A Full Evaporation Static Headspace Gas Chromatography Method with Nitrogen Phosphorous Detection for Ultrasensitive Analysis of Semi-volatile Nitrosamines in Pharmaceutical Products

The recent detection of potent carcinogenic nitrosamine impurities in several human medicines has triggered product recalls and interrupted the supply of critical medications for hundreds of millions of patients, illuminating the need for increased testing of nitrosamines in pharmaceutical products. However, the development of analytical methods for nitrosamine detection is challenging due to high sensitivity requirements, complex matrices, and the large number and variety of samples requiring testing. Herein, we report an analytical method for the analysis of a common nitrosamine, N-nitrosodimethylamine (NDMA), in pharmaceutical products using full evaporation static headspace gas chromatography with nitrogen phosphorous detection (FE-SHSGC-NPD). This method is sensitive, specific, accurate, and precise and has the potential to serve as a universal method for testing all semi-volatile nitrosamines across different drug products. Through elimination of the detrimental headspace-liquid partition, a quantitation limit of 0.25 ppb is achieved for NDMA, a significant improvement upon traditional LC-MS methods. The extraction of nitrosamines directly from solid sample not only simplifies the sample preparation procedure but also enables the method to be used for different products as is or with minor modifications, as demonstrated by the analysis of NDMA in 10+ pharmaceutical products. The in situ nitrosation that is commonly observed in GC methods for nitrosamine analysis was completely inhibited by the addition of a small volume solvent containing pyrogallol, phosphoric acid, and isopropanol. Employing simple procedures and low-cost instrumentation, this method can be implemented in any analytical laboratory for routine nitrosamine analysis, ensuring patient safety and uninterrupted supply of critical medications.

An insight into the botanical origins of propolis from permanent preservation and reforestation areas of southern Brazil

Brown propolis from permanent preservation and reforestation areas of southern Brazil have attracted international commercial interest and have a unique composition, although little is known about their botanical origins, which are the plant resins used by bee foragers to produce propolis. Hence, the volatile profiles of organic and non-organic brown propolis and resins of suspected botanical origins—Araucaria angustifolia, Pinus elliott and Pinus taeda—were determined using static headspace gas chromatography coupled to mass spectrometry (SHS-GCMS) and compared. Nighty nine volatiles were tentatively identified, and monoterpenes and sesquiterpenes were the most abundant classes. Principal component analysis (PCA) showed similarity between organic propolis and A. angustifolia volatile profiles (p < 0.05). Hierarchical clustering analysis showed singularities among propolis, even between propolis produced 1 km away from each other. Heatmaps were used to identify peaks present in similar relative intensities in both propolis and conifer resins. Hence, the approach using volatile profiles shed light to propolis botanical origins, which is important for authentication and traceability purposes.

Optimization of Residual Hexane in Edible Oils Analysis Using Static Headspace Gas Chromatography

This study aims to determine the residual hexane in four edible oils in Malaysia using a simple, rapid, and automated method in order to improve the efficiency and productivity of the analysis. Gas chromatography (GC/FID) equipped with a headspace autosampler (HS-20) was used to perform the analysis. Incubation time for each injection was successfully optimized from one hour to 30 minutes (50% reduction) compared to the official AOCS method Ca 3b-87. Out of the four tested edible oils, only the hexane residues detected in sunflower oil exceeded the maximum residue limit (MRL) set by the European Union regulation. Significant difference of the results obtained between large calibration range (0–938 mg kg−1) and small calibration range (0–68 mg kg−1) suggests that there is a need to use a lower standard calibration concentration to avoid misinterpretation of analysis results. Method validation applies to the technical hexane; 2-methylpentane, 3-methylpentane, cyclohexane, and methylcyclopentane, the signal-to-noise (S/N), as well as the limit of quantification (LoQ) values was found to be 218.20, 221.45, 746.37, 97.37 and 0.85, 0.84, 0.25, 1.93 mg kg−1, respectively. Good linearity, repeatability, and low carryover of this method have provided an alternative way to analyze the content of the residual hexane in edible oils in a more efficient manner. Current study might provide a fundamental reference for the improvement of the AOCS official Ca 3b-87 method for determination of hexane residues in fats and oils analysis in the future.

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. Potential pitfalls that would cause inaccurate quantification i.e., effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against a currently established method, namely, GC-MS, using actual wine samples. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.

An Insight into the Botanical Origins of Propolis from Permanent Preservation and Reforestation Areas of Southern Brazil

Brown propolis from permanent preservation and reforestation areas of southern Brazil have attracted international commercial interest and have a unique composition, although little is known about their botanical origins, which are the plant resins used by bee foragers to produce propolis. Hence, the volatile profiles of organic and non-organic brown propolis and resins of suspected botanical origins – Araucaria angustifolia, Pinus elliott and Pinus taeda – were determined using static headspace gas chromatography coupled to mass spectrometry (SHS-GCMS) and compared. Nighty nine volatiles were tentatively identified, and monoterpenes and sesquiterpenes were the most abundant classes. Principal component analysis (PCA) showed similarity between organic propolis and A. angustifolia volatile profiles (p < 0.05). Hierarchical clustering analysis showed singularities among propolis, even between propolis produced 1 km away from each other. Heatmaps were used to identify peaks present in similar relative intensities in both propolis and conifer resins. Hence, the approach using volatile profiles shed light to propolis botanical origins, which is important for authentication and traceability purposes.

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

<p>A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.</p>

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

<p>A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.</p>