ORGANOLEPTIC METHOD

TOP ABSTRACT ORGANOLEPTIC METHOD RESULTS MICROBIAL GENERATION RATES DISCUSSION CONCLUSIONS REFERENCES

 
To measure the efficacy of agents that interfere with VC production, researchers and clinicians generally prefer to use the organoleptic method. With this method, judges use a common scale to assess the intensity (strength) of the target odors. They offer no opinion about the quality of the odor. Typically, the organoleptic method is used to measure the efficacy of antiodor treatments. It may include testing agents that directly interfere with the biogenic production of VCs (that is, inhibitors of specific transformation steps), as well as agents that work indirectly by reducing microbial cell turnover of catalysts (that is, agents that are biostatic or biocidal against the causative microbes).

The organoleptic method has been used in human trials to measure the efficacy of many types of agents, including zinc mouthwash,¹ chlorine dioxide² and chlorhexidine and a two-phase mouthrinse.³ These trials used a four-point, five-point and six-point organoleptic scale, respectively.

Organoleptic scale. Researchers generally accept that human beings have a sense of smell that is capable of detecting differences in the strength or concentration of odor molecules.⁴ However, different groups of researchers have used different scales and different descriptions of what the scores mean. A scale commonly used in oral malodor research is the 0-to-5 intensity scale first described by Allison and Katz⁵ and more recently used by Rosenberg and colleagues.^6,7 In this six-point system, 0 indicates a concentration of odorant that is below a threshold, and 5 indicates concentrations that are extremely strong and assumed to be close to saturation (Table 1^6–9). Greenman and colleagues⁹ used this scale recently to study the relationships between odor scores and concentrations of pure malodor compounds that are representative of those likely to be involved in human oral malodor.

Simple model: single type of odorant and single type of smell receptor. In this type of model,¹⁰ we assume that the relationship between the odor compound (ligand) and the receptor follows a binding pattern that is encountered commonly in biology (that is, saturation-binding kinetics such as that between the agonist and receptor in smooth muscle). A flow of gas across the receptor-bearing area will allow molecules of ligand (odorant) to bind to the receptors. At the same time, it also allows bound ligand to dissociate from the receptor and diffuse back into the gas stream. If we assume that the binding follows the laws of mass action, then:

where Rec equals receptor and Lig equals ligand. At equilibrium, the backward (dissociation) reaction equals the forward association reaction. The equilibrium dissociation constant (K_d) equals k_off/k_on, and the concentration of ligand can be denoted as X. The specific binding (Y) is given as follows:

where B_max is the maximum binding, X is the concentration of the ligand (odorant) and K_d is the equilibrium dissociation constant. The resulting graph of this equation is called a rectangular hyperbola (or saturation-binding curve). We used the results reported by Greenman and colleagues⁹ with regard to odor assessment of dimethyldisulfide to illustrate simple binding (Figure 1A). A log plot of odorant concentrations produces a sigmoidally or exponentially shaped curve (Figure 1B).

View larger version (32K): [in this window] [in a new window]   Figure 1. Generalized saturation binding curve for dimethyldisulfide (data from Greenman and colleagues9) using (A) nontransformed and (B) log-transformed odorant concentrations (x-axis), with points fitted by both exponential and sigmoidal plots. (The nonlinear regression curve fit was performed using GraphPad Prism version 3.02 for Windows, GraphPad Software, San Diego.) mol dm–3: Moles per liter.

where B_max1 and B_max2 are the maximum binding of receptor 1 and 2, respectively, X is the concentration of the ligand (odorant) and K_d1 and K_d2 are the equilibrium dissociation constants for receptors 1 and 2, respectively.

For some odorants (for example, trimethylamine), the data can be interpreted as being either simple exponential (one-site binding), but with wide errors or scatter, or multiphasic, with two or more binding sites (Figure 2). In this latter model (Figure 2B), the lowest five data points form a much higher slope than do the remaining points, showing high-affinity binding when close to the threshold level and low-affinity binding at higher gas levels.

View larger version (36K): [in this window] [in a new window]   Figure 2. One-site and two-site saturation-binding regression curves for trimethylamine (data from Greenman and colleagues9) using (A) nontransformed and (B) log-transformed odorant concentrations. (The nonlinear regression curve fit was performed using GraphPad Prism version 3.02 for Windows, GraphPad Software, San Diego.) The two dotted lines indicate the ± 95 percent confidence interval for the regression line of all points. mol dm–3: Moles per liter.

Although a multitude of different receptors probably are involved in the assessment of any one odor, these receptors cannot be distinguished because of the limited level of accuracy achieved when using human judges. The judge responds as if there is only one type of affinity for each specific odor compound (with the possible exception of trimethylamine). Moreover, the level of accuracy achieved from odor judges is insufficient to distinguish between a simple exponential response and a sigmoidal response to odor concentrations (Figure 1B).

	RESULTS

TOP ABSTRACT ORGANOLEPTIC METHOD RESULTS MICROBIAL GENERATION RATES DISCUSSION CONCLUSIONS REFERENCES

 
Odor thresholds. Table 2^9,12–15 provides a comparison of odor thresholds from Greenman and colleagues⁹ with standardized human olfactory thresholds in the literature.¹⁴ The experiments conducted by Greenman and colleagues⁹ were not designed to precisely determine thresholds and, therefore, provide only approximate values. Nevertheless, a comparison of the derived values from Greenman and colleagues⁹ with those published elsewhere¹⁴ reveals that the same rank order was given for compounds (that is, skatole < methyl mercaptan < trimethylamine < isovalerate < butyrate < hydrogensulfide < putrescine < dimethyldisulfide).

Particular compounds. The contribution that any VC and/or VSC makes to an overall odor depends on odor threshold, odor power and gas concentration. We compare these variables below for five classes of compounds.

VSC, methyl mercaptan and hydrogen sulfide. Both methyl mercaptan and hydrogen sulfide are highly volatile. When expressed as Henry’s law constant (Kcc [that is, the dimensionless ratio between the aqueous concentration and its gas concentration at equilibrium]), these compounds have constants of approximately 1.7 x 10¹. However, methyl mercaptan has an odor threshold that, molecule for molecule, is more than 10-fold lower than that for hydrogen sulfide. Therefore, it is inherently more odoriferous.

However, hydrogen sulfide has higher odor power than does methyl mercaptan. If either VSC were present in sufficient amounts to elicit a breath score of 1, the concentration of hydrogen sulfide would only have to increase by a factor of 4.8-fold to elicit a score of 2, while the concentration of methyl mercaptan would have to increase by 7.2-fold to elicit a score of 2. Odor judges trained to recognize the characteristic odor of VSC almost always report this odor to be present on human breath (unpublished data, M.E., M.R., S.S., June 2003), and its presence in the breath has been well-established by others.^16,17 Moreover, numerous reports link oral anerobes to the production of these gases.^18,19

Indoles. The indole class of compounds includes indole and skatole. Both have low volatility (Henry’s law constants of approximately 4.0 x 10⁵ [that is, always more molecules in the aqueous liquid phase than in the vapor phase]). Their odor thresholds are very low (molecule for molecule, they are more odorous than are other VCs) and, thus, they may be important in oral malodor. If indole were present in sufficient amounts to elicit a breath score of 1, the concentration would have to increase by only eight times this amount to elicit a score of 2. Odor judges trained to recognize the characteristic odor of indoles occasionally report the presence of this odor on human breath (unpublished data, M.E., M.R., S.S., June 2003). Production rates of indole in dental plaque or on tongue biofilm have not been reported, but many of the oral anerobes isolated from tongue biofilm have the potential to produce indole when cultured in vitro.²⁰

Fatty acids (acetate, propionate, butyrate, isovalerate). In comparison with VSCs, the volatility of fatty acids in water is low (Henry’s law constants of about 4 x 10⁴), and the amount of fatty acid available in the solution for phase transition depends on the pH. The pK_a for fatty acids is close to pH 4.8. In buffered solutions, such as saliva or biofilm fluid, in which the pH usually is higher than 6.5, the majority of fatty acid molecules are in the ionic salt form, and as such are not volatile and do not contribute to the gas concentration.

It is likely that these compounds would have to be present at high millimolar levels for them to contribute to oral odor. In addition, acetate is not particularly odorous, with a 10-fold higher threshold concentration for detection than that for the longer chain acids (such as propionate or butyrate).¹⁴ Propionate and butyrate have been detected in plaque fluid at concentrations between 10 and 50 mmol/L.^21,22 However, isovaleric acid is barely detectable in plaque fluid.

The odor power for butyrate suggests that if it were present in sufficient amounts to elicit a breath score of 1, the concentration would have to be 20 times higher to elicit a score of 2. Odor judges trained to recognize the characteristic odor of fatty acids have not reported it to be prominent in human breath (unpublished data, M.E., M.R., S.S., 2003).

Amines (putrescine, cadaverine, trimethylamine). Although these compounds are more volatile than are the fatty acids, their pK_a is close to pH 9.0, and they exist mainly in the non-volatile ionic salt form at a neutral pH (for example, in fresh saliva). These compounds also would have to be present in high millimolar amounts to contribute to oral odor. However, Hayes and Hyatt²³ reported levels of amines in plaque only in the micromolar range; similarly, the levels of cadaverine in saliva have been shown to reach a concentration of only 200 µmol/L.²⁴ The smell threshold for putrescine is similar to that of butyrate, but the odor power is less. If putrescine were present in sufficient amounts to elicit a breath score of 1, its concentration would have to increase 30 times to elicit a score of 2. Odor judges have, on occasion, reported the presence of this odor on human breath (particularly among denture wearers) (unpublished data, M.E., M.R., S.S., June 2003).

Any increase in pH will promote the volatility of amines, and this could occur under conditions in which stagnant saliva rapidly loses carbon dioxide from its bicarbonate buffering and quickly becomes alkaline. Although trimethylamine might be produced by microbial decomposition of choline, the levels occurring in the healthy mouth generally are thought to be low. Trimethylamine levels in the breath become significant only in the rare metabolic condition of trimethylaminuria.²⁵

Other volatile compounds. The odor threshold concentrations for common alcohols, aldehydes and ketones are high.¹⁴ If present, they would have to be at relatively high concentrations to contribute to oral malodor. In the absence of an exogenous source (for example, food and drink) or production due to a host metabolic disorder (for example, diabetes mellitus), it is difficult for us to see how such compounds could arise. Oral microbes are not noted for producing significant amounts of these types of compounds.

	MICROBIAL GENERATION RATES

TOP ABSTRACT ORGANOLEPTIC METHOD RESULTS MICROBIAL GENERATION RATES DISCUSSION CONCLUSIONS REFERENCES

 
In the oral cavity, the microbial flora, particularly anerobes present within the tongue surface biofilm (the tongue coat), generate various types of VCs.²⁰ The relationship between the numbers of anerobes on the tongue dorsum surface and breath odor levels has been studied by Hartley and colleagues.²⁶ They found an approximate fourfold increase in anerobes per square centimeter of tongue surface per unit increase in breath score.

If we assume that a fourfold increase in cells (enzymes) would increase the production rate of VCs by fourfold (one breath score unit), and if we assume that the proportions of odor gas components within the mixture remain the same (ratios are preserved), then we suggest that the odorants involved must have high odor power. Moreover, studies of the dilution of breath odor (Figure 3) have shown that a fivefold dilution of breath odor is required to reduce the odor score (on the 0-to-5 scale) by one unit.^15,27 Taken together, these data support the view that hydrogen sulfide is the only gas with sufficient odor power to fully account for these findings.

View larger version (31K): [in this window] [in a new window]   Figure 3. Relationship between breath odor score and a fivefold dilution of a sample to the threshold level.15 The solid line indicates the best-fit regression line; dotted lines indicate the ± 95 percent confidence interval.

	DISCUSSION

TOP ABSTRACT ORGANOLEPTIC METHOD RESULTS MICROBIAL GENERATION RATES DISCUSSION CONCLUSIONS REFERENCES

Researchers could compare plots of odor score data with the means observed by others⁹ with respect to slope (that is, the magnitude of the judges’ responses for different concentrations) and threshold. Training with the same compounds would continue until judges reached acceptable limits around the means described. Such sets of odorants would have universal validity and could be used with all putative odor judges.

With regard to the interpretation of odor scores (for example, those obtained in a clinical trial of antimalodor agents), the realization of the exponential nature of the scale has certain consequences when we interpret the judges’ scoring data. For any brief sampling period (a few minutes in a day), the oral cavity is likely to be in an approximate steady state before treatment perturbation. The dilution rate (exchange rate) of VC in the gas phase is extremely rapid, and, therefore, it is the production rate of VC that will dictate the steady-state breath levels of odorant.

Any individual is likely to experience a relatively steady production rate of VCs and/or VSCs from the tongue and other oral biofilms. Microbes grow and biotransform in a continuous process that approximates a dynamic steady state (discounting the oscillations in gas flow—that is, breathing). A product (such as a mouthwash) that inhibits VC formation, either directly by enzyme inhibition or indirectly as an antimicrobial agent, will lower the rate of production by a certain fraction. The product achieves this regardless of the starting point in terms of microbial density, enzyme target numbers or consequent breath odor levels. It is the concentration of the active agent and the binding affinity of the agent to its targets, coupled with the agent diffusion rate, that determine the degree of inhibition.

Because the product concentration profile after exposure and dilution likely will be similar in all people, a similar degree of inhibition is likely to occur, regardless of the initial number of microbes or breath odor levels. For example, an 80 percent inhibition of hydrogen sulfide formation might be expected to occur regardless of the starting breath odor score and reduce a score of 4 to 3, 3 to 2 or 2 to 1 in an equal manner. In other words, a given percentage reduction in the VC generation rate will result in an equal reduction on the breath odor scale.

In a clinical trial of antiodor compounds (such as zinc, peroxides, chlorhexidine, triclosan), researchers take odor measurements before intervention (treatments or placebo) and compare these measurements with a series of readings after intervention. In a trial population (assuming that volunteers have not been selected on the basis of having the same breath odor levels), the standard deviations of the means of all pretreatment and posttreatment readings are bound to be wide, reflecting the wide range typically encountered in human populations (that is, anywhere between 0 and 5 on the odor scale). Even in a crossover trial, a large sample size is required to show statistical differences between subjects receiving the treatment and the same subjects serving as controls on another occasion.

Model data. Table 3 (page 755) presents an example using model data to illustrate this point. In this example, each of 10 subjects receives both the control product and treatment (on separate visits). Measurements are taken before and after intervention (with treatment or control). We should note that the scores are not significantly different from one another (P > .05; analysis of variance); thus, on the basis of these results, we would conclude that the treatment had no effect.

Therefore, measures of individual differences (when averaged) result in a mean value that is independent of the wide scatter of starting values inherent in a healthy population of subjects. The differences between treatment and control can be compared and discriminated to a higher degree of statistical probability than otherwise would be possible (Table 3).

	CONCLUSIONS

TOP ABSTRACT ORGANOLEPTIC METHOD RESULTS MICROBIAL GENERATION RATES DISCUSSION CONCLUSIONS REFERENCES

 
Different odorants have different properties of volatility, odor threshold and odor power. Hydrogen sulfide likely is the most important gas in oral malodor, and treatments should target this gas. The 0-to-5 organoleptic scale is sigmoidal in theory and exponential in nature. Realization of this can lead to better ways of training, calibrating and standardizing odor judges, as well as result in better ways of designing trials or interpreting data obtained from such trials on the efficacy of antiodor treatments.