Marijuana, the common or slang term for cannabis in its herbal form, is one of the most widely used illicit drugs in the world. Synthetic cannabinoids have similar psychotropic effects to the natural ones and are rapidly being integrated by the illicit market. To deal with their expanding number and diversity, a targeted and untargeted liquid chromatography–tandem mass spectrometry (LC–MS-MS) screening method was developed, allowing for the simultaneous analysis of 24 synthetic and natural cannabinoids in 8 min for a wide variety of samples such as herbal smoking mixtures, incense sticks, serums, and cannabis plant material. The particular advantage of this LC–MS-MS method is that the full scan event in the MS acquisition provides accurate masses for all detected species and thus allows postanalysis identification of initially untargeted compounds.

	The primary psychoactive compound in cannabis is Δ

-tetrahydrocannabinol (THC), which exerts its activity by interacting with the CB1 and CB2 cannabinoid receptors in the brain. Synthetic analogs of THC, when smoked or orally ingested, can mimic the psychotropic effects of cannabis by binding the same receptors (1). Cannabimimetic compounds can be found in herbal mixtures (incense stick, cigarette, Spice, K2), serums, and other matrices, often with no indication of their presence. The European monitoring center for drugs and drug addiction reported in 2009 (2) that spice products (3) were generally used by teenagers and young adults because it enabled them to pass drug-screening tests. Many governments have taken legal action to control specific synthetic cannabinoids. In the United States, they have been listed as Schedule I drugs on the Controlled Substances Act, and in Canada as Schedule II drugs. However, small structural modifications from the controlled substance result in new analogs being legal. Therefore, in May 2012 the United States amended the Act and proposed a bill to place all cannabimimetic agents as Schedule I drugs (4,5).

	Given the structural similarities between THC and its synthetic analogs, identification of the compounds in seized samples is a continuous challenge for government agencies. As quickly as analogs are added to controlled substance lists, new ones are synthesized, making their monitoring a moving target (6–9). These new generation analogs are obviously not present in mass spectrometry (MS) or UV spectra libraries; therefore, routine methods for screening cannabimimetics in both products and biofluids rapidly become less effective.

	The most common methods of cannabinoid analysis use gas chromatography (GC)–MS (10,11) and liquid chromatography (LC)–MS (9,12–14). GC–MS approaches use MS spectra of known cannabinoids for identification, and most LC–MS approaches are used in multiple reaction monitoring (MRM) mode. Both are targeted methods that are limited to screening known species and are therefore always one step behind in the monitoring of this dynamic designer drug market. To address this shortcoming, we report a targeted–untargeted high-resolution MS approach to screen a variety of samples for cannabinoid-like compounds. The current method includes a high-resolution, nontarget scan that allows identification of all species if present in the sample and targets a selection of 20 synthetic and four natural cannabinoids (Figure 1).


	Figure 1: Chemical structures and accurate masses of the 24 synthetic and natural cannabinoids investigated.

	LC–MS-grade methanol and acetonitrile were from J.T. Baker (TekniScience) and LC–MS-grade formic acid (98%) was from Fluka (Sigma-Aldrich). High performance liquid chromatography (HPLC)-grade water from a Milli-Q Reference A+ system (Fisher Scientific) was used to prepare all aqueous solutions and mobile phases.

	A total of 24 standards were investigated. JWH-018 and JWH-210 were obtained from Toronto Research Chemicals Inc. AKB48 

-(5-fluoropentyl) analog, AM-694, AM-694 3-iodo isomer, AM-1220, AM-2201, AM-2201 2'-naphthyl isomer, AM-2201 

-(4-fluoropentyl) isomer, CP 47,497, (±)-CP 47,497-C8-homolog, (±)-epi CP 47,497-C8-homolog, (±) 3-epi CP 47,497-C8-homolog, JWH-019, JWH-073, JWH-081, JWH-122, JWH-200, JWH-250, and STS-135 were obtained from Cayman Chemical. Δ

-Tetrahydrocannabinol and cannabinol were purchased from Alltech/Grace. Cannabidiol was purchased from Lipomed and cannabigerol was purchased from THC PHARM.

	Stock solutions of individual standards were prepared separately in 10-mL volumetric flasks at an approximate concentration of 100 μg/mL in methanol. Diluted stock solutions (100 ng/mL to 1 μg/mL) were directly infused into the mass spectrometer for adjustment of the experimental parameters for each analyte. A standard mixture of the 24 components was also prepared and injected to adjust the chromatographic separation of all analogs.

	To determine the effectiveness and robustness of the LC–MS-MS method, 10 seized samples and a cannabis sample were analyzed. The samples were present in two forms: tablets and herbal products (incense stick, cigarette, and a cannabis plant). They were finely ground, then aliquots of 5–10 mg of the resulting powder were transferred to 10-mL volumetric flasks and dissolved in 70:20:10 methanol–water–acetonitrile containing 1% formic acid. Following this, the solutions were vortexed for 2 min, sonicated for 10 min, and vortexed again for 3 min. The supernatant was filtered through a 0.45-μm pore polytetrafluoroethylene (PTFE) syringe filter (Phenomenex). Herbal samples required an additional centrifugation step at 3500 rpm for 10 min to avoid mass overloading of the syringe filter. Filtrates were diluted 10–100-fold in 80:20 water–acetonitrile, the initial mobile phase, before injection.

	Data were acquired on an LTQ Orbitrap XL mass spectrometer coupled to an Acella HPLC system (Thermo Scientific). Xcalibur 2.1 and Thermo LTQ Tune Plus 2.5.5 software (Thermo Scientific) were used to control the system and process the data. External mass calibration was used throughout the project. Four analytical columns were initially tested for their chromatographic performance: 100 mm × 2.1 mm, 3.5-μm 

 XTerra C18 and 100 mm × 2.1 mm, 1.7-μm 

Acquity BEH C18 columns, both from Waters; a 75 mm × 2.1 mm, 2.6-μm 

Kinetex C18 column from Phenomenex; and a 100 mm × 2.1 mm, 2.6-μm 

Accucore aQ C18 column from Thermo Scientific. Two eluent systems were tested during method development, water–methanol and water–acetonitrile, both containing 0.1% formic acid, under generic gradient conditions (5–95% organic).

	Optimized separations were carried out using the Accucore aQ column coupled to a 4 mm × 2.0 mm Phenomenex C18 guard column, both maintained at 40 °C, and the water–acetonitrile gradient. The autosampler temperature was set at 10 °C to avoid sample degradation. Eluents consisted of 0.1% formic acid in water (eluent A) and 0.1% formic acid in acetonitrile (eluent B), and the initial mobile phase contained 20% B. The following gradient elution was applied at a flow rate of 350 μL/min: 20–58% B over 1 min, held at 58% B for 1 min, increased to 85% B over 1 min, then held at 85% B for 2 min. Eluent B was then returned to 20% B over 0.2 min. The system was allowed to reequilibrate for 2.8 min, giving a total cycle time of 8.0 min. The injection volume was 3–5 μL. A needle wash step using 70:20:10 methanol–water–acetonitrile was included in the method. A 5-μL blank, consisting of the initial mobile phase, was injected after each sample to monitor and reduce any potential carryover.

	The electrospray interface was operated in positive ion mode. Nitrogen was used as both sheath gas and auxiliary gas while helium was used as collision gas. Using direct infusion, instrumental parameters were adjusted semiautomatically for every analyte using the tune tool in the LTQ Tune Plus software. The parent ions of all analytes showed similar behavior due to their similar structures. After screening every compound individually, the experimental parameters of the full scan event that were found to be suitable for all analytes were set to the following values: sheath and auxiliary gas at flow rates of 44 and 17 (instrument units), respectively; spray voltage, +3500 V; capillary temperature, 310 °C; capillary voltage, 28 V; tube lens, 101. The MS

 transitions for every compound were also determined using the tune tool by varying the normalized collision energy. They ranged between 25% and 33% after they were optimized. Therefore, a three-step collision energy function set at 25%, 30%, and 35% was used to perform average fragmentation on every compound. The ion transitions MS

 for each standard are shown in Table I, where the MS

 value shown in boldface type. Mass spectra were acquired from 

 50 to 1000 using two scan events: the first was a Fourier transform (FT)-MS full scan for accurate mass detection and the second was a data dependent step with MS-MS acquired only for precursors from the parent mass list with a dynamic exclusion of 10 s. Every standard was then injected onto the column individually to determine its retention time and confirm the parent ion accurate mass, MS

. To determine if there were any interactions between the compounds, a mixture of the 24 standards was injected.

	As seen in Figure 1, many of the 24 compounds have similar structures, which makes the chromatographic separation challenging. Between the mobile phases tested, the acetonitrile gradient gave better selectivity. Between the columns tested, the Accucore aQ gave the best selectivity and retention of early eluted analytes.

	Selectivity was further enhanced by coupling the optimized chromatographic method to the high-mass-resolution orbital ion trap mass spectrometer. By individual direct infusion of the standards, the final optimized parameters for full-scan detection (values presented in the LC–MS-MS operating conditions section) were selected to provide appropriate sensitivity for all 24 components in a single analysis. The mass accuracy across the whole study was within 3 ppm.


	Figure 2: Typical chromatograms obtained by LC–MS-MS in positive electrospray mode for a mixture containing all 24 analytes. The upper trace of the first panel represents the total ion chromatogram (TIC), followed by the extracted ion chromatograms of all the compounds spread over three panels for ease of presentation (parent ions shown).

	When operating the orbital ion trap MS system at a resolution of 30,000, approximately 1.5 scans (points) per second were obtained for the mixture, containing 24 standards analyzed simultaneously. This acquisition scan speed was well suited for the narrow peaks (5–8 s wide) produced by the core–shell particle chromatography and allowed a very reliable quantification and improved method sensitivity. The well selected parent-fragment transitions helped to enhance the method selectivity. As seen in Figure 2 (spread across 3 panels for ease of peak identification), it was possible to positively identify 24 cannabinoids by differentiating them with a combination of accurate mass, retention time, and fragmentation pattern (MS

-(4-fluoropentyl) have the same accurate mass and retention time and very similar fragmentation patterns, as shown in Figure 3. However, a signal at 

340, generated by the loss of fluorine from a secondary carbon, is only present in the MS

-(4-fluoropentyl) and allows distinction between the two. Similarly, JWH-019 and JWH-122 are eluted within 0.05 min of each other and have the same accurate mass. Without reinjecting, they could be identified by their completely different MS

 fragmentation patterns (Figure 4). The MS

 data were acquired but not actually needed for the screening method. In the eventuality of samples with a new analog of identical parent ion mass, retention time, and MS


	Figure 3: Fragmentation pattern of two isomers: (a) AM-2201 and (b) AM-2201 N-(4-fluoropentyl) isomer.

	Figure 2 shows all compounds eluted between 2.36 and 4.94 min. Adulterated natural remedies can contain new synthetic drug substances of unknown polarity. It is therefore necessary to use caution when developing fast chromatographic separations; if additional yet-to-be characterized synthetic cannabinoids are present, excessive coelution could compromise their postacquisition identification using the untargeted full scan event in the acquisition method.


	Figure 4: Fragmentation pattern of two isomers: (a) JWH-019 and (b) JWH-122.

	Matrix effects were evaluated in four samples (tablet and herbal based) spiked with the 24 analytes before extraction. A comparison of the chromatograms to that of the standard mixture revealed no difference in peak areas for the 24 analytes. To evaluate carryover, blanks injected after samples were used. No carryover was detected at analyte concentrations below 50 ng/mL whereas most compounds presented 0.1–0.3% carryover at 250 ng/mL and 0.4–1.0% at 1000 ng/mL. Therefore, we suggest that two blank injections be used between samples at high concentrations. The linearity of 15 compounds, selected to be representative of the 24, spiked into an herbal matrix, was evaluated across a concentration range of 0.01–1000 ng/mL (

 = 21). Linear regression was applied by plotting the peak area responses of each compound as a function of its respective concentration and applying a 1/

 weighting factor. Calibration curve correlation coefficients (

) ranged between 0.996 and 0.999. Detection limits (calculated at signal-to-noise ratio of 3) were between 0.03 ng/mL and 0.61 ng/mL for all but one compound regardless of the presence of matrix; the limit of detection (LOD) for (±) 3-epi-CP 47,497-C8-homolog was 1.52 ng/mL.

	It was important to develop a simple and economical extraction method that was also fast and effective with good recovery to complement the rapid LC–MS-MS separation. For 12 cannabinoids, selected to be representative of the 24, recoveries ranged between 92–110% across three concentrations (50, 250, and 1000 ng/mL).

	The precision and accuracy of the method were evaluated for 10 representative compounds at 50, 250, and 1000 ng/mL. Each concentration level was prepared in five replicates by spiking the appropriate amount of analyte standard into a matrix (tablet or herbal based) and each sample was injected five times. Intra-assay precision ranged from 1.2–4.0% relative standard deviation (RSD) across the three concentration levels. The procedure was repeated the following week to determine the interassay precision, which ranged from 2.9% to 9.7% RSD. Even though only 10 compounds were spiked for method validation, all 24 were injected numerous times individually, and together, during the method development with no significant changes (that is, within repeatability error) in peak areas and retention times. For example, after 25 injections of standard AM-694 (five replicates for each of the five different samples), essentially no change in retention time (0.09% RSD intra-assay and interassay) and only a very small change in peak area (1.7% RSD) was observed. The same results were obtained for the other compounds (data not shown). The method accuracy, determined by comparing the calculated concentration with the true value spiked into the matrix was within 10% for all 10 compounds at all concentrations tested.

Application to the Analysis of Seized Samples 

	We used the rapid LC–MS-MS screening method to analyze 11 seized samples (four incense sticks, two cigarettes, three herbal samples, one cannabis sample, and one tablet), all from nonregistered sources. Seven were found to be positive for cannabinoids. In one of the incense sticks, two synthetic cannabinoids were detected: JWH-018 at 4.48 min and JWH-073 at 4.24 min, as shown in Figure 5. These two synthetic analogs are controlled substances and, as highlighted in the introduction, their presence in these products is illegal. The incense sticks were therefore designated for withdrawal from distribution.


	Figure 5: Illegal product (incense stick) showing the presence of controlled synthetic cannabinoids: JWH-018 and JWH-073. The uppermost panel represents the TIC and the lower two extracted chromatograms showing detection of JWH-018 (middle panel) and JWH-073 (lower panel).

	In the chromatographic separation of the cannabis plant sample (Figure 6), a number of endogenous cannabinoids were detected. THC, the main psychoactive compound, was eluted at 4.93 min. Cannabigerol was detected at 4.36 min, and unlike THC, it does not mimic psychosis symptoms even though it interacts with the CB2 receptor in the brain (1). Cannabidiol, identified at 4.48 min, is another natural cannabinoid that is highly abundant in cannabis, up to 40% in the plant extract; however, it is not psychoactive. Cannabinol, which also interacts with the CB2 receptor, is usually present at low concentrations in fresh cannabis samples, but its abundance increases as it is formed by THC oxidative degradation by exposure to light or air (13). It was identified at 4.69 min with approximately a fivefold higher signal compared to THC (Figure 6), which suggests that the cannabis sample had undergone extensive oxidation.


	Figure 6: Cannabis sample showing the presence of THC, cannabidiol, cannabigerol, and cannabinol: (a) TIC, (b–d) extracted ion chromatograms showing the detection of the four cannabinoid compounds.

	The cannabis plant sample was previously analyzed by validated thin-layer chromatography (TLC) and GC–MS methods in a local government laboratory. The other samples in this study were previously analyzed by two validated HPLC–photodiode array (PDA) detection and GC–MS routine methods from the same government laboratory. The results obtained with the current rapid LC–MS-MS approach were in perfect agreement with the routine methods in that there were no false positive or false negative results; however, the new approach was four times faster than the validated HPLC–PDA method, six times more rapid than the validated GC–MS method, and more sensitive than both methods. Most cannabinoid analysis methods screen for metabolites in biological samples (such as urine, blood, and hair) because the parent compounds are rapidly metabolized (11,15). For screening suspected adulterated herbal mixtures, identification of the parent drug is required. Several rapid LC–MS-MS methods for cannabinoid screening have been reported recently in which 15–20 parent compounds and, in some cases, over 20 metabolites, have been separated in times ranging from 8 to 20 min (12,14,16). The large majority of these are MRM-based approaches, which means they are targeted and thus monitor only analogs predefined in the method; they are entirely inefficient for detecting new-generation cannabinoid analogs.

	The development of a rapid, selective, and sensitive LC–MS-MS screening method for simultaneous identification of 24 synthetic and natural cannabinoids present in herbal smoking mixtures, incense sticks, and tablet matrices has been described. The high mass-resolution power of an orbital ion trap mass spectrometer and its compatibility with the high peak efficiency provided by core–shell particle chromatography contributed to the excellent selectivity of the method. Additional confidence in analyte identification for the 24 compounds targeted was provided by the fragmentation patterns. The novelty of this work lies in the high-resolution full-scan event in the acquisition method that allows postanalysis identification, in an untargeted approach, of additional species in the complex matrices. This is highly relevant to the current application because of the emergence of new generations of cannabinoid analogs that try to be one step ahead of the controlled substances act. The need for such untargeted screening approaches is starting to be recognized by the analytical community as shown in recent reports by Scheidweiler and colleagues (15) and Shanks and colleagues (8). Our rapid LC–MS-MS screening method has the potential to be an indispensable forensic analysis tool for identifying illegal drug substances and adulterated products.

Philippe Lebel, Karen C. Waldron, and Alexandra Furtos

 are with the Department of Chemistry at the Université de Montréal, in Montréal, Canada. Direct correspondence to: 

	(1) L. Console-Bram, J. Marcu, and M.E. Abood,

 Prog. Neuro-Psychopharmacol. Biol. Psychiatry

	(2) Understanding the 'Spice' phenomenon, Lisbon, 2009, 

http://www.emcdda.europa.eu/publications/thematic-papers/spice

	(3) K.A. Seely, J. Lapoint, J.H. Moran, and L. Fattore, 

Prog. Neuro-Psychopharmacol. Biol. Psychiatry

	(4) Synthetic Drug Abuse Prevention Act of 2012, 

https://www.govtrack.us/congress/bills/112/s3190/text

	(5) L.N. Sacco and K. Finklea, "Synthetic Drugs: Overview and Issues for Congress," 2014, 

	(6) S. Dresen, N. Ferreirós, M. Pütz, F. Westphal, R. Zimmermann, and V. Auwärter, 

	(7) A.D. de Jager, J.V. Warner, M. Henman, W. Ferguson, and A. Hall, 

J. Chromatogr. B: Anal. Technol. Biomed. Life Sci.

	(8) K.G. Shanks, G.S. Behonick, T. Dahn, and A. Terrell, 

	(9) N. Uchiyama, M. Kawamura, R. Kikura-Hanajiri, and Y. Goda, F

	(10) T. Sobolevsky, I. Prasolov, and G. Rodchenkov, 

	(11) A. Grigoryev, S. Saychuk, A. Melnik, N. Moskaleva, J. Dzhurko, M. Ershov, A. Nosyrev, A. Vedenin, B. Izotov, I. Zabirova, and V. Rozhanets, 

	(12) K.B. Scheidweiler and M.A. Huestis, 

	(13) A.A.M. Stolker, J. van Schoonhoven, A.J. de Vries, I. Bobeldijk-Pastorova, W.H.J. Vaes, and R. van den Berg, 

	(14) S. Kneisel, M. Speck, B. Moosmann, T.M. Corneillie, N.G. Butlin, and V. Auwarter, 

	(15) K. Scheidweiler, M.Y. Jarvis, and M. Huestis, 

Published on-line: September 16, 2014, 1–15 (2014).

	(16) J.P. Danaceau, E.E. Chambers, and K.J. Fountain, "Analysis of Synthetic Cannabinoids from Urine for Forensic Toxicology using Oasis HLB μElution plates and CORTECS UPLC Columns," Waters Corporation, 2013, 

http://www.waters.com/waters/library.htm?lid=134763848&lset=1&locale=en_CA

Articles

Marijuana, the common or slang term for cannabis in its herbal form, is one of the most widely used illicit drugs in the world.

Rapid Determination of 24 Synthetic and Natural Cannabinoids for LC–MS-MS Screening in Natural Products and Drug Inspection Applications

The biologically active form of vitamin D is an important analytical target in both research and clinical practice. However, quantification of 1α,25-dihydroxyvitamin D

) has been challenging because of the extremely low levels in circulation - in the low picograms-per-milliliter range. Here, we report a sensitive, time-efficient, and cost-effective liquid chromatography–tandem mass spectrometry (LC–MS-MS) method that combines the use of immunoaffinity extraction, 4-phenyl-1,2,4-triazole-3,5-dione (PTAD) derivatization, and methylamine adduction. 

 plays an important role in the maintenance of bone health by promoting the absorption and metabolism of calcium and phosphate (1,2). Vitamin D

 is either produced in skin (under the influence of UV light) or absorbed from dietary or supplement intake (3,4). The primary circulating metabolite, 25-hydroxyvitamin D

), is formed following a first hydroxylation step in liver microsomes. The active form, 1α,25-dihydroxyvitamin D

), is formed in a second hydroxylation step, which occurs primarily in the kidney (Figure 1). Through upregulation of a wide variety of genes, 1,25(OH)

 is responsible for most of the biological action of vitamin D

. Areas of influence of the active metabolite include immune function, cell proliferation, differentiation, and apoptosis (5).


	Figure 1: Metabolic pathway of 1α,25-dihydroxyvitamin D

 are very low (low picograms per milliliter) (6) in normal human plasma. These extremely low concentrations and the potential interference from other vitamin D

 metabolites have made the accurate quantification of 1,25(OH)

 a challenge. Previous progress to increase the sensitivity of liquid chromatography–tandem mass spectrometry (LC–MS-MS) assays has been made by either using a more sensitive derivatization reagent (7) or by using the microflow LC–MS-MS (8) concept to improve the instrument sensitivity. But there are drawbacks associated with those methods, including cost, availability, the stability of the agents used, and the complexity of the system involved. Herein, we report a sensitive and selective LC–MS-MS method using immunoaffinity extraction (IAE), 4-phenyl-1,2,4-triazole-3,5-dione (PTAD) derivatization, and methylamine (CH

) adduction for the LC–MS-MS analysis. Our method is easier to use than current methods and offers significant advantages in cost effectiveness. The recovery and selectivity of the IAE are high for 1,25(OH)

 and PTAD is a stable and commercially available reagent.

	The finalized experimental conditions for IAE, PTAD derivatization, and methylamine adduction in the LC–MS-MS analysis of 1,25(OH)

	Samples were extracted using ImmunoTube extraction kits (Immundiagnostik AG, distributed by ALPCO). Internal standards (IS) consisted of 20 μL of a 10-ng/mL solution of 26,26,26,27,27,27-hexadeuterium-1α,25-dihydroxyvitamin D

) (Chemaphor) dissolved in acetonitrile and were spiked to 0.5 mL of human plasma sample. The sample was vortexed and centrifuged before being transferred into the ImmunoTubes. The ImmunoTubes were incubated on a rotator at room temperature for 1 h, then washed with 3 × 500 μL of WASHSOL (the wash solution provided by the manufacturer in the extraction kit), and finally eluted with 250 μL of ELUREAG (the elution reagent provided by the manufacturer in the extraction kit). The eluent was dried completely on a Speed Vac concentrator (Savant SPD121P-115, Thermo Electron Corporation), and then 50 μL of PTAD (0.2 mg/mL in acetonitrile) was added. The reaction was then held at room temperature for 2 h and finally terminated with 50 μL of water. Then the samples were transferred to high performance liquid chromatography (HPLC) vials containing inserts, and 10 μL was injected into the LC–MS-MS system. Next, 1,25(OH)

 calibration standards were prepared by spiking 50 μL of 1,25(OH)

 standard (Cerilliant) at different concentrations in acetonitrile into a 500-μL aliquot of vitamin D– depleted blank human serum (Golden West Biologicals Inc., VD-DDC Mass Spect Gold MSG 1000) at concentrations of 5.0, 10.0, 25.0, 50.0, 100.0, 250.0, 500.0, and 1000.0 pg/mL. The remaining procedures were carried out identically to those performed for the plasma samples.

	The LC–MS-MS system consisted of an Agilent 1100 system coupled to a tandem quadrupole 4000 Qtrap MS system (AB Sciex). Chromatographic separations were performed on a 50 mm × 2.1 mm, 2.7-μm Waters Cortecs C18+ column (90 Å), with the column temperature held at 60 °C. Mobile-phase A was 0.1% formic acid and 1 mM methylamine in water, and mobile-phase B was 0.1% formic acid in methanol.

	The gradient was as follows: 0–0.1 min, 50% B; 2 min, 90% B: 2.5–4.0 min, 100% B; 4.1–8.0 min, 50% B. The MS system was operated in positive electrospray ionization mode with an ion spray voltage of 5500 V. Nitrogen was used as the collision gas. The optimized source conditions were as follows (arbitrary units if not specified): gas 1: 50; gas 2: 40; curtain gas (CUR): 30; collision gas (CAD): 10; and temperature (TEM): 400. The optimized compound conditions were declustering potential (DP): 50; collision energy (CE): 32; entrance potential (EP): 10; collision cell exit potential (CXP): 8; and dwell time: 100 ms for all analytes. The multiple reaction monitoring (MRM) transitions used were 

. Data were processed with Analyst software version 1.5.1 (AB Sciex).


	Figure 2: A comparison of the chromatograms of a sample containing 5 pg/mL of 1,25(OH)

 extracted by different methods: (a) IAE, (b) IAE, and (c) SPE.

 from its matrix interferences, several different solid-phase extraction (SPE) cartridges were evaluated. IAE was clearly superior in sample cleanup and sensitivity (Figure 2). The 1,25(OH)

 peak was detected in the sample (containing 5 pg/mL of 1,25(OH)

) treated with IAE (Figure 2a), but not in the sample treated with SPE (Figure 2c). Figure 2b is the peak of IS for the retention time identification purpose for the main peak of 1,25(OH)

. No other interference peaks were observed near the main peak from a plasma sample treated with IAE (Figure 3c). Unlike SPE, which separates analytes based on their polarity, the immunoaffinity assay targets dihydroxyvitamin D metabolites only, resulting in higher selectivity. A cleaner sample made the subsequent LC–MS-MS analysis easier since an extensive separation on an LC column is not necessary. The run time was shortened by 50%, resulting in greater throughput efficiency and less cost to the investigator. The IAE procedures provided by the manufacturer were straightforward and easy to use with minimum preparation. IAE is a key step to improve the assay sensitivity, making it possible to measure 1,25(OH)

 in human plasma on the mass spectrometer. These results were not achieved with any of the tested SPE cartridges used previously as sample cleanup methods.


	Figure 3: Example chromatograms of 1,25(OH)

 in human plasma treated with IAE: (a) blank human plasma, (b) a standard, and (c) a patient sample.

Selection of the Derivatization Reagent and Use of Mobile-Phase Additive

	Besides the improvement in the sample cleanup method, using a sensitive derivatizing reagent is another key to improve the sensitivity. At the beginning, the Amplifex Diene (AD, AB Sciex) derivatizing reagent was used for the assay since it was able to provide a 10-fold higher signal-to-noise ratio compared to PTAD (7) (Figure 4). However, because of the cost, the current availability of the AD derivatizing reagent, and its low stability following exposure to ambient air, the choice of derivatizing reagent went back to PTAD since our intention was to develop a method with great practicality and relative low cost while still meeting the assay detection limit requirement. To achieve this goal, methylamine was used as a mobile-phase additive to enhance assay sensitivity after the PTAD derivatization. When methylamine was added to the mobile phase, the derivative provided methylammonium adduct ions ([M+ CH

 623.4) as the base peak ion (9). The intensities of the protonated molecules, other adduct ions, and the dehydrated ion significantly decreased. In summary, the combination of PTAD derivatization and the addition of methylamine to the mobile phase provided sensitive and reliable measurement of 1,25(OH)

 on the mass spectrometer with a lower limit of quantification (LLOQ) of 5 pg/mL in human plasma.


	Figure 4: Derivatization of 1α,25-dihydroxyvitamin D

Optimization of the Conditions for PTAD Derivatization and LC–MS-MS Analysis Using Methylamine as an Additive

	To obtain the maximum sensitivity, the amount of PTAD added for the derivatization, the concentration of methylamine in the mobile phase, the type of organic solvent in mobile-phase B, and the gradient were optimized to yield the highest signal-to-noise ratios and the lowest detection limit with repeatable results in a relatively short run time. For PTAD optimization, 50 μL of PTAD at different concentrations (0.05, 0.1, 0.2, 0.3, 0.4, 0.6, 0.8, 1.0, and 1.2 mg/mL in acetonitrile) was added to identical samples spiked with 500 pg/mL of 1,25(OH)

 and the IS. The samples were derivatized and analyzed according to the conditions described in the experimental section. The results are shown in Figure 5. Our data show that 0.1–0.2 mg/mL PTAD gave the highest peak area for both analyte and IS, and 50 μL of a 0.2-mg/mL solution of PTAD was chosen for the IAE sample to ensure that a sufficient derivatizing reagent was available in all reactions.


	Figure 5: Optimization of PTAD concentration in derivatization. Error bars represent standard deviations of three replicates.

	To optimize the methylamine concentration in the mobile phase, aliquots of the same sample were injected and analyzed on the LC–MS-MS system with different concentrations of methylamine in mobile-phase A. The optimal value is 1 mM methylamine in mobile-phase A because it gave the highest peak area for both analyte and IS (Figure 6).


	Figure 6: Optimization of methylamine concentration in the mobile phase. Error bars represent standard deviations of three replicates.

	Several different columns, organic components in mobile-phase B, and gradients were also evaluated to maximize the sensitivity. It was found that the column mentioned in the experimental section gave the best performance overall in terms of peak shape, separation, and column pressure. The detection sensitivity was shown to be higher when methanol instead of acetonitrile was used in mobile-phase B. Since IAE yielded a cleaner sample than other sample cleanup methods, and since PTAD is less hydrophilic than AD, 50% methanol was used as the initial gradient condition, resulting in a faster gradient that reduced the run time from 16 min (using AD as the derivatizing reagent) to 8 min (using PTAD as the derivatizing reagent) (see Figure 7). The 8-min run time is also significantly shorter than other methods reported for LC–MS-MS analysis of 1,25(OH)


	Figure 7: Mass chromatograms of the LC–MS-MS analysis of a patient sample derivatized with (a) AD and (b) PTAD. The arrows indicate the 1,25(OH)

 Results Obtained Using Different Derivatization Reagents 

	To make sure that the new method (using PTAD derivatization and 1 mM methylamine in mobile-phase A) with a shorter run time (8 min) was able to replace the initial method (using AD derivatization) developed for 1,25(OH)

analysis, six patient samples at low, middle, and high levels of 1,25(OH)

 were analyzed in both ways to compare the results side by side. By doing so, after the IAE sample cleanup, one set of the six patient samples went through the derivatization with PTAD and was analyzed by LC–MS-MS using the conditions described in the experimental section above. Another set of the samples went through the derivatization with AD and were analyzed on the same LC–MS-MS system using the optimized conditions, which was different from the one used for the PTAD method. Since the "best" chromatographic conditions (mainly the column and the mobile phases) developed for the PTAD method are not the best for the AD-derivatized samples, the optimized chromatographic conditions for the AD method are listed below. The column used was a 100 mm × 2.1 mm, 2.6-μm Phenomenex Kinetex C18 column (100 Å), mobile-phase A was 0.1% formic acid in water, and mobile-phase B was 0.1% formic acid in acetonitrile. The gradient was as follows: 0 min, 5% B; 0.85 min, 35% B; 6.0 min, 45% B; 6.5–10 min, 95% B, 10.1–16.0 min, 5% B. The optimized source conditions were as follows: gas 1: 40; gas 2: 60; CUR: 30; CAD: 11; and TEM: 450. The optimized compound conditions were as follows: DP: 70; CE: 40; EP: 13; and CXP: 11 for MRM transition 748.6→689.5 (1,25(OH)

), the conditions were DP: 65; CE: 50; EP: 11; and CXP: 9. Each patient sample was analyzed in triplicate, with the average reported in Table I. The results in Table I indicate that the percent difference of the results from the two methods is <9%, which is below the acceptance limit (±15%) generally set for LC–MS-MS analysis. The accuracy of the new method (using PTAD and methylamine) is very comparable to that of the initial method developed for 1,25(OH)

 in which the more sensitive derivatizing reagent AD was used. Both methods have the same LLOQ, which is 5 pg/mL for 1,25(OH)

. The calibration curve was linear over the range of 5.0–1000 pg/mL (Table II). Therefore, it is possible to use the existing low-cost reagent PTAD to replace the more expensive AD for the measurement of 1,25(OH)

 in human plasma as long as methylamine is added in the mobile phase.

	The last step in the method development was method validation to test for robustness and reproducibility. The method was validated for linearity, sensitivity, accuracy, precision, selectivity, recovery, and matrix effect. Excellent linearity was obtained for the eight-point calibration curve constructed by plotting the peak area ratio of 1,25(OH)

) versus the corresponding concentration ratio and fitting the data using linear least-squares regression with a 1/

 weighting factor. For three consecutive batches, the calibration curves showed an overall accuracy of 94.1–106.1% with RSD ≤7.2% over the concentration range of 5.0–1000.0 pg/mL (Table II). The correlation coefficient (

) of the linear regression was ≥ 0.9998. The LLOQ was taken as the lowest calibration concentration that passed acceptance criteria with a signal-to-noise ratio of at least 5:1. The LLOQ was found to be 5.0 pg/mL. The LLOQ obtained on the mass spectrometer is low enough to accomplish the 1,25(OH)

 measurement in human plasma since the level of 1,25(OH)

 in most human plasma samples is 15–60 pg/mL (10). In addition, our technique differs from the prior method (7) because it is faster and more cost effective.

	Method accuracy and precision were evaluated using quality control (QC) samples prepared by spiking 1,25(OH)

 into the blank plasma at four concentration levels (5.0, 15.0, 200.0, and 350.0 pg/mL) to serve as QC-LLOQ, low QC, mid QC, and high QC. Three consecutive batches were prepared and each batch contained a freshly prepared calibration curve and six replicates of QC samples at the four levels. Intra-assay precision was calculated by obtaining the relative standard deviation (RSD) of the six replicates of each QC level, and intra-assay accuracy was calculated by averaging the accuracies of six replicates of each QC level against the fresh curve. Interassay precision was calculated by obtaining the RSD of all 18 replicates at each QC level from all three batches, with overall accuracy calculated by averaging the accuracies of all 18 replicates at each QC level from all three batches. The method was found to be highly accurate and precise. The accuracy of 89.2–105.2% (of the theoretical value) and precision of 1.5–9.2% RSD for intra-assay, and accuracy of 94.3–104.2% and precision of 1.6–7.7% RSD for interassay were obtained for all QC levels including LLOQ (Table III).

	The method selectivity was evaluated by assaying blank plasma sample without an internal standard. No interfering peaks were detected at the retention time of interest (Figure 3). To evaluate the recovery of the immunoaffinity step plus matrix effects, three samples were each prepared in triplicate. Sample 1 was a blank plasma sample spiked with 1,25(OH)

 (500.0 pg/mL) and an internal standard. Sample 2 was a blank plasma sample without IS. Sample 3 was water without IS. All three samples were processed according to the procedures described in the experimental section above; however, for samples 2 and 3, instead of adding derivatization solutions, a solution containing 1,25(OH)

 and the IS at concentrations that mimic the concentrations of sample 1 in the final extract were added right before being dried down for derivatization with PTAD. These samples are referred to as the postextraction spike sample (for sample 2) and the pure solution sample (for sample 3), respectively. The mean peak area counts of 1,25(OH)

 and the IS from three replicates of sample 1 were compared with the corresponding mean peak area counts from three replicates of sample 2 to calculate the extraction recovery. As shown in Table IV, a recovery of 83.2% for 1,25(OH)

 and 81.6% for the IS were achieved. Although the recovery of 1,25(OH)

was lower than 100%, the percent recovery was very consistent for the three replicates performed. At the LLOQ detection limit, only the sample extracted by the immunoaffinity tubes showed a peak, which was not shown with other sample treatment methods like SPE (Figure 3). Similarly, matrix effects were calculated as follows: mean peak area from the postextraction spike samples minus the mean peak area from the pure solution samples, then divided by mean peak area from the pure solution samples and multiplied by 100. Positive values indicate percent enhancement and negative values indicate percent suppression. A matrix effect of 7.22% for 1,25(OH)

 and 13.42% for the IS was observed, and all three matrix lots showed very similar matrix effects. Although the matrix effect is a negative number, which indicates ion suppression for the samples treated by IAE, there was no other major interfering peak observed near the main peak (Figure 3) in the real patient sample. These data demonstrate the selectivity, robustness, and ruggedness of the method.

	This work represents the first report to combine the advantage of IAE, PTAD derivatization, and methylamine adduction in the LC–MS-MS analysis of 1,25(OH)

 in human plasma. First, IAE is a key step for improving the assay sensitivity and eliminating interfering metabolites that cannot be eliminated by SPE. Second, methylamine addition in the mobile phase resulted in the same LLOQ when comparing AD alone to PTAD with methylamine. The results from PTAD are the same as that from AD. In contrast, the cost of the PTAD plus methylamine method was significantly lower than the original AD method, needing only half the run time (8 min versus 16 min). In addition, this method can be broadly adopted in a majority of LC–MS-MS laboratories. In conclusion, the PTAD plus methylamine method has significantly lower cost and greater practicality.

	This research was paid for by a grant from the American Institute for Cancer Research (RTW). The authors would like to sincerely thank Dr. Subhakar Dey from AB Sciex for providing the Amplifex Diene derivatization reagent and the technical consultation for the initial development of the 1,25(OH)

 method on our mass spectrometry system. We also thank Dr. Curtis J. Hedman from the University of Wisconsin, Madison, for the discussion of using AD derivatization for the measurement of 1,25(OH)

. The authors also wish to thank Penn State College of Medicine Mass Spectrometry Core Facility for the support of instrumentation.

is with the Department of Pharmacology at Pennsylvania State University, College of Medicine, in Hershey, Pennsylvania. 

is Director at Keystone Bioanalytical Inc., in North Wales, Pennsylvania. 

is with the Department of Public Health Sciences at Pennsylvania State University, College of Medicine. 

is director of Section of Research Resources at Penn State University, College of Medicine. 

is an associate professor of Public Health Sciences at Pennsylvania State University, College of Medicine. Direct correspondence to: 

	(2) A.C. Ross, C.L. Taylor, A.L. Yaktine, and H.B. Del Valle, 

Institute of Medicine Committee to Review Dietary Reference Intakes for Vitamin D and Calcium

 (The National Academies Press, Washington, DC, 2011).

	(6) A.E. Broadus, R.L. Horst, R. Lang, E.T. Littledike, and H. Rasmussen, 

	(7) C.J. Hedman, D.A. Wiebe, S. Dey, J. Plath, J.W. Kemnitz, and T.E. Ziegler, 

	(8) X. Duan, B. Weinstock-Guttman, H. Wang, E. Bang, J. Li, M. Ramanathan, and J. Qu, 

	(9) T. Higashi, Y. Shibayama, M. Fuji, and K. Shimada,

	(10) P.A. Aronov, L.M. Hall, K. Dettmer, C.B. Stephensen, and B.D. Hammock, 

The biologically active form of vitamin D is an important analytical target in both research and clinical practice.

A Sensitive and Cost-Effective LC–MS-MS Method for Determination of 1α,25-Dihydroxyvitamin D3 in Human Plasma

This study focuses on United States Environmental Protection Agency (US EPA) Method 524.3 for volatile organic compounds (VOCs) in water using gas chromatography–mass spectrometry (GC–MS). The GC sample introduction and separation technique specified by the EPA is purge and trap and the detector is MS. This article discusses optimizing MS and chromatographic separation parameters when using alternative carrier gases. In particular, it discusses the results of using nitrogen and hydrogen as alternate carrier gases to helium for EPA Method 524.3 for VOC analysis and specifically the impact of MS and chromatography parameters on the optimization process. Data are presented showing that nitrogen could be a more suitable carrier gas than hydrogen when compared to helium.

	The United States Environmental Protection Agency (US EPA) has established several methods to ensure safe and contaminant-free drinking water. One of these methods is described in EPA Method 524.3 (1), the determination of 75 volatile organic compounds (VOCs) using purge-and-trap sample concentration and gas chromatography (GC) coupled with mass spectrometry (MS). In this method, the volatile components are concentrated onto a trap, which is then heated to elute the compounds onto a GC column, typically using helium as a carrier gas, where they are separated and finally detected by MS. However, the concerns of a helium shortage and the significant increase in market prices have resulted in chromatographers investigating the use of other carrier gases to see if acceptable performance can be achieved. This article describes a suite of MS and chromatographic separation optimization experiments that were performed to better understand whether hydrogen and nitrogen can be used as alternative carrier gases to helium and, in particular, how they compare from a performance perspective when monitoring VOCs according to EPA Method 524.3.

What Are Some of the Challenges to Using Hydrogen and Nitrogen?

	Even though hydrogen has excellent chromatographic separation efficiency with the widest range of useful linear velocities when compared to other carrier gases, it is extremely reactive and poses a safety risk, and as a result may not be the most suitable choice. In addition, the pumping efficiency of hydrogen is less than that of helium. Pumping efficiency is an important consideration because a good vacuum is critical to minimize collisions between target analytes and the carrier gas during electron ionization (EI) spectral acquisition. Additional collisions may result in atypical EI spectrum for targets and degraded sensitivity, mass resolution, and linear dynamic range. Furthermore, collisions in the source between the analytes and hydrogen atoms present may result in protonation. For these reasons, there are concerns about meeting the method tuning criterion using hydrogen as the carrier gas.

	Nitrogen also has its challenges. The heavier nitrogen molecule may scatter the analyte ions to a greater degree in the ionization source and in the analyzer, and may degrade the detection limits for the same analyte masses compared to helium. Finally, nitrogen's narrower range of useful linear velocities than helium or hydrogen can be easily overcome by careful flow rate selection.

	Another concern with using nitrogen is that it is more easily ionized than helium and therefore changes the space charge conditions in the ion source. Ionization of nitrogen within the source can also reduce the number of electrons available to ionize target compounds. In addition, nitrogen can cause scattering of molecular target ions in the analyzer. Tuning MS conditions can help to alleviate some of these problems, but unfortunately it may also defocus the electron beam, which can lead to less efficient analyte ionization. All of these limitations can cause reduced sensitivity when switching from helium to nitrogen as a carrier gas. Table I shows a comparison of the three gases, with regard to a number of performance metrics.

	The goal of the study was to meet all EPA Method 524.3 validation protocols using hydrogen and nitrogen as carrier gases by overcoming the traditional limitations described previously. The drinking water method was chosen because it has the most aggressive detection limits of any of the EPA methods for VOCs. It was believed that low detection capability was the most critical challenge to overcome, and if Method 524.3 requirements could be met, performance metrics for other EPA methods could also be achieved.

	Using a 20 ppb Method 524.3 standard, GC–MS conditions were established that provided adequate target component resolution and comparable peak efficiency for nitrogen and hydrogen compared to the reference helium data. The purge-and-trap multimatrix sample preparation system (Atomx, Teledyne-Tekmar) conditions are listed in Table II; the GC–MS (Clarus SQ 8 GC–MS, PerkinElmer) conditions are shown in Table III.

	A narrow-bore column with a low flow rate was used, which reduced the amount of nitrogen and hydrogen molecules in the source. This approach resulted in improved vacuum efficiency, increased sensitivity, and reduced protonation, thus overcoming the mass spectral challenges of these carrier gases.

	To prove this concept an example is provided using nitrogen. Two columns were investigated. The first was a 20 m × 0.18 mm, 1-μm 

 Restek VMS column, coupled to a narrow-bore piece of deactivated fused silica. The VMS column offered excellent separation of the compounds of interest, and the deactivated fused silica offered the increased backpressure necessary to operate the inlet at the low flow rates being investigated. Since connectors can often bring ease of use issues, the method was also developed on a 40 m × 0.18 mm, 1-μm 

Restek VMS column. The 40-m length provided enough back pressure that the added fused silica was unnecessary. Figure 1 shows the total ion chromatograms (TIC) of the EPA Method 524.3 20 ppb test mix for each of the three carrier gases.


	Figure 1: TICs of the Method 524.3 20 ppb test mix for (a) helium, (b) hydrogen, and (c) nitrogen.

	To investigate the effect of reducing the amount of nitrogen in the source, the target compound intensities were compared using nitrogen column flow rates of 0.3, 0.4, 0.6, and 0.8 mL/min. Ultimately, 0.3 mL/min was selected as the nitrogen flow rate because it provided efficient peak widths and target compound separation at a vacuum of 1.8 × 10

	The EPA tuning criterion for bromofluorobenzene was met for each carrier gas before calibration and was also continuously verified during the experiments. The results are displayed in Table IV.

	EPA Method 524.3 allows the use of a first order, 1/

 weighted calibration, which was used in our analysis. Calibrations ranged from 0.2 μg/L to 40 μg/L for all three carrier gas studies. Seven concentration levels were used for the helium and hydrogen studies, and five concentration levels were used for the nitrogen study.

	The following additional experiments were carried out on all three carrier gases to ensure Method 524.3 initial demonstration of capability (IDC) was met:

		Recovery and precision of the midpoint standard was performed using the 20 ppb standard.

		The minimum reporting limits (MRL) of 0.2 ppb and 0.5 ppb were investigated by injecting seven replicates of each concentration to calculate the upper and lower limits for prediction interval of results (UPIR and LPIR, respectively).

		All concentration levels were processed as quality control (QC) checks using the respective calibration.

		A blank was analyzed after the high-level standard and several times during the experiments to ensure system cleanliness and determine if any carryover was occurring.

	Using the optimum linear velocity for nitrogen, the chromatographic performance is very similar to helium on both columns tested; therefore, chromatographically, nitrogen works for this method, as demonstrated by the TICs in Figure 1. Additionally, the tuning criteria were met using all three carrier gases as demonstrated in Table IV. Therefore, under these GC–MS conditions, hydrogen protonation is not a concern for bromofluorobenzene tuning.

	An increase in nitrogen flow rate resulted in a decrease in target response and an increase in the background of N

 42). This result suggests that the increase of nitrogen molecules in the source decreased the response of the target analyte compounds, which could be attributed to a combination of increased electron consumption by nitrogen ionization, resulting in reduced target analyte ionization, and increased collisions of nitrogen molecules and ions with the analytes.

	Further study is required to determine the cause of this decrease in response and will be the focus of future work.

	Calibrations were qualified as required under EPA Method 524.3 (section 10.1.10). Table V contains the correlation coefficients and the reporting limit results. The range of correlation coefficients was 0.9990–1.0000 across the components. In addition, Table V contains the signal-to-noise ratio (S/N) achieved at the reporting limit. Please note a shorter list of targets is tabulated for space requirements; however, the full list of 75 compounds is available in the on-line version of this article.


	Table V: Correlation coefficients, reporting limit results, and signal-to-noise ratios (S/N)

	The method precision and accuracy criteria in Method 524.3 for the midpoint standard are ±20% and 80–120%, respectively. The performance criteria for all three carriers at the midpoint were exceeded. The precision results on selected targets are presented in Table VI. The results for both UPIR and LPIR criteria, calculated using the MDL, which are a part of the EPA Method 524.3 IDC requirements (section 9.2), are also displayed in Table VI. The method limits for the UPIR and LPIR are from 50–150%.


	Table VI: Precision performance criteria for the midpoint standard and LPIR and UPIR requirements

	The MRL criteria for the 0.2 ppb concentration were met for all 75 target analytes using helium as a carrier gas. For nitrogen, 72 of the target analytes met these criteria for the 0.2 ppb concentration, whereas the three remaining targets met the criteria for a concentration of 0.5 ppb. For hydrogen, 67 of the target analytes met these criteria for the 0.2 ppb concentration, whereas the remaining eight targets met the criteria for the concentration of 0.5 ppb. Even though these exceptions met the ±50% criteria at the 0.2 ppb standard concentration, they did not meet the LPIR and UPIR criteria, so for those three targets in nitrogen and eight targets in hydrogen, an MRL of 0.5 ppb was chosen. Since the 0.2 ppb calibration point was linear, this point was maintained on the calibration.

	The results of this study show that by using optimized GC–MS conditions, hydrogen and nitrogen are appropriate to use as alternate carrier gases to helium for EPA Method 524.3 analysis. With these optimized conditions the sensitivity limitations of these two gases have been overcome. Since nitrogen is more inert, less expensive, and doesn't have the safety concerns of hydrogen, it is recommended as the superior option for helium carrier gas replacement.

	The authors acknowledge and thank Dr. Adam Patkin, PhD, Principal Applications Scientist at PerkinElmer Instruments for his expertise and understanding of mass spectrometry, and Brett Boyer, Senior Service Specialist at PerkinElmer Instruments for his expertise and help with this project.

 is with PerkinElmer Instruments in Shelton, Connecticut. 

Tom Hartlein, Jacob Rebholz, and Roger Bardsley

 are with Teledyne Tekmar in Mason, Ohio. 

This study focuses on United States Environmental Protection Agency (US EPA) Method 524.3 for volatile organic compounds (VOCs) in water using gas chromatography–mass spectrometry (GC–MS).

Special Issues-03-01-2015

Rapid Determination of 24 Synthetic and Natural Cannabinoids for LC–MS-MS Screening in Natural Products and Drug Inspection Applications

A Sensitive and Cost-Effective LC–MS-MS Method for Determination of 1α,25-Dihydroxyvitamin D3 in Human Plasma

An Investigation into the Use of Alternate Carrier Gases for the Determination of Volatile Organic Compounds in Water by GC–MS

Development of a Fast LC–MS-MS Screen for Common Drugs of Abuse as an Alternative to Immunoassay Screening

Vol 13 No 1 Current Trends in Mass Spectrometry March 2015 Issue PDF