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. Author manuscript; available in PMC: 2009 Aug 1.
Published in final edited form as: Toxicol Appl Pharmacol. 2008 Apr 1;230(3):298–303. doi: 10.1016/j.taap.2008.03.011

A Cut-off in Ocular Chemesthesis from Vapors of Homologous Alkylbenzenes and 2-Ketones as Revealed by Concentration-Detection Functions

J Enrique Cometto-Muñiz a, Michael H Abraham b
PMCID: PMC2525871  NIHMSID: NIHMS60733  PMID: 18485434

Abstract

Studies of homologous series of environmental vapors have shown that their chemesthetic (i.e., sensory irritation) potency increases with carbon chain length (that is, their detection thresholds decrease) until they reach a homolog that fails to be detected, even at vapor saturation. All ensuing homologs cannot be detected either. In this investigation, we measured concentration-detection (i.e., psychometric) functions for ocular chemesthesis from homologous alkylbenzenes (pentyl, hexyl, and heptyl benzene) and 2-ketones (undecanone, dodecanone, and tridecanone). Using a three-alternative forced-choice procedure against air blanks, we tested a total of 18 to 24 subjects, about half of them females, average age 31 years, ranging from 18 to 56 years. Stimuli were generated and presented by a computer-controlled, vapor delivery device whose output was quantified by gas chromatography. Exposure time was 6 sec and delivery flow 2.5 L/min. Within the context of present and previous findings, the outcome indicated that the functions for heptylbenzene and 2-tridecanone reached a plateau where further increases in concentration did not enhance detection. We conclude that: a) a cut-off point in ocular chemesthetic detection is reached along homologous alkylbenzenes and 2-ketones at the level of heptylbenzene and 2-tridecanone, respectively, and b) the observed effect rests on the homologs exceeding a critical molecular size (or dimension) rather than on them failing to achieve a high enough vapor concentration.

Keywords: Eye irritation, Ocular chemesthesis, n-Alkylbenzenes, 2-Ketones, Concentration-detection functions, Molecular cut-off, Structure-activity relationships

Introduction

Chemosensory irritation has long been recognized as a very common, and often early, symptom of potentially dangerous exposure to airborne chemicals (Alarie, 1973a; Alarie, 1973b; Nielsen, 1991; Nielsen and Hansen, 1993; Nielsen et al., 2007). The sensory detection of a wide variety of compounds by means other than olfaction and taste (i.e., gustation) was originally included under the concept of a common chemical sense (Keele, 1962). More recently, it has been labeled chemical nociception (Lee et al., 2005) or chemically-induced somesthesis, from where the convenient term “chemesthesis” arises (Green et al., 1990; Green and Lawless, 1991; Bryant and Silver, 2000). Humans exposed to environmental vapors experience chemesthetic sensations in exposed mucosae, usually the eyes, nose, and throat (Doty et al., 2004). These sensations are often pungent, i.e., sharp, and include: stinging, piquancy, tingling, irritation, burning, cooling or freshness, prickling, and the like. In the specific case of the ocular and nasal mucosae, chemesthesis is mediated by the trigeminal nerve system (Finger et al., 1999; Doty and Cometto-Muñiz, 2003).

In mice, chemesthesis produced by volatile organic compounds (VOCs) has been measured by recording the airborne concentration depressing the respiratory rate by 50%, labeled RD50. These values can be used to extrapolate the data to humans (Schaper, 1993; Kuwabara et al., 2007; Nielsen et al., 2007). In humans, thresholds for nasal chemesthesis from VOCs have been measured by testing subjects lacking olfaction (i.e., anosmics) (Cometto-Muñiz and Cain, 1990; Cometto-Muñiz and Cain, 1991; Cometto-Muñiz and Cain, 1993; Cometto-Muñiz and Cain, 1994; Cometto-Muñiz et al., 1998a; Cometto-Muñiz et al., 1998b). Alternatively, human nasal trigeminal thresholds have also been measured by employing a nasal lateralization (i.e., localization) technique that requires subjects to identify the nostril receiving a VOC when the contralateral nostril receives just air (Wysocki et al., 1997; Cometto-Muñiz and Cain, 1998; Dalton et al., 2000). The two approaches aim to eliminate the interference from the sense of smell in assessing human nasal chemesthetic sensitivity to VOCs, see reviews in (Cometto-Muñiz, 2001; Doty et al., 2004). Human thresholds for ocular chemesthesis (eye irritation) from vapors also provide information on trigeminal chemesthetic sensitivity, unbiased by smell, e.g., (Cometto-Muñiz and Cain, 1991; Cometto-Muñiz et al., 1998b). To a first approximation, nasal and ocular trigeminal sensitivity to VOCs fall close to each other (Cometto-Muñiz and Cain, 1995).

Systematic studies measuring human chemesthetic thresholds for members of a variety of homologous chemical series found that sensitivity increases (i.e., thresholds decrease) with carbon chain length (Cometto-Muñiz, 2001). This trend is interrupted (i.e., cut-off) upon reaching a homolog that fails to elicit chemesthesis, even at vapor saturation. All ensuing larger homologs also fail. We have labeled this point in the series the cut-off point, and the shortest homolog that fails to be detected via chemesthesis, the cut-off homolog. In the present study we sought to identify the cut-off homolog for eye irritation among alkylbenzenes and 2-ketones by testing a range of concentrations up to vapor saturation and plotting concentration-detection (i.e., psychometric) functions. Previous results guided the present selection of three contiguous members from each series that were likely to bracket the cut-off point (Cometto-Muñiz and Cain, 1993; Cometto-Muñiz and Cain, 1994; Cometto-Muñiz et al., 2006).

Experiment 1: Alkylbenzenes

An institutional review board at the University of California, San Diego, approved the protocol for all experiments described here. All participants provided written informed consent.

Materials and Methods

Subjects

We recruited 18 subjects (9 female). Their average age (±SD) was 34 (±13) years, ranging from 18 to 56 years. All participants scored in the normosmic range of a standardized clinical olfactory test (Cain, 1989) (no standardized test is available for either nasal or ocular chemesthetic sensitivity). Three males were smokers. Three females used contact lenses but refrained from wearing them on testing days. Data from the few smokers and contacts users was within the range of that from nonsmokers and non-users of contacts.

A subset of 14 participants (6 female) from the group described above had available time to complete at least 20 trials per concentration (half with each eye) for all three alkylbenzenes (see Procedure). Data presented below for individual subjects refers to this more comprehensively tested group.

Stimuli

The chemicals tested (purity in parenthesis) were: pentylbenzene (99%), hexylbenzene (98%), and heptylbenzene (98%). Medical Air U.S.P. (humidified to 50% relative humidity, RH) served as blanks (see Procedure). Table 1 presents the actual vapor concentrations in nitrogen (N2) tested for each chemical as determined by gas chromatography (flame ionization detector, FID), and the nominal concentrations as determined by the ratio “stimulus flow / total (blank air + stimulus) flow” (see Apparatus).

Table 1.

Concentrations tested for each alkylbenzene as determined by gas chromatography (flame ionization detector, FID) of samples taken at the outlet of the vapor delivery device (expressed in ppm and in log ppm by volume) and as determined by the ratio of stimulus / total (air+stimulus) flow (in % v/v) set with the device (see Apparatus). SD indicates standard deviation.

CHEMICAL ppm ±SD log ppm ±SD % v/v
Pentylbenzene 24±1.5 1.375±0.027 20
69±8.2 1.834±0.050 40
132±17 2.118±0.061 60
207±20 2.315±0.042 80
245±31 2.386±0.057 100
Hexylbenzene 6.2±0.63 0.788±0.047 20
19±2.4 1.273±0.057 40
32±9.4 1.487±0.132 60
50±14 1.682±0.121 80
68±17 1.824±0.011 100
Heptylbenzene 2.7±1.7 0.332±0.324 20
7.9±5.1 0.830±0.269 40
13±4.2 1.096±0.141 60
21±4.0 1.313±0.083 80
27±4.7 1.432±0.070 100
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Apparatus

Stimuli and blanks were delivered to the subject’s eye from a dynamic dilution, vapor delivery device (VDD). The instrument is described in detail in a recent publication (Cometto-Muñiz et al., 2007a) and is based on a vacuum system analogous to that devised by Kobal (Kobal, 1985). Total flowrate to the eye, presented via a glass eyepiece (Cometto-Muñiz et al., 2005b), always equaled 2.5 L/min, and time of exposure was set to 6 sec.

Procedure

Each subject participated in three sessions, one per chemical. A session lasted between 2 and 3 hours and included two 5–10 min breaks. Order of presentation of chemicals across sessions and subjects was randomized. Within a session, a trial consisted of a three-alternative forced-choice procedure (3AFC) between a stimulus and two blanks. Order of stimulus and blanks was also randomized. Participants wore noseclips to avoid odor cues and had to decide which of the three presentations felt different (typically stronger) to the tested eye. In addition, they also rated the confidence in their decision on a scale from 1 (not confident at all, guessing) to 5 (extremely confident). The experimenter started the session by presenting a trial including the lowest concentration of the selected chemical to one eye (randomly selected) and then to the other. The procedure continued in ascending concentration (always alternating the tested eye) until the highest concentration (i.e., 100%v/v) was reached. A rest period of at least 3 minutes ensued before the whole process was repeated. No procedures were used to rinse the eyes either between trials or during the rest period. Testing continued until 20 trials per concentration (half with each eye) were completed.

Data analysis

The outcome was summarized as plots of detection probability, i.e., detectability, or confidence rating as a function of vapor concentration (log ppm by volume) for each chemical. Detectability (P) was corrected for chance and took a value between P=0.0 (chance detection) and P=1.0 (perfect detection), according to (Macmillan and Creelman, 1991):

P=(m·p(c)−1)/(m−1) Eq.(1)

where P = detectability corrected for chance, m = number of choices per trial (in our case, three), and p(c) = proportion correct (i.e., number of correct trials / total number of trials).

Statistical significance was tested by analysis of variance (ANOVA) for repeated measurements (software: SuperANOVA v.1.11, Abacus Concepts, Inc., Berkeley, CA). Adjustment factors correcting for the inherent correlation of repeated measurements via either the conservative Greenhouse-Geiser or the liberal Hunyh-Feldt epsilon values left all reported significant factors and interactions still significant at p ≤ 0.01.

Results

Figure 1 (upper section) shows the concentration-detection functions and confidence ratings for each alkylbenzene. Pentyl benzene and, to some extent, hexylbenzene showed increasing detection with concentration, reaching at full vapor strength P≈0.60 and P≈0.26, respectively. In contrast, heptylbenzene showed a flat function around chance detection (i.e., P≈0.0) barely reaching P≈0.17 at full vapor strength. Confidence ratings reflected the trend in detectability.

Figure 1.

Figure 1

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Upper section. Left. Group psychometric function (left y-axis, filled circles) and confidence ratings (right y-axis, empty squares) for the eye irritation evoked by pentylbenzene. Each point represents the average of 320 trials made by 16 subjects. Bars indicate standard error. Center. Same for hexylbenzene. Right. Same for heptylbenzene but where each point represents the average of 300 trials made by 15 subjects. Lower section. Individual functions from 14 subjects for eye irritation detection from pentylbenzene (left), hexylbenzene (center), and heptylbenzene (right). Each unique symbol represents the same subject across the three graphs. Each point represents the outcome of 20 trials per concentration for that subject. Filled circles joined by the thick line represent the average across the 14 subjects.

A look at the individual data from the 14 subjects that completed all three chemicals provided additional insight (Figure 1, lower section). No gender differences in detectability emerged. Despite individual variability, most subjects shared the group pattern observed for each alkylbenzene. Thus, for pentylbenzene, the majority of participants showed a sharp increase in detection with concentration, many of them reaching detectabilities close to perfect detection. For hexylbenzene, only three subjects continued to show clearly such trend. Finally, for heptylbenzene only two subjects showed the trend, with all other subjects either failing altogether to increase detection with concentration or reaching a plateau where further increases in concentration did not produce enhanced detection. A two-way ANOVA for repeated measurements performed on the individual data from the 14 subjects common to the three chemicals gave statistical support to the results. The ANOVA showed that the factors alkylbenzene (three levels) {F(2,26)=17.4, p<0.0001}, concentration (five levels) {F(4,52)=28.1, p<0.0001), and their interaction {F(8,104)=5.20, p<0.0001) were all significant. Contrast tests revealed that the function for pentylbenzene was significantly different from those of hexylbenzene (p=0.0008) and heptylbenzene (p<0.0001), and that the difference between the functions for hexyl and heptylbenzene came very close to significance (p=0.055).

Experiment 2: Ketones

Materials and Methods

Subjects

We recruited 24 subjects (13 female). Their average age (±SD) was 28 (±9) years, ranging from 18 to 52 years. All participants were normosmics (Cain, 1989), non-users of contact lenses, and, except for one occasional smoker (male, 24 years old), nonsmokers.

A subset of 18 participants (9 female) from the group described above had available time to complete at least 20 trials per concentration (half with each eye) for all three ketones (see Procedure). Data presented below for individual subjects refers to this more comprehensively tested group.

Stimuli

The chemicals tested (purity in parenthesis) were: 2-undecanone (98+%), 2-dodecanone (98+%), and 2-tridecanone (98%). Medical Air U.S.P. (humidified to 50% relative humidity, RH) served as blanks (see Procedure). Table 2 presents the actual vapor concentrations in N2 tested for each chemical as determined by gas chromatography (flame ionization detector, FID), and the nominal concentrations as determined by the ratio “stimulus flow / total (blank air + stimulus) flow” (see Apparatus).

Table 2.

Concentrations tested for each ketone as determined by gas chromatography (flame ionization detector, FID) of samples taken at the outlet of the vapor delivery device (expressed in ppm and in log ppm by volume) and as determined by the ratio of stimulus / total (air+stimulus) flow (in % v/v) set with the device (see Apparatus). SD indicates standard deviation.

CHEMICAL ppm ± SD log ppm ± SD % v/v
2-Undecanone 6.1 ± 1.5 0.769 ± 0.114 20
17 ± 2.5 1.232 ± 0.065 40
29 ± 9.2 1.434 ± 0.158 60
37 ± 8.9 1.554 ± 0.112 80
42 ± 15 1.598 ± 0.128 100
2-Dodecanone 1.6 ± 0.49 0.174 ± 0.143 20
4.6 ± 0.99 0.650 ± 0.099 40
5.9 ± 2.1 0.742 ± 0.192 60
6.9 ± 1.5 0.829 ± 0.092 80
8.1 ± 1.9 0.898 ± 0.089 100
2-Tridecanone 0.35* −0.451* 20
1.2 ± 0.50 0.034 ± 0.223 40
2.4 ± 0.41 0.374 ± 0.075 60
3.5 ± 0.73 0.535 ± 0.085 80
4.1 ± 0.58 0.606 ± 0.063 100
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*

Value extrapolated from measurements at the higher concentrations.

Apparatus

Same as in Experiment 1.

Procedure

Same as in Experiment 1.

Data analysis

Same as in Experiment 1.

Results

Figure 2 (upper section) presents the concentration-detection functions for each of the three ketones. Only 2-undecanone and, to a minor extent, 2-dodecanone showed an increase in detection with concentration, reaching at full vapor strength P=0.45 and P=0.18, respectively. 2-Tridecanone failed to be detected across the entire concentration range. Confidence ratings reflected the trend in detectability.

Figure 2.

Figure 2

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Upper section. Left. Group psychometric function (left y-axis, filled circles) and confidence ratings (right y-axis, empty squares) for the eye irritation evoked by 2-undecanone. Each point represents the average of 400 trials made by 24 subjects. Center. Same for 2-dodecanone. Right. Same for 2-tridecanone but where each point represents the average of 440 trials made by 24 subjects. Lower section. Individual functions from 18 subjects for eye irritation detection from 2-undecanone (left), 2-dodecanone (center), and 2-tridecanone (right). Each unique symbol represents the same subject across the three graphs. Each point represents the outcome of 20 trials per concentration for that subject. Filled circles joined by the thick line represent the average across the 18 subjects.

Using the data from the 18 participants tested on all three ketones, we plotted individual concentration-detection functions (Figure 2, lower section). No gender differences in detectability emerged. For 2-undecanone, most subjects increased detection with an increase in concentration, and some of them reached high levels of detectability (P > 0.80). For 2-dodecanone, only 3 subjects continued to show this trend (albeit one of them reached a detectability plateau at P = 0.7 where a further increase in concentration failed to increase detection). For 2-tridecanone, none of the subjects consistently increased detection with concentration, and all performed around chance detection across the entire concentration range. We performed a two-way ANOVA for repeated measurements on the data from these 18 participants, using the factors ketones (three levels) and concentration (five levels). The results revealed significance differences for ketones {F(2,34)=20.4, p<0.0001}, for concentration {F(4,68)=7.0, p<0.0001}, and for their interaction {F(8,136)=5.7, p<0.0001}. Contrast tests revealed that the function for 2-undecanone differed significantly from those for 2-dodecanone (p=0.0017) and 2-tridecanone (p<0.0001), and that the function for 2-dodecanone differed significantly from that for 2-tridecanone (p=0.0055). Thus, the outcome of the ANOVA gave statistical support to the differences among psychometric functions shown in Figure 2.

Discussion

At least two reasons could explain the appearance of a cut-off effect in the chemesthetic detection of homologous VOCs (Cometto-Muñiz et al., 1998a). One possibility is that a homolog is reached whose vapor saturation at room temperature (≈23°C) falls below the threshold concentration for detection. This represents a limitation based on vapor concentration. Another possibility is that a homolog is reached whose molecular dimensions exceed a critical value that allows it to reach or bind effectively to the appropriate receptor(s). This represents a limitation based on molecular size or structure. Previous work employed two strategies to investigate the issue. One strategy applied a well-established quantitative structure-activity relationship (QSAR) (Abraham et al., 1998; Abraham et al., 2001; Abraham et al., 2003) to predict the chemesthetic threshold concentration of the cut-off homolog and establish whether it was indeed higher than the saturated vapor concentration of that homolog at 23°C (Cometto-Muñiz et al., 1998a). The other strategy tested whether the detectability of the cut-off homolog could be significantly increased by presenting the vapor at an even higher concentration, for example, the saturated vapor at 37°C (body temperature) (Cometto-Muñiz et al., 2005b; Cometto-Muñiz et al., 2006; Cometto-Muñiz et al., 2007b). Results from both strategies pointed out to a limitation based on molecular dimension (size) as the reason for the cut-off, at least for the six series studied: acetate esters, n-alcohols, n-alkylbenzenes, 2-ketones, carboxylic acids and aliphatic aldehydes.

To gather additional evidence on the basis for the cut-off effect in chemesthetic detection of VOCs, we recently pursued an additional strategy, that is to measure concentration-detection (i.e., psychometric) functions for homologs approaching the cut-off point (Cometto-Muñiz et al., 2007a). We reasoned that, under a limitation based on molecular size, the function for a cut-off homolog should reach a plateau (well below P=1.0) where further increases in concentration would fail to increase detectability. This is the strategy employed here for the three homologous alkylbenzenes and ketones.

The psychometric functions for the alkylbenzenes (Figure 1) revealed that the detectability of heptylbenzene, even at full strength (100% v/v), only reached P=0.17. Nevertheless, there were no indications of a detectability plateau (as defined above) across the concentration range tested. This range can be extended by adding data from a previous study of heptylbenzene that tested its detection by eye irritation at two concentrations: vapor saturation at 23°C and at 37°C (Cometto-Muñiz et al., 2006) (Figure 3). Then, it becomes clear that the ocular chemesthetic detectability of heptylbenzene indeed reaches a plateau at P≈0.20, particularly considering that chemesthetic psychometric functions grow from slightly above chance to perfect detection within one order of magnitude as seen here for pentylbenzene (Figure 1) and in previous studies for other VOCs (Cometto-Muñiz et al., 1999; Cometto-Muñiz et al., 2002). In Figure 3, an increase in concentration from about 26 ppm to 141 ppm fails to increase detectability further. Thus, the present results for alkylbenzenes provide additional support to the notion of a cut-off based on molecular dimension(s) at the level of heptylbenzene.

Figure 3.

Figure 3

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A plot for heptylbenzene combining the psychometric function for ocular chemesthesis obtained here (circles) with previous detectability data for vapor saturation at 23 and at 37 °C (squares) (Cometto-Muñiz et al., 2006) clearly shows the emergence of a detection plateau at P≈ 0.2. Bars indicate standard error.

Regarding the ketones, the psychometric functions obtained suggest a cut-off at the level of 2-dodecanone or 2-tridecanone (Figure 2). For this series, previous detectability data for 2-dodecanone is available only for vapor saturation at 23°C, whereas for 2-tridecanone it is available for vapor saturation at 23 and at 37 °C (Cometto-Muñiz et al., 2006). Figure 4 merges these previous values with the present psychometric functions. The outcome in terms of reaching a detectability plateau is not evident for 2-dodecanone but it is quite clear for 2-tridecanone, again in the context of the characteristic steepness of chemesthetic functions as shown here for 2-undecanone (Figure 2) and as seen for other compounds (Cometto-Muñiz et al., 1999; Cometto-Muñiz et al., 2002). The present results for 2-ketones also indicate that the cut-off observed at the level of 2-tridecanone is based on molecular dimension(s). In turn, Table 3 lists the particular cut-off homolog found for each of the series tested so far, and includes the mucosal site probed and the corresponding references.

Figure 4.

Figure 4

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Left. A plot for 2-dodecanone combining the psychometric function for ocular chemesthesis obtained here (circles) with previous detectability data for vapor saturation at 23°C (square) (Cometto-Muñiz et al., 2006). Right. Same for 2-tridecanone but where previous data includes detectability for vapor saturation at 23 and at 37 °C (squares) (Cometto-Muñiz et al., 2006). The lack of a detectability value for 2-dodecanone saturated vapor at 37°C leaves the emergence of a plateau inconclusive, but for 2-tridecanone the plateau emerges clearly at P≈0.2. Bars indicate standard error.

Table 3.

List of the particular cut-off homolog found for the homologous series studied so far, including the mucosal site tested and the corresponding citations.

Homologous series Cut-off point for chemesthesis Tested mucosa References
n-Alcohols 1-Undecanol Ocular (Cometto-Muñiz et al., 2005b; Cometto-Muñiz et al., 2007a)
Esters (n-Acetates) Decyl acetate Ocular (Cometto-Muñiz et al., 2005b; Cometto-Muñiz et al., 2007a)
Decyl acetate Nasal (Cometto-Muñiz et al., 2005a)
Esters (n-Butyrates) 2-Ketones Hexyl butyrate Nasal (Cain et al., 2006)
2-Ketones 2-Tridecanone Ocular (Cometto-Muñiz et al., 2006) (This study)
n-Alkylbenzenes Heptyl benzene Ocular (Cometto-Muñiz et al., 2006) (This study)
Carboxylic acids Heptanoic acid Ocular (Cometto-Muñiz et al., 2007b)
Octanoic acid Nasal (Cometto-Muñiz et al., 2005a)
Aldehydes Dodecanal Ocular (Cometto-Muñiz et al., 2007b)
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The chemesthetic detection of general VOCs in the eyes and nose is achieved via polymodal nociceptors within free nerve endings of C- and A-delta fibers from the trigeminal nerve that innervate the ocular and nasal mucosae (Doty et al., 2004). Nevertheless, the molecular mechanisms involved have not been clearly established. Probable participants are members of a family of transient receptor potential (TRP) channels (Pedersen et al., 2005; Ramsey et al., 2006), involved in a wide variety of sensory systems, including temperature, touch, taste, and chemical nociception, among others (Clapham, 2003; Voets and Nilius, 2003; Voets et al., 2005; Nilius, 2007). For example, subtypes of TRP channels are implicated in the detection of typical pungent stimuli such as capsaicin, piperine, isothiocyanates, acrolein, thiosulfinates, cinamaldehyde and menthol, to name a few (Julius, 2005; Bautista et al., 2006; Bandell et al., 2007). Thus, TRPs are strong candidates to play a role in the detection of the wide structural variety of environmental VOCs capable of eliciting chemesthetic sensations, such as the alkylbenzenes and ketones studied here. Additional relevant receptors include acid-sensing ion channels (ASIC), purinergic receptors (P2X), and nicotinic acetylcholine receptors (nAChR), all present in trigeminal nerve fibers (Silver et al., 2006). Furthermore, other not yet identified receptors and mechanisms are also likely to participate in the detection of airborne irritants (Symanowicz et al., 2004; Inoue and Bryant, 2005).

Ultimately, the overall effect of nociceptive agents, endogenous and exogenous, rests on the combined input of multiple channels and mechanisms as has been pointed out (Tominaga et al., 1998; Garle and Fry, 2003; Voets and Nilius, 2003; Ramsey et al., 2006). In this context, studies probing the integrated, psychophysical outcome of human chemesthetic detection within a structure-activity approach become particularly relevant. A quite successful quantitative structure-activity relationship (QSAR) has been developed for human ocular and nasal chemesthesis, as measured psychophysically (Abraham et al., 1998; Abraham et al., 2003). In line with the evidence discussed above, this model shows that the chemesthetic potency of VOCs, at least up to the cut-off point, is largely based on “selective” processes. These processes involve transfer-driven effects in which gradual structural changes in the VOC evoke predictable, and rather small, changes in biological activity. They reflect the transfer of the irritant from the vapor phase through various biological phases (biophases) until reaching the receptor(s) environment(s). In contrast, the observation of the cut-off effect indicates the appearance of a “specific” process, that is, one in which a small structural change in the VOC evoke a less predictable, and often large, change in activity. A cut-off effect fits this category, and it is not presently contemplated in the otherwise successful QSARs cited above.

Results at the molecular and psychophysical level, as discussed, suggest that chemesthesis rests on processes integrating many mechanisms, and can be evoked by a large variety of chemical stimuli (Cometto-Muñiz, 2001). Many, if not all, of these pathways rely on receptors involving protein structures (Owsianik et al., 2006; Ramsey et al., 2006). It is, then, not surprising that potential irritants might reach a critical molecular size, i.e., the cut-off point, beyond which they fail to activate the relevant receptors or to fit into the binding pocket of a receptive macromolecule. The present experiments are part of a project that aims to identify the cut-off homologs across a broad range of homologous series and to ascertain whether the phenomenon is based on restrictions related to molecular dimension or to vapor concentration. These and previous results favor the first interpretation (Cometto-Muñiz et al., 1998a; Cometto-Muñiz et al., 2005b; Cometto-Muñiz et al., 2006; Cometto-Muñiz et al., 2007a; Cometto-Muñiz et al., 2007b). With the help of molecular modeling programs, and once the cut-off homologs are identified across as many series as possible, their critical dimensions could be quantified and the outcome incorporated as an additional parameter into the established QSAR, expanding its applicability to VOCs located beyond the cut-off boundaries.

Acknowledgments

The work described in this article was supported by research grants R01 DC 005003 and DC 002741 from the National Institute on Deafness and Other Communication Disorders, National Institutes of Health, and by Philip Morris USA Inc. and Philip Morris International. The funding sources played no role in the study other than monetary support. Thanks are due to J. Keeley and C. Santiago for excellent technical assistance. Thanks are also due to D. Giancola, A. Alfaro, and D. Nahl for their help in various stages of the study.

Footnotes

Conflict of Interest Statement

There are no conflicts of interest.

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