condensate and exhaled breath aerosol using a feedback regulated sampling device. Journal of Breath Research 2017, 11 (4) , 047107. https://doi.org/10.1088/1752-7163/aa8bbc
M. Ariel Geer Wallace, Joachim D. Pleil, Sibel Mentese, Karen D. Oliver, Donald A. Whitaker, Kenneth W. Fent. Calibration and performance of synchronous SIM/scan mode for simultaneous targeted and discovery (non-targeted) analysis of exhaled breath samples from firefighters. Journal of Chromatography A 2017, 1516 , 114-124. https://doi.org/10.1016/j.chroma.2017.07.082
Alexander A. Aksenov, Konstantin O. Zamuruyev, Alberto Pasamontes, Joshua F. Brown, Michael Schivo, Soraya Foutouhi, Bart C. Weimer, Nicholas J. Kenyon, Cristina E. Davis. Analytical methodologies for broad metabolite coverage of exhaled breath condensate. Journal of Chromatography B 2017, 1061-1062 , 17-25. https://doi.org/10.1016/j.jchromb.2017.06.038
Jinchang Tian, Xin Huang, Guijie Mao, Feng Xu, Wenyi Chu, ZhiZhong Sun. Synthesis, photophysical, electrochemical and theoretical studies of the novel indolo[3,2-b]indole derivatives. Journal of Molecular Structure 2017, 1144 , 129-135. https://doi.org/10.1016/j.molstruc.2017.05.021
Joachim Pleil, Jonathan Beauchamp, Wolfram Miekisch. Cellular respiration, metabolomics and the search for illicit drug biomarkers in breath: report from PittCon 2017. Journal of Breath Research 2017, 11 (3) , 039001. https://doi.org/10.1088/1752-7163/aa7174
Young-Mi Go, Dean P. Jones. Redox theory of aging: implications for health and disease. Clinical Science 2017, 131 (14) , 1669-1688. https://doi.org/10.1042/CS20160897
Matthew A. Stiegel, Joachim D. Pleil, Jon R. Sobus, Tina Stevens, Michael C. Madden. Linking physiological parameters to perturbations in the human exposome: Environmental exposures modify blood pressure and lung function via inflammatory cytokine pathway. Journal of Toxicology and Environmental Health, Part A 2017, 80 (9) , 485-501. https://doi.org/10.1080/15287394.2017.1330578
Ildiko Horváth, Peter J. Barnes, Stelios Loukides, Peter J. Sterk, Marieann Högman, Anna-Carin Olin, Anton Amann, Balazs Antus, Eugenio Baraldi, Andras Bikov, Agnes W. Boots, Lieuwe D. Bos, Paul Brinkman, Caterina Bucca, Giovanna E. Carpagnano, Massimo Corradi, Simona Cristescu, Johan C. de Jongste, Anh-Tuan Dinh-Xuan, Edward Dompeling, Niki Fens, Stephen Fowler, Jens M. Hohlfeld, Olaf Holz, Quirijn Jöbsis, Kim Van De Kant, Hugo H. Knobel, Konstantinos Kostikas, Lauri Lehtimäki, Jon O. Lundberg, Paolo Montuschi, Alain Van Muylem, Giorgio Pennazza, Petra Reinhold, Fabio L.M. Ricciardolo, Philippe Rosias, Marco Santonico, Marc P. van der Schee, Frederik-Jan van Schooten, Antonio Spanevello, Thomy Tonia, Teunis J. Vink. A European Respiratory Society technical standard: exhaled biomarkers in lung disease. European Respiratory Journal 2017, 49 (4) , 1600965. https://doi.org/10.1183/13993003.00965-2016
Syam S. Andra, Christine Austin, Dhavalkumar Patel, Georgia Dolios, Mahmoud Awawda, Manish Arora. Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome. Environment International 2017, 100 , 32-61. https://doi.org/10.1016/j.envint.2016.11.026
Xue Li, Lei Huang, Hui Zhu, Zhen Zhou. Direct human breath analysis by secondary nano‐electrospray ionization ultrahigh‐resolution mass spectrometry: Importance of high mass resolution and mass accuracy. Rapid Communications in Mass Spectrometry 2017, 31 (3) , 301-308. https://doi.org/10.1002/rcm.7794
Eva Pose-Juan, Tania Fernández-Cruz, Jesús Simal-Gándara. State of the art on public risk assessment of combined human exposure to multiple chemical contaminants. Trends in Food Science & Technology 2016, 55 , 11-28. https://doi.org/10.1016/j.tifs.2016.06.011
Jonathan Williams, Joachim Pleil. Crowd-based breath analysis: assessing behavior, activity, exposures, and emotional response of people in groups. Journal of Breath Research 2016, 10 (3) , 032001. https://doi.org/10.1088/1752-7155/10/3/032001
Andras Bikov, James H. Hull, Laszlo Kunos. Exhaled breath analysis, a simple tool to study the pathophysiology of obstructive sleep apnoea. Sleep Medicine Reviews 2016, 27 , 1-8. https://doi.org/10.1016/j.smrv.2015.07.005
Matthew A. Stiegel, Joachim D. Pleil, Jon R. Sobus, Michael C. Madden, . Inflammatory Cytokines and White Blood Cell Counts Response to Environmental Levels of Diesel Exhaust and Ozone Inhalation Exposures. PLOS ONE 2016, 11 (4) , e0152458. https://doi.org/10.1371/journal.pone.0152458
Syam S. Andra, Christine Austin, Manish Arora. The tooth exposome in children's health research. Current Opinion in Pediatrics 2016, 28 (2) , 221-227. https://doi.org/10.1097/MOP.0000000000000327
Joachim D Pleil. Cellular respiration: replicating in vivo systems biology for in vitro exploration of human exposome, microbiome, and disease pathogenesis biomarkers. Journal of Breath Research 2016, 10 (1) , 010201. https://doi.org/10.1088/1752-7155/10/1/010201
Joachim D Pleil, Kristin K Isaacs. High-resolution mass spectrometry: basic principles for using exact mass and mass defect for discovery analysis of organic molecules in blood, breath, urine and environmental media. Journal of Breath Research 2016, 10 (1) , 012001. https://doi.org/10.1088/1752-7155/10/1/012001
Jonathan Beauchamp. Current sampling and analysis techniques in breath research—results of a task force poll. Journal of Breath Research 2015, 9 (4) , 047107. https://doi.org/10.1088/1752-7155/9/4/047107
Joachim D Pleil, Michelle M Angrish, Michael C Madden. Immunochemistry for high-throughput screening of human exhaled breath condensate (EBC) media: implementation of automated quanterix SIMOA instrumentation. Journal of Breath Research 2015, 9 (4) , 047108. https://doi.org/10.1088/1752-7155/9/4/047108
M. A. Stiegel, J. D. Pleil, J. R. Sobus, M. M. Angrish, M. K. Morgan. Kidney injury biomarkers and urinary creatinine variability in nominally healthy adults. Biomarkers 2015, 20 (6-7) , 436-452. https://doi.org/10.3109/1354750X.2015.1094136
Jon R. Sobus, Robert S. DeWoskin, Yu-Mei Tan, Joachim D. Pleil, Martin Blake Phillips, Barbara Jane George, Krista Christensen, Dina M. Schreinemachers, Marc A. Williams, Elaine A. Cohen Hubal, Stephen W. Edwards. Uses of NHANES Biomarker Data for Chemical Risk Assessment: Trends, Challenges, and Opportunities. Environmental Health Perspectives 2015, 123 (10) , 919-927. https://doi.org/10.1289/ehp.1409177
Karl Unterkofler, Julian King, Pawel Mochalski, Martin Jandacka, Helin Koc, Susanne Teschl, Anton Amann, Gerald Teschl. Modeling-based determination of physiological parameters of systemic VOCs by breath gas analysis: a pilot study. Journal of Breath Research 2015, 9 (3) , 036002. https://doi.org/10.1088/1752-7155/9/3/036002
Joachim D Pleil, Jonathan D Beauchamp, Wolfram Miekisch, William E Funk. Adapting biomarker technologies to adverse outcome pathways (AOPs) research: current thoughts on using in vivo discovery for developing in vitro target methods. Journal of Breath Research 2015, 9 (3) , 039001. https://doi.org/10.1088/1752-7155/9/3/039001
Martin Harper, Christopher Weis, Joachim D Pleil, Benjamin C Blount, Aubrey Miller, Mark D Hoover, Steven Jahn. Commentary on the contributions and future role of occupational exposure science in a vision and strategy for the discipline of exposure science. Journal of Exposure Science & Environmental Epidemiology 2015, 25 (4) , 381-387. https://doi.org/10.1038/jes.2014.91
Jonathan D Beauchamp, Joachim D Pleil. Breath: An Often Overlooked Medium in Biomarker Discovery. 2015, 75-93. https://doi.org/10.1002/9783527680658.ch5
Joachim D. Pleil. Understanding new “exploratory” biomarker data: a first look at observed concentrations and associated detection limits. Biomarkers 2015, 20 (2) , 168-169. https://doi.org/10.3109/1354750X.2015.1040841
Matthew A. Stiegel, Joachim D. Pleil, Jon R. Sobus, Marsha K. Morgan, Michael C. Madden. Analysis of inflammatory cytokines in human blood, breath condensate, and urine using a multiplex immunoassay platform. Biomarkers 2015, 20 (1) , 35-46. https://doi.org/10.3109/1354750X.2014.988646
Heather D. Bean, Jaime Jiménez-Díaz, Jiangjiang Zhu, Jane E. Hill. Breathprints of model murine bacterial lung infections are linked with immune response. European Respiratory Journal 2015, 45 (1) , 181-190. https://doi.org/10.1183/09031936.00015814
Anton Amann, Ben de Lacy Costello, Wolfram Miekisch, Jochen Schubert, Bogusław Buszewski, Joachim Pleil, Norman Ratcliffe, Terence Risby. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. Journal of Breath Research 2014, 8 (3) , 034001. https://doi.org/10.1088/1752-7155/8/3/034001
Jens Herbig, Jonathan Beauchamp. Towards standardization in the analysis of breath gas volatiles. Journal of Breath Research 2014, 8 (3) , 037101. https://doi.org/10.1088/1752-7155/8/3/037101
Joachim D Pleil, Matthew A Stiegel, Kenneth W Fent. Exploratory breath analyses for assessing toxic dermal exposures of firefighters during suppression of structural burns. Journal of Breath Research 2014, 8 (3) , 037107. https://doi.org/10.1088/1752-7155/8/3/037107
Paweł Mochalski, Karl Unterkofler, Patrik Španěl, David Smith, Anton Amann. Product ion distributions for the reactions of NO + with some physiologically significant volatile organosulfur and organoselenium compounds obtained using a selective reagent ionization time‐of‐flight mass spectrometer. Rapid Communications in Mass Spectrometry 2014, 28 (15) , 1683-1690. https://doi.org/10.1002/rcm.6947
Anton Amann, Wolfram Miekisch, Jochen Schubert, Bogusław Buszewski, Tomasz Ligor, Tadeusz Jezierski, Joachim Pleil, Terence Risby. Analysis of Exhaled Breath for Disease Detection. Annual Review of Analytical Chemistry 2014, 7 (1) , 455-482. https://doi.org/10.1146/annurev-anchem-071213-020043
Joachim D Pleil, Wolfram Miekisch, Matthew A Stiegel, Jonathan Beauchamp. Extending breath analysis to the cellular level: current thoughts on the human microbiome and the expression of organic compounds in the human exposome. Journal of Breath Research 2014, 8 (2) , 029001. https://doi.org/10.1088/1752-7155/8/2/029001
Paweł Mochalski, Karl Unterkofler, Patrik Španěl, David Smith, Anton Amann. Product ion distributions for the reactions of NO+ with some physiologically significant aldehydes obtained using a SRI-TOF-MS instrument. International Journal of Mass Spectrometry 2014, 363 , 23-31. https://doi.org/10.1016/j.ijms.2014.02.016

Download PDF

Get e-Alerts

Analytical Chemistry

Cite this: Anal. Chem. 2013, 85, 21, 9984–9990

Click to copy citationCitation copied!

https://doi.org/10.1021/ac402306f

Published September 25, 2013

Request reuse permissions

Article Views

Altmetric

Citations

Learn about these metrics

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.

Abstract
High Resolution Image
Download MS PowerPoint Slide
Figure 1
Figure 1. Relatives like the grandfather and grandson share genetic traits, but their environmental lifetime experiences result in very different personal exposomes despite sharing the same exposures for a short time on occasion. Photo Copyright: C. Maureen Pleil.
High Resolution Image
Download MS PowerPoint Slide
Figure 2
Figure 2. The diagram shows the classical concepts of bottom-up, targeted analysis (left triangle) in contrast to top-down discovery analysis (right triangle) for assessing the effects on the human community or subpopulation (center). Center image photo credit: Shuttershock. Targeted analysis seeks out specific compounds of exposure in the environment from multiple sources (food, air, water, dust, etc.) whereas discovery analysis starts with human biological media (blood, breath, urine, etc.) to look for all possible compounds and then narrow them down to those with potential exposure to health linkages.
High Resolution Image
Download MS PowerPoint Slide
Figure 3
Figure 3. Left side graphics are a depiction of a “whole breath” gas sample analyzed with GC/MS under full scan, or discovery mode (top), and with selected ion monitoring, or targeted mode (bottom). The right side graphics show only the extracted traces for specific ions, and a close-up for two specific compounds, 3-methylbutanol and benzene. Although the extractions of the discovery mode (top) show a “noisier” result than those of the targeted mode (bottom), the targeted mode is missing many ions that can be seen in discovery mode.
High Resolution Image
Download MS PowerPoint Slide
References
This article references 62 other publications.
1. 1
  Pleil, J. D.; Blount, B. C.; Waidyanatha, S.; Harper, M. J. Exposure Sci. Environ. Epidemiol. 2012, 22, 317– 319
  1
  Establishing exposure science as a distinct scientific discipline
  Pleil Joachim D; Blount Benjamin C; Waidyanatha Suramya; Harper Martin
  Journal of exposure science & environmental epidemiology (2012), 22 (4), 317-9 ISSN:.
  There is no expanded citation for this reference.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38jjtFChtQ%253D%253D&md5=a520800c7dd7c6485b04e5b2afabfc8c
2. 2
  Barr, D. B. J. Exposure Sci. Environ. Epidemiol. 2006, 16
  There is no corresponding record for this reference.
3. 3
  Lioy, P. J. Environ. Health. Perspect. 2010, 118, 1081– 1090
  There is no corresponding record for this reference.
4. 4
  Cohen-Hubal, E. A.; Barr, D. B.; Koch, H. M.; Bahadori, T. J. J. Exposure Sci. Environ. Epidemiol. 2011, 21, 121– 122
  4
  The promise of exposure science
  Cohen Hubal Elaine A; Barr Dana B; Koch Holger M; Bahadori Tina
  Journal of exposure science & environmental epidemiology (2011), 21 (2), 121-2 ISSN:.
  There is no expanded citation for this reference.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3M7psFKisw%253D%253D&md5=6b4d5103bebbbf8e2d32faa45ee68c50
5. 5
  Wild, C. P. Cancer Epidemiol. Biomarkers Prev. 2005, 14, 1847– 1850
  There is no corresponding record for this reference.
6. 6
  Pleil, J. D.; Stiegel, M. A.; Madden, M. C.; Sobus, J. R. Chemosphere 2011, 84, 716– 23
  There is no corresponding record for this reference.
7. 7
  Helix Project: Building the Early-Life Exposome. http://www.projecthelix.eu/ (accessed September 10, 2013).
  There is no corresponding record for this reference.
8. 8
  National Research Council of The National Academies. The National Academies Press, Washington, DC, 2013.
  There is no corresponding record for this reference.
9. 9
  Berkeley Center for Exposure Biology: University of California, Berkeley. Biological Response Indicators of Environment Stress Centers. http://www.niehs.nih.gov/research/supported/dert/cris/programs/exposure/biological_response/berkeley/index.cfm (accessed September 10, 2013).
  There is no corresponding record for this reference.
10. 10
  Health and Exposome Research Center: Understanding Lifetime Exposures. http://news.emory.edu/stories/2013/05/hercules_esposome_grant_rollins/ (accessed September 10, 2013).
  There is no corresponding record for this reference.
11. 11
  Rappaport, S. M.; Smith, M. T. Science 2010, 330, 460– 461
  There is no corresponding record for this reference.
12. 12
  Pleil, J. D.; Sheldon, L. S. Biomarkers 2011, 16, 99– 105
  There is no corresponding record for this reference.
13. 13
  Pleil, J. D. J. Toxicol. Environ. Health, B: Crit. Rev. 2012, 15, 264– 80
  There is no corresponding record for this reference.
14. 14
  Paoloni-Giacobino, A. Swiss Med. Wkly. 2011, 141, w13321
  There is no corresponding record for this reference.
15. 15
  Klepeis, N. E.; Nelson, W. C.; Ott, W. R.; Robinson, J. P.; Tsang, A. M.; Switzer, P.; Behar, J. V.; Hern, S. C.; Engelmann, W. H. J. Exposure Anal. Environ. Epidemiol. 2001, 11, 231– 252
  15
  The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants
  Klepeis, Neil E.; Nelson, William C.; Ott, Wayne R.; Robinson, John P.; Tsang, Andy M.; Switzer, Paul; Behar, Joseph V.; Hern, Stephen C.; Engelmann, William H.
  Journal of Exposure Analysis and Environmental Epidemiology (2001), 11 (3), 231-252CODEN: JEAEE9; ISSN:1053-4245. (Nature America Inc.)
  Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey (NHAPS), a 2-yr probability-based telephone survey (n = 9386) of exposure-related human activities in the USA sponsored by the US Environmental Protection Agency (EPA). The primary purpose of the NHAPS was to provide comprehensive and current exposure information over broad geog. and temporal scales, particularly for use in probabilistic population exposure models. The NHAPS was conducted on a virtually daily basis from late Sept., 1992, through Sept., 1994, by the University of Maryland's Survey Research Center using a computer-assisted telephone interview instrument (CATI) to collect 24-h retrospective diaries and answers to a no. of personal and exposure-related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day (i.e., each microenvironment). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an av. of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly const. across the various regions of the USA and Canada and for the California population between the late 1980s, when the California Air Resources Board (CARB) sponsored a state-wide activity pattern study, and the mid-1990s, when the NHAPS was conducted. However, the no. of people exposed to environmental tobacco smoke (ETS) in California seems to have decreased over the same time period, where exposure is detd. by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXmtVSmsbs%253D&md5=6c8e00fa03e935e7abf4c454556c1b29
16. 16
  Zhang, L.; McHale, C. M.; Rothman, N.; Li, G.; Ji, Z.; Vermeulen, R.; Hubbard, A. E.; Ren, X.; Shen, M.; Rappaport, S. M.; North, M.; Skibola, C. F.; Yin, S.; Vulpe, C.; Chanock, S. J.; Smith, M. T.; Lan, Q. Chem. Biol. Interact. 2010, 184, 86– 93
  16
  Systems biology of human benzene exposure
  Zhang, Luoping; McHale, Cliona M.; Rothman, Nathaniel; Li, Guilan; Ji, Zhiying; Vermeulen, Roel; Hubbard, Alan E.; Ren, Xuefeng; Shen, Min; Rappaport, Stephen M.; North, Matthew; Skibola, Christine F.; Yin, Songnian; Vulpe, Christopher; Chanock, Stephen J.; Smith, Martyn T.; Lan, Qing
  Chemico-Biological Interactions (2010), 184 (1-2), 86-93CODEN: CBINA8; ISSN:0009-2797. (Elsevier Ireland Ltd.)
  A review. Toxicogenomic studies, including genome-wide analyses of susceptibility genes (genomics), gene expression (transcriptomics), protein expression (proteomics), and epigenetic modifications (epigenomics), of human populations exposed to benzene are crucial to understanding gene-environment interactions, providing the ability to develop biomarkers of exposure, early effect and susceptibility. Comprehensive anal. of these toxicogenomic and epigenomic profiles by bioinformatics in the context of phenotypic endpoints, comprises systems biol., which has the potential to comprehensively define the mechanisms by which benzene causes leukemia. We have applied this approach to a mol. epidemiol. study of workers exposed to benzene. Hematotoxicity, a significant decrease in almost all blood cell counts, was identified as a phenotypic effect of benzene that occurred even below 1 ppm benzene exposure. We found a significant decrease in the formation of progenitor colonies arising from bone marrow stem cells with increasing benzene exposure, showing that progenitor cells are more sensitive to the effects of benzene than mature blood cells, likely leading to the obsd. hematotoxicity. Anal. of transcriptomics by microarray in the peripheral blood mononuclear cells of exposed workers, identified genes and pathways (apoptosis, immune response, and inflammatory response) altered at high (>10 ppm) and low (<1 ppm) benzene levels. Serum proteomics by SELDI-TOF-MS revealed proteins consistently down-regulated in exposed workers. Preliminary epigenomics data showed effects of benzene on the DNA methylation of specific genes. Genomic screens for candidate genes involved in susceptibility to benzene toxicity are being undertaken in yeast, with subsequent confirmation by RNAi in human cells, to expand upon the findings from candidate gene analyses. Data on these and future biomarkers will be used to populate a large toxicogenomics database, to which we will apply bioinformatic approaches to understand the interactions among benzene toxicity, susceptibility genes, mRNA, and DNA methylation through a systems biol. approach.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXktVWqtro%253D&md5=8cfa665ab0aa2c430cba152f2bf7c63b
17. 17
  Rappaport, S. M. J. Exposure Sci. Environ. Epidemiol. 2011, 21, 5– 9
  17
  Implications of the exposome for exposure science
  Rappaport, Stephen M.
  Journal of Exposure Science & Environmental Epidemiology (2011), 21 (1), 5-9CODEN: JESEBS; ISSN:1559-0631. (Nature Publishing Group)
  A review. During the 1920s, the forerunners of exposure science collaborated with health professionals to investigate the causes of occupational diseases. With the birth of U.S. regulatory agencies in the 1970s, interest in the environmental origins of human diseases waned, and exposure scientists focused instead upon levels of selected contaminants in air and water. In fact, toxic chems. enter the body not only from exogenous sources (air, water, diet, drugs, and radiation) but also from endogenous processes, including inflammation, lipid peroxidn., oxidative stress, existing diseases, infections, and gut flora. Thus, even though current evidence suggests that non-genetic factors contribute about 90% of the risks of chronic diseases, we have not explored the vast majority of human exposures that might initiate disease processes. The concept of the exposome, representing the totality of exposures received by a person during life, encompasses all sources of toxicants and, therefore, offers scientists an agnostic approach for investigating the environmental causes of chronic diseases. In this context, it is appropriate to regard the "environment" as the body's internal chem. environment and to define "exposures" as levels of biol. active chems. in this internal environment. To explore the exposome, it makes sense to employ a top-down approach based upon biomonitoring (e.g. blood sampling) rather than a bottom-up approach that samples air, water, food, and so on. Because sources and levels of exposure change over time, exposomes can be constructed by analyzing toxicants in blood specimens obtained during crit. stages of life. Initial investigations could use archived blood from prospective cohort studies to measure important classes of toxic chems., notably, reactive electrophiles, metals, metabolic products, hormone-like substances, and persistent org. compds. The exposome offers health scientists an avenue for integrating research that is currently fractured along lines related to particular diseases and risk factors, and can thereby promote discovery of the key exposures responsible for chronic diseases. By embracing the exposome as its operational paradigm, exposure science can play a major role in discovering and mitigating these exposures.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFyku7nF&md5=dbc872e9f5a98a2f742b032c520e12c5
18. 18
  Liu, L.; Li, Y.; Tollefsbol, T. O. Curr. Issues. Mol. Biol. 2008, 10, 25– 36
  18
  Gene-environment interactions and epigenetic basis of human diseases
  Liu, Liang; Li, Yuanyuan; Tollefsbol, Trygve O.
  Current Issues in Molecular Biology (2008), 10 (1 and 2), 25-36CODEN: CMBIF6; ISSN:1467-3037. (Horizon Scientific Press)
  A review. Most human diseases are related in some way to the loss or gain in gene functions. Regulation of gene expression is a complex process. In addn. to genetic mechanisms, epigenetic causes are gaining new perspectives in human diseases related to gene deregulation. Most eukaryotic genes are packed into chromatin structures, which lead to high condensations of the genes that require dynamic chromatin remodeling processes to facilitate their transcription. DNA methylation and histone modifications represent two of the major chromatin remodeling processes. They also serve to integrate environmental signals for the cells to modulate the functional output of their genome. Complex human diseases such as cancer and type 2 diabetes are believed to have a strong environmental component in addn. to genetic causes. Aberrancies in chromatin remodeling are assocd. with both genetically and environmentally-related diseases. We will focus on recent findings of the epigenetic basis of human metabolic disorders to facilitate further exploration of epigenetic mechanisms and better understandings of the mol. cues underlying such complex diseases.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXos1Wju7g%253D&md5=0f033ba89b1e02b0b86bb25c6fd498d0
19. 19
  The White House, Office of the Press Secretary. President Clinton Announces the Completion of the First Survey of the Entire Human Genome, Hails Public and Private Efforts Leading to This Historic Achievement; http://web.ornl.gov/sci/techresources/Human_Genome/project/clinton1.shtml (accessed September 10, 2013).
  There is no corresponding record for this reference.
20. 20
  Wade, N. In New York Times; New York Times: New York, 2010.
  There is no corresponding record for this reference.
21. 21
  Hall, S. S. Sci. Am. 2010, 303, 60– 67
  21
  Revolution postponed
  Hall Stephen S
  Scientific American (2010), 303 (4), 60-7 ISSN:0036-8733.
  There is no expanded citation for this reference.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cfnsVOrsw%253D%253D&md5=a56bd07653d970e6d91cf63b7ea9629d
22. 22
  Kaiser, J. Science 2012, 338, 1016– 1017
  There is no corresponding record for this reference.
23. 23
  Egeghy, P. P.; Hauf-Cabalo, L.; Gibson, R.; Rappaport, S. M. Occup. Environ. Med. 2003, 60, 969– 976
  There is no corresponding record for this reference.
24. 24
  Rigas, M. L.; Okino, M. S.; Quackenboss, J. J. Toxicol. Sci. 2001, 61, 374– 381
  24
  Use of a pharmacokinetic model to assess chlorpyrifos exposure and dose in children, based on urinary biomarker measurements
  Rigas, Marc L.; Okino, Miles S.; Quackenboss, James J.
  Toxicological Sciences (2001), 61 (2), 374-381CODEN: TOSCF2; ISSN:1096-6080. (Oxford University Press)
  Chlorpyrifos is a common agricultural insecticide and has been used residentially in the United States until the year 2000 when this use was restricted by the U.S. Environmental Protection Agency (U.S. EPA). A chlorpyrifos metabolite, 3,5,6-trichloro-2-pyridinol (TCPy), has been found in urine samples collected during exposure field studies. In this work, the authors use urinary biomarker data and the inverse soln. of a simple pharmacokinetic (PK) model for chlorpyrifos to est. the magnitude and timing of doses. Three urine samples were collected on sep. days from each of 15 children (ages 3-12) who were participants in the Minnesota Children's Pesticide Exposure Study (MNCPES). The total vol. of urine was noted and samples analyzed for TCPy. The urinary data was used along with constraints imposed on dose timing, based on responses of the individuals to pesticide-use surveys. The authors predicted the time and magnitude of multiple event exposures characterized by short-term, relatively high doses superimposed over a continuous background exposure. The av. dose of chlorpyrifos predicted by the model was 1.61 μg/kg per reported event. Av. background dose rate for these children that reported exposure events was 0.0062 μg/kg/h, or 0.15 μg/kg/day. In addn. to predicting the total dose of chlorpyrifos received by an individual from urinary biomarker measurements, the model can then be run in a forward manner once the exposure regime is detd. This will allow the prediction of the total amt. of TCPy eliminated in the urine over any time period of interest.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXktVajt74%253D&md5=5633070a9c2ca9b7f2315feaf323db54
25. 25
  Toxic Substances Control Act. U.S. Code, Chapter 53, Title 15, pp 2601– 2629, 1976.
  There is no corresponding record for this reference.
26. 26
  U.S. Environmental Protection Agency. Framework for an EPA Chemical Safety for Sustainability Research Program; U.S. Government Printing Office: Washington, DC, 2011.
  There is no corresponding record for this reference.
27. 27
  Judson, R.; Richard, A.; Dix, D. J.; Houck, K.; Martin, M.; Kavlock, R.; Dellarco, V.; Henry, T.; Holderman, T.; Sayre, P.; Tan, S.; Carpenter, T.; Smith, E. Environ. Health Perspect. 2009, 117, 685– 695
  There is no corresponding record for this reference.
28. 28
  Sheldon, L. S.; Cohen Hubal, E. A. Environ. Health Perspect. 2009, 117, 119– 1194
  There is no corresponding record for this reference.
29. 29
  National Research Council of The National Academies. Toxicity Testing in the 21st Century: A Vision and a Strategy; 2007.
  There is no corresponding record for this reference.
30. 30
  Dix, D. J.; Houck, K. A.; Martin, M. T.; Richard, A. M.; Setzer, R. W.; Kavlock, R. Toxicol. Sci. 2007, 95, 5– 12
  30
  The ToxCast Program for Prioritizing Toxicity Testing of Environmental Chemicals
  Dix, David J.; Houck, Keith A.; Martin, Matthew T.; Richard, Ann M.; Setzer, R. Woodrow; Kavlock, Robert J.
  Toxicological Sciences (2007), 95 (1), 5-12CODEN: TOSCF2; ISSN:1096-6080. (Oxford University Press)
  A review. The U.S. Environmental Protection Agency (EPA) is developing methods for utilizing computational chem., high-throughput screening (HTS), and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources toward chems. that likely represent the greatest hazard to human health and the environment. This chem. prioritization research program, entitled "ToxCast," is being initiated with the purpose of developing the ability to forecast toxicity based on bioactivity profiling. The proof-of-concept phase of ToxCast will focus upon chems. with an existing, rich toxicol. database to provide an interpretive context for the ToxCast data. This set of several hundred ref. chems. will represent numerous structural classes and phenotypic outcomes, including tumorigens, developmental and reproductive toxicants, neurotoxicants, and immunotoxicants. The ToxCast program will evaluate chem. properties and bioactivity profiles across a broad spectrum of data domains: Phys.-chem., predicted biol. activities based on existing structure-activity models, biochem. properties based on HTS assays, cell-based phenotypic assays, and genomic and metabolomic analyses of cells. These data will be generated through a series of external contracts, along with collaborations across EPA, with the National Toxicol. Program, and with the National Institutes of Health Chem. Genomics center. The resulting multidimensional data set provides an informatics challenge requiring appropriate computational methods for integrating various chem., biol., and toxicol. data into profiles and models predicting toxicity.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtlChtLjK&md5=73fbf7b6fcaf532721dbe1584c6ee8f8
31. 31
  Knudsen, T.; Martin, M.; Chandler, K.; Kleinstreuer, N.; Judson, R.; Sipes, N. Methods Mol. Biol. 2013, 947, 343– 374
  31
  Predictive models and computational toxicology
  Knudsen, Thomas; Martin, Matthew; Chandler, Kelly; Kleinstreuer, Nicole; Judson, Richard; Sipes, Nisha
  Methods in Molecular Biology (New York, NY, United States) (2013), 947 (Teratogenicity Testing), 343-374CODEN: MMBIED; ISSN:1064-3745. (Springer)
  A review. Understanding the potential health risks posed by environmental chems. is a significant challenge elevated by the large no. of diverse chems. with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicol. research program was launched by EPA in 2007 and is part of the federal Tox21 consortium to develop a cost-effective approach for efficiently prioritizing the toxicity testing of thousands of chems. and the application of this information to assessing human toxicol. ToxCast addresses this problem through an integrated workflow using high-throughput screening (HTS) of chem. libraries across more than 650 in vitro assays including biochem. assays, human cells and cell lines, and alternative models such as mouse embryonic stem cells and zebrafish embryo development. The initial phase of ToxCast profiled a library of 309 environmental chems., mostly pesticidal actives having rich in vivo data from guideline studies that include chronic/cancer bioassays in mice and rats, multigenerational reproductive studies in rats, and prenatal developmental toxicity endpoints in rats and rabbits. The first phase of ToxCast was used to build models that aim to det. how well in vivo animal effects can be predicted solely from the in vitro data. Phase I is now complete and both the in vitro data (ToxCast) and anchoring in vivo database (ToxRefDB) have been made available to the public (http://actor.epa. gov/). As Phase II of ToxCast is now underway, the purpose of this chapter is to review progress to date with ToxCast predictive modeling, using specific examples on developmental and reproductive effects in rats and rabbits with lessons learned during Phase I.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXktlaqt78%253D&md5=46aeb3afb59ebfe6a48f3d779ba3321a
32. 32
  Bouhifd, M.; Hartung, T.; Hogberg, H. T.; Kleensang, A.; Zhao, L. J. Appl. Toxicol. 2013, DOI: 10.1002/jat.2874
  There is no corresponding record for this reference.
33. 33
  Pleil, J. D.; Williams, M. A.; Sobus, J. R. Toxicol. Lett. 2012, 215, 201– 207
  33
  Chemical Safety for Sustainability (CSS): Human in vivo biomonitoring data for complementing results from in vitro toxicology-A commentary
  Pleil, Joachim D.; Williams, Marc A.; Sobus, Jon R.
  Toxicology Letters (2012), 215 (3), 201-207CODEN: TOLED5; ISSN:0378-4274. (Elsevier Ireland Ltd.)
  A review. The U.S. Environmental Protection Agency (EPA) has instituted the Chem. Safety for Sustainability (CSS) research program for assessing the health and environmental impact of manufd. chems. This is a broad program wherein one of the tasks is to develop high throughput screening (HTS) methods and follow-up confirmation for toxicity at realistic environmental exposure levels. The main tools under this task are in vitro toxicity testing, in silico mol. modeling, and in vivo (systemic) measurements documentation. The in vivo research component is intended to support and corroborate in vitro chem. toxicity prioritization with observations of systemic perturbations and statistical parameters derived from intact (living) organisms. Based on EPA's Biomonitoring Framework for human health research, such observations are intended to link environmental exposures to a cascade of biomarker chems. to help identify and clarify adverse outcome pathways within the context of systems biol. This commentary discusses the issues regarding interpretation of in vitro changes from HTS as an adverse result, an adaptive (non-adverse) response, or a random/irrelevant occurrence. A second goal is to inform in vitro strategies as to relevant dosing (potency) levels at the cellular level that reflect realistic systemic exposures. Although the authors recognize the high value of in vivo animal toxicity testing, herein the authors focus on observational (minimally invasive) human biomonitoring methods and propose complementary in vivo testing that could help guide the design of high-throughput analyses and the ultimate interpretation of their outcomes.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhslKqtLnO&md5=558ef74730e1d618413066e0b29e0673
34. 34
  Ankley, G. T.; Bennett, R. S.; Erickson, R. J.; Hoff, D. J.; Hornung, M. W.; Johnson, R. D.; Mount, D. R.; Nichols, J. W.; Russom, C. L.; Schmieder, P. K.; Serrrano, J. A.; Tietge, J. E.; Villeneuve, D. L. Environ. Toxicol. Chem. 2010, 29, 730– 741
  There is no corresponding record for this reference.
35. 35
  Liu, H.; Bebu, I.; Li, X. Front. Biosci. 2010, 2, 325– 338
  35
  Microarray probes and probe sets
  Liu, Hongfang; Bebu, Ionut; Li, Xin
  Frontiers in Bioscience, Elite Edition (2010), E2 (1), 325-338CODEN: FBEEAS; ISSN:1945-0508. (Frontiers in Bioscience)
  A review. DNA microarrays have gained wide use in biomedical research by simultaneously monitoring the expression levels of a large no. of genes. The successful implementation of DNA microarray technologies requires the development of methods and techniques for the fabrication of microarrays, the selection of probes to represent genes, the quantification of hybridization, and data anal. In this paper, we conc. on probes that are either spotted or synthesized on the glass slides through several aspects: sources of probes, the criteria for selecting probes, tools available for probe selections, and probes used in com. microarray chips. We then provide a detailed review of one type of DNA microarray: Affymetrix GeneChips, discuss the need to re-annotate probes, review different methods for regrouping probes into probe sets, and compare various redefinitions through public available datasets.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXovFalsLs%253D&md5=ec191e5e945cf3a652e75ebd7a5c3148
36. 36
  Patel, C. J.; Bhattacharya, J.; Butte, A. J. PLoS One 2010, 5, e10746
  There is no corresponding record for this reference.
37. 37
  Rappaport, S. M. Biomarkers 2012, 17, 483– 489
  There is no corresponding record for this reference.
38. 38
  Amann, A.; Corradi, M.; Mazzone, P.; Mutti, A. Expert Rev. Mol. Diagn. 2011, 11, 202– 217
  There is no corresponding record for this reference.
39. 39
  Mazzone, P. J. J. Breath Res. 2012, 6, 027106
  There is no corresponding record for this reference.
40. 40
  Slatore, C. G.; Gould, M. K.; Au, D. H.; Deffebach, M. E.; White, E. BMC Cancer 2011, 11, 7
  There is no corresponding record for this reference.
41. 41
  Bunn, P. A. Arch. Pathol. Lab. Med. 2012, 136, 1478– 1481
  41
  Worldwide overview of the current status of lung cancer diagnosis and treatment
  Bunn Paul A Jr
  Archives of pathology & laboratory medicine (2012), 136 (12), 1478-81 ISSN:.
  Lung cancer is the leading worldwide cause of cancer deaths. Smoking is the dominant cause of lung cancer and smoking cessation is the established method to reduce lung cancer mortality. While lung cancer risk is reduced in former smokers, they have a lifelong increase in risk, compared to never-smokers. Novel chemoprevention strategies, such as oral or inhaled prostacyclin analogs, hold promise for these subjects. Low-dose spiral computed tomography screening reduced lung cancer mortality by 20% in high-risk heavy smokers older than 50 years. However, the high false-positive rate (96%) means that screened patients required controlled follow-up in experienced centers. An increasing percentage of patients with advanced lung cancer have molecular drivers in genes for which oral tyrosine kinase inhibitors have been developed.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3s7nsVClsA%253D%253D&md5=f750891f4b27e02022112eddeafbffef
42. 42
  Pleil, J. D.; Stiegel, M. A.; Risby, T. H. J. Breath Res. 2013, 7, 017107
  There is no corresponding record for this reference.
43. 43
  Miekisch, W.; Herbig, J.; Schubert, J. K. J. Breath Res. 2012, 6, 036007
  There is no corresponding record for this reference.
44. 44
  Rosias, P. J. Breath Res. 2012, 6, 027102
  There is no corresponding record for this reference.
45. 45
  Loukides, S.; Kontogianni, K.; Hillas, G.; Horvath, I. Curr. Med. Chem. 2011, 18, 1432– 1443
  45
  Exhaled breath condensate in asthma: from bench to bedside
  Loukides, S.; Kontogianni, K.; Hillas, G.; Horvath, I.
  Current Medicinal Chemistry (2011), 18 (10), 1432-1443CODEN: CMCHE7; ISSN:0929-8673. (Bentham Science Publishers Ltd.)
  A review. The need for non-invasive assessment of airway inflammation is imperative, since inflammatory airway diseases, such as asthma and COPD, are characterized by variation in their clin. presentation throughout their course. Exhaled breath condensate (EBC) collection represents a rather appealing method that can be used to conveniently and noninvasively collect a wide range of volatile and non-volatile mols. from the respiratory tract, without affecting airway function or inflammation. Although promising, EBC is currently used only as a research tool, due to the lack of appropriate standardization and the absence of ref. values. A large no. of mediators of inflammation, oxidative and nitrosative stress, including adenosine, ammonia, hydrogen peroxide, isoprostanes, leukotrienes, prostanoids, nitrogen oxides, peptides and cytokines, were studied in EBC. This review focuses mainly on the presentation of the above biomarkers in asthma as well as on the effect of various factors on their concns. Concns. of such mediators have been shown to be related to the underlying asthma and its severity and to be modulated by therapeutic interventions. Despite the encouraging pos. results up-to-date, the introduction of EBC in everyday clin. practice requires the work-out of some methodol. pitfalls, the standardization of EBC collection, and finally the identification of a reliable biomarker which is reproducible, has normal values and provides information for the underlying inflammatory process and the response to treatment. So far none of the parameters studied in EBC fulfils the aforementioned requirements.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXpslOitrw%253D&md5=8646af52349f8cc18e4892411b0ddf30
46. 46
  Kazani, S.; Israel, E. J. Breath Res. 2010, 4, 047001
  There is no corresponding record for this reference.
47. 47
  Lee, W.; Thomas, P. S. Clin. Transl. Sci. 2009, 2, 150– 155
  47
  Oxidative stress in COPD and its measurement through exhaled breath condensate
  Lee, Wei; Thomas, Paul S.
  Clinical and Translational Science (2009), 2 (2), 150-155CODEN: CTSLCA; ISSN:1752-8062. (Wiley-Blackwell)
  A review. Oxidative stress and airway inflammation together form a vicious cycle, which is responsible for the disease progression in chronic pulmonary obstructive disease (COPD). The damaging effects of oxidative stress accumulate over the years, causing increased bronchial hyperresponsiveness and inflammation and destruction of airway epithelial cells and impairing the functions of antiproteases and surfactant. Although the lung expresses a no. of antioxidants, cigarette smoking and recurrent infections assocd. with this disease overwhelm this protective mechanism. Studies of antioxidants in COPD have yielded conflicting results, probably due to the compartmentalization of these mediators, and because of the fact that the lung is a difficult organ to sample. Chronic exposure to oxidants upregulates the prodn. of antioxidants, which become depleted during acute exacerbations. Future studies of the pathogenesis of COPD require a noninvasive yet accurate sampling procedure, of which exhaled breath condensate (EBC) is a good candidate. EBC samples the epithelial lining fluid, which contains the local oxidative stress markers in the lung. Oxidative stress markers such as hydrogen ions, hydrogen peroxide, 8-isoprostanes, thiobarbituric acid reactive products, nitrosothiols, and nitrite/nitrate have been identified in EBC of COPD patients, whereas many other markers of the oxidative-antioxidative balance have yet to be investigated.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXisVGktL0%253D&md5=2bc7e9b1b37393fc6f98a27e34352a66
48. 48
  Chambers, S. T.; Scott-Thomas, A.; Epton, M. Curr. Opin. Pulm. Med. 2012, 18, 228– 232
  48
  Developments in novel breath tests for bacterial and fungal pulmonary infection
  Chambers Stephen T; Scott-Thomas Amy; Epton Michael
  Current opinion in pulmonary medicine (2012), 18 (3), 228-32 ISSN:.
  PURPOSE OF REVIEW: Breath testing has developed over the last 20 years. New techniques that can identify fingerprints for specific diseases and specific markers of respiratory pathogens have been applied to breath analysis. This review discusses the recent advances in breath analysis for the diagnosis of bacterial and fungal lower respiratory tract infections. RECENT FINDINGS: The current techniques continue to develop rapidly, but preconcentration techniques are needed to analyse many target volatile organic compounds for most systems. Breath testing with an electronic nose is promising for the diagnosis of tuberculosis (TB), and specific volatiles identifiable by gas chromatography with mass spectrometry have been identified in breath for Mycobacterium tuberculosis, Pseudomonas aeruginosa and Aspergillus fumigatus, but are found at very low concentrations in breath. Contamination from the environment is an ongoing confounding influence. Exhaled breath condensate (EBC) is disappointing as a diagnostic sample. SUMMARY: Careful attention needs to be paid to the sensitivity and specificity of a technique and confounding from the environment. The role of technologies such as selected ion flow tube-mass spectrometry is emerging. The electronic nose requires further validation for TB. The identification of specific microbial biomarkers aids the quest for improved accuracy. EBC is currently of limited value.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38vktlGhtQ%253D%253D&md5=0d6bd7dae5aa07124669143e684cebf6
49. 49
  Zhang, J.; Zhu, T.; Kipen, H.; Wang, G.; Huang, W.; Rich, D.; Zhu, P.; Wang, Y.; Lu, S.-E.; Ohman-Strickland, P.; Diehl, S.; Hu, M.; Tong, J.; Gong, J.; Thomas, D.; H. E. I. H. R. Committee Res. Resp. Health Eff. Inst. 2013, 5– 174
  There is no corresponding record for this reference.
50. 50
  Hubbard, H. F.; Sobus, J. R.; Pleil, J. D.; Madden, M. C.; Tabucchi, S. J. Chromatogr., B: Anal. Technol. Biomed. Life Sci. 2009, 877, 3652– 3658
  50
  Application of novel method to measure endogenous VOCs in exhaled breath condensate before and after exposure to diesel exhaust
  Hubbard, H. F.; Sobus, J. R.; Pleil, J. D.; Madden, M. C.; Tabucchi, S.
  Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences (2009), 877 (29), 3652-3658CODEN: JCBAAI; ISSN:1570-0232. (Elsevier B.V.)
  Polar volatile org. compds. (PVOCs) such as aldehydes and alcs. are byproducts of normal human metab. and thus are found in blood and exhaled breath. Perturbation of the normal patterns of such metabolites may reflect exposures to environmental stressors, disease state, and human activity. Presented herein is a specific methodol. for assaying PVOC biomarkers in exhaled breath condensate (EBC) samples with application to a series of samples from a controlled chamber exposure to dil. diesel exhaust (DE) or to purified air. The collection/anal. method is based on condensation of normal (at rest) exhaled breaths for 10 min (resulting in 1-2 mL of liq.) with subsequent analyte adsorption onto Tenax cartridges followed by thermal desorption and anal. by gas chromatog./mass spectrometry (GC/MS). Anal. data have linearity of response (R2 > 0.98) across a range of 0-160 ng/mL with a detection limit ranging from 0.2 to 7 ng/mL depending on the compd. Statistical analyses of the results of the controlled exposure study indicate that metab., as reflected in simple breath-borne oxygenated species, is not affected by exposure to ambient airborne levels of DE. Linear mixed-effects models showed that PVOC biomarker levels are affected by gender and vary significantly among nominally healthy subjects. Differences among PVOCs analyzed in clinic air, purified chamber air, and chamber air contg. dil. DE confirm that most of the compds. are likely of endogenous origin as the exogenous exposure levels did not perturb the EBC measurements.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht1GksLbM&md5=3228e609899d64daa4bafd026a7a8187
51. 51
  Sawyer, K.; Samet, J. D.; Ghio, A. J.; Pleil, J. D.; Madden, M. C. J. Breath Res. 2009, 2, 037019
  There is no corresponding record for this reference.
52. 52
  Pleil, J. D.; Hubbard, H. F.; Sobus, J. R.; Sawyer, K.; Madden, M. C. J. Breath Res. 2008, 2, 026001
  There is no corresponding record for this reference.
53. 53
  Koester, C. J.; Moulik, A. Anal. Chem. 2005, 77, 3737– 3754
  There is no corresponding record for this reference.
54. 54
  Boja, E. S.; Rodriguez, H. Proteonomics 2012, 12, 1093– 1110
  54
  Mass spectrometry-based targeted quantitative proteomics: Achieving sensitive and reproducible detection of proteins
  Boja, Emily S.; Rodriguez, Henry
  Proteomics (2012), 12 (8), 1093-1110CODEN: PROTC7; ISSN:1615-9853. (Wiley-VCH Verlag GmbH & Co. KGaA)
  A review. Traditional shotgun proteomics used to detect a mixt. of hundreds to thousands of proteins through mass spectrometric anal., has been the std. approach in research to profile protein content in a biol. sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biol. conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biol. samples in the hope of elucidating the mol. mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, std. operating procedures, and well characterized reagents.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XmslKkt70%253D&md5=37fc2943ca29273badb4fa9bca24f483
55. 55
  Dasilva, N.; Díez, P.; Matarraz, S.; González-González, M.; Paradinas, S.; Orfao, A.; Fuentes, M. Sensors (Basel) 2012, 12, 2284– 2308
  55
  Biomarker discovery by novel sensors based on nanoproteomics approaches
  Dasilva Noelia; Diez Paula; Matarraz Sergio; Gonzalez-Gonzalez Maria; Paradinas Sara; Orfao Alberto; Fuentes Manuel
  Sensors (Basel, Switzerland) (2012), 12 (2), 2284-308 ISSN:.
  During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38vos1Slsw%253D%253D&md5=ef7668a264a0df9f70de970e1924c392
56. 56
  Grebe, S. K.; Singh, R. J. Clin. Biochem. Rev. 2011, 32, 5– 31
  56
  LC-MS/MS in the Clinical Laboratory - Where to From Here?
  Grebe Stefan Kg; Singh Ravinder J
  The Clinical biochemist. Reviews (2011), 32 (1), 5-31 ISSN:.
  Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has seen enormous growth in clinical laboratories during the last 10-15 years. It offers analytical specificity superior to that of immunoassays or conventional high performance/pressure liquid chromatography (HPLC) for low molecular weight analytes and has higher throughput than gas chromatography-mass spectrometry (GC-MS). Drug/Toxicology and Biochemical Genetics/Newborn Screening laboratories were at the vanguard of clinical LC-MS/MS use, but have been eclipsed by Endocrine laboratories. In USA reference/referral laboratories, most steroids and biogenic amines are now assayed by LC-MS/MS, and the technology has started to penetrate into smaller laboratories. Assays for mineralo- and gluco-corticoids and their precursors, sex steroids, metanephrines and 25-hydroxy vitamin D highlight the advantages of LC-MS/MS.However, several limitations of LC-MS/MS have become apparent, centring on the interacting triangle of sensitivity - specificity - throughput. While sample throughput is higher than for conventional HPLC or GC-MS, it lags behind automated immunoassays. Techniques which improve throughput include direct sample injection, LC-multiplexing and samplemultiplexing. Measures to improve specificity and sensitivity include sample clean-up and optimising chromatography to avoid interferences and ion suppression due to sample-matrix components. Next generation instrumentation may offer additional benefits.The next challenge for clinical LC-MS/MS is peptide/protein analysis. The quest for multi-biomarker profiles for various diseases has largely failed, but targeted peptide and protein testing by LC-MS/MS, directed at analytical and clinical questions that need to be answered, is proving highly successful. We anticipate that this will result in similar growth of clinical protein/peptide LC-MS/MS as has been seen for low molecular weight applications.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3MzotFCgtg%253D%253D&md5=a26bc85caf25ed329080b925ab407562
57. 57
  Lacorte, S.; Fernandez-Alba, A. R. Mass Spectrom. Rev. 2006, 25, 866– 880
  57
  Time of flight mass spectrometry applied to the liquid chromatographic analysis of pesticides in water and food
  Lacorte, Silvia; Fernandez-Alba, Amadeo R.
  Mass Spectrometry Reviews (2006), 25 (6), 866-880CODEN: MSRVD3; ISSN:0277-7037. (John Wiley & Sons, Inc.)
  A review. Liq. chromatog. coupled to mass spectrometry (LC-MS) is an excellent technique to det. trace levels of polar and thermolabile pesticides and their degrdn. products in complex matrixes. LC-MS can be equipped with several mass analyzers, each of which provides unique features capable to identify, quantify, and resolve ambiguities by selecting appropriate ionization and acquisition parameters. The authors discuss in this review the use of LC coupled to (quadrupole) time-of-flight mass spectrometry (LC-(Q)ToF-MS) to det. the presence of target and non-target pesticides in water and food. This technique is characterized by operating at a resolving power of 10,000 or more. Therefore, it gives accurate masses for both parent and fragment ions and enables the measurement of the elemental formula of a compd. achieving compd. identification. In addn., the combination of quadrupole-ToF permits tandem mass spectrometry, provides more structural information, and enhances selectivity. The purpose of this article is to provide an overview on the state of the art and applicability of liq. chromatog. time-of-flight mass spectrometry (LC-ToF-MS), and liq. chromatog. quadrupole time-of-flight mass spectrometry (LC-QToF-MS) for the anal. of pesticides in environmental matrixes and food. The performance of such techniques is depicted in terms of accurate mass measurement, fragmentation, and selectivity. The final section is devoted to describing the applicability of LC-(Q)ToF-MS to routine anal. of pesticides in food matrixes, indicating those operational conditions and criteria used to screen, quantify, and identify target and suspected pesticides and their degrdn. products in water, fruits, and vegetables. The potential and future trends as well as limitations of LC-(Q)ToF-MS for pesticide monitoring are highlighted.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht1eiu7bE&md5=b0f6a6270bacfe3e5ccb1cca70e8e529
58. 58
  Ferrer, I.; Thurman, E. M.; Fernández-Alba, A. R. Anal. Chem. 2005, 77, 2818– 2825
  There is no corresponding record for this reference.
59. 59
  Zubarev, R. A.; Makarov, A. Anal. Chem. 2013, 85, 5288– 5296
  59
  Orbitrap Mass Spectrometry
  Zubarev, Roman A.; Makarov, Alexander
  Analytical Chemistry (Washington, DC, United States) (2013), 85 (11), 5288-5296CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)
  A review. Orbitrap is the newest addn. to the family of high-resoln. mass spectrometry analyzers. With its revolutionarily new, miniature design, Orbitrap combines high speed with excellent quantification properties, ranking favorably in many anal. applications.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXmtVyltro%253D&md5=3c3fdcddc24dd230f449b673e4c25cfa
60. 60
  Sobus, J. R.; Pleil, J. D.; McClean, M. D.; Herrick, R. F.; Rappaport, S. M. Toxicol. Lett. 2010, 199, 247– 253
  60
  Biomarker variance component estimation for exposure surrogate selection and toxicokinetic inference
  Sobus, Jon R.; Pleil, Joachim D.; McClean, Michael D.; Herrick, Robert F.; Rappaport, Stephen M.
  Toxicology Letters (2010), 199 (3), 247-253CODEN: TOLED5; ISSN:0378-4274. (Elsevier Ireland Ltd.)
  Biomarkers are useful exposure surrogates given their ability to integrate exposures through all routes and to reflect interindividual differences in toxicokinetic processes. Also, biomarker concns. tend to vary less than corresponding environmental measurements, making them less-biasing surrogates for exposure. In this article, urinary PAH biomarkers (namely, urinary naphthalene [U-Nap]; urinary phenanthrene [U-Phe]; 1-hydroxypyrene [1-OH-Pyr]; and 1-, (2+3)-, 4-, and 9-hydroxyphenanthrene [1-, (2+3)-, 4-, and 9-OH-Phe]) were evaluated as surrogates for exposure to hot asphalt emissions using data from 20 road-paving workers. Linear mixed-effects models were used to est. the within- and between-person components of variance for each urinary biomarker. The ratio of within- to between-person variance was then used to est. the biasing effects of each biomarker on a theor. exposure-response relationship. Mixed models were also used to est. the amts. of variation in Phe metab. to individual OH-Phe isomers that could be attributed to Phe exposure (as represented by U-Phe concns.) and covariates representing time, hydration level, smoking status, age, and body mass index. Results showed that 1-OH-Phe, (2+3)-OH-Phe, and 1-OH-Pyr were the least-biasing surrogates for exposure to hot asphalt emissions, and that effects of hydration level and sample collection time substantially inflated bias ests. for the urinary biomarkers. Mixed-model results for the individual OH-Phe isomers showed that between 63% and 82% of the obsd. biomarker variance was collectively explained by Phe exposure, the time and day of sample collection, and the hydration level, smoking status, body mass index, and age of each worker. By difference, the model results also showed that, depending on the OH-Phe isomer, a max. of 6-23% of the total biomarker variance was attributable to differences in unobserved toxicokinetic processes between the workers. Therefore, toxicokinetic processes are probably less influential on urinary biomarker variance than are exposures and observable covariate effects. The methods described in this anal. should be considered for the selection and interpretation of biomarkers as exposure surrogates in future exposure investigations.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVGnsL%252FO&md5=3f906a3477c45c8ac4c3ed50ad6660ce
61. 61
  Pleil, J. D.; Stiegel, M. A.; Sobus, J. R. J. Breath Res. 2011, 5, 046005
  There is no corresponding record for this reference.
62. 62
  Pleil, J. D.; Sobus, J. R.; Sheppard, P. R.; Ridenour, G.; Witten, M. L. Chem. Biol. Interact. 2012, 196, 68– 78
  62
  Strategies for evaluating the environment-public health interaction of long-term latency disease: The quandary of the inconclusive case-control study
  Pleil, Joachim D.; Sobus, Jon R.; Sheppard, Paul R.; Ridenour, Gary; Witten, Mark L.
  Chemico-Biological Interactions (2012), 196 (3), 68-78CODEN: CBINA8; ISSN:0009-2797. (Elsevier Ireland Ltd.)
  Environmental links to disease are difficult to uncover because environmental exposures are variable in time and space, contaminants occur in complex mixts., and many diseases have a long time delay between exposure and onset. Furthermore, individuals in a population have different activity patterns (e.g., hobbies, jobs, and interests), and different genetic susceptibilities to disease. As such, there are many potential confounding factors to obscure the reasons that one individual gets sick and another remains healthy. An important method for deducing environmental assocns. with disease outbreak is the retrospective case-control study wherein the affected and control subject cohorts are studied to see what is different about their previous exposure history. Despite success with infectious diseases (e.g., food poisoning, and flu), case-control studies of cancer clusters rarely have an unambiguous outcome. This is attributed to the complexity of disease progression and the long-term latency between exposure and disease onset. In this article, we consider strategies for investigating cancer clusters and make some observations for improving statistical power through broader non-parametric approaches wherein sub-populations (i.e., whole towns), rather than individuals, are treated as the cases and controls, and the assocd. cancer rates are treated as the dependent variable. We subsequently present some ecol. data for tungsten and cobalt from studies by University of Arizona researchers who document elevated levels of tungsten and cobalt in Fallon, NV. These results serve as candidates for future hybrid ecol. case-control investigations of childhood leukemia clusters.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xls1egsL0%253D&md5=082a94747b0b88286dce76c819237543

You have not visited any articles yet, Please visit some articles to see contents here.

All Types

Evolution of Environmental Exposure Science: Using Breath-Borne Biomarkers for “Discovery” of the Human Exposome
Click to copy article linkArticle link copied!

Analytical Chemistry

Publication History

Subjects

Environmental Exposure Science and the Human Exposome

Figure 1

Targeted Biomarker Research

Discovery Biomarker Research

Figure 2

Environment Wide Association Study (EWAS) and Case-Control Discovery

Biomarkers in Exhaled Breath Condensate (EBC) and Aerosols (EBA)

Comparisons of Discovery and Targeted Biomarker Data

Figure 3

Summary of Discovery Approaches in Breath Biomarker Research

Author Information

Biography

Joachim D. Pleil

Acknowledgment

References

Cited By

Analytical Chemistry

Publication History

Article Views

Altmetric

Citations

Recommended Articles

Abstract

Figure 1

Figure 2

Figure 3

References

Evolution of Environmental Exposure Science: Using Breath-Borne Biomarkers for “Discovery” of the Human ExposomeClick to copy article linkArticle link copied!

Analytical Chemistry

Environmental Exposure Science and the Human Exposome

Figure 1

Targeted Biomarker Research

Discovery Biomarker Research

Figure 2

Environment Wide Association Study (EWAS) and Case-Control Discovery

Biomarkers in Exhaled Breath Condensate (EBC) and Aerosols (EBA)

Comparisons of Discovery and Targeted Biomarker Data

Figure 3

Summary of Discovery Approaches in Breath Biomarker Research

Author Information

Biography

Joachim D. Pleil

Acknowledgment

References

Cited By

Analytical Chemistry

Article Views

Altmetric

Citations

Recommended Articles

Abstract

Figure 1

Figure 2

Figure 3

References

Evolution of Environmental Exposure Science: Using Breath-Borne Biomarkers for “Discovery” of the Human Exposome
Click to copy article linkArticle link copied!