OR WAIT 15 SECS
The evaluation of the oral uptake of engineered nanoparticles (ENPs) contained in personal care products like mouthwashes is of great relevance to estimate the potential hazards and the toxicity of engineered nanomaterials (ENMs). Various experiments were performed while two commercially available mouthwash products (named M1 and M2) were selected as samples of interest. Asymmetric flow field‑flow fractionation (AF4) was chosen and optimized as the particle separation technique and two detectors were on-line coupled while dynamic light scattering (DLS) was used for evaluation and signals obtained by ultraviolet–visible (UV–vis) detection at 254 nm were used to gather additional information about the fate of the ENPs.
Petra Krystek1, Markus J. Spallek, Thorsten Klein2, and Jacob de Boer1, 1Institute for Environmental Studies (IVM), VU University, Amsterdam, The Netherlands, 2Postnova Analytics, Landsberg am Lech, Germany
The evaluation of the oral uptake of engineered nanoparticles (ENPs) contained in personal care products like mouthwashes is of great relevance to estimate the potential hazards and the toxicity of engineered nanomaterials (ENMs). Various experiments were performed while two commercially available mouthwash products (named M1 and M2) were selected as samples of interest. Asymmetric flow fieldâflow fractionation (AF4) was chosen and optimized as the particle separation technique and two detectors were on-line coupled while dynamic light scattering (DLS) was used for evaluation and signals obtained by ultraviolet–visible (UV–vis) detection at 254 nm were used to gather additional information about the fate of the ENPs.
In a rapidly increasing number of modern personal care and health products, engineered nanomaterials (ENMs) are used to improve their properties and gain specific effects. Nanomaterials are defined as natural, incidental, or manufactured material containing particles, in an unbound state or as an aggregate or agglomerate and where, for 50% or more of the particles in the number size distribution, one or more external dimensions is in the size range between 1 and 100 nm (1). In the case of engineered nanoparticles (ENPs), three dimensions must be in the nano-range. Since there is only limited information about the nanoscaled content of the products, it is crucial to gather more insights in the human exposure processes and effectively manage potential human health hazards of these materials (2,3). In addition, products like cosmetics, food and feed have to be labelled for containing ENMs according to European regulations (4–6). Direct oral uptake of ENMs and ENPs can occur during the ingestion of food or during the use of oral care products, for example. The fate of the ENPs is addressed in the first instance of contact with human saliva.
In commercially available oral care products like toothpaste and mouthwashes, the addition of ENPs is intended to either support the cleaning or help repair as well as enhance the remineralization process of teeth. Titanium dioxide (TiO2) ENPs are used for cleaning and whiting purposes. For biomimetic approaches, ENMs have been developed for inclusion in a variety of oral healthcare products. Complex particles like hydroxyapatites are applied for remineralization (7) and on the bacterial adherence in situ (8,9). Repair of demineralized enamel structures is said to be improved by nano-apatite particles fitting to the size of the nano-sized teeth defects and corresponding to the scale of the smallest building unit of enamel (8). Next to the described complex inorganic ENPs made of nanoâhydroxyapatites, more simple-structured inorganic ENPs also get more relevant in novel oral care products. Their potential is already shown by pilot studies before introduction into the market. In particular, the modification of different zinc (Zn) salts and its derivatives with new formulations are useful to control oral plaque and gingival bleeding (10).
Orally ingested ENPs are exposed to continuously changing environmental conditions, while transiting through the gastrointestinal (GI) tract, which influences the characteristics of the ENPs. Digestion methods typically include the oral, gastric, and small intestinal phases, and occasionally large intestinal fermentation. These methods try to mimic physiological conditions in vivo, taking into account the presence of digestive enzymes and their concentrations, pH, digestion time, and salt concentrations, among other factors (11). Several in vivo oral studies have been performed for evaluating the uptake of foodârelevant ENPs such as silica and TiO2 (12).
Saliva is the first medium of contact in the mouth and this medium has the crucial potential to change the physicochemical properties of ENMs and ENPs contained in food or oral consumer products. The contact time with saliva is normally between a few seconds up to a few minutes and it initiates digestion. Saliva is composed of a variety of electrolytes including sodium, potassium, calcium, and magnesium cations as well as bicarbonate and phosphates anions. Immunoglobulins, proteins, enzymes, mucins, and nitrogenous products such as urea and ammonia also occur in saliva. These components interact in related multiple essential functions in the following general areas:
An analytical platform tool needs to be established to obtain more details about the abundance and stability of ENPs in oral exposure experiments. Determination in hyphenation to on-line size-dependent particle separation by asymmetric flow field-flow fractionation (AF4) represents the state-of-the-art technology. Recently, methods for the identification and quantification of ENPs were developed; AF4 on-line coupled to inductively coupled plasma–mass spectrometry (ICP-MS) is applied for quantification of metallic ENPs (14–16). But also other field-flow fractionation types and hyphenations with detection methods like ultraviolet–visible (UV–vis) and dynamic light scattering (DLS) were tested for other applications such as protein identification (17–19). To the best of our knowledge, only one publication has dealt with the oral care nanoproduct characterizations, but did not study the interaction with saliva after oral uptake for gathering more information about the potential hazard of human oral exposure (20).
Within this study, two experimental scenarios with commercially available mouthwashes (M1 and M2) are investigated in relation to the product characterization and the human oral exposure with a special focus on the time-dependent interaction with saliva via state-of-the-art AF4 coupled to multiple detector systems.
Material and Methods
Oral Care Products and Sample Materials: The following two commercially available mouthwashes were used:
Human saliva from one healthy volunteer and ingested mouthwash–saliva mixtures were analyzed; for details see the “Experiments” section.
Chemicals and Consumables: Ultrapure water (H2O) with a resistivity of >18 MΩ·cm was obtained from a Milli-Q Plus system (Millipore). The detergent NovaChem100 was purchased from Postnova Analytics. Glass wool from Carl Roth GmbH & Co. KG, was used as the filtration medium.
Instrumentation: Both mouthwash products (M1 and M2) as well as the ingested mouthwash–saliva mixtures were analyzed with a Postnova AF2000 system (Postnova Analytics) consisting of an AF4 module for particle size separation coupled to an UV–vis detector (PN3211) and a DLS detector equipped with a quartz-flow cell (Malvern Zetasiser Nano ZS instrument from Malvern Instrument). The instrumental settings of the AF4 and the developed method are given in Tables 1 and 2. A 0.2% NovaChem (aq.) solution was chosen as the carrier liquid. The method is built from the following steps: The initial focus step provides enough time and cross-flow strength for the sample to reach the relaxation equilibrium. The elution step gives the start point of sample elution followed by the programmed cross-flow decay. A custom build field-flow fractionation method was used featuring a sigmoidal (S-shaped) cross-flow decay to ensure sample relaxation in the beginning (smooth elution) combined with an exponential decay to fasten sample elution in the late steps of analysis. A constant detector flow rate of 0.5 mL/min was optimal. Between samples a rinse step with eluent was applied.
The AF4 system was coupled on-line to a UV–vis detector, which was used for the identification of nanoparticles by monitoring the absorbance at a wavelength of 254 nm. Afterwards the particle size was determined by on-line DLS in the flow stream equipped with a special quartz flow cell. The signals were detected at a backscattering angle of 173° and obtained as hydrodynamic radius of spherical particles. The analysis was performed by AF4–UV–vis–DLS as described above.
Two series of experiments were performed as follows:
For the identification of ENPs in mouthwashes, two commercially available mouthwash products (M1 and M2) were analyzed. Clear product solutions were directly injected, and turbid products solutions from M2 were filtered before injection. In this case, a representative sample of the original mouthwash 5 mL was diluted 1:10 (v/v) respectively 1:100 (v/v) with 0.2% NovaChem (v/v) and filtrated (glass wool) before injection and AF4–UV–vis–DLS analysis.
For investigating the behaviour of ENPs from mouthwash in contact with saliva, 5 mL of mouthwash product (confirmed to contain ENPs by experiment A) was used. The healthy volunteer performed different mouth flush time experiments, each one conducted once a day in the morning:
The mouthwash–saliva mixture was collected and the volume was recorded.
Results and Discussion
For the identification of abundant ENPs in complex oral care products and for studying the possible oral exposure to ENPs, AF4 coupled to UV–vis and DLS detection proved to be suitable. Two experimental scenarios with commercial mouthwashes were investigated in relation to the product characterization and to the human oral exposure with a special focus on the time-dependent interaction with saliva. Within this study, only commercially available products and no self-designed mixtures of mouthwashes were used to emphasize the practice relevance. For each experimental series, the results are presented and discussed in detail.
Experiment A: Nanoparticles in Two Commercially Available Mouthwashes M1 and M2: Two commercially available mouthwashes were selected and the identification of ENPs was investigated by AF4–UV–vis–DLS. The M1 mouthwash product was analyzed directly with no abundant particle fraction being identified that was larger than the cutoff of the AF4 membrane (10 kDa). In the second - the so-called biomimetic mouthwash (M2) - lots of particles were present. Therefore, sample pretreatment and different dilution factors for the particle size determination were evaluated more closely. The obtained results for the dilution 1:100 are given in Table 3. The determined particle size range of M2 (34–101 nm) is in agreement with measurements by batch DLS in a dilution of 1:10 (20), and it covers the size range of the classification of ENMs (1).
In the biomimetic mouthwash (M2), the ENPs of interest are complex structured nano-hydroxyapatites (Ca10(PO4)6(OH)2 with zinc carbonate (ZnCO3). Although the product group of mouthwashes was already intensively tested by consumer organizations, the characterization of the products was only related to the concentration of fluoride, ethanol, and pH (23). Up to now, the content and the characteristics of possible ENMs was never a test criterion. We do, however, recommend to extend the list by this parameter.
Experiment B: Particle Fractions in Mouthwash–Saliva Mixtures After Rinsing the Mouth for Different Periods of Time: The findings of the time-dependent study of mouthwash and saliva are based on the use of AF4–UV–vis–DLS instrumentation. All results are given in Table 3, while the fractograms obtained by AF4–UV–vis and AF4–DLS are shown in Figure 1. All fractograms show the ENP species and remaining ENPs of the mouthwash before and after use (see Figure 1). It is shown that after using the mouthwashes, ENPs stayed in the mouth and were not spat out completely (see Table 3). All obtained results are further evaluated regarding to particle size ranges and particle abundance.
The unused, biomimetic mouthwash M2 shows ENPs with a size range of 34–101 nm; no ENPs were detected in the pure saliva reference sample.
By contact with saliva, agglomeration of ENPs was observed because the measured particle sizes are larger than in the original mouthwash; especially in the experiment with 30 s (see Table 3). During a longer period (1 and 3 min) in the oral phase, further mechanical mastication and salivation led to less agglomeration. The ENPs from the mouthwash product became agglomerated over time. Although the average particle diameter after 1 min of flushing (retention time: 32–57 min) was comparable to the original mouthwash, fewer small primary particle species were detected first (retention time: 32–48 min). In particular, a slight increase in particle size along prolonged flushing was detected (approximately 10 nm). The overall UV response was decreasing over time, which indicates a loss of particles, and after 3 min of rinsing the UV signal became more comparable to the pure saliva sample as to the original biomimetic mouthwash (M2). About 40% of the ENPs were detected after 1 min and only 3% after 3 min of flushing compared to the original mouthwash comparing either UV signal or DLS intensity (see Figure 1). Therefore, prolonged contact with saliva led to increasing agglomeration products remaining in the mouth region. In case the particle–saliva products reached the filtration limit of the glass wool used, a lower particle content might be observed. However, strong interaction between ENPs and saliva was responsible for increasing particle sizes and lowering of the overall UV response over time. The investigations indicate that after 3 min of flushing 97% of the ENPs stayed in the mouth. These results are relevant for further investigation about the behaviour of deposed nano-apatite ENPs in, for example, complete digestion models and in the following phase of the GI tract.
UV–vis detection at 254 nm was used for detection of proteinogenic compounds of saliva as a non-compound-specific signal and the results were compared to the measured particle size obtained by DLS. The UV trace showed a similar trend compared to DLS (see Figure 1). ENPs were not detected in the pure (reference) saliva, while proteinogenic compounds were eluted in the first steps of analysis (10–35 min); see Figure 1.
With the investigations performed in this study, relevant approaches for the identification of ENPs in commercially available mouthwashes and in saliva were explored. Relevant insights in the particle size stability and the interpretation of uptake scenarios of ENPs during oral exposure are obtained, which explains time-dependent uptake results. The great influence of saliva as the first contact medium in the complete digestion process of ENPs was successfully illustrated for a mouthwash product.
The presented examples show great advantages of the on-line hyphenation of AF4 to DLS and UV–vis detection. The timeâdependent presence of various sized ENPs in saliva has been addressed. In the case of complex biomimetic mouthwashes, for the elemental and structural identification of ENPs in relevant care products, also other off-line analytical techniques, such as transmission electron microscopy (TEM) or X-ray diffraction (XRD) are necessary, which can only be applied as off-line techniques. The on-line characterization of ENPs associated with the first contact medium (saliva) represents a facile approach without the need for time-consuming sample pre-treatment. It offers a better identification of the abundance of ENPs in the oral phase of digestion and enables exposure assessments from personal care and food products.
Altogether, the preliminary examples confirm the future relevance of our developed analytical approach for the analysis of commercially available mouthwashes.
This work is partly funded by NanoNext.nl, a micro- and nanotechnology consortium of the Dutch Government and 130 partners. The authors declare that they have no competing interests.
Petra Krystek was formerly with Philips Innovation Services in Eindhoven, The Netherlands and is with the Institute for Environmental Studies (IVM) at VU University in Amsterdam, The Netherlands.
Markus J. Spallek was formerly with Postnova Analytics in Landsberg am Lech, Germany.
Thorsten Klein is with Postnova Analytics.
Jacob de Boer is with the Institute for Environmental Studies (IVM) at VU University.