Chem. Senses 28: 467-477,
2003
© Oxford University Press 2003
Quantification of Chemical Vapors in Chemosensory Research
? Chemosensory Perception Laboratory, Department of Surgery (Otolaryngology), University of California, San Diego, La Jolla, CA 92093–0957, USA 1 Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
Correspondence to be sent to: J. Enrique Cometto-Muñiz, Chemosensory Perception Laboratory, Department of Surgery (Otolaryngology), 9500 Gilman Drive—Mail Code 0957, University of California, San Diego, La Jolla, CA 92093–0957, USA. e-mail: ecometto{at}ucsd.edu
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Studies of olfaction and chemesthesis often rely on nominal, liquid-phase dilutions to quantify the chemicals tested, even though the associated vapor concentrations constitute the actual stimuli. For more than a decade now, our systematic studies of the olfactory and chemesthetic potency of members of homologous chemical series have routinely included quantification of vapors via gas chromatography. This article depicts the relationships between liquid- and vapor-phase concentrations for 60 volatile organic compounds and summarizes the theoretical and technical factors influencing these relationships. The data presented will allow other investigators working with these materials to express them as vapor concentrations even when they lack the resources to perform the analytical measurements. The paper represents a step toward creation of a practical archive for vapor quantification in chemosensory science.
Key words: gas chromatography, irritant vapor quantification, odorous vapor quantification, olfactometry, vapor–liquid concentration relationships
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(see
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The scientific study of olfaction and chemesthesis (i.e. chemical sensory irritation) inevitably requires some attempt to deliver controlled amounts of chemical vapors. Control of concentration may occur via static or dynamic means (Cain et al., 1992
). In static olfactometry the stimulus vapor is presented from
the headspace of an enclosed container (e.g. a squeeze bottle or a glass
vessel), whereas in dynamic olfactometry the stimulus vapor flows continuously
in a carrier gas (e.g. nitrogen or odorless air). In the case of static
control, an investigator may make the assumption that the number of molecules
present in the vapor phase at steady state follows Raoult's law for ideal
solutions or Henry's law for ideal dilute solutions. These laws assume
proportionality of concentration in the headspace above a solution to molar
fraction of solute. A solution 10 times less concentrated than another should
have 10-fold fewer molecules in the headspace.
From time to time, a chemist may remind chemosensory investigators that it
is not uncommon to observe deviations from these laws of proportionality
(Haring, 1974). Depending upon
interactions between solute and solvent, the concentration of a volatile
organic compound (VOC) may sometimes exceed expectations, so-called positive
deviations, and may sometimes lie below them, negative deviations. Without
knowledge of whether one or another such deviation has occurred, an
investigator may need to limit the conclusions of a study or may even
promulgate an incorrect answer.
It remains rather common for investigators to express the magnitude of the
chemosensory stimulus in nominal or relative terms. Nominal expression
normally takes the form of specification of a liquid dilution, such
as, a 0.1% v/v solution of 1-butanol in mineral oil. An investigator who reads
about this nominal stimulus may wish to use another solvent, such as water,
and may wonder if the same nominal concentration will lead to the same number
of molecules in the headspace (Tsukatani
et al., 2003). One can readily invent scenarios where
investigations will lead to incompatible results because of such matters.
Undoubtedly, investigators have sometimes failed to take opportunities for
direct comparison of their work with that of others when they feel insecure
about whether their vapor-phase concentrations match that of others.
Measurement of the headspace above solutions for a wide range VOCs became feasible in the 1960s with the availability of commercial gas chromatographs (GCs). Five decades have led to many improvements in this and other technologies for analysis of vapors, but three matters plague its application in chemosensory research: (i) expense, for a GC system will often cost upwards of $20,000; (ii) the need for a highly trained operator; and (iii) the labor-intensive nature of the work. Specification of headspace concentration for a series of dilutions may entail days of work for a knowledgeable operator. Even then, the sensitivity of the instrument may not extend to the low concentrations used in an olfactory experiment. Faced with the expense, lack of expertise, consumption of time and eventual need to extrapolate anyway, an investigator may opt not to measure concentration and merely to express it nominally. Is the decision defensible? Perhaps. Does it hold back advances in chemosensory science? Inevitably.
During the year 2002, some chemosensory investigators outside the field of
human psychophysics realized that studies from the Chemosensory Perception
Laboratory have typically entailed actual measurement of concentration and,
further, that calibration curves for headspace concentrations might exist for
various VOCs of interest, such as aliphatic alcohols, ketones, esters, etc.
The potential usefulness of the data to these investigators has led to the
present attempt to make the information and the experiences of more than a
decade of measurement available more generally. The core of the results
presented below describes the relationship between liquid- and vapor-phase
concentrations for three dozen chemicals from six homologous chemical
series—as has been found using techniques of static olfactometry—
and discusses the trends and factors that influence these relationships. The
data for these chemicals could serve as the nucleus of an archival set to
enable investigators to calculate vapor-phase concentration for solutions of
VOCs. Whereas the present report focuses upon issues largely pertinent to
static olfactometry, another focuses upon issues pertinent to dynamic
olfactometry (Schmidt and Cain,
2003).
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Materials and methods |
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Stimuli
All chemicals were analytical grade reagents. They included homologous n-alcohols: propanol, butanol, hexanol and octanol; homologous acetates: methyl, ethyl, propyl, butyl, pentyl, hexyl, heptyl, octyl, decyl and dodecyl acetate; homologous 2-ketones: propanone (i.e. acetone), pentanone, heptanone, and nonanone; homologous alkylbenzenes: methyl (i.e. toluene), ethyl, propyl, butyl, pentyl, hexyl, heptyl and octyl benzene; homologous aliphatic aldehydes: butanal, pentanal, hexanal, heptanal and octanal; and homologous carboxylic acids: methanoic (i.e. formic), ethanoic (i.e. acetic), butanoic (i.e. butyric), hexanoic and octanoic acid. The solvent was mineral oil (light, Food Chemicals Codex quality) except for 1-propanol, 2-propanone, formic acid and acetic acid, where it was distilled water. 1-Butanol was tested in both solvents.
Equipment
Vapor-phase concentrations were measured in Hewlett-Packard 5890 GCs with a
flame ionization detector (FID) or a photoionization detector (PID). The GCs
were equipped with a gas-sampling valve (0.25 or 1.00 ml sampling loop).
Pre-concentration of chemicals
(Cometto-Muñiz et al.,
2003) was accomplished by using a gas-tight syringe to load
samples of vapor into an adsorption tube and, later, thermally desorbing it in
a Thermal Desorption Unit (ACEM Model 900, CDS Analytical, Inc.) whose output
fed a GC. We employed Sorbent Tubes, 4.5 in. long x 4 mm i.d., packed
with 20–35 Tenax-TA/Carboxen1000/CarbosieveSIII. The GC signal was
integrated by a Hewlett-Packard 3390A or 3396A integrator, or by an STD MacLab
A/D Converter (MacLab version 3.5, Chart version 3.5.6, Scope version 3.5.6
and Peaks version 1.4). The GC columns used were a DB-1, 30 m x 0.53 mm
i.d., used alone or in series with a DB-WAX, 30 m x 0.53 mm i.d. (both
from J&W Scientific), and, for the carboxylic acids, an HP-FFAP, 30 m
x 0.53 mm i.d., 1.0 µm film thickness (from Hewlett-Packard). The
coefficient of variation of replicate gas chromatographic measurements across
VOCs and concentrations typically averaged 
10%
(Cometto-Muñiz et al.,
2000) and ranged from 5%
(Cometto-Muñiz et al.,
2002) to 13%
(Cometto-Muñiz et al.,
2003).
Vapors were sampled from the headspace of either 270 ml plastic squeeze
bottles (Cain, 1989;
Cometto-Muñiz and Cain,
1990) or 1900 ml glass vessels adapted for nasal
(Cometto-Muñiz et al.,
2000) or ocular
(Cometto-Muñiz et al.,
2001) chemosensory stimulation. To minimize the potential for
depletion of the headspace concentration of the containers we have prepared a
number of replicas for each concentrattion (from two to five replicas used
sequentially) and have shaken the containers in a circular fashion to speed up
re-equilibration (Dravnieks,
1975). Nevertheless, a comprehensive and strict quantitative
appraisal of this potential problem awaits further research.
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Results and discussion |
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Relationship between liquid and vapor concentrations
Throughout systematic studies of odor, nasal pungency and eye irritation
thresholds along and across homologous chemical series [see reviews in
(Cometto-Muñiz, 2001;
Cometto-Muñiz and Cain,
1996)], we have gathered a considerable amount of data on the
relationship between liquid-phase concentration (in % v/v) and vapor-phase
concentration (in p.p.m. by volume). Across the entire concentration range,
the vapor pressure (Pst) of a solute in solution with a
solvent is given by Raoult's law for an ideal solution:
 | (1) |
 | (2) |
 | (3) |
In the figures presented below and in
Table 1, we depict the
following relationship:
 | (4) |
 | (5) |
 | (6) |
 | (7) |
 | (8) |
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In early work, we relied on the assumption that published values of vapor pressure provided an accurate estimate of saturated vapor concentration above neat VOC. We expressed vapor concentrations of our dilution series based on GC readings relative to these estimates. As discussed below, we eventually saw risks from relying on a single bibliographic source for a value of vapor saturation and began exploring a number of sources for each substance in order to select the most reliable data, particularly data corresponding to experimental measures of the saturated vapor as opposed to data calculated from fitted equations.
Figure 1 shows, for four homologous n-alcohols, the relationship between the concentration in the liquid phase and concentration of vapor in the headspace above the source. The latter concentration is the actual stimulus presented to subjects. It is important to report the solvent used to prepare the dilution series since, as illustrated below, the same liquid dilution of a certain chemical will very likely produce different vapor concentrations above the solution depending on the solvent used. In the case of the alcohols depicted in Figure 1, the solvent used for 1-propanol was distilled water, whereas the solvent used for the other homologs was mineral oil. In Figure 1 and Table 1, all alcohols showed slopes near unity, i.e. showed simple proportionality between liquid and vapor concentration. Another characteristic of these functions is a departure from simple proportionality for relatively high liquid concentrations, commonly above 1–10% v/v. Departures from proportionality might also appear at very low liquid concentrations and they can be attributed to having reached the limit of sensitivity of the GC. Accurate measurements of vapor concentrations at and below these low levels would require accumulation of the mass of the stimulus, for example, on an adsorbent material and later desorption into the GC. We will address this technique below.
Figure 2a,2b,2c,2d,2e,2f,2g presents similar graphs to Figure 1 for homologous acetate esters, 2-ketones, alkylbenzenes, aliphatic aldehydes and carboxylic acids. Similar considerations regarding proportionality between liquid- and vapor-phase concentrations apply here. Deviations at the higher end of the range were often observed. Again, an exponent close to unity characterized all functions (see also Table 1). Nevertheless, the largest homologs in some of the series—for example, octyl and higher acetates, and octyl benzene— tended to show a flattening of their slope. Henry's law only applies across the entire liquid concentration range if the two components form an ideal mixture according to Raoult's law. Usually, positive deviations from Raoult's law are observed; in that case, the observed Henry's law constant would become smaller as the solute liquid concentration becomes larger, exactly as we observe.
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Direct injection of an aliquot of the headspace from the stimulus-container into the GC was done with either a gas-sampling valve or a gas-tight syringe. The heavier stimuli (i.e. long carbon chain members) may tend to adsorb to the sampling loop of the gas sampling valve. The measurements presented in Figures 1 and 2 were done using a gas-sampling valve. In more recent work, we have used gas-tight syringes. Below we will discuss advantages and disadvantages of both methods and will show that, generally, they yielded comparable results.
Deviations from proportionality in the form of a downward concavity at the very high end of the functions (i.e. positive deviations from Raoult's law) were quite pronounced for the lower homologs in each series and tended to be less pronounced for the higher homologs. Table 1 shows the maximum concentration of each VOC that, in our conditions, still followed the proportional trend before the concavity appeared.
Influence of the solvent
With the few exceptions noted, the bulk of the data presented so far rests
on solutions of the chemical of interest in mineral oil. As mentioned, it is
necessary to take the solvent into account when deriving the vapor-phase
concentration in equilibrium with a liquid-phase concentration
(Tsukatani et al.,
2003).
To illustrate the point, Figure
3 presents the vapor concentrations in equilibrium with a series
of liquid dilutions of 1-butanol in either mineral oil or distilled water.
Both dilution series were prepared in squeeze bottles. The series in water
corresponded to the dilutions of 1-butanol used in the Connecticut
Chemosensory Clinical Research Center (CCCRC) test of olfactory functioning
(Cain et al., 1988;
Cain, 1989). It is clear that,
across the range of liquid concentrations explored, use of mineral oil
produced higher vapor-phase concentrations than use of water. Nevertheless,
note that the functions are approximately parallel, with exponents close to
unity. Although the set of butanol in water does not include liquid
concentrations above 4% v/v, the trend of the relationship will necessarily
have to curve at higher values because the vapor-phase concentration of
1-butanol cannot exceed the saturated vapor concentration, 8057 p.p.m. In
summary, we can expect that below a certain liquid concentration the
relationship between liquid and vapor concentration of a solute in a solvent
will be approximately proportional, but the actual value of the vaporphase
concentration will depend on interactions between the particular solute and
solvent. For 1-butanol in water and 1-butanol in hexadecane (a surrogate for
mineral oil), Henry's constant (Hc in equation 3) is 3.5
x 10–4 and 25.0 x 10–4
respectively, i.e. a factor of 7.1, showing how a change of solvent can lead
to quite different solute vapor pressures
(Abraham et al.,
1994). The intercept in the equation for 1-butanol in water and in
mineral oil (Table 1) differ by
a similar factor, 7.7.
Calibration of vapor-phase vs. liquid-phase concentration functions
Using the value of vapor saturation of the chemical.
GC readings, which typically quantify an area under a curve, do not express
values of concentration per se. They need to be calibrated to
indicate actual concentrations. One strategy is to tie a GC reading to a known
vapor concentration and, then, use the resulting factor to convert all other
GC readings. A good reference concentration can be the saturated vapor
concentration of the chemical at room temperature and normal atmospheric
pressure. Such a reference has two important advantages: first, the value can
be obtained from handbooks or databases, and, second, it can be prepared
easily. Its preparation simply involves placing neat chemical into a
container.
We have found that not all sources will agree on the vapor pressure of a
chemical at a given temperature. This was surprising since vapor pressure is a
fundamental physicochemical property. An extreme example occurred for the
vapor pressure of octanal. The value calculated at 23°C from tabular
information in the Handbook of Chemistry and Physics
(Weast, 1981–1982)
equaled 0.0053 mmHg, corresponding to a saturated vapor concentration of 6.97
p.p.m. The value obtained from other handbooks
(Beilstein, 1984;
Stephenson and Malanowski,
1987) equaled 2.14 mmHg, corresponding to a concentration of 2816
p.p.m., 404 times higher. Values of vapor pressure from the
Handbook of Chemistry and Physics come from fitted equations and may
rely on very old experimental data, where the purity of the chemical is
unknown. In some cases, the measurements may have been taken at temperatures
far from ambient and errors of extrapolation may be sizable.
This example of a difference of more than two orders of magnitude might
occur infrequently, but in other cases the difference has approached one order
of magnitude, hardly a trivial amount. For hexanoic acid, for example, the
Hazardous Substances Data Bank (HSDB)-TOXNET cites a vapor pressure of 0.20
mmHg at 20°C, whereas (de Kruif et
al., 1982) cite a value of 0.031 mmHg, about six
times lower.
To illustrate the disparities, we compare in Table 2 the values of saturated vapor pressure at room temperature retrieved by the authors at the University of California, San Diego and the author at University College London.
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In summary, if one needs to rely on a reported value of saturated vapor concentration, the safest strategy is to find more than one source and choose the value that appears more reliable. Such a task can often be hard to accomplish. If one cannot arrive at a reliable value for vapor saturation at room temperature, it is necessary to create a calibration curve based on injection of known masses of chemical into the GC. It is hard to argue against such direct calibration in all cases, even though it entails extra work.
Building of a calibration curve for mass
Chromatographic analysis of liquid samples of known masses of VOC can
obviate reliance on archived values of vapor pressure. The equation that
describes the relationship of the GC reading to the mass in liquid samples can
serve to transform GC readings of vapor samples into absolute concentration.
Care should be taken to use the same chromatographic conditions of flow,
temperatures, etc., in the creation of the calibration curve as in the
analysis of the actual headspace samples. Instead of relying on an indirect
calibration point, as does the previous method, this approach relies on direct
and multiple calibration points selected to cover the range of GC readings
expected from the dilution-step headspace samples.
Figure 4 shows a calibration
curve obtained for butyl acetate. The mass injected covers the range
3.8–3752 p.p.m. for vapor-phase samples of 0.250 ml.
Comparability of approaches and methods to establish vapor-phase concentration
Over time, we have switched from use of plastic squeeze bottles
(Cometto-Muñiz et al.,
1999) to use of glass vessels (Cometto-Muñiz et
al., 2001,
2003) that provide improved
stimulus delivery and better chemosensory performance
(Cometto-Muñiz et al.,
2000). In terms of calibration strategy, we have always relied on
gas chromatography (Cometto-Muñiz
and Cain, 1990). Initially, we used the indirect calibration
strategy based on the value of vapor saturation. More recently, when the focus
of our studies progressed from testing groups of single compounds to testing
binary mixtures, we switched to the direct calibration approach based on
injection of known masses of chemical.
To sample headspace and introduce it into the GC, we started by using a gas-sampling valve, but now use mostly gas-tight syringes. A gas-sampling valve allows volumes as large as 5 ml. A gas-tight syringe >0.25 ml is often impractical to use due to limitations of volume in the injection port and column of the GC. Against the advantage of a larger volume of sample, the gas-sampling valve has the disadvantage of potential adsorption of the chemical on the stainless steel or nickel walls of the loop.
The sensitivity of the GC rarely poses an issue in studies of chemesthetic
responses, where concentrations of vapors are high
(Cometto-Muñiz et al.,
2001). It poses an issue more commonly in studies of olfactory
responses, where concentrations are low. It becomes especially troublesome in
the study of odor detection of mixtures where components might lie at even
lower concentrations (Cometto-Muñiz
et al., 2003). In the case of mixtures, it is even more
important to measure the vapor concentration of the components since it is not
uncommon to observe deviations from theoretically predicted values
(Haring, 1974). In such
circumstances, we have employed pre-concentration of vapors followed by
thermal desorption (Cometto-Muñiz
et al., 2003). The method uses adsorbent-filled tubes
that are loaded with quite large samples of headspace (e.g. 10–20 ml) by
means of appropriate gas-tight syringes. The preconcentrated samples are then
thermally desorbed into the GC.
We have measured vapor/liquid concentration relationships in squeeze bottles, in glass vessels, via gas-sampling valves, via gas-tight syringes, calibrated through the indirect single-point method, calibrated through the direct multiplepoint method, for chemicals presented singly and for chemicals presented in mixtures. Despite some variability underlying the use of different instruments and conditions, a relatively uniform vapor vs. liquid concentration relationship should emerge for any particular chemical, independently of the specific approach used to obtain it. Figure 5a,5b,5c,5d presents such vapor vs. liquid concentration relationships, measured under the above mentioned variety of conditions, for the compounds 1-butanol, 2-heptanone, butyl acetate and toluene, respectively. The results showed considerable uniformity. In the cases of butyl acetate (Figure 5c) and toluene (Figure 5d), readings from low concentrations in the range of odor detection were not possible through direct headspace sampling, so they were measured via preconcentration and subsequent thermal desorption. Note how this outcome merged with that of the direct sampling techniques at higher concentrations.
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As a rule, any compound should produce a consistent vapor vs. liquid concentration relationship irrespective of the particular procedure employed to calculate vapor concentrations and of the container from whence the sample is taken. To illustrate this, Figure 6a,6b,6c show plots of vapor vs. liquid concentrations across members of homologous alcohols, acetate esters and ketones, respectively. Despite the diversity of conditions, the relationship for each substance often held quite well. Nevertheless, there were instances where calibration based on a reported value of saturated vapor differed by >25% amount from calibration using liquid injections. For example, this happened for 1-hexanol, hexyl acetate, octyl acetate, 2-pentanone and 2-nonanone. If one cannot know whether the two approaches will agree, the investigator with the wherewithal to do chromatography should use the liquid injection for increased certainty. Thus, the value of the parameters reported in Table 1 for these five VOCs correspond to calibration by liquid injection.
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Although we have developed the themes of this report around the members of
six homologous series, we have assessed vapor-phase concentrations for other
VOCs as well (Cometto-Muñiz and Cain,
1990,
1993,
1994;
Cometto-Muñiz et al.,
1998). The table in the Appendix shows the parameters for these in
the same format as Table 1.
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Summary and conclusions |
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TopAbstractIntroductionMaterials and methodsResults and discussionSummary and conclusionsReferences |
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Based on GC measurements for three dozen VOCs from six homologous chemical series, we found that, as a general rule, there was a simple proportionality between the liquid- and vapor-phase concentrations of these VOCs when they were in equilibrium in a closed container. Nevertheless, deviations from proportionality were common for solutions above 1–10% v/v. The most volatile members of a series (i.e. lower homologs) began to depart from proportionality at concentrations of
1% v/v. As volatility decreased,
departure from proportionality began only at higher concentrations, 10% v/v or
higher. Departures were also observed for the highest molecular weight
compounds (e.g. decyl acetate, octyl benzene) and were likely due to
deviations of the solutions from the behavior of an ideal mixture.
Measurements obtained with 1-butanol exemplified how use of different solvents
to dilute an odorant can alter the vapor concentration above a liquid solution
although maintaining a proportional relationship. Specification of the
concentration of vapors delivered as stimuli in studies on olfaction and
chemesthesis can be accomplished by actual experimental measurement or by
reliance on a dataset that has performed those measurements. Towards the aim
of beginning to build such archival dataset, the present article presents the
vapor-phase concentrations associated with a wide range of liquid dilutions
for 60 VOCs commonly used as olfactory and chemesthetic stimuli. |
Acknowledgments |
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Thanks are due to R. Loya, C. Sorensen, and C. Vo for excellent technical assistance. Preparation of this article was supported by research grant number R01 DC02741 from the National Institute on Deafness and Other Communication Disorders, National Institutes of Health.
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References |
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TopAbstractIntroductionMaterials and methodsResults and discussionSummary and conclusionsReferences |
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Accepted May 23, 2003
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 W. Doucette, J. Milder, and D. Restrepo Adrenergic modulation of olfactory bulb circuitry affects odor discrimination Learn. Mem., August 3, 2007; 14(8): 539 - 547. [Abstract] [Full Text] [PDF]
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B. Slotnick Olfactory Performance of Rats after Selective Deafferentation of the Olfactory Bulb by 3-Methyl Indole Chem Senses, February 1, 2007; 32(2): 173 - 181. [Abstract] [Full Text] [PDF]
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 K. McBride and B. Slotnick Discrimination between the Enantiomers of Carvone and of Terpinen-4-ol Odorants in Normal Rats and Those with Lesions of the Olfactory Bulbs J. Neurosci., September 27, 2006; 26(39): 9892 - 9901. [Abstract] [Full Text] [PDF]
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 J. E. Cometto-Muniz, W. S. Cain, M. H. Abraham, and R. Sanchez-Moreno Chemical Boundaries for Detection of Eye Irritation in Humans from Homologous Vapors Toxicol. Sci., June 1, 2006; 91(2): 600 - 609. [Abstract] [Full Text] [PDF]
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A. C. Clevenger and D. Restrepo Evaluation of the Validity of a Maximum Likelihood Adaptive Staircase Procedure for Measurement of Olfactory Detection Threshold in Mice Chem Senses, January 1, 2006; 31(1): 9 - 26. [Abstract] [Full Text] [PDF]
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J. E. Cometto-Muniz, W. S. Cain, and M. H. Abraham Determinants for Nasal Trigeminal Detection of Volatile Organic Compounds Chem Senses, October 1, 2005; 30(8): 627 - 642. [Abstract] [Full Text] [PDF]
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B. Slotnick, R. Cockerham, and E. Pickett Olfaction in Olfactory Bulbectomized Rats J. Neurosci., October 13, 2004; 24(41): 9195 - 9200. [Abstract] [Full Text] [PDF]
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W. Lin, J. Arellano, B. Slotnick, and D. Restrepo Odors Detected by Mice Deficient in Cyclic Nucleotide-Gated Channel Subunit A2 Stimulate the Main Olfactory System J. Neurosci., April 7, 2004; 24(14): 3703 - 3710. [Abstract] [Full Text] [PDF]
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C. E. Reisenman, T. A. Christensen, W. Francke, and J. G. Hildebrand Enantioselectivity of Projection Neurons Innervating Identified Olfactory Glomeruli J. Neurosci., March 17, 2004; 24(11): 2602 - 2611. [Abstract] [Full Text] [PDF]
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