Ion-Pairing Hydrophilic Interaction Chromatography for Impurity Profiling of Therapeutic Phosphorothioated Oligonucleotides

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 20th October 2025? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you applicaton notes by <strong>Agilent Technologies, EST Analytical, Shimadzu </strong>and <strong>Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: FAMEs Analysis of Oils by GC-FID Coupled with Fully Automated Sample Preparation using a PAL3 Series 2 RTC</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_fame_oil_gc_pal3_5994_8543en_agilent_418da94d17.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The analysis of fatty acid methyl esters (FAMEs) is a widely used technique for characterizing lipid profiles in various food products, including oils, meats, and seeds. Fats are composed of a complex mixture of saturated, monounsaturated, and polyunsaturated fatty acids, each with varying carbon chain lengths.2 This type of analysis is routinely performed in governmental, quality control (QC), and contract research laboratories worldwide. The resulting data often informs product labeling. Among the analytical techniques available, gas chromatography (GC) with flame ionization detection (GC-FID) is one of the most common methods for determining fatty acid composition in&nbsp;foods.&nbsp;</p><p>This application note describes the use of automated sample preparation and analysis of FAMEs using the PAL3 Series&nbsp;2 RTC Autosampler system coupled with Agilent 8890 GC system equipped with an FID. The results shown here focus on two different methods of derivatization for FAMEs extraction: (1) base catalyzed reactions using potassium hydroxide (KOH) (part&nbsp;number M5795-14000) and (2) base plus acid catalyzed reactions using boron trifluoride (BF3 ) 1 (part number M5795-14001). For ease of use, both processes have been transcribed into dedicated sample preparation methods. These methods are part of the Agilent automated sample preparation workflow suite of solutions. These workflows improve process safety, optimizes throughput, and minimizes&nbsp;errors.</p><h4><strong>Experimental&nbsp;</strong></h4><p>The 37 component FAME mix standard was purchased from Sigma-Aldrich (part number CRM47885), and three consumer oil products were purchased from a local grocery store. The samples were prepared and injected into the GC using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3"><strong>PAL3 Series 2-RTC system</strong></a>. The analysis was performed using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC"><strong>8890 GC</strong></a> equipped with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=DB%E2%80%91FastFAME"><strong>Agilent DB‑FastFAME GC column</strong></a>, 30&nbsp;m × 250 µm, 0.25&nbsp;µm, (part number G3903‑63011) and configured with an FID using Agilent&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS+v2.7"><strong>OpenLab CDS v2.7+</strong></a>.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In summary, the current study demonstrated excellent reproducibility and accuracy using automated sample preparation and analysis of FAMEs. Two different sample preparation methods were demonstrated, both delivering comparable and reliable results. The base-catalyzed method enables rapid analysis but is not suitable for samples containing free fatty acids. In contrast, the acid-catalyzed method, while more extensive, is compatible with a broader range of lipid classes, including free fatty acids, phosphoglycerides, and triglycerides. The Agilent automated sample preparation workflow suite of solutions deliver a comprehensive package by combining preconfigured hardware, optimized analytical methods, and the necessary consumables to ensure efficient and reliable results.</p><h3><strong>2. EST Analytical: Unregulated Contaminant Monitoring Rule 3 for USEPA Method 524.3 and 524.4</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/Purge_and_Trap_Unregulated_Contaminant_Monitoring_Rule_3_for_USEPA_Method_524_3_and_524_4_b774e6ab4c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The third Unregulated Contaminant Monitoring Rule (UCMR 3) was finalized in April of 2012. UCMR 3 requires public water systems to monitor for a specific list of 30 contaminants under three separate lists: list one, assessment monitoring, list two, screening survey, and list three, pre-screen testing. This application note will address the volatile organic compounds found in list one, assessment monitoring contaminants. USEPA Method 524.3 and 524.4 will be the methods evaluated for sampling and analysis.</p><h4><strong>Discussion&nbsp;</strong></h4><p>The amendments to the Safe Drinking Water Act (SDWA) require the EPA to list no more than 30 unregulated contaminants to be monitored by public water systems. Every five years, this list needs to be updated. List one contaminants include seven volatile organic compounds to be analyzed by USEPA Method 524.3. The detection limits for these compounds are much lower; therefore, Single Ion Monitoring (SIM) must be used for compound detection. USEPA Method 524.3 and 524.4 allow for modification of purge and trap parameters in order to take advantage of purge and trap improvements. Thus, method parameters can be modified in order to optimize purge and trap cycle times. Since the purge and trap parameters were established for these methods previously, refer to application note Drinking Water Analysis Conditions for USEPA Method 524.3 and the Newly Proposed Method 524.4, purge and trap method development was not required for this application. For this study, Helium and Nitrogen purge gases were compared utilizing the same purge volume then comparing experimental results for the linearity, precision, accuracy and overall compound response for the low level requirements set by UCMR 3.&nbsp;</p><h4><strong>Experimental&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2160"><strong>EST Analytical Encon Evolution purge and trap concentrator</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2159"><strong>Centurion WS autosampler </strong></a>were interfaced to an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7890%2F5975"><strong>Agilent 7890/5975 GC/MS</strong></a>. The purge and trap concentrator was configured with a Vocarb 3000 (K) analytical trap. A chiller unit capable of keeping the sample vials cooled below 10°C was installed on the Centurion WS autosampler. The experimental parameters are listed in Tables 1 and 2.</p><h4><strong>Conclusion</strong></h4><p>The Encon Evolution and Centurion WS in conjunction with the Agilent 7890/5975 GC/MS performed very well using both the Helium and Nitrogen purge gases and employing SIM for compound detection. The Nitrogen and the Helium purge gases met USEPA Method 524.3 curve linearity criteria and produced comparable results for precision and accuracy at the low and mid-levels of the calibration curve. Overall, the principal difference between the two purge gases was exhibited in the compound response. When examining the overall compound response factors over the curve range, it is evident that the analytes’ responses are slightly lower with the Nitrogen purge gas as opposed to the Helium purge gas.</p><h3><strong>3. Shimadzu: Comparison of Metabolites in Rice from Different Production Areas Using GC-MS/MS</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01000_en_9c1d7cfe70.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Metabolomics is a research method for comprehensively analyzing metabolites contained in an organism. It is used for a wide variety of fields, such as medical science and food. Because food quality is affected by many components complexly, comprehensive analysis of metabolites can help improve food development and manufacturing processes. Rice contains metabolites, such as sugars, amino acids, and fatty acids. In recent years, development of more flavorful rice has been studied.&nbsp;</p><p>This article describes simultaneous analysis of 502 metabolites and multivariate analysis of a variety of rice from different production areas. The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-TQ8040+NX"><strong>GCMS-TQ8040 NX</strong></a> with the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Smart+Metabolites+Database+ver.+2"><strong>Smart Metabolites Database Ver. 2</strong></a> was used for measurement. <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=LabSolutions+Insight"><strong>LabSolutions Insight </strong></a>was used for data processing, and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=eMSTAT+Solution"><strong>eMSTAT Solution</strong></a> was used for multivariate analysis. The process flow, from pretreatment to data analysis, is shown in Fig. 1.</p><h4><strong>eMSTAT Solution&nbsp;</strong></h4><p>eMSTAT Solution is statistical analysis software that enables multivariate and discriminant analysis of chromatogram data. For multivariate analysis, it can discriminate between samples, and it can search for the marker peaks that contribute to those differences. For discriminant analysis, it can create a discriminant model based on training data and use the model for discriminant analysis. Users can easily switch both modes with just a single click. Workflow of the data analysis is shown in Fig. 2.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Metabolites in same variety of rice from different production areas were analyzed, and the differences between samples were identified by multivariate analysis. Score plots were used to visualize differences between the samples, and loading plots were used to confirm the characteristic compounds. Smart Metabolites Database Ver. 2, LabSolutions Insight, and eMSTAT Solution make metabolites analysis, data processing, and multivariate analysis easy for beginner users.</p><h3><strong>4. Thermo Fisher Scientific: Automated, multi-parameter gasoline characterization using GC-VUV and ASTM D8071</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_003957_gc_vuv_trace_1610_vga_industrial_an003957_na_en_3c0a64e3b2.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Gasoline is a complex hydrocarbon blend whose composition directly impacts combustion behavior, emissions, and regulatory compliance. Accurately quantifying components such as aromatics, olefins, ethanol, and benzene is critical, but traditional ASTM methods require multiple techniques (FIA, GC-FID, GC-MS, etc.) to measure all relevant parameters. Table 1 summarizes several test methods and their respective scopes.&nbsp;</p><p>ASTM D8071 introduces a consolidated method using GC-VUV, offering improved precision, spectral resolution, and reduced operational burden. This approach is now recognized as an EPA- and CARB-approved alternative to several legacy test methods, including ASTM D1319, D5599, D5769, and D3606.</p><h4><strong>Experimental&nbsp;</strong></h4><p>Gasoline samples were analyzed on the VUV Analyzer Platform for Fuels with no sample preparation required. The VUV Analyzer consists of the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/486"><strong>Thermo Scientific™ TRACE™ 1610 gas chromatograph</strong></a> coupled to the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=3&amp;search=VGA-100"><strong>VGA-100™ spectrometer detector </strong></a>(VUV Analytics, Inc.).&nbsp;</p><p>Data are acquired and processed with the VUVision™ Software and VUV Analyze™ Software (VUV Analytics, Inc), respectively, specifically configured to run ASTM D8071.&nbsp;</p><h5><strong>Workflow overview&nbsp;</strong></h5><p>The VUV Analyzer Platform for Fuels performs gasoline PIONA class analysis using a streamlined five-step workflow:&nbsp;</p><ol><li>System validation – Verifies instrument performance using standard hydrocarbons.&nbsp;</li><li>Sample prep – No preparation required.&nbsp;</li><li>Data acquisition – Performed using VUVision Software.&nbsp;</li><li>Spectral matching – Automated deconvolution with VUV Analyze Software.&nbsp;</li><li>Quantitation – Volume % and mass % calculated with high accuracy using built-in response factors and density data.</li></ol><h4><strong>Conclusion&nbsp;</strong></h4><p>GC-VUV with ASTM D8071 enables complete hydrocarbon group and compound-level analysis of gasoline in a single method. Its ability to automate spectral deconvolution and report mass and volume percentages simplifies operations while meeting strict compliance standards. This solution not only enhances analytical accuracy and repeatability but also drastically reduces operating costs and lab complexity.&nbsp;</p><ul><li>Short analysis time with full gasoline class and compound profiling in 34 minutes&nbsp;</li><li>Faster throughput with full automation from injection to reporting&nbsp;</li><li>12× lower cost-per-analysis, due to reduced labor, no calibration standards, and consolidated workflow</li></ul>

News from LabRulezGCMS Library - Week 43, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 29th December 2025? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies </strong>and<strong> Shimadzu!</strong></p><h3><strong>1. Agilent Technologies: Fatty Acid Methyl Ester Analysis Using the Agilent 8850 GC System</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_fame_analysis_8850_gc_5994_8743en_agilent_2bed33b70d.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Fatty acids are components of fat and are an essential component of a healthy diet. They are found in a variety of foods, including oily fish, nuts, seeds, and vegetable oils. Fatty acids can be categorized as saturated fat, monounsaturated fat, polyunsaturated fat (including omega-3 and omega-6 fatty acids), and trans fat. Unsaturated fatty acids play a beneficial role in maintaining heart and vascular performance. However, artificial trans fatty acids, found in processed foods, should be strictly limited. The measurement of fatty acids in food plays an important role in:</p><ul><li><strong>Nutritional assessment: </strong>Analyzing the omega-3/omega-6 ratio for dietary nutrient balance&nbsp;</li><li><strong>Safety regulation: </strong>Identifying health risks such as trans fatty acids&nbsp;</li><li><strong>Quality control: </strong>Detecting oil adulteration and process&nbsp;defects&nbsp;</li><li><strong>R&amp;D support:</strong> Providing data support for the development of functional foods&nbsp;</li></ul><p>Techniques available for fatty acid determination in food include gas chromatography, liquid chromatography, and spectroscopic techniques. Each technique has its own advantages, disadvantages, and applicable scenarios. For example, liquid chromatography is suitable for analyzing heat-labile fatty acids, but it suffers from low resolution. Fluorescence spectroscopy is simple to operate but susceptible to matrix effects and poor specificity. Gas chromatography is the most used technique for fatty acid measurement. Fatty acids in food primarily exist in the form of triglycerides. Before analysis, triglycerides must be extracted, saponified, and methylated to the corresponding FAMEs. FAMEs are less polar and more volatile than fatty acids, making them suitable for analysis on gas chromatography platforms. Polar columns, such as those with polyethylene glycol and cyanopropyl siloxane stationary phases, are primarily used for the FAMEs analysis. Polyethylene glycol stationary phases are good at analyzing simple fatty acid mixtures and are not suitable for the analysis of cis-trans isomers. A column coated with high‑content cyanopropyl phase is recommended in different analytical methods for FAMEs analysis. However, an analysis based on this phase type usually takes more than 70 minutes to finish, and the retention time (RT) stability is not very good. The Agilent J&amp;W DB-FastFAME column features a modified cyanopropyl phase to accelerate the analysis and improve&nbsp;repeatability.&nbsp;</p><p>Agilent offers DB-FastFAME columns in different dimensions; the 20-meter and 30-meter sizes can help improve the analysis speed for 37 representative FAMEs in food. Previous work demonstrated the analysis speed improvement using the conventional oven ramp rate on the two columns.<sup>1</sup> With the launch of the Agilent 8850 GC, rapid temperature programming can be achieved in an air bath oven. This application note demonstrates the fast analysis of 37 FAMEs using nitrogen (N2 ) and helium (He) carrier gases on the 8850&nbsp;GC. Meanwhile, more complex FAME mixtures including 37&nbsp;FAMEs and 15 trans FAMEs were analyzed on a 90-meter DB-FastFAME column and a 100-meter Agilent J&amp;W HP-88 column to demonstrate the 8850 GC performance in cis/trans FAMEs and position isomers analysis.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>An <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8850+GC"><strong>8850 GC system </strong></a>equipped with a split/splitless inlet and a flame ionization detector (FID) was used for the analysis. An <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7650A"><strong>Agilent 7650A automatic liquid sampler (ALS)</strong></a> (part&nbsp;number&nbsp;G4567A) was applied for sample injection.&nbsp;</p><p>The methods performed on the four analytical columns using He and N2 carrier gases are listed in Table 1. The settings on inlet and detector temperatures are the same. The column head pressure and the oven temperature program were optimized based on the column type and carrier gas. Data were acquired and processed using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS"><strong>Agilent OpenLab CDS</strong></a> 2.8. The list of consumables used is shown in Table 2.</p><h4><strong>Results and discussion&nbsp;</strong></h4><h5><strong>Fast analysis of 37 fatty acid methyl esters on short&nbsp;columns&nbsp;</strong></h5><p>The 37 FAMEs mimic the fatty acid composition of many food samples, including most of the important saturated, monounsaturated, and polyunsaturated FAMEs. They are well‑established and widely accepted reference materials.&nbsp;</p><p>A 20 m × 0.18 mm&nbsp;id, 0.2&nbsp;µm DB-FastFAME&nbsp;column and a 30&nbsp;m × 0.25 mm&nbsp;id, 0.25 µm DB-FastFAME&nbsp;column were used to demonstrate the high-speed analysis of 37 FAMEs on the 8850 GC. The oven ramp program and column flow rate were based on previous work and further optimized for the 8850 GC. Both He and N2 carrier gas-based methods were developed considering the increasing alternative carrier gas need and lab operation habits in different regions.&nbsp;</p><p>The GC-FID chromatograms obtained on the two columns using different carrier gases are shown in Figures 1A, 1B, 2A, and 2B. All compounds were well resolved in the He methods. Three compound pairs that cannot be baseline-separated are shown in black squares. Among them, the peaks of c22:2n6 and c23:0 had the lowest resolution of 1.27 and 1.31 on the 20-meter and 30-meter columns, respectively, using the He method. The AOAC International Method 996.062 requires separating the FAME pair of adjacent peaks of C18:3 and C20:1 and the FAME trio of adjacent peaks of C22:1, C20:3, and C20:4 with a resolution of 1.0 or greater. This requirement is mainly recommended for high-content cyanopropyl 4 stationary phases. The six probe FAMEs eluted in different orders on the DB-FastFAME column, as marked by the yellow squares in the chromatogram. Their separation exceeded the resolution requirement easily due to the DB-FastFAME column's unique selectivity. The analysis times of the He methods were less than 7 minutes and 10 minutes on the two columns. The analysis speed was five to eight times faster than that of conventional methods.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>A high-speed FAMEs analysis was achieved on an Agilent&nbsp;8850 GC system with excellent repeatability when running the FAMEs standards on specially engineered 20-meter and 30-meter Agilent J&amp;W DB-FastFAME columns under optimized oven programs. The analysis time is less than 10&nbsp;minutes using He carrier gas and less than 15&nbsp;minutes using N2 carrier gas, which is five to eight times faster than the conventional method. Peak resolutions obtained by the fast methods met the AOAC 996.06 standard requirements. The methods can help improve lab productivity significantly for routine analysis of 37 FAMEs.&nbsp;</p><p>The analysis of 52 FAMEs on 90-meter DB-FastFAME and 100-meter Agilent J&amp;W HP-88 columns demonstrated that the 8850 GC can deliver performance equivalent to the Agilent 8890 GC system when analyzing complex fatty acids—including cis/trans fatty acids and positional isomers— in terms of resolution, area repeatability (&lt; 2.5%), and RT&nbsp;precision (&lt; 0.04%).</p><h3><strong>2. Shimadzu: Quantification of 8 Disinfection Byproducts from Water by Liquid-Liquid Extraction and Gas Chromatography-MassSpectrometry</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_07_2507_en_52b8f30f0c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Disinfectants such as chlorine and chloramine are widely used to eliminate microorganisms in water. However, these disinfectants react with naturally occurring chemical constituents, such as amino acids and other labile organic chemicals, forming a range of disinfection byproducts (DBPs). Chronic exposure to DBPs elevates the risk of developing cancer, liver damage, and decreased nervous system activity. Hence, accurate detection and quantification of DBPs in water is crucial.&nbsp;</p><p>Although official recommended method for measuring DBPs is based on GC/ECD, GC/MS offers significant advantages in terms of simultaneous quantification and identification of both known and unknown compounds in a single analysis, providing comprehensive data on complex water samples. Unlike ECD, which has a limited dynamic range and can only detect electroactive compounds, MS offers a broader dynamic range, allowing the detection of analytes at varying concentrations. Additionally, GC/MS provides superior sensitivity, specificity, and structural information, making it the ideal method for detailed, high-precision analysis of disinfection byproducts and other water contaminants.</p><h4><strong>2.2. Analytical Conditions</strong></h4><h5><strong>Preparation of instrument and analysis:</strong></h5><p>The analytical method was established, and the instrument parameters are detailed in Table 1. Prior to the analysis, both the instrument and the column were conditioned. The “HighSensitivity” autotune mode of the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2020+NX"><strong>GCMS-QP2020 NX</strong></a> was used for the analysis. A standard solution containing 500 ppb of the target analytes, surrogate, and internal standard was injected using the MS fullscan mode to determine the retention times.</p><p>The peaks corresponding to the target compounds, internal standard, and surrogate were identified using the NIST GC/MS library. Quantifier and qualifier ions for each analyte were selected, and a compound table was created accordingly and the same was used to develop a Scan/SIM method using the “Creation of Automatic Scan/SIM Table” (COAST) wizard within the GCMSsolutionTM software. The ultra-fast scanning capability (20,000 u/s) of the GCMS-QP2020 NX enables simultaneous acquisition of Scan and SIM events without compromising data quality.&nbsp;</p><p>The newly created Scan/SIM method was used for the quantification and reporting of analytical data. Calibration standards were analyzed. The data and the calibration curve, using the internal standard method, were processed using LabSolutions InsightTM software which enables the analysis of large numbers of data simultaneously. Following this, both the unspiked and spiked (5 ppb) samples were analyzed and quantified.</p><h4><strong>3. Result and Discussion</strong></h4><p>A 6-point calibration curve was created for all target analytes. A good linear response, with correlation coefficients (r²) greater than 0.99, and accuracy within 80-120% was observed for all analytes. A signal-to-noise ratio (S/N) ≥ 10 was observed for all analytes at 5 ppb standard. The results are shown in Table 2.</p><h4><strong>4. Conclusion</strong></h4><ul><li>A highly sensitive GC/MS method was developed for 8 halogenated DBPs using Shimadzu GCMS-QP2020 NX following USEPA 551.1 sample preparation protocol.&nbsp;</li><li>Excellent linearity results and recovery results at 5.0 ppb concentration for all the analytes demonstrate that the analytical workflow is suitable for analyzing the listed DBPs in tap water using GC/MS technique at a low concentration level.</li></ul>

News from LabRulezGCMS Library - Week 53, 2025

News from LabRulezLCMS Library - Week 53, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 12th January 2026? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies, Shimadzu, Waters Corporation </strong>and poster by<strong> Thermo Fisher Scientific / HPLC!</strong></p><h3><strong>1. Agilent Technologies: B Vitamin Analysis in Dietary Supplements on the Agilent 1290 Infinity III LC System</strong></h3><p><strong>Using ion-pairing reagent and supported by time‑saving automation of routine tasks using the Agilent InfinityLab Assist</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_b_vitamin_dietary_supplements_1290_infinityiii_lc_5994_8826en_agilent_56b5eb2fb1.pdf"><strong>Full PDF for download</strong></a></li></ul><p>There is a huge variety of (multi)vitamin supplements on the market, with different vitamin combinations and different concentrations available. To ensure that the claimed vitamin contents are met, analysis of those supplements is&nbsp;necessary.&nbsp;</p><p>To ensure constant and good analytical performance, preparation of the analytical system is fundamental. There are different approaches to preparing the system for analysis. Purging the solvent lines from bottle to pump removes possible air bubbles, especially after longer breaks between instrument usage or changing eluent to the ion-pairing and buffer-containing eluent after the weekend. Equilibration can either be done by a calculated time (10–20 column volumes)1 , set as a fixed experimentally determined value, or manually monitored. Using a fixed time for equilibration can lead to unnecessary high solvent consumption, as equilibration may already be established and no monitoring was previously done. In contrast, manual monitoring of equilibration can be time-consuming and error-prone. For example, if there are no written rules regarding key points for equilibration of the column, its determination can be subjective (constant&nbsp;pressure and baseline of e.g. UV absorption).&nbsp;</p><p>As vitamins are grouped according to their water solubility and not their chemical structure, separation behavior can greatly differ as they have different charges at physiological pH. In such cases, ion-pairing reagents such as hexane sulfonic acid can enable the separation of those vitamins while using a reversed phase column. As ion-pairing LC depends on good equilibration to ensure the presence of ion‑pairing reagent within the system, the process of preparing the instrument is an inevitable step. This is essential for good and reproducible analytical results.&nbsp;</p><p>With the Agilent InfinityLab Assist, making your instrument ready is no longer a time-consuming and unpleasant procedure.<sup>1</sup> This application note demonstrates the separation of multiple B vitamins in multivitamin tablets and effervescent tablets using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?search=1290+Infinity+III"><strong>Agilent 1290 Infinity III LC System</strong></a>. Furthermore, it is shown how the InfinityLab Assist can help users ensure good chromatographic results, save time, and reduce errors by replacing manual tasks with InfinityLab Assist tasks.&nbsp;</p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Equipment&nbsp;</strong></h5><ul><li>Agilent 1290 Infinity III High-Speed Pump (G7120A)&nbsp;</li><li>Agilent 1290 Infinity III Multisampler (G7167B) with Agilent InfinityLab Sample Thermostat (G4761A)&nbsp;</li><li>Agilent 1290 Infinity III Multicolumn Thermostat (G7116B) with Agilent InfinityLab Quick Connect Heat Exchanger (G7116-60015)&nbsp;</li><li>Agilent InfinityLab Level Sensing (G7175A)&nbsp;</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=InfinityLab+Assist"><strong>Agilent InfinityLab Assist</strong></a> (G7180A) with Agilent InfinityLab Assist Control Software, version 2.0&nbsp;</li><li>Agilent 1290 Infinity III Diode Array Detector (G7117B) with Agilent InfinityLab Max-Light Cartridge Cell (10 mm, 1.0 µL, G4212-60008)&nbsp;</li></ul><h5><strong>Software&nbsp;</strong></h5><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS"><strong>Agilent OpenLab CDS,</strong></a> version 2.8, update 7 (or later versions)&nbsp;</li></ul><h5><strong>Column&nbsp;</strong></h5><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=InfinityLab+Poroshell+120+EC-C18"><strong>Agilent InfinityLab Poroshell 120 EC-C18</strong></a>, 2.1&nbsp;mm × 100 mm, 2.7 µm column (p/n 695775-902).</li></ul><h4><strong>Results and discussion&nbsp;</strong></h4><h5><strong>Separation of vitamin B1, B2, B5, B9, and B12&nbsp;</strong></h5><p>To analyze vitamin B1, B2, B5, B6, B7, B9, and B12 in vitamin supplements, different columns, mobile phases, and gradients were evaluated. The selected chromatographic conditions (Table 1) showed the best separation from peak to peak and additional matrix peaks. Hexane sulfonate was needed as an ion-pairing reagent to ensure good peak shapes, as all vitamins investigated, except vitamin B12, are expected to be charged based on their pKa values.3 The method detects the B vitamins investigated in vitamin tablets and effervescent tablets as demonstrated in Figure 1, showing chromatograms of aqueous standards and real samples. As some vitamins are present at higher doses, such as the 12 mg tablet (vitamin&nbsp;B5) compared to the 2.5 µg tablet (B12) in supplement 3 (Figure 1), parallel analysis is rather difficult, and not all vitamins present were detectable in each&nbsp;supplement.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Using the Agilent 1290 Infinity III LC System setup detection of vitamins B1, B2, B5, B6, B7, B9, and B12 in effervescent tablets and multivitamin supplement matrix, good separation was achieved. Using the Agilent InfinityLab Assist "Make&nbsp;Ready" task, the system was prepared for B vitamin analysis using only one automated task and no manual monitoring. Running this task automatically by scheduling saved more than 20 minutes of working time. Additionally, the time required for medium equilibration monitoring sensitivity was reduced by approximately six minutes, compared to manual equilibration. Furthermore, using the schedulable InfinityLab Assist "Standby" task, the risk of errors regarding instrument standby can be drastically reduced. User-defined settings enable adjustment for different purposes, such as switching of all modules except the sampler thermostat.<sup>2</sup> The ability to remove the used buffer and ion-pairing reagent from the flow path for longer storage by scheduling a standby task also greatly helps to prevent salt precipitation in the system without additional effort. Also, the InfinityLab Assist can clearly help to accelerate checking the instrument status while preparing the instrument, as well as during running&nbsp;samples.<sup>2</sup></p><h3><strong>2. Shimadzu: Analysis of Ammonia as an Impurity in Fuel Cell Grade Hydrogen According to ISO 14687 Grade D Using a Gas Generator</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01070_en_43a535bf87.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Hydrogen is expected to be a new power and heat source to reduce greenhouse gas emissions. Hydrogen is an easily available substance that can be produced from the electrolysis of water in our daily lives. However, when used in fuel cells, it is necessary to control impurities in hydrogen gas because certain impurities introduced during the manufacturing process deteriorate the electrode and electrolyte membrane, reducing the performance of the fuel cell or shortening its life. When ammonia is used as a carrier of hydrogen gas due to its distribution as a chemical, there is a possibility that ammonia may be introduced into hydrogen. This article presents an example of analysis of ammonia in hydrogen using an ion chromatograph (IC) based on the standard values described in ISO 14687 Grade D.<sup>1)</sup></p><h4><strong>Analysis of Ammonium Ion by IC</strong></h4><p>A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=HIC-NS"><strong>non-suppressor IC (HIC-NS)</strong></a> was used to analyze NH<sub>4</sub>. Since the IC can selectively measure ions dissolved in the sample, it is less affected by contaminants than other methods and can measure NH<sub>4</sub> with high accuracy. In addition, by using the same device together with a suppressor IC, it is possible to measure inorganic halogens and formic acid, which are other impurities listed in ISO 14687. Table 1 shows the analytical conditions for NH<sub>4</sub>, Fig. 2 shows the chromatogram of a standard sample at a concentration near the specified value (25 μg/L), and Fig. 3 shows the calibration curve in the range from 2.5 μg/L to 200 μg/L. As shown in Fig. 3, the linearity was greater than 0.9999. Table 2 shows the reproducibility of the sample at 10 μg/L, which is around 1/2 of the specified concentration, repeated 7 times.</p><h4><strong>Conclusion</strong></h4><p>Ammonia, an impurity in hydrogen, was analyzed using a nonsuppressor IC, and it was confirmed that the method met the standard value specified by ISO 14687 Grade D. In addition, when ammonia standard gas near the standard value was mixed into hydrogen using a gas generator, a good recovery rate was obtained, which confirmed the validity of the method including the collection flow of pretreatment.</p><h3><strong>3. Thermo Fisher Scientific / HPLC: High-sensitive multi-attribute analysis of ADCs under native conditions by using an online multiple heart-cut 2D-LC-HRAM mass spectrometry system</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_high_sensitive_multi_attribute_analysis_adcs_native_conditions_po_en_28e7e0b002.pdf"><strong>Full PDF for download</strong></a></li></ul><p>ADCs are a rapidly expanding class of biotherapeutics for cancer treatment. Critical quality attributes such as charge heterogeneity, DAR, and drug distribution are essential for ensuring the safety, stability, and efficacy of ADCs. Strong cation exchange (SCX) and hydrophobic interaction chromatography (HIC) are conventional methods employed for charge variant analysis and DAR determination of ADCs1. However, these methods frequently utilize MS-incompatible salts, limiting their use for MS characterization. Online 2D-LC addresses this by enabling desalting in the second dimension(2D) and offering multi-attribute analysis in one method. Here, multiple heart-cut 2D-LC-HRAM MS methods were developed to achieve high sensitivity for the multi-attribute analysis of polatuzumab vedotin under native conditions.</p><h4><strong>Methods</strong></h4><p>A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/742"><strong>Thermo Scientific Vanquish 2D UHPLC system</strong></a>, coupled with a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/402"><strong>Thermo Scientific Orbitrap Exploris 240 mass spectrometer</strong></a> with Biopharma option, were utilized to configure the multiple heart-cut 2D-LC-HRAM MS system. HIC-SEC and SCXSEC methods were developed and optimized for the charge variants, drug-to-antibody ratio (DAR) and drug load distribution (DLD) characterization of ADCs under native conditions.</p><h4><strong>Conclusions&nbsp;</strong></h4><p>In this study, an online multiple heart-cut 2D-LC-HRAM MS system was configured and optimized for the multi-attribute analysis of polatuzumab vedotin. This approach provides detailed and comprehensive insights into the charge heterogeneity analysis, DAR, and DLD analysis of polatuzumab vedotin under native conditions.&nbsp;</p><ul><li>The online multiple heart-cut 2D-LC system enables the direct transfer of SCX and HIC fractions to mass spectrometry analysis by utilizing SEC as a desalting step, thereby overcoming the MS-incompatibility buffer in the LC separation.&nbsp;</li><li>The backflush transfer of fractions was employed to enhance peak shape and sensitivity in the 2D SEC separation.&nbsp;</li><li>The 2D SEC-MS analysis enables the characterization of ADCs under native conditions.&nbsp;</li><li>The high sensitivity of the Orbitrap Exploris 240 MS allows for the identification of fractions with low abundance in the 1D chromatography</li></ul><h3><strong>4. Waters Corporation: Automated Multiple Reaction Monitoring (MRM) Method Development for Peptide Drugs Using waters_connect for Quantitation Software</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009123_en_1f51e50be8.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>Benefits&nbsp;</strong></h5><ul><li>Rapid evaluation and optimization of MRM conditions freeing up bioanalysts to perform other valuable tasks</li><li>Interactive graphical review of results facilitating informed decision making.&nbsp;</li><li>Elimination of transcription errors via direct transfer of MRM results to the LC-MS method editor.</li></ul><p>LC-MS/MS is the technology of choice for the quantification of drugs, metabolites, and biomarkers in biofluids, typically employing tandem quadrupole mass spectrometry (MS) with detection via MRM. MRM method development for classic small molecule drugs involves the selection of the best precursor and product ion followed by optimization of cone voltages and collision energies. This is achieved by infusion or LC injection of the analyte(s) of interest. For small molecule drug compounds, this process is usually straightforward and lends itself to automation as they largely generate singly charged ions. However, in electrospray mass spectrometry, biomolecules such as peptides, oligonucleotides, and proteins normally form several multiply charged precursor ions, e.g., M+3H3+, M+4H4+. This significantly complicates MRM method development, as each charge state can generate multiple fragment ions, all of which need to be compared both within and across each charge state to choose the best transition or transitions for analyte measurement.&nbsp;</p><p>The MRM Optimization tool with the waters_connect for Quantification Software has been specifically designed to address the challenge of MRM method development for multiply charged biomolecules. The Optimization tool facilitates the automatic acquisition of data from multiple precursor and product ion and collision energy combinations across several charge states, with the results reviewed via an interactive graphical interface. Here, the use of this optimization is illustrated, using the GLP-1 peptide, semaglutide, as an example.</p><h4><strong>Experimental</strong></h4><h5><strong>Mass Spectrometry</strong></h5><p>Mass spectrometry was performed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2100"><strong>Waters Xevo™ TQ Absolute XR Mass Spectrometer</strong></a>, operated in positive ion electrospray ionization mode (ESI). Nitrogen was used as the nebulizer gas and argon as the collision gas. The cone voltage, collision energy, and MS/MS transitions were adjusted and evaluated using the waters_connect MRM Optimization tool.</p><h5><strong>Informatics&nbsp;</strong></h5><p>The mass spectrometer was controlled and resulting data evaluated using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1544"><strong>waters_connect for Quantitation</strong></a> Application Manager version 1.9.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The number of candidate biomolecule drugs, peptides, oligonucleotides, and proteins in pharmaceutical discovery and development is steadily increasing. These biomolecules require the development of quantitative LC-MS/MS assays to support discovery, preclinical, and human DMPK studies. Unlike small molecules, these biomolecules form multiply charged ions in the MS source, making MRM method development more challenging, as multiple charge state–product ion combinations must be evaluated and compared. The Optimization tool in waters_connect for Quantitation Software provides an automated, fast platform for the optimization and evaluation of the precursor ion → product ion pairs formed at each charge state, simplifying the process of LCMS/MS method development for biomolecules.</p>

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