Concepts of Nanoparticle Dose Metric and Response Metric

Referencing: In Search of the Most Relevant Parameter for Quantifying Lung Inflammatory Response to Nanoparticle Exposure: Particle Number, Surface Area or What?

Wittmaack (2007) did not agree with our suggestion (Oberdörster et al. 2005) that particle surface area is a more appropriate dose metric than particle mass or particle number when evaluating dose–response relationships of nanoparticle-induced pulmonary inflammation. According to his understanding of nanotoxicology and based on his calculations, he found particle number to work best as a dose metric. Throughout our review we pointed out that the surface area concept should be considered in the context of nanoparticle surface properties such as chemistry, charge, coating, crystallinity, porosity, and reactivity. For example, nano-titanium dioxide (TiO₂) or nano-copper particles, very distinct from one another, will predictively create separate well-fitting surface area dose–response relationships. Yes, particle number is of importance as well, as we indicated in our review, but not as a direct dose metric.

We would like to address some of the issues Wittmaack (2007) raised in his article. First, Wittmaack suggested that when expressing a pulmonary inflammatory response, a response metric is better done using the ratio of lavaged neutrophils (PMN; polymorphonuclear leukocytes) to macrophages instead of using the fraction of PMNs. Because the purpose of our review (Oberdörster et al. 2005) was not to describe these responses in mathematical terms (whether threshold, linear, or nonlinear) but rather to illustrate that dose–response relationships on a mass basis—but not on a surface area basis—are very different, the choice of the response metric is irrelevant. To demonstrate this, we present our data again (Figure 1), expressed as absolute numbers of elicited PMNs and as PMN/macrophage ratios as a function of administered mass (Figure 1A,B), number (Figure 1C,D), or surface area (Figure 1E,F) of fine and ultrafine (nanosized) TiO₂. The dose–response relationships based on mass and surface area are essentially the same as those shown in our review (Oberdörster et al. 2005) using the percentage of elicited neutrophils.

Figure 1. Inflammatory cell response in lung lavage 24 hr after intratracheal instillation of fine (~ 250 nm) and ultrafine (20–30 nm) TiO2 expressed by different dose metrics [particle mass (A,B), number (C,D), and surface area (E,F)] and different response metrics [number of PMNs (A,C,E) and PMN/macrophage ratio (B,D,F)].

Second, regarding the issue of particle number being the best dose metric, the particle number dose–response relationships (Figure 1B) are several orders of magnitude apart for fine and ultrafine TiO₂, whereas the surface area plot (Figure 1C) shows a good fit for the combined particle sizes. The reviewers of Wittmaack's article (2007) apparently overlooked this flaw in his argument.

Finally, Wittmaack (2007) calculated that the surface area for ultrafine TiO₂ should be 77 m²/g and not 50 m²/g, as we reported (Oberdörster et al. 2005). He derived his value on the basis of the specific density of TiO₂ (anatase) and a spherical primary particle size of 20 nm. BET surface area for this TiO₂ (Degussa P25) has been measured independently by a number of investigators, including our group (Jwo et al. 2005; Long et al. 2006; Wahl et al. 2005), and ranges between 48 and 55 m²/g. There is no reason to mathematically manipulate this number to a value that is completely at odds with actual measurements. In contrast to the well-established surface area, the average primary particle size of TiO₂ has not been firmly established, with values of 20–30 nm. Indeed, a size of 30 nm (calculated surface area, 51.2 m²/g) conforms best to the measured BET surface. Thus, we added particle number dose–response data for 30 nm TiO₂ to Figure 1C and 1D; the order of magnitude difference of the dose response between fine and ultrafine particles is obvious, regardless of whether the ultrafines are considered to be 20 or 30 nm in size.

We have concluded that of the three dose metrics discussed, particle number is the worst to describe nanoparticle-induced pulmonary inflammatory effects.

The authors declare they have no competing financial interests.

References

Jwo CS, Tien DC, Chen LC, Teng TP, Chang H, Lin CH, et al. 2005. Photodecomposition of gaseous toluene using TiO₂ prepared by SANSS. J Phys Conf Ser 13:438–441.

Long TC, Saleh N, Tilton RD, Lowry GV, Veronesi B. 2006. Titanium dioxide (P25) produces reactive oxygen species in immortalized brain microglia (BV2): implications for nanoparticle neurotoxicity. Environ Sci Technol 40(14):4346–4352.

Oberdörster G, Oberdörster E, Oberdörster J. 2005. Nanotoxicology: an emerging discipline evolving from studies of ultrafine particles. Environ Health Perspect 113:823–839.

Wahl RK, Yu WW, Liu Y, Mejia ML, Falkner JC, Nolte W, et al. 2005. Photodegeneration of Congo Red catalyzed by nanosized TiO₂. J Mol Catal A Chem 242:48–56.

Wittmaack K. 2007. In search of the most relevant parameter for quantifying lung inflammatory response to nanoparticle exposure: particle number, surface area, or what? Environ Health Perspect 115:187–194; doi:10.1289/ehp.9254 [Online 3 October 2006].

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Dose and Response Metrics in Nanotoxicology: Wittmaack Responds to Oberdörster et al. and Stoeger et al.

In their letters, Oberdörster et al. and Stoeger et al. present some comments on a few out of many issues that I addressed in my reanalysis of literature data on lung inflammatory response to nanoparticle exposure (Wittmaack 2007). I appreciate the opportunity to strengthen and expand my arguments.

Figure 1. Particle-size dependence of the A/M and the ΣAae. The straight line relates to TiO2 particles, the open and solid circles indicate ambient aerosol particles, and the crosses indicate two BET data. According to Oberdoerster et al.'s letter, the so-called 20-nm TiO2 particles may well have been 30 nm in size.

I argue that results of nanoparticle toxicology studies should not be interpreted on the basis of the reasoning that the number of surface atoms, relative to all atoms in a (spherical) particle, increases as the inverse of the diameter, D (Oberdörster et al. 2005). If the toxicity of an insoluble particle scales with the number of surface atoms, it is the surface area (A) that counts, not its ratio to the mass (M). Figure 1 shows the size dependence of the specific surface area (S = A/M = 6/D) for TiO₂ particles [mass density, (anatase) = 3.9 g/cm³]. Also presented is an example for the cumulative surface area (ΣA_ae) calculated from the mean number concentration of an ambient aerosol (Wittmaack 2002), including extrapolated data for D < 10 nm. ΣA_ae decreases rapidly with decreasing D, notably for D < 100 nm. In contrast, S_ae = ΣA_ae/ΣM_ae = ΣA_ae/ΣV_ae (= 1.5 g/cm³) increases as 1/D, for D < 200 nm, where V is the particle volume. If toxicity is assessed by reference to S_ae rather than to A_ae, the danger of exposure to nanoparticles (e.g., for D = 30 nm), compared to fine particles (D = 1 µm), is overestimated by a factor of 1,130. By taking the ratio A/M, we compare apples (the surface area of insoluble particles) and oranges (the mass of soluble particles).

This type of reasoning in terms of S_ae (Oberdörster et al. 2005) has been used often (Kreyling et al. 2006; Nel et al. 2006 ); Gwinn and Vallyathan (2006) even characterized ultrafine particles (UFPs; i.e., particles with D ≤ 100 nm) as "UFPs with larger surface area."

In their Figure 1, Oberdörster et al. (2005) reproduced some of their own data in two ways: as the number (n_PMN) of lavaged polymorphonuclear leukocytes (PMNs) and as the ratio (r_P,m) of n_PMN to the number (n_ma) of macrophages (r_P,m = n_PMN/n_ma). To demonstrate that the particle number is not an appropriate dose metric in the special case of TiO₂, the data could have been presented in a single graph. I found that particle number is a suitable dose metric for differently prepared carbon nanoparticles (Wittmaack 2007). In their letter, Oberdörster et al. use the comparison between n_PMN and r_P,m to argue that "the choice of the response metric is irrelevant." Data analysis shows that in their study n_ma was essentially constant (10.9 ± 0.5) 10⁶. Hence, if n_PMN is divided by n_ma ≅ constant, on appropriate scales, the ratio r_P,m looks essentially the same as the n_PMN. Clearly, this result is not proof of the cited assertion.

Figure 2. Response of rats to the instillation of 250 nm TiO2 particles shown as the rP,m as reported by Oberdörster et al. in their letter, and the derived fP,mcorresponds to the linear fit through the rP,m data.

To explore this issue further, Figure 2 shows a direct comparison of r_P,m with the corresponding fractions f_P,m= n_PMN /(n_PMN + n_ma) = r_P,m /(1+r_P,m) for the 250-nm TiO₂ data, according to Oberdörster et al.'s letter. The solid line in Figure 2, derived by linear regression analysis of the r_P,m data, agrees well with previous results (Wittmaack 2007). Further evaluation provided the clue to the issue in question. By converting the r_P,m regression data to fractions f_P,m, I obtained the curve (dashed line), which is clearly nonlinear. Hence, using the f_P,m approach, Oberdörster (2000) converted an existing linear dose–response relationship (for n_PMN or r_P,m) artificially to a dependence that feigns the onset of saturation effects. Therefore, the choice of the response metric is not irrelevant.

Preparing Figure 1 of their letter, Stoeger et al. changed from the right (n_PMN) (Stoeger et al. 2006) to the wrong (f_P,m) response metric. For mice exposed to different types of carbon particles except for those with high carbon content (SootH), I derived from their Figure 1B rather high mean lung masses of 0.287 ± 0.047 g, and even higher values (0.469 ± 0.028 g) for the SootH-exposed animals. The ratio of these two masses (0.61) is the same as that of the ratio S_BET(SootH)/S_BET (SootL). This means that their data were erroneously permuted. Also, the f_P,m carbon particle data are poorly correlated with the original n_PMN data (Stoeger et al. 2006) because the numbers of "lavaged cells," presumably macrophages, derived from the n_PMN and f_P,m data, differ vastly (i.e., between about 2 10⁵ and 3 10⁶. Hence, either the f_P,m data in the letter of Stoeger et al. were miscalculated, or n_ma exhibited a biologically unreasonable spread. Furthermore, they include 15 response data for carbon in their letter, but the linear dose–response region contains only 13 (Wittmaack 2007).

In their effort to show that the surface area constitutes a proper all-particle dose metric, Stoeger et al. (2006) discredited their own transmission electron microscopy analysis. Their argument is irrelevant because the spark-generated particles contributed only one data point to a total of 13. Finally, Stoeger et al. do not accept one of the most important points of my article: Carbon particles of different origin exhibit large differences in surface toxicity and, therefore, they cannot be used to identify the best dose metric. Moreover, combining TiO₂ and carbon data in one graph is not an appropriate comparison.

The author declares he has no competing financial interests.

References

Gwinn MR, Vallyathan V. 2006. Nanoparticles: health effects—pros and cons. Environ Health Perspect 114:1818–1825.

Kreyling WG, Semmler-Behnke, Möller W. 2006. Health implications of nanoparticles. J Nanoparticle Res 8:534–562.

Nel A, Xia T, Mädler L, Li N. 2006. Toxic potential of materials at the nanolevel. Science 311: 622–627.

Oberdörster G. 2000. Toxicology of ultrafine particles: in vivo studies. Phil Trans R Soc Lond A358:2719–2740.

Oberdörster G, Oberdörster E, Oberdörster J. 2005. Nanotoxicology: an emerging discipline evolving from studies of ultrafine particles. Environ Health Perspect 113:823–839.

Stoeger T, Reinhard C, Takenaka S, Schroeppel A, Karg E, Ritter B, et al. 2006. Instillation of six different ultrafine carbon particles indicates a surface area threshold dose for acute lung inflammation in mice. Environ Health Perspect 114:328–333.

Wittmaack K. 2002. Advanced evaluation of size-differential distributions of aerosol particles. J Aerosol Sci 33:1009–1025.

Wittmaack K. 2007. In search of the most relevant parameter for quantifying lung inflammatory response to nanoparticle exposure: particle number, surface area, or what? Environ Health Perspect 115:187–194; doi:10.1289/ehp.9254 [Online 3 October 2006].