Method Development for the Quantitative Analysis of Multivitamin Supplements by Laser Ablation– Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS)

doi:10.21203/rs.3.rs-1638944/v1

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Method Development for the Quantitative Analysis of Multivitamin Supplements by Laser Ablation– Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS)

https://doi.org/10.21203/rs.3.rs-1638944/v1

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We present the development and optimization of an analytical method based on Laser Ablation–Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS) for the analysis of multivitamin dietary supplements. Samples were ground and mixed with a cellulose powder containing internal standard elements; the resulting powder was pressed into pellets. Two calibration strategies were compared: (1) using increasing mass fractions of cellulose powder fortified with multiple elements of interest, and (2) matrix matching using a multivitamin reference material in addition to the multi-element cellulose powder. Laser and ICP-MS parameters were closely monitored to produce the best signal while reducing the variability between replicate measurements. An energy output of 0.5 J/cm², a repetition rate of 30 Hz, and a He carrier gas flow rate of 800 mL/min provided the best compromise between sensitivity and reproducibility. These parameters produced the most similar ablation behavior between cellulose and a matrix-matched calibration strategy. The dissimilarities in ablation yield due to differences in focal points were successfully corrected after normalizing to an internal standard, resulting in relative differences of less than 10%. The results from the two different calibration approaches were compared to those obtained from solution ICP-MS and Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) analyses. For most multivitamins, both calibration methods (i.e., cellulose and matrix-matched calibrations) performed adequately for As, B, Co, Cr, Cu, Mg, Ni, Na, Pb, and Zn. Matrix-matched calibration additionally resulted in better recoveries for S and Fe. Overall, matrix-matched calibration resulted in better recoveries for more multivitamins in comparison with cellulose calibration.

LA-ICP-MS

multivitamins

quantitative analysis

calibration

Multivitamins are consumed for a wide assortment of reasons such as to compensate for diets or eating habits that limit the intake of essential vitamins and nutrients. The National Center for Health Statistics reported that among U.S. adults aged 20 and over, 57.6% used any dietary supplement in the past 30 days, with multivitamin-minerals being the most commonly used supplement (Mishra et al., 2021). It is estimated that one-third of all adults in the United States, and one-quarter of children and adolescents consume multivitamins.(Cowan et al., 2018; Qato et al., 2018) Additionally, most pregnant women take multivitamins as a source of folic acid, iron, iodine, and vitamin D. (Wong et al., 2019)

Research has shown that several mineral components are beneficial and necessary for the wellbeing of individuals (National Academies, 2019). For example, iron is needed for growth and development, in the production of hemoglobin, and to make essential hormones. However, high levels of iron can cause an upset stomach, constipation, nausea, abdominal pain, vomiting, and fainting (National Institutes of Health, 2021). Trace elements can also impact human health. Chromium, copper, zinc, selenium, iodine, and molybdenum are among the nutritional elements; toxic elements include arsenic, cadmium, lead, and mercury (Mehri, 2020).

Monitoring nutritional and toxic elements in food, cosmetics, and multivitamins is part of the Food and Drug Administration’s (FDA) mission to protect and promote public health. The companies selling these products are responsible to ensure that the labels meet all the requirements, including the accuracy of nutrient declarations. To assist in verifying that the nutrient contents are accurately listed, there is a great interest in methods that ensure that the labels for multivitamins are reflective of the actual contents of the product.

Determination of the elemental composition of foods and multivitamins typically involves acid decomposition followed by analysis using Inductively Coupled Plasma – Mass Spectrometry (ICP-MS) and/or Optical Emission Spectroscopy (ICP-OES) (Canbay & Doğantürk, 2017; Cubadda, 2004; Dolan et al., 2003; Kauffman et al., 2007; Krejčová et al., 2006; Marrero et al., 2013). Additionally, square wave anodic stripping voltammetry, neutron activation analysis, flame graphite furnace atomic absorption spectroscopy, and electrothermal atomic absorption spectrometry, among others, have been reported (Hight et al., 1993; Reis & Saiki, 2009; Soltyk et al., 2003; Turk et al., 2013). Solution-based methods of analysis of multivitamin supplements require decomposition of the materials using perchloric, hydrofluoric, hydrochloric, and/or nitric acid followed by dilution of the samples. Such methods invariably involve extensive sample preparation, handling of toxic substances, and are time consuming and labor intensive. A review article published in 2011 describes the use of atomic spectroscopy in the pharmaceutical industry (Lewen, 2011).

Direct analysis of solids by Laser Ablation–Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS) is widely accepted and constitutes a powerful analytical tool for numerous types of materials (Becker, 2002; Gunther & Hattendorf, 2005; Koch & Gunther, 2011; Limbeck et al., 2015; Russo et al., 2002). Some benefits of LA-ICP-MS for food and supplement analysis include a smaller amount of sample required, fast sample exchange and high throughput, minimal carryover in comparison with liquid sample introduction, reduction of contamination and analyte loss that would otherwise occur during acid digestion, and minimal sample preparation requirements (Russo et al., 2002). One drawback of solid analysis by LA-ICP-MS is elemental fractionation, where the isotope or elemental ratio detected may not be entirely representative of the composition of the original sample (Limbeck et al., 2015). In terms of ablation behavior, elements fall into several distinct clusters in which they correlate well with each other during the ablation period; therefore, an element from the same cluster can be used as an internal reference for the rest of the elements in the same group, thus mitigating the quantitative discrepancies that result from fractionation (Longerich et al., 1996). A second drawback of LA-ICP-MS is the dissimilarity in the interaction between the laser beam and the sample surface observed with different matrices. This effect causes changes in the ablated mass in relation to the properties of the matrices in question (Kroslakova & Günther, 2007). A promising approach for quantification is the preparation of matrix-matched calibration standards using materials with the same matrix composition as the samples (Fitzpatrick et al., 2008; Miliszkiewicz et al., 2015; Perkins et al., 1991; Shaheen & Fryer, 2011; Sinclair et al., 1998; Vanheuzen & Morsink, 1991; Zhu et al., 2013).

Analytical methods of pharmaceuticals and multivitamin supplements by LA-ICP-MS is limited, especially studies in which solution and laser ablation ICP-MS complementary results are reported. The scarcity of laser ablation studies is mostly due to the lack of reference materials and matrix-matched calibration standards; only a few studies are available (Augusto et al., 2017; Bu et al., 2013; Lam & Salin, 2004; Rudovica et al., 2014). Augusto et al. described the use of cellulose as a binder for creating pellets followed by LA-ICP-MS determination of nutrients and contaminants in food and supplements (Augusto et al., 2017). Bu et al. reported the analysis of six herbal products by LA and solution-based ICP-MS using the National Institute of Standards and Technology (NIST) Standard Reference Material (SRM®) 1573a (tomato leaf) as a one-point calibrant (Bu et al., 2013). Lam and Salin described the analysis of pharmaceutical tablets (10% and 20% Neusilin) by LA-ICP-MS and Laser Ablation–Inductively Coupled Plasma–Atomic Emission Spectroscopy (LA-ICP-AES) using a three point calibration made of Neusilin at different concentrations (Lam & Salin, 2004). Rudovika et al. reported the LA-ICP-MS analysis of elemental impurities in an active pharmaceutical ingredient using laboratory-made matrix calibration standards for quantification by adding inorganic salts at certain concentrations to the main pharmaceutical ingredient (Rudovica et al., 2014).

In this work, the development and optimization of an analytical method based on LA-ICP-MS that can be applied specifically to multivitamins is presented. The technique offers quick and automated sample analysis without the use of corrosive acids and extensive sample preparation. This method is especially useful for products such as multivitamin tablets which are resistant to nitric acid digestion and require the use of hydrofluoric and/or perchloric acids. The developed method aims to reduce the effects of fractionation and differences in ablation yields between different materials by creating a matrix-matched calibration and by normalization to an internal standard added to the samples.

3.1 Sample preparation

Cellulose multielement and internal standard powders were prepared by mixing a multielement stock solution with a particle size ≤ 20 µm cellulose binder (3642, Spex, Metuchen, NJ). The multielement stock solution concentrations are represented in Table S 1 (left); this solution was prepared using 1,000 and 10,000 µg/mL single element ICP-MS standards (Inorganic Ventures, Christiansburg, VA) diluted to 1 L with 1% nitric acid. The stock was then mixed with the cellulose powder and stirred for at least 1 hour, filtered using vacuum filtration and dried in an oven at 60°C until most of the moisture evaporated. The resulting material was ground into a fine powder (i.e., approximately 20 µm, D50) using a knife mill (GM 300, Retsch, Haan, NRW, Germany). The multielement standard powder was further characterized by two solution ICP-MS instruments and ICP-OES to determine the final concentration of each element in the powder, shown in Table S 1 (right). The internal standard solution stock consisted of a solution of 5 µg/mL of Bi, Ge, Ir, Rh, Sc, and 10 µg/mL of Te and the internal standard powder material was prepared in the same way as the multielement powder.

The cellulose calibration standards were prepared by mixing the multielement cellulose powder at increasing mass fractions with 2 g of internal standard and cellulose blank for a total mass of 4 g. The calibrants consisted of five to six standards with concentrations ranging from zero to up to 4 mg/kg for the trace elements (i.e., As, Cr, Co, Ni, Pb), and from zero to up to 70 mg/kg for the major elements (i.e., B, Cu, Fe, Mg, Na, S and Zn). The matrix-matched calibration standards were prepared by mixing the multielement cellulose powder at increasing concentrations with 1 g of multivitamin reference material VITA-1 (National Research Council NRC, Canada), 2 g of internal standard and cellulose for a total mass of 4 g. The concentrations of the matrix-matched calibration standards ranged from zero to approximately 2 mg/kg in the pellets, for the trace elements. The concentrations of the major elements were predominantly those present in the VITA-1 reference material. The addition of the multivitamin reference material, which was created to mimic the composition of multivitamins tablets, aimed to create calibration standards that matched the matrix of the unknown multivitamin samples.

Twelve multivitamins were locally purchased from retail stores; the list included the typical variety available to the public (i.e., general multivitamins for adults, iron-free and iron-rich, for age 50+, and for men or women). Most multivitamins were tablets, and one was in the form of capsules. The twelve multivitamins were ground and mixed with 2 g of internal standard.

All samples and standards were separately ground using disposable grinding chambers (IKA, Wilmington, NC, USA) at 15,000 RPM for 3 minutes. A mass of approximately 300 mg from each homogenized sample was pressed into 13 mm by 1 mm pellets at 10 ton for 30 second using a pellet press (3613 13 mm pellet die set and 3635 X-Press, Spex Sample Prep, Metuchen, NJ, USA). The pellets were stored in a vacuum oven at approximately 40°C prior to analysis to limit the absorption of moisture from the air.

The multivitamins, reference materials, and cellulose powders were analyzed by solution ICP-MS and ICP-OES following microwave digestion. Digestion was performed according to the method in FDA’s Elemental Analysis Manual (EAM) Section 4.7 (Gray et al., 2020) using the ultraWAVE microwave digestion system (Milestone, Shelton, CT, USA) by adding 5 mL of concentrated nitric acid and 1 mL of hydrogen peroxide to PTFE digestion vessels containing 250 mg-500 mg of sample. The digests were diluted to 50 mL resulting in a final acid concentration of 5% nitric acid and 0.5% hydrochloric acid. Additional dilutions were required prior to ICP-MS and ICP-OES analyses (i.e., 5-times for trace elements and 500-times for the major elements).

VITA-1 and VITB-1 (NRC, Canada), and NIST SRM 3280 (NIST, Gaithersburg, MD, USA) were used as reference materials. These materials served as quality control for solution and LA-ICP-MS analyses, and for the creation of matrix-matched calibration standards (VITA-1). Although NIST SRM 3280 is no longer available, NIST SRM 3294 Multielement Tablets can be purchased instead.

3.2 Instrumentation

The pellets were ablated and analyzed using a 193 nm excimer-based laser ablation system (NWR193, Elemental Scientific Lasers LLC, Bozeman, MT, USA) coupled to an ICP-MS instrument (iCap Q, Thermo Fisher Scientific, Waltham, MA, USA). The laser system was equipped with a small volume self-seal chamber. The ablated material was transported using helium at 800 mL/min. The carrier gas was then mixed with nitrogen at 5 mL/min and argon at 400 mL/min. The sample was finally introduced to the ICP-MS using a signal smoothing mixing chamber (NWR193, Elemental Scientific Lasers LLC, Bozeman, MT). The analysis was performed in kinetic energy discrimination (KED) mode using 4.8 mL/min He as collision gas to minimize interferences. Table 1 describes the optimized parameters for LA-ICP-MS analysis. A 60 seconds “gas blank” (no ablation) and five 3-mm long ablation lines were performed on each pellet.

Table 1

Optimized parameters for LA-ICP-MS analysis
Instrumental Parameter	Optimized Value
Fluence	0.50 J/cm²
Frequency	30 Hz
Scan speed	50 µm/s
Spot size	150 µm
Carrier gas flow, He	800 mL/min
Makeup gas flow, Ar	400 mL/min
Additional gas, N₂	5 mL/min
RF power	1550 W
Dwell time	10 ms – 50 ms
KED mode	He, 4.8 mL/min
Analytes monitored	⁷⁵As, ¹¹B, ²⁰⁹Bi, ¹³C, ⁵³Cr, ⁵⁹Co, ^{63, 65}Cu, ^{56, 57}Fe, ⁷⁴Ge, ¹⁹³Ir, ^{24, 26}Mg, ²³Na, ⁶⁰Ni, ^{206, 207, 208}Pb,¹⁰³Rh, ^{32, 34}S, ⁴⁵Sc, ¹²⁵Te, ⁶⁶Zn

The solution ICP-MS analyses were performed using Agilent 8800 (Agilent, Santa Clara, CA) and Element 2 (Thermo Scientific, Waltham, MA) systems. The sample was introduced to the quadrupole ICP-MS using 0.762 mm inner diameter PVC peristaltic pump tubing at 6 rpm. The solution was aspirated using a MicroMist nebulizer into a Peltier-chilled Scott double-pass spray chamber (Glass Expansion, Port Melbourne, Victoria, Australia). Helium was used as the collision gas and oxygen as the reaction gas for selected isotopes (i.e., As and S), to mass-shift the analyte away from polyatomic interferences. Sample was introduced to the magnetic sector ICP-MS using a 0.762 mm inner diameter PVC peristaltic pump tubing at 3 rpm. The sample was aspirated using a MicroMist nebulizer into a Peltier-chilled cyclonic spray chamber (Elemental Scientific Inc, Omaha, NE, USA). For both ICP-MS analyses, the internal standard solution (¹⁰³Rh) was mixed with the sample using 0.762 mm inner diameter PVC peristaltic pump tubing and a T-connector resulting in a 1:1 sample-to-internal standard ratio. The concentration of internal standard solution was approximately 2.5 ng/g Rh for the Agilent 8800 analyses and 2 ng/g Rh for the Element HR-ICP-MS analyses.

ICP-OES analyses were performed using the Agilent 5900 (Agilent Technologies, Inc., Santa Clara, CA) system. Samples were introduced into the plasma using 1.03 mm inner diameter PVC peristaltic pump tubing at 12 rpm. Sample solution was aspirated into a double-pass glass cyclonic spray chamber (Agilent Technologies, Inc., Santa Clara, CA) using a concentric glass nebulizer (SeaSpray) prior to introduction into the plasma. Nitrogen was used as the polychromator purge gas. Sc II 361.383 nm and In I 325.609 nm were used as internal standards for the ionic and atomic lines, respectively. The concentration of internal standard solution was 2 µg/g for scandium and 20 µg/g for indium. The internal standard solution was mixed with the sample using 1.03 mm inner diameter PVC peristaltic pump tubing and a T-connector resulting in a 1:1 sample-to-internal standard ratio.

Concentration results from both ICP-MS instruments and from ICP-OES were combined, and the uncertainties propagated to find the concentration mean for all multivitamins. The recoveries from the multivitamin reference materials were used as quality controls for the digestion and for the ICP-MS and ICP-OES analyses. Additionally, Initial Calibration Verification standards (ICV) and Continuing Calibration Verification standards (CCV) were added to the analysis sequence every ten samples to monitor instrument drift and the performance of the calibration across the sampling sequence. Acceptable ICV and CCV recoveries were those in the range of 90–110%. Acceptable reference material recoveries were those in the range of 80–120%. The multivitamin digests were diluted by a factor of 5 and 500, for trace and major elements, respectively. In addition, dilution/additional gas downstream from the spray chamber was needed to reduce the total dissolved solid concentration in the ICP-MS sampling. Solution ICP-MS and ICP-OES parameters are summarized in Table 2.

Table 2

Instrumental parameters for the solution ICP-MS and ICP-OES analyses
Instrumental Parameter	Agilent 8800 ICP-MS	Element 2 HR-ICP-MS	Agilent 5900 ICP-OES
RF power	1550 W	1250 W	1200 W
Collision gas, flow	He, 4.8 mL/min	-	-
Reaction gas, flow	O₂, 28%	-	-
Carrier gas, flow	Ar, 0.7 L/min	Ar, 0.6 L/min	0.7 L/min
Additional/dilution gas	Ar, 0.5 L/min	Ar, 0.5 L/min	-
Sweeps/replicate	100	-	-
Replicates	9	-	3
Runs	-	3	-
Passes	-	5	-
Read time	-	-	5 s
Stabilization time	-	-	15 s
Analytes monitored	⁷⁵As, ¹¹B, ²⁰⁹Bi, ¹³C, ⁵³Cr, ⁵⁹Co, ^{63, 65}Cu, ^{56, 57}Fe, ⁷⁴Ge, ¹⁹³Ir, ^{24, 26}Mg, ²³Na, ⁶⁰Ni, ^{206, 207, 208}Pb,¹⁰³Rh, ^{32, 34}S, ⁴⁵Sc, ¹²⁵Te, ⁶⁶Zn		As I 188.980 nm^a, B I 249.678 nm^a, Co II 230.786 nm^a, Cr II 267.716 nm^a, Cu I 327.395 nm^a, Fe II 238.204 nm^a, Mg II 279.800 nm^r, Na I 589.592 nm^r, Ni II 216.555 nm^a, P I 213.618 nm^a, Pb II 220.353 nm^a, S 180.669 nm^a, Zn II 206.200 nm^a
^a Axial viewing ^r Radial viewing

3.3 Data processing

Following LA-ICP-MS analysis, the transient signal corresponding to the gas blank (no ablation) and five ablation lines was obtained using the ICP-MS data analysis software, Qtegra (Qtegra, Version 2.10.4345.64, Thermo Scientific, Waltham, MA). The acquired transient data was exported to .csv files and processed using a custom R script (R Core Team, 2021) (R version 1.3.959) and the R package “outliers” (Komsta, 2015). The script was responsible for removing spikes from the signal using the Grubbs’ test for outliers (at a significance, α = 0.0005), integrating the area for the signal and blank regions, and subtracting the area of the blank from the signal. The integrated signal and blank areas consisted of 50 seconds of analysis time. Area ratios were obtained by normalizing each element’s area by the internal standard (i.e., ¹³C, ²⁰⁹Bi, ¹⁹³Ir, ⁷⁴Ge, ¹⁰³Rh, ⁴⁵Sc, ¹²⁵Te). These ratios were averaged (n = 5) and plotted against the concentrations (ng/g) of the calibration standards in the pellets to create external calibration curves for each element. For elements present in the matrix-matching material (VITA-1) at high concentrations, a single-point calibration approach was applied instead using the highest calibration standard as the calibrant. The analytes calibrated using a single-point calibration were B, Cu, Fe, Mg, Na, S and Zn.

The analytes reported for laser ablation analyses were those without unavoidable polyatomic and isobaric interferences and with solution concentrations above the limits of detection. For this reason, cadmium, mercury, potassium, and calcium were not reported. Cadmium isotopes suffer interferences from molybdenum oxide polyatomics, which formed in the ICP from high Mo concentrations in most of the multivitamins (Begu et al., 2019). Mercury was not determined above limits of detection in the solution analyses; therefore, it could not be compared to the LA-ICP-MS concentrations. Potassium and calcium suffer interferences from argon (May & Wiedmeyer, 1998).

Different laser and ICP-MS parameters were closely monitored to produce the best signal while reducing the variability between replicate measurements (%RSD). Table 1 summarizes the optimized parameters for the analysis of multivitamins by LA-ICP-MS. Parameters optimized included laser energy (fluence), repetition rate (frequency), and flow rates of the carrier and makeup gasses. The final optimized parameters were used for the LA-ICP-MS analysis of the twelve multivitamins. Additionally, an experiment was conducted to determine the effect of differences in focal points between pellets on instrument signal.

4.1 Optimization of the instrumental parameters

The laser energy optimization was critical to minimize the differences in ablation between the cellulose and multivitamin pellets, thus reducing the impact of fractionation and matrix differences on the results. Figure 1 shows the intensity counts obtained after ablating at different energy outputs and the relative percent difference (RPD) between the cellulose and NIST SRM 3280 pellets, for rhodium. Both pellets contained 2 g of internal standard, therefore the concentration of rhodium in the pellets was the same. The same trend was observed for all the other internal standard elements. A fluence of 0.5 J/cm² was selected for future experiments as it provided a small relative difference between the materials in terms of ablation yield, while still resulting in acceptable sensitivity for most analytes.

The effect of laser repetition and He carrier gas flow rates were investigated to provide optimal sensitivity and lower repeatability between replicate measurements. Figure 2A shows the intensity counts at different repetition rates for lead (²⁰⁸Pb), as an example. A frequency of 30 Hz was selected for further analyses as it resulted in higher counts, adequate repeatability, and the removal of sufficient material for LA-ICP-MS accurate analyses for most of the elements monitored.

Figure 2B shows the intensity counts and relative standard deviation (RSD) obtained for lead at different flow rates. A flow rate of 800 mL/min of carrier helium gas was selected for further analyses as it provided higher counts and lower %RSD between the five replicates for most of the elements monitored.

4.2 Effect of differences in focal point

Integration of a carousel autosampler allowed for automated and unattended LA-ICP-MS analysis of the pellets. The pellets (13 mm diameter and 1 mm width) were inserted in 3D printed holders and placed on the carrousel wheel. The instrumental parameters for the analysis, including the z-position, or focal point, were initially set for the first sample in a sequence of up to 20 samples. The surface focal point varied slightly between pellets due to microscopic height differences of the sample holders and variations in pellet thickness due to the nature of the materials. Typically, the largest observed difference in focal point was 100 µm, meaning that the surface of the sample appeared to be out of focus in either the positive or negative “z” directions by up to 100 µm. An experiment was designed to assess the effect of these focal point differences in the resulting signals.

The experiment consisted of 11 ablation lines on a multielement cellulose pellet where the focal point was adjusted by lowering or raising the laser stage. The center line (i.e., 0 µm), was ablated at the best possible image focus on the surface of the pellet. The rest of the lines were ablated 20, 40, 60, 80 and 100 µm away from the focal point in both positive and negative “z” directions; for example, lines 5 and 7 were ablated at -20 and + 20 µm away from the focal point, respectively. The intensity counts for each line were plotted for all elements before and after normalization to another element already present in the sample.

Figure 3 shows the results of the focusing experiment for lead before and after signal normalization. The graph shows the relative percent difference (RPD) of the intensities with respect to the center focal point (zero µm out of focus) after lowering and raising the stage from − 100 to + 100 µm. Although the resulting signals varied considerably as the surface of the sample moved away from the center focal point, the dissimilarities in ablation yield were successfully corrected after normalizing to the internal standard element (¹⁰³Rh), resulting in RPD of less than 10%.

4.3 LA-ICP-MS quantitative analysis of multivitamins

4.3.1 Internal standard selection

To select the most suitable internal standard for each analyte, seven isotopes were monitored: ¹³C, ²⁰⁹Bi, ⁷⁴Ge, ¹⁹³Ir, ¹⁰³Rh, ⁴⁵Sc, and ¹²⁵Te. Figure 4 shows the experimentally determined and certified concentrations for arsenic in pellets from reference materials VITB-1 and NIST SRM 3280 after normalization to the different internal standards, and without internal standard normalization. In this case, tellurium was selected as the best internal standard for arsenic for the analysis of multivitamins as it resulted in the highest accuracy for both the reference materials as well as in commercial multivitamins. Similar to arsenic in Fig. 4, the selection of the internal standard for all the other analytes was accomplished by monitoring the recovery of the certified reference materials (and of the multivitamins in comparison to solution results) with each internal standard. The selection of the appropriate internal standard is essential to accurately quantify the elements in the samples.

The use of internal standards was critical to mitigate the differences in ablation yield between the multivitamins and the calibration standards, to correct for focal differences between the different samples, and to compensate for variability in the signal intensity caused by the presence of matrix components and differences in ionization energies. The internal standard selection was dependent on the sample matrix; for example, in matrix-matched calibration, the best internal standard for lead was found to be rhodium, while carbon provided better recoveries for the reference materials and multivitamins when calibrating with cellulose. The internal standard elements used for each analyte, for both calibration strategies, are shown in Table 3.

4.3.2 Calibration and quantitative analysis

Different calibration strategies were explored for the analysis of multivitamins. Two calibration strategies were compared: (1) using increasing concentrations of cellulose powder fortified with multiple elements of interest, and (2) matrix matching using a multivitamin reference material in addition to the cellulose multi-element powder. External calibration was applied with either single or multiple calibrants, depending on the analyte’s concentration in the samples. In the cellulose calibration, the calibrants consisted of five to six standards with concentrations ranging from zero to up to 4 mg/kg for the trace elements, and from zero to up to 70 mg/kg for the major elements, such as magnesium. In the case of the matrix-matched calibration, the concentrations ranged from zero to approximately 2 mg/kg in the pellets for the trace elements. The two calibration ranges differed because of the amount of multielement powder added. In the case of the matrix-matched calibration the maximum amount of multielement powder that was added was 1 g, plus 1 g of VITA-1 and 2 g of internal standard for a total of 4 g. Concentrations of the major elements were predominantly those present in the VITA-1 reference material, which was used for creating the matrix-matched calibrants. Most of the major elements in the matrix-matched material were present at much higher concentrations than in the cellulose multielement powder; therefore, an external multiple-point calibration curve was not feasible. In these cases, a single point calibration approach was used instead. The analytes quantified with a single-point calibration included B, Cu, Fe, Mg, Na, S, and Zn.

Figure 5 shows the calibration curves for arsenic using cellulose (Fig. 5A) and matrix-matched calibration standards (Fig. 5B). The intensity ratios consist of the ratio of the analyte intensity to that of the internal standard element. The calibration curves were linear for all the monitored trace elements with both calibrations. The major elements that fell outside the calibration curves, or that were already present at high concentrations in the multivitamin matrix (VITA-1), were calibrated using a single-point calibration using the highest standard as calibrant, after internal standard correction.

Limits of detection (LOD) and quantitation (LOQ) were estimated from the analyses of cellulose “blanks” (i.e., cellulose powder mixed with 2 g of internal standard without any of the elements of interest added). The LOD were calculated as 3 times the standard deviation of the blanks and the LOQ were calculated as 10 times the standard deviation of the blanks and are summarized in Table 3. Ten cellulose blank pellets were used for the LOD and LOQ calculations.

Table 3

Limits of detection (LOD) and quantitation (LOQ) calculated as 3 times and 10 times the standard deviation of ten cellulose blanks, respectively, and internal standard used for each analyte
Analyte	LOD (mg/kg)	LOQ (mg/kg)	Internal Standard
As	0.010	0.035	Te
B	0.59	2.0	Te^a, C^b
Co	0.16	0.54	Rh^a, C^b
Cr	13	43	C^a, Ge^b
Cu	0.14	0.46	C^a, Ge^b
Fe	320	1100	Te
Mg	11	37	C
Na	5.4	18	C
Ni	1.2	3.9	Ge
Pb	0.0094	0.031	Rh^a, C^b
S	19	64	Te
Zn	4.7	16	C^a, Ge^b
^a Matrix-matched calibration ^b Cellulose calibration

For most multivitamins, both calibrations performed adequately for the following elements: As, B, Co, Cr, Cu, Mg, Na, Ni, Pb, and Zn. Figure 6 shows the LA-ICP-MS determined concentrations of arsenic in the twelve multivitamins for both calibrations, in comparison to the solution ICP results. Table 4 summarizes the LA-ICP-MS determined concentrations for all the analytes for the twelve multivitamins by the different calibration approaches in comparison to the solution results.

Matrix-matched calibration resulted in more accurate recoveries for S and Fe. This could be related to the fact that concentrations in the reference material matrix (VITA-1) were high for those elements, and therefore closer to the actual concentration in the samples. Overall, matrix-matched calibration resulted in better recoveries for more multivitamins in comparison to cellulose calibration. Matrix-matched calibration resulted in a recovery range (mean) for each element: 81–140% (112%) As, 80–129% (107%) B, 58–140% (81%) Co, 89–122% (103%) Cr, 71–114% (90%) Cu, 77–125% (102%) Mg, 86–141% (119%) Na, 86–116% (101%) Ni, 77–179% (114%) Pb, and 31–122% (93%) Zn, for the samples above LOQ. Matrix matched calibration additionally resulted in better recoveries for iron 53–121% (98%) vs. 21–59% (37%), with cellulose; and sulfur (88–167% (122%) vs. 47–80% (60%), with cellulose. Overall, matrix-matched calibration resulted in better recoveries for more multivitamins in comparison with cellulose calibration.

Table 4

Determined laser ablation and solution ICP concentrations (Average ± SD, mg/kg) for twelve multivitamins.
Analyte	Calibration^a	MV01	MV02	MV03	MV04	MV05	MV06	MV07	MV08	MV09	MV10	MV11	MV12
As	Matrix-Matched	0.12 ± 0.03	0.05 ± 0.01	0.07 ± 0.02	0.24 ± 0.05	0.15 ± 0.02	0.156 ± 0.008	0.15 ± 0.04	0.14 ± 0.02	0.13 ± 0.02	0.11 ± 0.01	0.10 ± 0.01	0.05 ± 0.01
	Cellulose	0.10 ± 0.02	0.041 ± 0.008	0.06 ± 0.01	0.18 ± 0.01	0.13 ± 0.02	0.15 ± 0.02	0.123 ± 0.006	0.116 ± 0.008	0.128 ± 0.009	0.09 ± 0.01	0.10 ± 0.02	0.054 ± 0.006
	Solution	0.15 ± 0.02	0.033 ± 0.006	0.062 ± 0.002	0.20 ± 0.01	0.150 ± 0.007	0.143 ± 0.009	0.130 ± 0.008	0.123 ± 0.007	0.130 ± 0.009	0.099 ± 0.005	0.08 ± 0.02	0.044 ± 0.007
B	Matrix-Matched	51 ± 7	1.3 ± 0.2*	1.2 ± 0.3*	164 ± 30	81 ± 7	119 ± 8	101 ± 30	151 ± 21	127 ± 17	92 ± 10	93 ± 9	12 ± 3
	Cellulose	47 ± 11	1.2 ± 0.2*	1.0 ± 0.2*	119 ± 9	75 ± 20	107 ± 17	93 ± 9	135 ± 8	118 ± 9	73 ± 10	85 ± 12	11 ± 1
	Solution	63 ± 1	0.09 ± 0.02	0.11 ± 0.04	127 ± 4	70 ± 1	117 ± 4	87 ± 1	159 ± 3	128 ± 1	85 ± 3	85 ± 1	10.8 ± 0.2
Co	Matrix-Matched	0.8 ± 0.3	1.8 ± 0.3	0.7 ± 0.2	1.2 ± 0.3	1.13 ± 0.08	0.8 ± 0.2	4.3 ± 0.3	2.1 ± 0.5	2.8 ± 0.3	2.2 ± 0.6	2 ± 1	1.1 ± 0.2
	Cellulose	1.0 ± 0.3	1.5 ± 0.2	0.6 ± 0.2	1.3 ± 0.3	1.4 ± 0.4	0.80 ± 0.09	4.6 ± 0.8	2.4 ± 0.6	3.4 ± 0.6	2.5 ± 0.7	0.82 ± 0.08	1.5 ± 0.4
	Solution	1.26 ± 0.04	3.1 ± 0.1	1.1 ± 0.1	1.77 ± 0.04	1.42 ± 0.05	1.22 ± 0.02	5.4 ± 0.1	2.24 ± 0.05	2.64 ± 0.06	2.45 ± 0.05	1.10 ± 0.03	1.70 ± 0.02
Cr	Matrix-Matched	44 ± 5	<LOD	<LOD	47 ± 7	58 ± 7	35 ± 2*	49 ± 2	43 ± 5*	44 ± 5	40 ± 4*	49 ± 7	54 ± 10
	Cellulose	38 ± 3*	<LOD	<LOD	38 ± 2*	54 ± 10	36 ± 4*	54 ± 3	38 ± 4*	52 ± 5	32 ± 5*	47 ± 7	59 ± 5
	Solution	42 ± 1	8.2 ± 0.3	0.66 ± 0.04	38 ± 1	53 ± 2	37 ± 1	55 ± 4	38 ± 1	48 ± 3	39 ± 1	48 ± 3	55 ± 2
Cu	Matrix-Matched	365 ± 106	3 ± 1	<LOD	291 ± 82	350 ± 93	729 ± 265	250 ± 81	374 ± 58	361 ± 53	461 ± 61	418 ± 64	6 ± 1
	Cellulose	328 ± 110	2.1 ± 0.5	<LOD	178 ± 24	338 ± 100	477 ± 165	400 ± 319	309 ± 41	311 ± 59	352 ± 24	371 ± 59	8 ± 2
	Solution	413 ± 9	4.5 ± 0.2	0.5 ± 0.2	361 ± 10	406 ± 16	638 ± 14	349 ± 9	401 ± 6	339 ± 9	444 ± 12	441 ± 17	7.9 ± 0.1
Fe	Matrix-Matched	7983 ± 2004	45097 ± 17181	<LOD	11252 ± 7070	<LOD	6872 ± 3697	<LOD	13805 ± 2452	5543 ± 1947	18193 ± 5328	<LOD	<LOD
	Cellulose	5258 ± 3013	9490 ± 2448	<LOD	4516 ± 3233	<LOD	1589 ± 170	<LOD	5374 ± 1945	2927 ± 2110	6970 ± 2642	<LOD	<LOD
	Solution	15020 ± 293	44276 ± 764	34 ± 6	13610 ± 251	65 ± 3	5687 ± 116	112 ± 26	13064 ± 145	4935 ± 89	16617 ± 306	61 ± 19	42 ± 9
Mg	Matrix-Matched	31208 ± 4057	589 ± 49	740 ± 110	90071 ± 8467	42576 ± 2512	70139 ± 3577	57029 ± 13003	70311 ± 4008	67693 ± 1218	45194 ± 1672	43413 ± 2388	548 ± 35
	Cellulose	33893 ± 6168	570 ± 52	762 ± 165	84003 ± 5544	45686 ± 9366	68557 ± 4251	54317 ± 3205	65459 ± 3535	73893 ± 4581	45377 ± 4039	47157 ± 7545	536 ± 33
	Solution	39889 ± 1677	769 ± 26	915 ± 48	71804 ± 2337	38580 ± 923	68190 ± 954	49266 ± 874	75994 ± 861	64182 ± 1646	42459 ± 1382	41489 ± 1044	447 ± 25
Na	Matrix-Matched	1915 ± 299	1989 ± 74	1171 ± 185	1561 ± 671	1680 ± 281	1719 ± 423	1653 ± 784	239 ± 29	435 ± 23	390 ± 51	528 ± 46	1446 ± 64
	Cellulose	1609 ± 177	1869 ± 101	974 ± 41	1768 ± 295	1811 ± 270	1513 ± 339	2402 ± 281	229 ± 13	441 ± 34	390 ± 20	520 ± 54	1438 ± 63
	Solution	1551 ± 24	2309 ± 49	870 ± 30	1434 ± 24	1329 ± 38	1460 ± 36	1491 ± 22	205 ± 4	327 ± 11	301 ± 5	373 ± 5	1435 ± 14
Ni	Matrix-Matched	2.6 ± 0.5*	2.2 ± 0.7*	<LOD	6.1 ± 0.7	1.8 ± 0.3*	3.6 ± 0.4*	1.9 ± 0.2*	3.8 ± 0.5*	3.9 ± 0.4*	3.3 ± 0.5*	2.1 ± 0.3*	<LOD
	Cellulose	2.8 ± 0.6*	1.4 ± 0.3*	<LOD	4.8 ± 0.9	1.9 ± 0.3*	3.8 ± 0.6*	2.2 ± 0.2*	3.9 ± 0.5*	4.3 ± 0.4	2.7 ± 0.5*	2.3 ± 0.5*	<LOD
	Solution	4.1 ± 0.3	6.0 ± 0.3	0.5 ± 0.1	5.3 ± 0.3	1.8 ± 0.1	3.0 ± 0.2	1.8 ± 0.2	5.3 ± 0.1	4.5 ± 0.2	4.8 ± 0.3	3.2 ± 0.1	0.8 ± 0.1
Pb	Matrix-Matched	0.17 ± 0.05	0.09 ± 0.02	0.08 ± 0.02	0.13 ± 0.02	0.15 ± 0.02	0.128 ± 0.004	0.13 ± 0.01	0.13 ± 0.02	0.14 ± 0.02	0.15 ± 0.01	0.15 ± 0.02	0.13 ± 0.05
	Cellulose	0.16 ± 0.02	0.06 ± 0.01	0.026 ± 0.005*	0.13 ± 0.01	0.15 ± 0.01	0.12 ± 0.02	0.10 ± 0.01	0.12 ± 0.01	0.15 ± 0.01	0.14 ± 0.02	0.16 ± 0.02	0.09 ± 0.02
	Solution	0.164 ± 0.005	0.052 ± 0.003	0.052 ± 0.004	0.158 ± 0.006	0.196 ± 0.005	0.13 ± 0.02	0.09 ± 0.02	0.107 ± 0.004	0.128 ± 0.001	0.150 ± 0.006	0.135 ± 0.004	0.140 ± 0.004
S	Matrix-Matched	1488 ± 132	928 ± 119	1240 ± 288	1367 ± 372	1595 ± 209	1485 ± 159	1781 ± 447	1025 ± 71	1206 ± 183	1343 ± 142	1193 ± 125	3526 ± 599
	Cellulose	777 ± 95	377 ± 36	418 ± 76	637 ± 119	813 ± 118	794 ± 160	893 ± 196	549 ± 60	673 ± 52	748 ± 78	686 ± 85	1680 ± 248
	Solution	1574 ± 24	738 ± 17	744 ± 9	1343 ± 23	1549 ± 17	1685 ± 34	1413 ± 17	785 ± 15	841 ± 19	937 ± 16	913 ± 25	3309 ± 44
Zn	Matrix-Matched	11413 ± 616	36 ± 11	<LOD	5898 ± 731	8939 ± 465	9115 ± 392	7066 ± 254	6606 ± 344	9547 ± 487	9226 ± 378	9084 ± 1499	6446 ± 2752
	Cellulose	10893 ± 599	28 ± 4	<LOD	5336 ± 475	9938 ± 1312	9847 ± 1123	8580 ± 583	6257 ± 676	10087 ± 978	8354 ± 1253	9598 ± 1190	7487 ± 2179
	Solution	9356 ± 330	119 ± 5	3.4 ± 0.1	5269 ± 105	8460 ± 416	7890 ± 123	10100 ± 79	5856 ± 94	9271 ± 108	8746 ± 175	8670 ± 197	15680 ± 589
* Levels between LOD and LOQ ^a Laser ablation (i.e., matrix-matched and cellulose) results consisted of the average of five replicate measurements (n = 5), solution results consisted of three digestion replicates (n = 3)

In this study, we presented the development and optimization of an LA-ICP-MS analytical method for the analysis of multivitamins. This technique offers quick and automated sample analysis without the need for corrosive acids and extensive sample preparation. Integration of a carrousel autosampler allows for automated and unattended analysis, resulting in high sample throughput. In comparison with the solution ICP-MS analysis, the laser ablation method was considerably quicker and simpler. The main notable advantage was the ability to analyze the samples without having to decompose them by acid digestion. In addition, the digests required two sets of dilutions (i.e., a 5X dilution, for trace elements, and a 500X dilution for the major elements), which was not only time consuming, but also generated large amounts of hazardous waste and involved the use of costly ICP-MS standards, high-purity concentrated acids, and consumables.

The optimum energy output selected was 0.5 J/cm² which resulted in less differences in ablation between the two materials, without significantly sacrificing sensitivity. A repetition rate of 30 Hz and a carrier gas flow rate of 800 mL/min were determined to be optimum as they provided the best compromise between sensitivity and reproducibility. The dissimilarities in ablation yield due to differences in focal points were successfully corrected after normalizing to internal standard elements, resulting in relative differences of less than 10%. The use of internal standards was critical for some elements, such as arsenic, for the accurate quantification of the multivitamins. The selection of internal standards was dependent on the analyte and on the sample matrix.

The results from the two different calibration approaches were compared to those obtained from solution ICP-MS and ICP-OES analyses. Both calibration methods (i.e., cellulose and matrix-matched calibrations) performed adequately for most of the monitored elements in the multivitamins. Matrix-matched calibration additionally resulted in better recoveries for S and Fe.

Specifically, matrix-matched calibration resulted in a recovery range (mean) for each element: 81–140% (112%) As, 80–129% (107%) B, 58–140% (81%) Co, 89–122% (103%) Cr, 71–114% (90%) Cu, 77–125% (102%) Mg, 86–141% (119%) Na, 86–116% (101%) Ni, 77–179% (114%) Pb, and 31–122% (93%) Zn, for the samples above LOQ. Matrix matched calibration additionally resulted in better recoveries for iron 53–121% (98%) vs. 21–59% (37%), with cellulose; and sulfur (88–167% (122%) vs. 47–80% (60%), with cellulose. Overall, matrix-matched calibration resulted in better recoveries for more multivitamins in comparison with cellulose calibration.

Acknowledgments

Funding

Conflict of Interest

Claudia Martinez Lopez declares that she has no conflict of interest. Jake A. Carter declares that he has no conflict of interest. Ruthmara Corzo declares that she has no conflict of interest. Todor I. Todorov declares that he has no conflict of interest.

Ethical Approval

Not applicable.

Informed Consent

Not applicable.

Food analytical methods: https://www.springer.com/journal/12161/

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Method Development for the Quantitative Analysis of Multivitamin Supplements by Laser Ablation– Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS)

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Abstract

Figures

2 Introduction

3 Materials And Methods

3.1 Sample preparation

3.2 Instrumentation

3.3 Data processing

4 Results And Discussion

4.1 Optimization of the instrumental parameters

4.2 Effect of differences in focal point

4.3 LA-ICP-MS quantitative analysis of multivitamins

4.3.1 Internal standard selection

4.3.2 Calibration and quantitative analysis

5 Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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