<p><strong>In the research article recently published in ACS <em>Analytical Chemistry</em> journal the researchers Weier Hao and Daniel B. Cardin from Entech Instruments Inc., describe a Full Evaporative Vacuum Extraction (FEVE) method for efficient analysis of a wide range of semivolatile organic compounds (SVOCs) in water.</strong></p>
<p>This study introduces a <strong>Full Evaporative Vacuum Extraction (FEVE)</strong> method for analyzing (<a href="https://gcms.labrulez.com/library?search=SVOCs"><strong>semivolatile organic compounds SVOCs</strong></a>) in drinking and surface water using sorbent pens. The method involves a two-stage process to capture both lighter and heavier SVOCs, followed by desorption into a GC-MS with optimized parameters for enhanced sensitivity. The sorbent pens can be stored for up to 10 days with minimal loss in analyte recovery. Testing 10 water samples, the method detected 69 analytes, none of which exceeded California Proposition 65 safety limits.</p>
<blockquote>
<h4><strong>The original article</strong></h4>
</blockquote>
<blockquote>
<h5><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.2c03414"><strong>Full Evaporative Vacuum Extraction─A Quantitative and Green Approach for Analysis of Semivolatile Organic Compounds in Drinking Water and Surface Water Using GC–MS</strong></a></h5>
<p>Weier Hao, Daniel B. Cardin</p>
<p><em>Analytical Chemistry</em> <strong>2023</strong> <em>95</em> (8), 2959-3967</p>
<p>DOI: 10.1021/acs.analchem.2c03414</p>
<h6>licensed under <a href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6>
</blockquote>
<h5>Selected sections from the article follow.</h5>
<h3><strong>Abstract</strong></h3>
<p><strong>Full evaporative vacuum extraction</strong> (<strong>FEVE</strong>) was developed in this work for analysis of a broad range of <strong>semivolatile organic compounds</strong> (<strong>SVOCs</strong>) in drinking water and surface water. Sorbent pens are used in a two-stage process that first evaporates the sample matrix through sorbent beds under vacuum to recover the lighter SVOCs, followed by the application of a higher temperature and stronger vacuum to the sample vial to recover the remaining heavier SVOCs once the matrix has evaporated. After extraction, the sorbent pens are desorbed into a <strong>GC–MS</strong> using a uniquely designed “splitless” delivery system to maximize sensitivity. Critical extraction and desorption parameters that affect the method performance were optimized. After FEVE, the sorbent pens can be stored for 7–10 days at room temperature while maintaining a less than 15% loss in analyte recovery. As a proof of concept, 10 drinking water and surface water samples were analyzed using this method. 69 analytes were detected in these water samples, with the highest concentration of 1986 ng/L for bromacil. Heptachlor epoxide, chlorpyrifos, metolachlor, butachlor, and 2,3′,4′,5-tetrachlorobiphenyl were detected in four samples. None of the analytes were above the health and safety thresholds set by California Proposition 65.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_2023_95_8_2959_3967_cover_image_95d3812bb7.jpg" alt="Anal. Chem. 2023, 95 (8), 3959-3967: graphical abstract."/></p>
<h3><strong>Experimental Section</strong></h3>
<h4><strong>Design of FEVE</strong></h4>
<p>The <a href="https://gcms.labrulez.com/library?instrumentationItems=8&amp;manufacturerItems=42&amp;search=FEVE"><strong>FEVE sorbent pen</strong></a> (FSP) has a special design that extends into the neck of 2 mL FEVE sample vials to ensure recovery of heavy SVOCs. To capture a broad range of SVOCs, the sorbent bed consists of two sorbents in series: first, PDMS-coated glass beads and then 35/60 mesh Tenax TA. This FSP design is shown in <a href="https://pubs.acs.org/doi/10.1021/acs.analchem.2c03414#fig1"><strong>Figure 1</strong></a>. PDMS-coated glass beads were chosen as a first bed to minimize the desorption heat needed to recover the heavier and the more thermally labile compounds, thereby optimizing their recoveries. For analysis of more volatile compounds, a stronger third sorbent like Carboxen or Carbosieve can be added in the FSP to capture these lighter compounds. However, for the suite of SVOCs in this study, a third sorbent was not necessary.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_8_2959_3967_Figure_1_Photograph_a_and_cross_section_b_of_an_FSP_showing_the_internal_sorbent_beds_PDMS_coated_glass_beads_red_and_Tenax_white_b3702abd97.jpg" alt="Anal. Chem. 2023, 95 (8), 2959-3967: Figure 1. Photograph (a) and cross-section (b) of an FSP showing the internal sorbent beds: PDMS-coated glass beads (red) and Tenax (white). The FSPs are stored in a sleeve when not in use (c)."/></p>
<p>As shown in <a href="https://pubs.acs.org/doi/10.1021/acs.analchem.2c03414#fig2"><strong>Figure 2</strong></a>, a 2 mL sample vial with 1 mL of the water sample was attached to an FEVE vacuum sleeve, and then, an FSP was inserted. A silicone O-ring was placed between the top of the sample vial and the bottom of the vacuum sleeve to create a leak-tight seal. The FEVE assemblies were placed into the extraction module shown in <a href="https://pubs.acs.org/doi/10.1021/acs.analchem.2c03414#fig3"><strong>Figure 3</strong></a>. A top plate was used to compress the two upper vacuum sleeve O-rings against the vacuum manifold to ensure a leak-tight seal. The multi-position design of the manifold allows for up to 30 samples to be extracted simultaneously.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_8_2959_3967_Figure_2_Components_comprising_the_FEVE_sample_assembly_including_2_m_L_sample_vial_with_1_m_L_of_the_water_sample_a_FEVE_vacuum_aa27c782ef.jpg" alt="Anal. Chem. 2023, 95 (8), 2959-3967: Figure 2. Components comprising the FEVE sample assembly, including 2 mL sample vial with 1 mL of the water sample (a), FEVE vacuum sleeve with a vial nut and silicone O-rings (b), and FSP (c). Photograph (d) and cross-section of the completed assembly showing the entrance of the FSP extending into the vial to ensure recovery of heavy SVOCs (e)."/></p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_8_2959_3967_Figure_3_Front_cross_section_view_of_the_FEVE_module_during_extraction_of_multiple_water_samples_a_Top_down_view_of_the_FEVE_top_plate_f257be0976.jpg" alt=" Anal. Chem. 2023, 95 (8), 2959-3967: Figure 3. Front cross-section view of the FEVE module during extraction of multiple water samples (a). Top-down view of the FEVE top plate, FSP cooling fan, vacuum output, and 30 FEVE sample assemblies in place (b)."/></p>
<p>The FEVE process consists of four major steps: vacuum verification, matrix evaporation, high-vacuum dehydration, and high-temperature diffusive desorption. During vacuum verification, the FEVE instrument is pumped down through the low-vac valve to reach a target vacuum pressure. Then, the valve is turned off, and the rate of pressure increase is used to determine whether the system is leak-tight. After the vacuum verification standard is met, the matrix evaporation starts. The low-vac valve is left on to help slowly remove the water matrix under vacuum. When the pressure of the instrument drops below 10 Torr, the process advances to high-vacuum dehydration, where the high-vac valve is turned on to provide a stronger vacuum, pulling the remaining volatile matrix in the vial through the FSP sorbents to the pump. When the pressure drops to 1 Torr, the sample vials are heated at 200 °C for 7.5 min. This step helps transfer the heavier SVOCs from the vials to the sorbents. An FSP cooling fan is turned on at this stage to keep the FSP sorbent cool to maximize its adsorption capacity. After the vial heater is cooled down, the FSPs are ready for <a href="https://gcms.labrulez.com/library?instrumentationItems=8&amp;manufacturerItems=42&amp;search=TD%E2%80%93GC%E2%80%93MS"><strong>TD–GC–MS</strong></a> analysis. The entire FEVE process takes 4–6 h, depending on the number of samples extracted simultaneously. Extraction of 30 samples in 6 h equates to an average time of 12 min per sample. As this is approximately half the time of a standard GC cycle, one FEVE system can provide maximum throughput for two GC–MS systems.</p>
<h4><strong>TD and GC–MS</strong></h4>
<p>After completion of the FEVE extraction process, the FSPs were loaded into a 30-position sorbent pen sample tray. The sample handling was performed using an SPR40 sample preparation rail (Entech Instruments) with full automation. The <strong>5800-SPDU Sorbent Pen</strong> Desorption Unit (Entech Instruments) was used as the TD system to deliver the analytes to the GC–MS. A <a href="https://gcms.labrulez.com/library?instrumentationItems=3&amp;mainauthorItems=10&amp;search=5977c"><strong>7890B/5977C GC–MS (Agilent Technologies, Santa Clara, CA)</strong></a> was used for optimization of the extraction and desorption parameters. A <a href="https://gcms.labrulez.com/library?instrumentationItems=3&amp;mainauthorItems=3&amp;search=ISQ+7000"><strong>Trace 1310/ISQ 7000 GC–MS (Thermo Fisher Scientific, Waltham, MA)</strong></a> with an advanced electron impact ion source operating in the selected ion monitoring mode was utilized to further optimize the detection limits of the method, evaluate the method, and analyze the water samples. A UAC-1MS precolumn (5 m × 0.53 mm × 0.15 μm, methylpolysiloxane; Quadrex Corp, Bethany, CT) was used to collect the SVOCs during sample desorption while using a 7–8 mL/min flow rate, with excess flow eliminated through a split tee positioned at the junction between the precolumn and the analytical column. The analytical column used for GC separation was an Agilent HP-5MS (30 m × 0.25 mm × 0.5 μm, 5%-phenyl-methylpolysiloxane). The carrier gas was helium, at a flow rate of 1.2 mL/min.</p>
<p><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.2c03414#fig4"><strong>Figure 4</strong></a> shows the configuration of the 5800-SPDU, the precolumn (column 1), the analytical column (column 2), and the flow and split control. This design of the instrument enables sorbent pen pre-purging and pre-heating, desorption, GC delivery, split control, and residual backflushing during the analysis of each sample. After an FSP is inserted into the desorption unit, valves 2 and 4 are turned on during preheating, thereby bypassing the FSP. Once the desorption starts, valves 1 and 4 are turned on, enabling desorption flow through the FSP to deliver SVOCs to column 1. During desorption, compounds more volatile than the lightest analyte of interest are split out through valve 4. After desorption, valves 1 and 3 are tuned on, allowing the analytes to proceed splitlessly to column 2. By using a thicker film on column 2 than that on column 1, the analytes dynamically refocus on column 2, resulting in narrower chromatographic peaks. In practice, column 2 with a film thickness of 0.25 or 0.5 μm is recommended, while column 1 is 0.15 μm. The length of column 1 can be greater than 5 m if longer desorption time is needed. During transfer of the analytes in the two columns, the desorption unit is baked at 260 °C to eliminate potential carryover in the FSP. After the heaviest analyte of interest is eluted out from column 1 and starts separating on column 2, valves 2 and 3 are turned on to backflush unwanted heavy compounds out through the entrance of column 1. Finally, the desorption unit cools down and returns to the idle status where valves 2 and 4 are on and ready for the next sample. The valve controls and flow directions of each stage are shown in <a href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.2c03414/suppl_file/ac2c03414_si_001.pdf"><strong>Figure S2</strong></a> in the Supporting Information. The GC oven temperature was held at 40 °C for 3 min during sample desorption, ramped at 12 °C/min to 160 °C, then ramped at 8 °C/min to 320 °C, and held for 1 min until the end of the run. Data acquisition and analysis were performed using Agilent <a href="https://gcms.labrulez.com/library?instrumentationItems=22&amp;manufacturerItems=1&amp;search=MassHunter+Workstation"><strong>MassHunter Workstation</strong></a>, Thermo <a href="https://gcms.labrulez.com/library?instrumentationItems=22&amp;manufacturerItems=2&amp;search=Chromeleon"><strong>Chromeleon</strong></a>, Entech SPRINT software, and Microsoft Excel.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_8_2959_3967_Figure_4_Configuration_of_the_5800_SPDU_two_column_design_and_split_control_of_the_TD_GC_MS_system_Column_1_Quadrex_UAC_1_MS_55fcff8331.jpg" alt="Anal. Chem. 2023, 95 (8), 2959-3967: Figure 4. Configuration of the 5800-SPDU, two column design, and split control of the TD–GC–MS system. Column 1: Quadrex UAC-1MS (5 m × 0.53 mm × 0.15 μm). Column 2: Agilent HP-5MS (30 m × 0.25 mm × 0.5 μm)."/></p>
<h3><strong>Conclusions</strong></h3>
<p>In this work, FEVE, a quantitative and green approach, was designed, developed, evaluated, and applied to analysis of 123 SVOCs in drinking water and surface water samples. This method enables quantification of a broad range of semivolatile compounds simultaneously, meanwhile providing a high level of sensitivity, accuracy, and precision. The extraction and analysis process is highly automated, enabling a simple and efficient workflow for analytical laboratories, and completely eliminates the use of solvents during sampling, analysis, and cleanup. Besides drinking water and surface water, FEVE also has the potential to be applied to other matrices. For example, for analysis of more complex environmental, biological, and foodstuff samples, after a simple pre-extraction to remove suspendid solids in the samples, a mixture of water and extract can be analyzed using FEVE. A 6 mL version of the FEVE technology will also be available to analyze up to 5 mL of the sample, which can further lower the detection limits.</p>


Full Evaporative Vacuum Extraction─A Quantitative and Green Approach for Analysis of Semivolatile Organic Compounds in Drinking Water and Surface Water Using GC–MS

<p><strong>In the research article published in ACS <em>Analytical Chemistry</em> journal the researchers from Van ’t Hoff Institute for Molecular Sciences (HIMS) of the University of Amsterdam, Queensland Alliance for Environmental Health Sciences (QAEHS) of The University of Queensland, and Agilent Technologies Deutschland GmbH presented a new algorithm for improving spectral cleanup in nontarget analysis.</strong></p>
<p>This study presents an algorithm for improving spectral cleanup in nontarget analysis (NTA) workflows by integrating both time and mass domain information. The algorithm uses a probability-based cumulative neutral loss (CNL) model to achieve efficient fragment deconvolution. When optimized, the model demonstrated a high true positive rate (TPr) of 95.0% and was tested on real samples, consistently achieving a TPr above 88.8% across various conditions. Compared to other methods, a combination of correlation analysis and the CNL model was most effective, providing robust results with an 84.7% TPr and significant reduction in spectral noise.</p>
<blockquote>
<h4><strong>The original article</strong></h4>
</blockquote>
<blockquote>
<h5><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.3c00896"><strong>Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data</strong></a></h5>
<p>Denice van Herwerden, Jake W. O’Brien, Sascha Lege, Bob W. J. Pirok, Kevin V. Thomas, and Saer Samanipour</p>
<p><em>Analytical Chemistry</em> <strong>2023</strong> <em>95</em> (33), 12247-12255</p>
<p>DOI: 10.1021/acs.analchem.3c00896</p>
<h6>licensed under <a href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6>
</blockquote>
<h5>Selected sections from the article follow.</h5>
<h3><strong>Abstract</strong></h3>
<p>Clean high-resolution mass spectra (HRMS) are essential to a successful structural elucidation of an unknown feature during nontarget analysis (NTA) workflows. This is a crucial step, particularly for the spectra generated during data-independent acquisition or during direct infusion experiments. The most commonly available tools only take advantage of the time domain for spectral cleanup. Here, we present an algorithm that combines the time domain and mass domain information to perform spectral deconvolution. The algorithm employs a probability-based cumulative neutral loss (CNL) model for fragment deconvolution. The optimized model, with a mass tolerance of 0.005 Da and a scoreCNL threshold of 0.00, was able to achieve a true positive rate (TPr) of 95.0%, a false discovery rate (FDr) of 20.6%, and a reduction rate of 35.4%. Additionally, the CNL model was extensively tested on real samples containing predominantly pesticides at different concentration levels and with matrix effects. Overall, the model was able to obtain a TPr above 88.8% with FD rates between 33 and 79% and reduction rates between 9 and 45%. Finally, the CNL model was compared with the retention time difference method and peak shape correlation analysis, showing that a combination of correlation analysis and the CNL model was the most effective for fragment deconvolution, obtaining a TPr of 84.7%, an FDr of 54.4%, and a reduction rate of 51.0%.</p>
<h3><strong>Experimental Section</strong></h3>
<h4><strong>LC-ESI-Q-TOF Analysis</strong></h4>
<p>Chromatographic separation of analytes was performed using a <a href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+II+LC"><strong>1290 Infinity II LC system (Agilent Technologies, Germany)</strong></a>, consisting of a binary pump (G7120A), an autosampler (G7129B), and a column oven (G7116B). Samples were kept in the autosampler at room temperature (ca. 20 °C) and the injection volume was usually 1 μL. Analytes were separated on a <a href="https://lcms.labrulez.com/library?instrumentationItems=34&amp;mainauthorItems=10&amp;search=Poroshell+EC-C18"><strong>Poroshell EC-C18</strong></a> column (2.1 mm × 150 mm, 2.7 μm, Agilent Technologies) at a constant flow rate of 0.5 mL/min and a column temperature of 40 °C. The mobile phases were water + 0.1% formic acid (A) and acetonitrile + 0.1% formic acid (B). The following gradient program was used for the separation of analytes: at 0 min, 95% A; at 1 min, 95% A; at 21 min, 5% A; at 23 min, 5% A; at 23.1 min, 95% A; and at 28 min, 95% A. The HPLC system was connected to a <a href="https://lcms.labrulez.com/library?instrumentationItems=31-30-32-29&amp;mainauthorItems=10&amp;search=G6546A"><strong>G6546A quadrupole time-of-flight (Q-TOF) mass spectrometer (Agilent Technologies)</strong></a>, equipped with an electrospray ionization (ESI) source using the Dual Spray Agilent Jet Stream technology. The Q-TOF was operated in the high-resolution mode for the low (m/z 1700) mass range. The acquisition rate was set to 6 Hz performing all ion full scan measurements at alternating collision energies of 0, 20, and 40 eV. Data were always recorded for a mass range of m/z 50–1200 in profile storage mode. Ionization was performed in the positive mode and the ESI source was operated under the following conditions: a drying gas temperature of 225 °C, a drying gas flow of 12 L/min, a sheath gas temperature of 350 °C, a sheath gas flow of 11 L/min, and a nebulizer pressure of 35 psi. The capillary and nozzle voltages were kept at 3500 and 500 V, respectively. A reference solution, containing purine and hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine (HP-0921), was continuously supplied to the second sprayer of the ESI source using an isocratic pump (G7110B, Agilent Technologies, Germany).</p>
<h4><strong>Cumulative Neutral Loss Model</strong></h4>
<p>The CNL model was built based on the MassBank EU, MoNA, and NIST20 database entries that were obtained using electrospray ionization in positive mode with a mass resolution ≥5000, including any type of mass analyzer (i.e., Q-TOF and Orbitrap) and collision energy. (37−39) Where multiple entries for a single chemical were found, the spectra were merged to ensure that the CNLs for each compound would have equal contribution to the model, using a 0.001 Da mass window. It should be noted that 0.001 Da was not assumed to be the inherent uncertainty of the data and was used as bin width for generation of average spectra. To obtain the CNLs for each compound, the fragment m/z values from the merged spectra were subtracted from the precursor ion mass. This resulted in reducing the 360,750 individual spectra to 24,487 merged CNL spectra for unique chemical constituents. The CNLs were used in place of the fragments to better capture the structural information implicitly present in the spectra. For example, while a high-frequency fragment may not contain much structural information, a highly frequent CNL provides information on the parts of the structure that are detached during fragmentation. (40) For the CNL model building, a Bayesian (i.e., probabilistic) approach was employed to overcome the issues related to limited database and potential data leakage. (41)</p>
<p>These CNL spectra were used to build the true positive (TP) and true negative (TN) probability distributions that were required for the Bayesian CNL model. To calculate these, the CNL spectra were converted to binary vectors for a CNL range of 0–1000 Da with 0.001 Da steps (i.e., 1,000,001 CNL values). The TP binary vector, for each chemical, contains ones for CNLs found in the spectra and zeros for the remaining bits, while the TN binary vector contains ones for the CNLs that were not found in a spectrum (<a href="https://pubs.acs.org/doi/10.1021/acs.analchem.3c00896#fig1"><strong>Figure 1A</strong></a>). The CNL masses that were larger than the precursor ion were set to zero for the TN binary vector. The TP and TN CNL occurrence distributions were calculated by summing the binary vectors obtained for all 24,487 CNL spectra and adding 1 to each CNL bin to avoid obtaining probabilities equal to 0. Finally, the TP and TN probability distributions were obtained by dividing each CNL occurrence by the total number of TP and TN CNL occurrences, respectively. Overall, building the CNL model took about 1–2 h and depended on the number of spectra and unique chemicals in the databases.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_33_12247_12255_Figure_1_Workflow_figure_for_construction_of_the_CNL_model_A_and_an_example_calculation_for_using_the_CNL_model_with_a_dafcb42a5a.jpg" alt="Anal. Chem. 2023, 95, 33, 12247-12255: Figure 1. Workflow figure for construction of the CNL model (A) and an example calculation for using the CNL model with a mass tolerance of 0.005 Da and a scoreCNL threshold of 0.00 (B). The abbreviations are listed in (C)."/></p>
<p>These calculated TP and TN CNL probabilities were used as the conditional probability (i.e., P(B|A)) in the Bayes theorem (eq 1). Additionally, to be able to calculate the TP or TN probability of a precursor ion having a specific CNL (i.e., posterior probability or P(A|B)), a flat prior (P(A)) is assumed, and since the marginal probability (P(B)) is a constant normalizing factor, the Bayes theorem can be reduced to eq 2, meaning that the TP and TN probabilities given a certain CNL are proportional to the probability of a CNL given that it is a TP or TN.</p>
<p>(1) 𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)×𝑃(𝐴)𝑃(𝐵)</p>
<p>(2) 𝑃(𝐴|𝐵)∝𝑃(𝐵|𝐴)</p>
<p>Through eq 2, the TP and TN probabilities for a CNL can be obtained, which were used to calculate scoreCNL (eq 3). This score is used to evaluate whether a CNL belongs to a specific precursor ion mass. To calculate scoreCNL, the TP and TN sums of probability (i.e., ∑P(TP|CNL) and ∑P(TN|CNL), respectively) are obtained for specified CNL ± mass tolerance. For example, if the mass tolerance is set to 0.010 Da and a CNL mass of 18 has been found, then ∑P(TP) corresponds to the summed TP probabilities of the CNL masses of 17.99 to 18.01. After similarly calculating ∑P(TN), scoreCNL can be used to assess if the CNL in question relates to a true fragment mass of the precursor ion mass or not, corresponding to above or below the scoreCNL threshold, respectively. An example of calculating scoreCNL is depicted in Figure 1B.</p>
<p>(3) scoreCNL=1−∑𝑃(TN|CNL)/∑𝑃(TP|CNL)</p>
<h3><strong>Results and Discussion</strong></h3>
<h4><strong>Exploring the CNL Model</strong></h4>
<p>When building the CNL model, the TP and TN counts for each CNL were calculated. At first sight, a general trend of a decrease in the total number of CNL counts after a CNL of 125 Da was found (<a href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.3c00896/suppl_file/ac3c00896_si_001.pdf"><strong>Figure S1</strong></a>). This was expected, since the median of all precursor ions is ±300 Da and the higher CNLs are not possible (i.e., precursor ion mass &lt; CNLs) for more and more compounds. Additionally, a distribution of the fragment m/z counts was also generated for comparison (<a href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.3c00896/suppl_file/ac3c00896_si_001.pdf"><strong>Figure S2</strong></a>). Here, it can be seen that the fragment m/z counts are less clearly defined than the CNL distribution (<a href="https://pubs.acs.org/doi/10.1021/acs.analchem.3c00896#fig3"><strong>Figure 3</strong></a>). Finally, the CNL counts were converted to probabilities, and still, the same trend was observed (<a href="https://pubs.acs.org/doi/10.1021/acs.analchem.3c00896#fig3"><strong>Figure 3</strong></a>). However, the probabilities in the TN distribution are much smaller than the TP probability distribution due to the larger number of TN cases than TPs. Therefore, scoreCNL is calculated that evaluates the relationship between P(TP) and P(TN).</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2023_95_33_12247_12255_Figure_3_TP_and_TN_CNL_probability_distributions_that_are_implemented_in_the_CNL_model_A_Full_probability_distribution_b5806f45b0.jpg" alt="Anal. Chem. 2023, 95, 33, 12247-12255: Figure 3. TP and TN CNL probability distributions that are implemented in the CNL model. (A) Full probability distribution, (B) a zoomed-in fraction of the TP probability distribution, and (C, D) the TN probability distribution zoomed-in on the probability range and CNL range, respectively."/></p>
<p>To provide an idea of what these probabilities mean in terms of chemical information, an overview of a few CNL masses with high TP probability can be found in <a href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.3c00896/suppl_file/ac3c00896_si_001.pdf"><strong>Table S2</strong></a> with the potential CHNO compositions of these CNL masses. The most prominent CNL has been found at a mass of 18.01, which corresponds to a commonly known neutral loss of water or H₂O. Other frequently occurring losses such as ammonia (NH₃), methanol (CH4O), and, when looking at larger CNLs, C₂H₄O₂ correspond to CNLs of 17.03, 32.03, and 60.02, respectively. These examples show that the CNL masses contain valuable information related to the neutral losses of the precursor ion, meaning that a fragment mass might not have the same m/z value for multiple precursor ions, while their CNL mass with that fragment is actually the same. Moreover, the CNL occurrence probabilities could potentially be used to assist fragmentation pattern prediction tools, by, for example, ranking the fragments based on their CNL occurrence probability.</p>
<h3><strong>Conclusions</strong></h3>
<p>In this paper, we showed a fragment deconvolution technique that is able to clean up LC-HRMS information, using only the information of the mass domain. For the measurements used to evaluate the performance, the CNL model, with the optimized parameters of a mass tolerance of 0.005 Da and a scoreCNL of 0.00, was able to maintain a TPr above 95%, and depending on the sample or aspect evaluated, FD rates between 33 and 79% and reduction rates between 9 and 45% have been found. Moreover, when time domain methods were combined with the CNL model, an optimal combination of correlation analysis with the CNL model was found, using a correlation threshold of 0.57 and the optimized CNL parameters. This combination was able to achieve a 51.0% reduction in the total number of fragments with a TPr of 84.7% and an FDr of 54.4%.</p>
<p>However, when evaluating the CNL range influence, the model performed best for the lower-range CNLs, which could be related to the higher number of TP and TN counts in this range. Therefore, it would be good if a larger number of spectra with an exact mass above 200 could be collected and included in the model. As the databases (i.e., MassBank EU, MoNA, and NIST) grow over time, the model can be easily rebuilt and optimized for the same data with the provided CNL model package. Additionally, the current model is built based on positive mode spectra. Since different fragments were found for the same chemical depending on the ionization mode, this paper focuses on the positive-mode CNL model due to the lower number of database spectra measured in negative mode. However, the developed CNLforFragments package could also be used to generate a negative-mode CNL model. Finally, when there are sufficient data available for all of the precursor ions, the potential to expand the model to obtain the likelihood of a CNL depending on the precursor ion mass could be investigated. However, there are currently too little data to implement this in the CNL model.</p>
<p>Overall, we showed the potential of a mass domain approach for the cleanup of fragments. The CNL model can be used when there is no time domain (e.g., for DDA) and assist existing methods when a time domain is present. Additionally, a score is calculated for each potential CNL mass, which could potentially be used as a prioritization technique to order the fragments based on true fragment likelihood. The developed algorithm is able to clean up MS2 spectra that can be fed to the structural elucidation workflows, ultimately resulting in highly confident identifications, independently from the workflow and the database. The incorporation of this model into the CompCreate.jl package for use with ULSA or other library search algorithms is an ongoing project in our group.</p>


Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 12th August 2024? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p>
<blockquote>
<h4>👉 <a href="https://gcms.labrulez.com/library"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></a></h4>
</blockquote>
<blockquote>
<p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p>
</blockquote>
<p>This week we bring to you a poster from <a href="https://gcms.labrulez.com/events/568"><strong>ASMS 2024</strong></a> by <strong>LECO</strong>, applications and other documents by <strong>Agilent Technologies</strong>, and <strong>Shimadzu</strong>!</p>
<h4><strong>1. LECO: <a href="https://gcms.cz/labrulez-bucket-strapi-h3hsga3/Leachables_Topical_Ointments_Sample_Prep_BTX_GC_TOFMS_Chroma_TOF_Sync_JB_ASMS_24_LPSS_325_c545e07c6d.pdf">Employing Novel Sample Preparation and Analysis by GC-TOFMS for Improved Target and Non-Target Detection of Leachables in Cream/Gel Drug Products</a></strong></h4>
<ul>
<li>poster / <a href="https://gcms.labrulez.com/companies/296"><strong>ASMS 2024</strong></a></li>
</ul>
<p><strong>Introduction:</strong> Topical ointments are commonly used to treat diseases and skin conditions by introducing the active drug ingredient through the dermis. To ensure the safety of the product for consumers, the US FDA requires that these formulations undergo leachables studies to determine the presence of chemicals which may migrate into the product from the packaging materials. Topical ointments such as creams and gels often take the form of oil-in-water emulsions which presents a challenging matrix for these analyses. Since these emulsions cannot be analyzed directly, novel sample preparations must be developed. Even with improved sample preparation techniques, the resulting extracts can still be challenging for traditional GC-MS systems. In this collaborative study, two different sample preparation methods were employed to extract a group of five chemicals commonly found in metal packaging containers such as tubes and tins. Unspiked and blind spiked samples from extraction methods A and B were provided for analysis on LECO’s Pegasus® BTX GC-Time-of-Flight (TOF) MS system. The goal was to determine the ability of the system to effectively detect and identify these chemicals with a non-target approach by leveraging mass spectral deconvolution and a software tool (ChromaTOF® Sync) designed for the comparison of samples.</p>
<p><strong>Conclusions</strong></p>
<ul>
<li>The Pegasus BTX GC-TOFMS successfully detected and identified all five spiked leachables in this non-target case study. Non-target analyses can be critically important for extractable and leachable studies to ensure drug product safety.</li>
<li>ChromaTOF Sync was used to successfully compare unspiked and blind-spiked ointment extracts to quickly find the leachable analytes which were present at significantly higher levels in the spikes. Automated deconvolution was crucial for uncovering the spiked analytes from the complex matrix interferences.</li>
<li>A brief demonstration of GCxGC separation power to improve the trace level identification of 9,10-anthracenedione in the presence of heavy matrix background was effectively demonstrated.</li>
</ul>
<h4><strong>2. Agilent Technologies: <a href="https://gcms.cz/labrulez-bucket-strapi-h3hsga3/an_residual_nmp_lithium_ion_battery_electrodes_5994_7677en_agilent_66bf9d9256.pdf">Analysis of Residual N-Methyl-2-Pyrrolidone (NMP) in Lithium-Ion Battery Electrodes</a></strong></h4>
<ul>
<li>Application</li>
</ul>
<p><strong>An analysis approach using the Agilent 8697 headspace sampler with the Agilent 8860 GC system and flame ionization detector</strong></p>
<p><strong>Abstract:</strong> Accurately measuring N-methyl-2-pyrrolidone (NMP) residue is crucial for ensuring appropriate control of electrode quality in lithium-ion battery manufacturing. This necessitates the extraction of residual NMP from battery electrodes for subsequent gas chromatography (GC) analysis. Two common extraction approaches include liquid extraction (LE) of NMP from electrodes and heated extraction through a headspace sampler. This application note describes an NMP analysis method using headspace-based extraction and GC analysis with a flame ionization detector (FID). Residual NMP analysis was then conducted on real electrode samples to compare the results between headspace sampling (HS) and LE techniques.</p>
<p><strong>Conclusion:</strong> In this study, a method for analyzing residual NMP in electrodes was developed using the Agilent 8697 headspacesampler coupled with the Agilent 8860 GC system and FID. The method&#39;s investigation assessed the system&#39;s performance in terms of matrix-matched calibration, quantitation precision, detection limit, and system carryover. The HS approach demonstrated an excellent detection limit and quantitation precision for targeted NMP analysis. In the carryover test, no NMP was detected in the blank run immediately after analyzing a blank cathode spiked with 100 µg NMP. The comparison between HS and LE analytical methods showed that HS could accurately quantify NMP in anode samples. The recovery rate of NMP from cathodes using the HS technique was approximately 65 to 78% of that achieved by the LE-based method. Given its operational simplicity and quantitation precision, HS is suitable for the process control of an established electrodes manufacturing route, while LE is recommended for the development of manufacturing processes and troubleshooting electrode quality issues.</p>
<h4><strong>3. Agilent Technologies: <a href="https://gcms.cz/labrulez-bucket-strapi-h3hsga3/flyer_5q_gc_column_campaign_5994_7659en_agilent_5f55755564.pdf">Get the Most from Your MS Agilent J&amp;W DB-5Q and HP-5Q GC columns</a></strong></h4>
<ul>
<li>Other</li>
</ul>
<h5><strong>Agilent J&amp;W DB-5Q and HP-5Q GC columns</strong></h5>
<p><strong>Meet the new gold standard for GC/MS</strong></p>
<p>Agilent J&amp;W 5Q GC columns are designed to ensure optimal analyte delivery to your quadrupoles. They combine industry-leading ultra inert performance with ultra low-bleed technology, setting a new standard for GC/MS column reliability and productivity.</p>
<ul>
<li><strong>Ultra low-bleed performance</strong> enhances data accuracy with high spectral fidelity and stable baseline integration.</li>
<li><strong>Ultra inert performance</strong> increases sensitivity for active, trace-level analytes and provides balanced deactivation for multiclass analyte panels.</li>
<li><strong>Ultrafast conditioning and outstanding column durability</strong> improve uptime by minimizing the frequency of column changes.</li>
<li><strong>Identical selectivity to current 5ms columns</strong> simplifies adaptation to existing retention time libraries and retention time locking.</li>
<li><strong>Compatibility with any GC/MS system</strong> ensures a seamless fit for all Agilent GC platforms.</li>
</ul>
<h4><strong>4. Shimadzu: <a href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/c180_e101_c8f3739683.pdf">GC/GC-MS Glass Insert/Liner Selection Guide</a></strong></h4>
<ul>
<li>Guides</li>
</ul>
<h5><strong>Contents</strong></h5>
<p><strong>1. Introduction</strong></p>
<ul>
<li>1-1. Glass Inserts/Liners 3</li>
<li>1-2. Sample Injection Unit/Injection Method 4</li>
</ul>
<p><strong>2. Glass Insert Selection</strong></p>
<ul>
<li>2-1. Glass Insert Selection by GC Model/Sample Injection Unit<ul>
<li>GC-2030/GC-2050</li>
<li>GC-2010 series</li>
<li>GC-2014 series</li>
<li>GC-2025</li>
<li>HS-10</li>
</ul>
</li>
<li>2-2. Glass Insert Selection by Application<ul>
<li>SPME/SPME Arrow</li>
<li>Aqueous Solvent Analysis</li>
<li>SPL (Split/Splitless)</li>
</ul>
</li>
</ul>
<p><strong>3. Selection Guide</strong></p>
<p><strong>4. All Glass Insert List</strong></p>
<ul>
<li>4-1. Glass Insert Compatible Instruments</li>
<li>4-2. Glass Insert Information Table</li>
</ul>
<p><strong>5. Accessories</strong></p>


News from LabRulezGCMS Library - Week 33, 2024

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 12th August 2024? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p>
<blockquote>
<h4>👉 <a href="https://lcms.labrulez.com/library"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></a></h4>
</blockquote>
<blockquote>
<p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p>
</blockquote>
<p>This week we bring to you posters, applications, and other documents from <strong>Agilent Technologies</strong>, <strong>Shimadzu</strong>, <strong>Thermo Fisher Scientific,</strong> and <strong>Waters Corporation</strong>!</p>
<h4><strong>1. Agilent Technologies: <a href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_amino_acid_ecd_6545xt_advancebio_5994_7506en_agilent_bbe30346d8.pdf">Identification of Amino Acid Isomers Using Electron Capture Dissociation in the Agilent 6545XT AdvanceBio LC/Q-TOF System</a></strong></h4>
<ul>
<li>Application</li>
</ul>
<p><strong>Abstract:</strong> Accurately determining the amino acid sequence is crucial for understanding a protein&#39;s structure and function. However, distinguishing between leucine (Leu) and isoleucine (Ile) poses a challenge, because they are positional isomers and cannot be differentiated using traditional collision-based fragmentation techniques. Electron‑based fragmentation offers a promising solution by producing side chain fragments that can be used to distinguish between Leu/Ile and other isobaric residues such as aspartate (Asp) and isoaspartate (isoAsp). This application note demonstrates the identification of isobaric residues in peptides and intact proteins using the Agilent 6545XT AdvanceBio LC/Q-TOF system equipped with an ExD cell for electron capture dissociation. Agilent ExDViewer software enables intuitive analysis of side chain fragmentation in Q-TOF datasets, enhancing the ability to discern between isobaric amino acids.</p>
<p><strong>Conclusion:</strong> This application note describes the analysis of isobaric amino acids using an Agilent 6545XT AdvanceBio Q-TOF LC/MS system equipped with an Agilent ExD cell and the Agilent ExDViewer software tool for analysis. Electron capture dissociation is a powerful fragmentation technique that provides complementary information to CID fragmentation. These methods can be applied to investigate peptide backbone and side chain fragmentation for a range of molecules, reducing ambiguity in protein sequence analysis. The sensitivity of the Q-TOF to detect ECD fragments combined with ExDViewer for fragment analysis provides an effective solution for targeted amino acid isobar identification.</p>
<h4><strong>2. Waters Corporation: <a href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_amino_acid_ecd_6545xt_advancebio_5994_7506en_agilent_bbe30346d8.pdf">MODERNIZATION OF A LEGACY NORMAL PHASE METHOD ON A MODERN HPLC SYSTEM</a></strong></h4>
<ul>
<li>Poster / <a href="https://lcms.labrulez.com/companies/303"><strong>HPLC 2024</strong></a></li>
</ul>
<p><strong>INTRODUCTION</strong></p>
<p>In regulated laboratories, particularly those within the  pharmaceutical industry, High-Performance Liquid  Chromatography (HPLC) systems play a crucial role in  routine analysis. However, some challenges arise due to  legacy methods that were developed during the early  days of HPLC technology. These methods have not kept  pace with recent advancements and modernization in the  field and do not fully leverage the latest technological  improvements. Advancements in column chemistry and  system robustness allow for better separation and  detection of analytes.</p>
<p>Modern HPLC systems are more robust, reliable, and  capable of handling challenging analyses and can  accommodate various chromatographic modes, including  Normal Phase chromatography. While legacy methods  persist, regulatory agencies such as the United States  Pharmacopeia (USP) provide guidance on how to adapt  and adjust these methods. This helps bridge the gap  between legacy methods and modern HPLC systems.</p>
<p>In this study, we examine the modernization of a legacy  normal phase method, USP Propofol Assay, for use with a  HPLC system. The original method specified an older L3  column in a non-standardized column configuration (4.6  mm x 200 mm). Given these column specifications, we  compared a suitable column to coupling two columns to  match the specified column dimensions. We also  explored the use of a column that was scaled in  accordance with USP Chapter 6211 that meets the L/dp  requirement.</p>
<p><strong>CONCLUSION</strong></p>
<ul>
<li>Legacy columns, like the L3 used for column 1, has an  older packing technology and is unable to provide a  suitable chromatography. </li>
<li>The use of a newer packing as in BEH Columns helps provide a successful analysis</li>
<li>Coupling two columns, albeit successful, may prove to  be a much more expensive option and may be introducing more opportunities for issues to arise.</li>
<li>The third column derived from the use of the columns  calculator may be the more suitable route since it  adheres to the USP guidance as well as not being more  expensive and time consuming as the coupling of two columns.</li>
</ul>
<h4><strong>3. Waters Corporation: <a href="https://lcms.cz/labrulez-bucket-strapi-h3hsga3/asms_2024_mccullagh_the_utility_of_cyclic_ion_mobility_to_improve_selectivity_and_analysis_efficiency_of_environmental_pfas_contamination_and_exposure_3f331eafb6.pdf">THE UTILITY OF CYCLIC ION MOBILITY TO IMPROVE SELECTIVITY AND ANALYSIS EFFICIENCY OF ENVIRONMENTAL PFAS CONTAMINATION AND EXPOSURE</a></strong></h4>
<ul>
<li>Poster / <a href="https://lcms.labrulez.com/companies/296"><strong>ASMS 2024</strong></a></li>
</ul>
<p><strong>INTRODUCTION</strong></p>
<p>Polyfluorinated alkyl substances (PFAS) exposure is a  potential contributor to increased cancer occurrence in the  human population. The bio-accumulative nature of PFAS  enables monitoring of levels in human biofluids to help gain  understanding into exposure levels and pathways. However  PFAS isomeric compounds, can be challenging to efficiently  separate using liquid chromatography.</p>
<p>Cyclic ion mobility (cIM) provides an added dimension of  separation and collision cross section (CCS) values can  provide a a complimentary identification descriptor. CCS  values provide an additional identification point across  multiple application areas. At low concentrations where  fragment information may be absent, CCS and arrival time  distribution (ATD) provide an additional identification point  alongside retention time (tr).</p>
<p>To highlight confidence of the utility of CCS values,  independent of ion mobility (IM) technology, when performing  PFAS non-targeted screening assays, we have used an  internally developed PFAS library to cross correlate PFAS  CCS reproducibility. The SELECT SERIESTM CyclicTM IMS  mass spectrometer (see Figure 1) has been used to perform  an inter-site/intra-site comparison and compared to published  drift tube (DT) ion mobility PFAS CCS values.1</p>
<p>Using LC-cIM-MS, branched and linear PFAS isomers have  been fully resolved. Detection of individual PFAS isomers  provides opportunity to correlate cancer risk with exposure to  specific PFAS isomers. Human serum samples were  analysed, and data generated for PFAS isomers and isobaric  biomarker isomer composition.</p>
<p>LC-cIM-MS (cIM resolution (R)<del>65-145) analyses were  performed using a SELECT SERIES Cyclic IMS mass  spectrometer. PFAS standards and human serum samples  were analysed, using a 22 min reversed phase separation  gradient. Using the combined peak capacity of LC-cIM,  enabled resolution of linear and branched isomers, whilst  simultaneously achieving an increase in analysis efficiency of  75 %. The enhanced resolution has the potential to facilitate a  time efficient correlation between PFAS isomeric structure,  concentration, and exposure. Linear and branched PFOS  isomers were IM resolved in anonymized human serum  extracts, using a 5.5-minute LC gradient. Importantly  chromatographic separation was achieved for PFOS and bile  acid biomarkers. Using ion mobility resolution (</del>145), we  report IM enhanced specificity and resolution for biomarker  isomers Taurodeoxycholic, Taurochenodeoxycholic and  Tauroursodeoxycholic acid.</p>
<p>A focus on LC-cIM-MS as a potential strategy to generate  time efficient, additional toxicological correlation specificity  with individual PFAS isomeric species and resultant elevation  of isobaric biomarker isomers is presented. Identification of  perfluoroalkyl carboxylic acids (PFCAs), cIM conformeric  profiles and corresponding CCS identification finger prints  provides newfound specificity.</p>
<h4><strong>4. Shimadzu: <a href="https://lcms.cz/labrulez-bucket-strapi-h3hsga3/an_01_00757_en_5e7f73a1aa.pdf">Qualitative Analysis of Drug Metabolites Using LCMS-9050</a></strong></h4>
<ul>
<li>Application</li>
</ul>
<p><strong>User Benefits</strong></p>
<ul>
<li>The LCMS-9050 quadrupole time-of-flight (Q-TOF) mass spectrometer and LabSolutions Insight Explore™provide qualitative analysis of drug metabolites.</li>
<li>Analyze and Target Screening function in LabSolutions Insight Explore enables peak extraction of candidate drug metabolites</li>
</ul>
<p><strong>Introduction:</strong> After a drug is ingested into the body, it is metabolized by various reactions, including oxidation, reduction, hydrolysis, and conjugation. The prediction of drug metabolites is important because the metabolites may differ from the original drug in terms of efficacy and toxicity.</p>
<p>This Application News introduces an example of qualitative analysis of drug metabolites using the LCMS-9050 quadrupole time-of-flight (Q-TOF) mass spectrometer. Lenvatinib, a known anticancer drug, was administered orally to rats, and the metabolites in the liver were analyzed. Drug metabolite peaks were extracted using the Analyze function in LabSolutions Insight Explore. The Target Screening function narrowed down the candidate peaks based on a list of drug metabolites, and the MS and MS/MS spectra were analyzed in detail.</p>
<p><strong>Conclusion:</strong> Several metabolites derived from lenvatinib were detected by the LCMS-9050 quadrupole time-of-flight mass spectrometer and LabSolutions Insight Explore. By preparing a list of drug metabolites, it was possible to easily extract candidate metabolite peaks. This workflow can also be applied to the metabolite analysis of drugs otherthan lenvatinib.</p>
<h4><strong>5. Agilent Technologies: <a href="https://lcms.cz/labrulez-bucket-strapi-h3hsga3/an_lib_electolyte_cary_3500_flexible_uv_vis_5994_7602en_agilent_ebebd9a4ad.pdf">Quality Control of Lithium-Ion Battery Electrolytes and Solvents by UV-Vis Spectroscopy</a></strong></h4>
<ul>
<li>Application</li>
</ul>
<h5><strong>Color measurements and safe chemical handling using an Agilent Cary 3500 Flexible UV-Vis with Cary Sipper pump</strong></h5>
<p><strong>Abstract:</strong> Ensuring the quality of electrolytes used in lithium-ion batteries (LIBs) is crucial for maintaining the safety, performance, and longevity of these energy storage devices. LIB electrolytes consist of lithium salts dissolved in organic solvents. Any discoloration (yellowness) of these near-clear solutions can indicate contamination or degradation. Industry methods such as ASTM D5386-16 Standard Test Method for Color of Liquids Using Tristimulus Colorimetry can be applied to assess the quality of electrolytes by conducting instrumental color measurements using UV-Vis spectroscopy. Given the low absorbance of colorless-to-near-colorless liquid samples like LIB electrolytes and solvents, a highly accurate and sensitive UV-Vis spectrophotometer is essential.</p>
<p>This study demonstrates an effective quality assessment method for LIB electrolytes and solvents using the Agilent Cary 3500 Flexible UV-Vis spectrophotometer fitted with the optional Agilent Cary Sipper flow cell pump. The method is suitable for production quality control of hazardous samples, ensuring safe sample handling, high throughput, and high quality results for production-critical chemicals.</p>
<p><strong>Conclusion:</strong> The Agilent Cary 3500 Flexible UV-Vis spectrophotometer provided accurate and precise color measurements for colorless to near-colorless LIB electrolytes and solvents in accordance with the ASTM D5386 standard method. Advantages of the Cary 3500 Flexible method and findings based on the data set include:</p>
<ul>
<li>Hazardous samples were introduced directly into a 10 mm path length flow cell using the Cary Sipper pump, ensuring user safety and high sample throughput without compromising data quality.</li>
<li>The superior sensitivity (high signal-to-noise ratio) of the Cary 3500 combined with Agilent Cary WinUV Color application software enabled the reliable monitoring and control of electrolyte properties by analyzing light absorption in the visible spectrum.</li>
<li>Higher Pt-Co color (APHA) values of the used LIB electrolytes compared to fresh samples suggested a deterioration in quality due to the color changes.</li>
<li>Color measurements could be used to improve the quality control of LIB electrolytes and solvents by identifying discoloration—an indication of contamination or degradation that could affect battery performance.</li>
<li>This effective method could be implemented in both manufacturing QC settings and R&amp;D laboratories.</li>
</ul>
<p>QC color measurements using the Cary 3500 Flexible UV-Vis would ensure that only high-quality electrolytes are used in the production of LIBs, enhancing their safety, efficiency, and durability.</p>
<h4><strong>6. Thermo Fisher Scientific: <a href="https://lcms.cz/labrulez-bucket-strapi-h3hsga3/xx_002781_lc_vanquish_method_moderization_guide_tip_sheet_xx002781_en_aca7492d0b.pdf">A Helpful Guide To Modernizing Your Old HPLC Methods</a></strong></h4>
<ul>
<li>Guide</li>
</ul>
<p><strong>Modernizing older or compendial methods can help increase your lab’s productivity and lower your cost and carbon footprint. This guide gives you an overview of what method parameters to consider changing, as defined by USP 621.</strong></p>
<h4><strong>7. Thermo Fisher Scientific: <a href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/wp_003007_lsms_Stellar_LCMS_translational_research_ffe410ad04.pdf">Transitioning biomarkers from discovery to validation at unprecedented scale with the Stellar mass spectrometer</a></strong></h4>
<ul>
<li>Technical note</li>
</ul>
<h5><strong>Expanded target capacity, higher sensitivity with greater specificity with unrivaled quantitative productivity for translational research</strong></h5>
<p><strong>Keywords:</strong> Stellar mass spectrometer, biomarker verification, targeted quantitative solutions, protein, metabolite, lipid, dynamic retention time adjustment, automated method creation, fast polarity switching, translational research.</p>
<p><strong>Introduction:</strong> The Thermo Scientific™ Stellar™ mass spectrometer establishes a new paradigm to drive biomarker verification by achieving 10X the sensitivity for 5X more compounds at scale compared to existing technologies. By synergistically combining the robust quantitative performance of triple quadrupole technology with the sensitive, rapid full scan MSn acquisition of dual-pressure linear ion trap technology, the Stellar mass spectrometer extends the unprecedented analytical capabilities to a wider range of compounds. Single-ion detection capabilities expand robust targeted quantitation for single cell or low protein load studies minimizing the potential for missing data. Novel software tools streamline highly multiplexed targeted quantitative method creation, implementation, and data acquisition, bypassing lengthy and costly replicate injections associated with existing technology. The new experimental capabilities of the Stellar mass spectrometer make it ideally suited for transitioning putative biomarker candidates from discovery to validation for translational proteomics, metabolomics, and lipidomics research.</p>


News from LabRulezLCMS Library - Week 33, 2024

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in week 33, 2024? Check out new documents from the field of spectroscopy, especially ICP/MS techniques!</strong></p>
<blockquote>
<h4>👉 <a href="https://icpms.labrulez.com/library"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT ICPMS AND RELATED TECHNIQUES</strong></a></h4>
</blockquote>
<blockquote>
<p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p>
</blockquote>
<h4><strong>1. Agilent Technologies: <a href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/wp_optimization_grain_analysis_icp_ms_8900_5994_7599en_agilent_fa0cf47344.pdf">Economical Carbon Enhanced Plasma Ionization: Substituting Acetic Acid with Carbon Dioxide</a></strong></h4>
<ul>
<li>Application</li>
</ul>
<h5><strong>Cost-effective method suitable for routine analysis of Australian grain export cargoes by Agilent 8900 ICP-QQQ</strong></h5>
<p><strong>Conclusion</strong></p>
<p>A custom process was developed for mixing carbon dioxide in argon and supplying it to the plasma of the Agilent 8900 ICP-QQQ. The study showed that the use of gaseous carbon for plasma ionization enhancement provided advantages over traditional liquid sources of carbon, such as acetic acid, in terms of cost and performance. The scalability of the gas supply system can be enhanced by increasing the size of the ballast tank, enabling the efficient use with multiple ICP-MS instruments. This optimization would lead to more cost reductions.</p>
<p>The use of CO2  in Ar, supplied from a ballast tank, ensures easy and rapid adjustment of the carbon composition of the plasma with minimal flush out times, addressing a common challenge associated with liquid carbon sources. Carbon was shown to enhance the signal of key elements such as arsenic in the plasma, while maintaining the sensitivity of other elements. The carbon buffering effects of the modified plasma enable the quantification of low concentrations of analytes in food samples, such as grains. Adding carbon to the plasma if especially useful for samples that have variable carbon content, as it compensates for any sample differences and minimizes the variability from easily ionized elements. Based on our experience, the 8900 ICP-QQQ has proven to be a highly efficient and cost-effective tool for analyzing export grain cargoes, especially in a high-throughput laboratory setting.</p>
<h4><strong>2. Shimadzu: <a href="https://icpms.cz/labrulez-bucket-strapi-h3hsga3/C113_E036_94c7dfae0c.pdf">LA-ICP-MS Software</a></strong></h4>
<ul>
<li>Brochures and specifications</li>
</ul>
<p><strong>By combining this software with Shimadzu ICPMS Series Systems connected to a laser ablation instrument, sample measurement and data output in a format compatible with imaging data analysis software are possible.</strong></p>
<p><strong>Batch registration of line scan information</strong></p>
<ul>
<li>The sample information can be entered using the image of the irradiation area (Number of lines x irradiation time) set by the laser ablation instrument. Reduce the time and effort required to enter information to 1/10 or less*.</li>
</ul>
<h6>*When 10 or more lines are registered</h6>
<p><strong>Data output per sample</strong></p>
<ul>
<li>The acquired data is output as one data file per sample. Prevents missing or mixed data when multiple line data are selected and output.</li>
</ul>
<p><strong>Supports imdx format</strong><br/>The data of the output imdx format can be read as it is by Shimazu Mass Spectrometry Imaging Data Analysis Software IMAGEREVEAL™ MS. You can start the analysis immediately without converting the data.</p>
<h4><strong>3. Agilent Technologies: <a href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_lib_electolyte_cary_3500_flexible_uv_vis_5994_7602en_agilent_ebebd9a4ad.pdf">Quality Control of Lithium-Ion Battery Electrolytes and Solvents by UV-Vis Spectroscopy</a></strong></h4>
<ul>
<li>Applications</li>
</ul>
<h5><strong>Color measurements and safe chemical handling using an Agilent Cary 3500 Flexible UV-Vis with Cary Sipper pump</strong></h5>
<p><strong>Abstract:</strong> Ensuring the quality of electrolytes used in lithium-ion batteries (LIBs) is crucial for maintaining the safety, performance, and longevity of these energy storage devices. LIB electrolytes consist of lithium salts dissolved in organic solvents. Any discoloration (yellowness) of these near-clear solutions can indicate contamination or degradation. Industry methods such as ASTM D5386-16 Standard Test Method for Color of Liquids Using Tristimulus Colorimetry can be applied to assess the quality of electrolytes by conducting instrumental color measurements using UV-Vis spectroscopy. Given the low absorbance of colorless-to-near-colorless liquid samples like LIB electrolytes and solvents, a highly accurate and sensitive UV-Vis spectrophotometer is essential.</p>
<p>This study demonstrates an effective quality assessment method for LIB electrolytes and solvents using the Agilent Cary 3500 Flexible UV-Vis spectrophotometer fitted with the optional Agilent Cary Sipper flow cell pump. The method is suitable for production quality control of hazardous samples, ensuring safe sample handling, high throughput, and high quality results for production-critical chemicals.</p>
<p><strong>Conclusion:</strong> The Agilent Cary 3500 Flexible UV-Vis spectrophotometer provided accurate and precise color measurements for colorless to near-colorless LIB electrolytes and solvents in accordance with the ASTM D5386 standard method. Advantages of the Cary 3500 Flexible method and findings based on the data set include:</p>
<ul>
<li>Hazardous samples were introduced directly into a 10 mm path length flow cell using the Cary Sipper pump, ensuring user safety and high sample throughput without compromising data quality.</li>
<li>The superior sensitivity (high signal-to-noise ratio) of the Cary 3500 combined with Agilent Cary WinUV Color application software enabled the reliable monitoring and control of electrolyte properties by analyzing light absorption in the visible spectrum.</li>
<li>Higher Pt-Co color (APHA) values of the used LIB electrolytes compared to fresh samples suggested a deterioration in quality due to the color changes.</li>
<li>Color measurements could be used to improve the quality control of LIB electrolytes and solvents by identifying discoloration—an indication of contamination or degradation that could affect battery performance.</li>
<li>This effective method could be implemented in both manufacturing QC settings and R&amp;D laboratories.</li>
</ul>
<p>QC color measurements using the Cary 3500 Flexible UV-Vis would ensure that only high-quality electrolytes are used in the production of LIBs, enhancing their safety, efficiency, and durability.</p>
<h4><strong>4. Thermo Fisher Scientific: <a href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/sp_002912_tea_icp_oes_metals_sp002912_em_en_b66a04979b.pdf">Discover more with the SemiQuant feature of Thermo Scientific Qtegra ISDS Software</a></strong></h4>
<ul>
<li>Other</li>
</ul>
<h5><strong>Thermo Scientific iCAP PRO Series ICP-OES</strong></h5>
<p><strong>Discover more with the SemiQuant feature of Thermo Scientific Qtegra ISDS Software</strong></p>
<p>Semi-quantitative analysis can be carried out by inductively coupled plasma-optical emission spectroscopy (ICP-OES) and involves determining the relative concentrations of elements in a sample rather than obtaining precise quantitative measurements. The semiquantitative approach is often used for rapid screening of samples or for identifying elemental composition trends rather than obtaining exact concentrations. Interpretation of semi-quantitative analysis may involve identifying major and minor elements present in the sample, detecting elemental trends or patterns, or comparing the elemental composition of different samples.</p>
<p><strong>What is SemiQuant?</strong></p>
<p>The SemiQuant feature within the Thermo Scientific™ Qtegra™ Intelligent Scientific Data Solution™ (ISDS) Software is a data acquisition tool leveraging Artificial Intelligence and employing deep neural networks to simplify the complex process of intra- and inter-element correction, selecting only non-interfered peaks, automatically. This supports fast screening of samples to gain insights into sample composition. It can be a useful aid in method development and enables the collection and archiving of approximate elemental concentrations of a broader range of analytes in the samples in case they can be of interest at a future date. Its unique implementation allows users to get a good understanding of the presence of certain elements in their sample and also offers the concentration amount and a level of confidence for the given concentration to allow the best possible interpretation of the results.</p>


News from LabRulezICPMS - Library Week 33, 2024

<p><strong>In the research article published in ACS <em>Analytical Chemistry</em> journal the researchers from the Department of Physical and Analytical Chemistry, and the Department of Functional Biology (Physiology), University of Oviedo, Spain presented novel analytical strategy for detecting miRNA in human plasma without relying on nucleic acid amplification.</strong></p>
<p>MicroRNAs (miRNAs) are short RNA sequences that play a key role in gene expression and respond to physiological changes, such as those induced by physical exercise. This study presents a novel analytical strategy for detecting miRNA in human plasma without relying on nucleic acid amplification (eg PCR). The method uses a double hybridization process with a magnetic microparticle and a gold nanoparticle for highly selective detection, even at single nucleotide variations. The approach is validated against rt-qPCR and can differentiate between sedentary and active individuals based on miRNA levels. Additionally, this versatile platform can be easily adapted for other miRNA sequences.</p>
<blockquote>
<h4><strong>The original article</strong></h4>
</blockquote>
<blockquote>
<h5><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.4c01904"><strong>Amplification-Free Strategy for miRNA Quantification in Human Serum Using Single Particle ICP–MS and Gold Nanoparticles as Labels</strong></a></h5>
<p>Sara González Morales, Carlos López-Portugués, Manuel Fernández-Sanjurjo, Eduardo Iglesias-Gutiérrez, María Montes Bayón, and Mario Corte-Rodríguez</p>
<p><em>Analytical Chemistry</em> <strong>2024</strong> <em>96</em> (30), 12414-12423</p>
<p>DOI: 10.1021/acs.analchem.4c01904</p>
<h6>licensed under <a href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6>
</blockquote>
<h3><strong>Abstract</strong></h3>
<p>MicroRNAs (miRNAs), which are short single-stranded RNA sequences between 18 and 24 nucleotides, are known to play a crucial role in gene expression. Changes in their expression are not only involved in many diseases but also as a response to physiological changes, such as physical exercise. In this work, a new analytical strategy for the sensitive and specific analysis of miRNA sequences in human plasma is presented. The developed strategy does not depend on any nucleic acid amplification process and can be obtained in direct correlation to the number of events obtained by using single-particle ICP–MS measurements. The high selectivity of the assay (up to single nucleotide polymorphisms) can be achieved by a double hybridization process of the target miRNA with a complementary capture oligonucleotide that is conjugated to a magnetic microparticle and simultaneously with a complementary reporter oligonucleotide conjugated to a gold nanoparticle. Thanks to the novel approach followed in this method, the stoichiometry of the oligonucleotide-nanoparticle conjugates does not need to be addressed for the quantification of the target miRNA, which also represents a big advantage over other similar methods. The optimized method is applied to the determination of a miRNA as a biomarker of physical exercise in non-spiked human serum samples, and the results are validated against rt-qPCR. The achieved sensitivity permits the direct differentiation among sedentary and sportive subjects. This general platform can be easily applied to any other sequence by only modifying the capture and reporter oligonucleotides, paving the way for multiple clinically interesting applications.</p>
<h3><strong>Introduction</strong></h3>
<p>Microribonucleic acids (miRNAs) are small noncoding RNA biomolecules with a length between 18 and 24 nucleotides that are involved in different cellular processes, such as gene expression modulation. In fact, the main function of miRNAs consists of their union with mRNAs by base complementarity, either preventing their translation or inducing their degradation, resulting in both cases in a negative post-transcriptional regulation of gene expression. Over 60% of protein-coding genes are known to be regulated by different miRNAs. (1)...</p>
<p>...In this work, miRNA quantification is based on the specificity of nucleic acid hybridization and the highly sensitive and specific nanoparticle counting capabilities of individual nanoparticles by SP-ICP-MS. The amplification-free workflow that we propose is based on the hybridization of a specific target miRNA sequence (miR-16-5p) with two DNA sequences that are each complementary to half of the target, respectively. One of them is conjugated to a magnetic microparticle (capture probe) that is used for the enrichment and washing of the target sequence. The other half-complementary sequence is conjugated to a gold nanoparticle that is detected by SP-ICP-MS (detection probe). Although the analytical strategy is comparable to this from Xu et al., (34) it is important to note that our methodology is applied to quantify different levels of expression of miRNA sequences as short as 22 nucleotides that are naturally present in human serum samples. Scheme 1 summarizes the main differences between the proposed strategy and other methods for miRNA quantification. Therefore, this methodology represents a step forward in facing challenges like miRNA pre-concentration in a complex matrix with the important role of quantification, which is crucial to extracting conclusions depending on the expression levels.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2024_96_30_12414_12423_Scheme_1_Main_Differences_of_the_Methodology_Proposed_in_This_Article_in_Comparison_With_Other_Traditional_Techniques_6f30e97f14.jpg" alt="Anal. Chem. 2024, 96, 30, 12414-12423: Scheme 1. Main Differences of the Methodology Proposed in This Article in Comparison With Other Traditional Techniques."/></p>
<h3><strong>Experimental Section</strong></h3>
<h4><strong>Instrumentation</strong></h4>
<p>The measurements were performed by using the <a href="https://icpms.labrulez.com/library?instrumentationItems=83-90&amp;mainauthorItems=3&amp;search=+iCAP+TQ"><strong>iCAP TQ triple quadrupole ICP–MS system from Thermo Fisher Scientific</strong></a>. All measurements, including single particle ICP–MS measurements, were done using the standard configuration for sample introduction, including the MicroMist nebulizer at a sample flow rate of 0.4 mL min–1 and a cyclonic spray chamber because a high transport efficiency was not crucial for this application. The sample introduction system was operated in combination with an ASX-560 autosampler from Teledyne Cetac. The ICP–MS was tuned daily to maximize sensitivity while keeping the formation of oxides and doubly charged species below 3 and 5%, respectively.</p>
<p>For spectrophotometric measurements of nucleic acid concentrations, a NanoDrop spectrophotometer (Thermo Fisher Scientific) was used. A transmission electron microscope MET JEOL-JEM-2100F was used to obtain images of the nanoparticles. A scanning electron microscope MEB JEOL-6610LV with EDX microanalysis was used for the images and elemental analysis of microparticles. Other basic laboratory instrumentation was also used, including an analytical precision balance, an ultrasonic bath, a vortex mixer, and a block heater...</p>
<h3><strong>Results and Discussion</strong></h3>
<h4><strong>Characterization of Naked and Conjugated Gold Nanoparticles</strong></h4>
<p>The gold nanoparticles used as metal labels for the detection probe were characterized both before and after their conjugation with the DNA oligo by SP-ICP-MS, transmission electron microscopy (TEM), and DLS. The results of SP-ICP-MS, shown in Table 1 and Figure 1, reveal that the obtained mean diameters were 23.3 ± 3.3 nm, which was slightly larger than the value provided by the manufacturer (22 nm). When a Student-t test was performed to compare the mean diameters of the conjugated and original nanoparticles, no statistical differences between them or compared to the value given by the manufacturer was observed at a 95% confidence level. Under these conditions, the size limit of detection was calculated as 18 nm, well below the size of the nanoparticles. Both sets of particles showed a narrow distribution, as can be seen in Figure 1, although the nanoparticles showed a more monodisperse distribution after the conjugation (Figure 1B), probably due to an increased stability in solution when coated with negatively charged oligonucleotides...</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2024_96_30_12414_12423_Table_1_Theoretical_Specified_by_Manufacturer_and_Experimental_Diameter_for_the_Pegylated_Gold_Nanoparticles_Before_9374c01b7b.jpg" alt="Anal. Chem. 2024, 96, 30, 12414-12423: Table 1. Theoretical (Specified by Manufacturer) and Experimental Diameter for the Pegylated Gold Nanoparticles Before (Bare) and After (Conjugated) Conjugation With the Oligo_ᵃ."/></p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2024_96_30_12414_12423_Figure_1_Histograms_showing_the_diameters_distribution_of_the_gold_nanoparticles_analyzed_by_SP_ICP_MS_A_in_black_39075eec62.jpg" alt="Anal. Chem. 2024, 96, 30, 12414-12423: Figure 1. Histograms showing the diameters distribution of the gold nanoparticles analyzed by SP-ICP-MS. (A) (in black) Unconjugated nanoparticles and (B) (in red) nanoparticles after being conjugated with the oligonucleotide probe, with a shift to higher diameter values."/></p>
<h3><strong>Conclusions</strong></h3>
<p>In this study, we introduce a novel amplification-free miRNA analysis method using magnetic microparticles for capture and preconcentration and gold nanoparticles as labels that amplify the response for ICP–MS detection. Eliminating the need for nucleic acid sequence amplification, our approach streamlines the analysis process while reducing potential sources of error that are common in conventional techniques. Moreover, it circumvents the often challenging considerations of oligonucleotide-nanoparticle conjugation stoichiometry. Importantly, this methodology also demonstrates remarkable resilience to batch-to-batch variations in conjugation processes, which are accounted for in daily calibration.<br/>The high selectivity of the assay, thanks to the complementarity interactions between probes and analytes, has been demonstrated, achieving the possibility of clearly discriminating a 2-base mismatch. Even more, the response to single nucleotide polymorphisms is seriously affected, and these kinds of important sequence variations can also be also discriminated. The developed method, which has been validated against the gold-standard RT-qPCR, can be easily modified to detect any miRNA sequence by changing only the detection and capture probes. This allows for high versatility with minimal optimization for the detection of any miRNA sequence.</p>


Amplification-Free Strategy for miRNA Quantification in Human Serum Using Single Particle ICP–MS and Gold Nanoparticles as Labels

<p><strong>In the research article published in ACS <em>Analytical Chemistry</em> journal the researchers from the University of Natural Resources and Life Sciences, BOKU Vienna, and from Novartis Technical Operations Anti-Infectives, MS&amp;T Laboratories reported a new approach towards the quantification of N-acetylglucosamine in biotechnological cell samples using <a href="https://gcms.labrulez.com/library?instrumentationItems=4">GC–MS/MS</a> and <a href="https://gcms.labrulez.com/library?instrumentationItems=13">GC–TOFMS</a>.</strong></p>
<p>N-Acetylglucosamine is a crucial component of bacterial and fungal cell walls and the extracellular matrix in animals, playing roles in cell surface structure and signaling pathways. Given the challenges in distinguishing its stereoisomers, which share identical masses and similar fragmentation patterns, efficient separation techniques are essential. A gas chromatography method using automated online derivatization was developed for precise quantification of these stereoisomers. This approach, combined with ¹³C-labeled internal standards and mass spectrometric analysis, allows accurate detection of low-abundance stereoisomers, as demonstrated in <em>Penicillium chrysogenum</em> cultivations with strong consistency across different mass spectrometric techniques.</p>
<blockquote>
<h4><strong>The original article</strong></h4>
</blockquote>
<blockquote>
<h5><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.9b04582"><strong>Selective and Accurate Quantification of <em>N</em>-Acetylglucosamine in Biotechnological Cell Samples via GC–MS/MS and GC–TOFMS</strong></a></h5>
<p>Teresa Mairinger, Michael Weiner, Stephan Hann, and Christina Troyer</p>
<p><em>Analytical Chemistry</em> <strong>2020</strong> <em>92</em> (7), 4875-4883</p>
<p>DOI: 10.1021/acs.analchem.9b04582</p>
<h6>licensed under <a href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6>
</blockquote>
<h5>Selected sections from the article follow.</h5>
<h3><strong>Abstract</strong></h3>
<p>N-Acetylglucosamine is a key component of bacterial and fungal cell walls and of the extracellular matrix of animal cells. It plays a variety of roles at the cell surface structure and is under discussion to be involved in signaling pathways. The presence of a number of <em>N</em>-acetylhexosamine stereoisomers in samples of biological or biotechnological origin demands for dedicated high efficiency separation methods, due to identical exact mass and similar fragmentation patterns of the stereoisomers. Gas chromatography offers high sample capacity, separation efficiency, and precision under repeatability conditions of measurement, which is a necessity for the analysis of low abundant stereoisomers in biological samples. Automated online derivatization facilitates to overcome the main obstacle for the use of gas chromatography in metabolomics, namely, the derivatization of polar metabolites prior to analysis. Using alkoximation and subsequent trimethylsilylation, carbohydrates and their derivatives are known to show several derivatives, since derivatization is incomplete as well as highly matrix dependent inherent to the high number of functional groups present in carbohydrates. A method based on efficient separation of ethoximated and trimethylsilylated <em>N</em>-acetylglucosamines was developed. Accurate absolute quantification is enabled using biologically derived ¹³C labeled internal standards eliminating systematic errors related to sample pretreatment and analysis. Due to the lack of certified reference materials, a methodological comparison between tandem and time-of-flight mass spectrometric instrumentation was performed for mass spectrometric assessment of trueness. Both methods showed limits of detection in the lower femtomol range. The methods were applied to biological samples of <em>Penicillium chrysogenum</em> cultivations with different matrices revealing excellent agreement of both mass spectrometric techniques.</p>
<h3><strong>Experimental Section</strong></h3>
<h4><strong>Automated Derivatization</strong></h4>
<p>The two-step derivatization of samples and standards with (1) ethylhydroxylamine or methylhydroxylamine hydrochloride and (2) MSTFA with 1% TMCS was performed automatically on a Gerstel <a href="https://gcms.labrulez.com/library?mainauthorItems=2&amp;search=MPS2+dual+rail+sample+preparation+robot"><strong>MPS2 dual rail sample preparation robot</strong></a> (Gerstel GmbH, Muehlheim, Germany). The robot was equipped with two parallel rails, each carrying a robotic tower capable of performing independent liquid handling steps. One tower was equipped with a 10 μL syringe for sample injection; the second tower was equipped with a 100 μL syringe for the addition of the reagents. Both towers were also in use for transportation of the samples. Each rail was equipped with a heated agitator for derivatization. Underivatized dried samples were stored at 6 °C in a cooled stack until the onset of just-in-time derivatization. Reagents were stored at 6 °C in a Peltier cooled tray. Sample preparation as well as the injection were controlled by the <a href="https://gcms.labrulez.com/library?mainauthorItems=2&amp;search=Maestro"><strong>Maestro software</strong></a> package 1.4.30.6. (Gerstel), which was linked with the <a href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=MassHunter"><strong>MassHunter</strong></a> Acquisition software B07.06 (Agilent Technologies Inc.).</p>
<p>For derivatization and analysis, aliquots of 60 μL of standards, 50 μL of extracts, 80 μL of washing and quenching solutions, and 120 μL of the cultivation supernatant were used. The ratio of internal standard volume/sample volume was 0.2 for extracts, 0.15 for washing and quenching solutions, and 0.1 for supernatants.</p>
<p>20 μL of O-ethylhydroxylamine hydrochloride in pyridine (c(EtOX) = 20 mg mL−1) was added to the spiked samples and standards prior to drying in a vacuum centrifuge, in order to prevent the degradation of keto carbonyl group containing compounds. (23) The samples were evaporated to complete dryness at pressures of &lt;1 mbar to ensure efficient and quick drying at low temperatures. Dried samples were immediately crimped with magnetic caps to enable transportation on the robot and were placed in the drawer cooled stack (6 °C) of the MPS 2 autosampler until derivatization. If dried samples were not analyzed within 24 h, they were redried before analysis. In the first derivatization step, the samples were dissolved in 18 μL of water-free pyridine containing 19 mg mL–1 EtOx. The samples were incubated (25 °C, 120 min) under agitation (250 rpm) to convert ketone and aldehyde carbonyl groups into ethylhydroxylamino groups. Subsequently, 42 μL of MSTFA with 1% TMCS were added and the samples were heated and agitated (250 rpm) at 40 °C for 50 min to replace acidic protons by trimethylsilyl groups. Syringes were washed with pyridine before and after each liquid dosage. After a cool down to room temperature for 1.5 min in an open tray of the MPS2, samples were cooled in the cooled stack at 6 °C for 5 min and were then injected for GC–MS analysis. After injection, samples were placed back into the cooled tray at 6 °C. Derivatization was controlled by Maestro software package (Gerstel). Sequences were scheduled in a way that samples were derivatized during the GC runs of the preceding samples, hence enabling injection of the derivatized samples immediately after sample preparation was finished.</p>
<h4><strong>GC–MS/MS and GC–TOFMS Analysis</strong></h4>
<p>GC separation was carried out on <a href="https://gcms.labrulez.com/library?manufacturerItems=1&amp;search=Agilent+7890B"><strong>Agilent 7890B</strong></a> gas chromatographs coupled either with an Agilent Technologies <a href="https://gcms.labrulez.com/library?manufacturerItems=1&amp;search=7200B+Q-TOF"><strong>7200B</strong></a> Q-TOF (GC–TOFMS) mass spectrometer or with an Agilent Technologies <a href="https://gcms.labrulez.com/library?manufacturerItems=1&amp;search=7010B+Triple+Quadrupole"><strong>7010B Triple Quadrupole</strong></a> (GC–MS/MS) mass spectrometer (Agilent Technologies Inc.). Both GC–MS systems were equipped with (1) a nonpolar deactivated precolumn (3 m × 0.25 μm i.d., Phenomenex), which was connected to the analytical column via a backflush unit (purged ultimate union), and (2) a nonpolar deactivated postcolumn (3 m × 0.18 μm i.d., Phenomenex), which was connected with the analytical column via a second ultimate union T-piece serving as a restrictor column to the MS. The following analytical columns were tested: ZORBAX DB-5MS + 10 m Duragard capillary column (5% phenyl–95% dimethylpolysiloxane, 30 m × 250 μm × 0.25 μm) from Agilent Technologies Inc., and Optima 5 MS Accent (5% phenyl–95% dimethylpolysiloxane, 60 m × 250 μm × 0.25 μm) and Optima 1 MS Accent (100% dimethylpolysiloxane, 30 m × 250 μm × 0.25 μm), both from Macherey Nagel.<br/>The GC–QTOFMS instrument was equipped with an Agilent split/splitless injector, whereas the GC–MS/MS was equipped with an Agilent Multi Mode Inlet. Agilent Ultra Inert splitless liners with a single taper were used. Sample aliquots of 1 μL were injected in the splitless mode (220 °C, splitless time 2 min, septum purge flow 3 mL min–1). The following GC-temperature program was used: 70 °C (hold for 1 min), 30 °C min–1 to 240 °C, 2 °C min–1 to 260 °C, with 30 °C min–1 to 310 °C (hold for 3 min). The transfer line to the MS was kept at 280 °C. Helium 5.0 was used as carrier gas with a constant flow of 1.1 mL min–1 for the precolumn, 1.2 mL min–1 for the analytical column, and 1.4 mL min–1 for the post column. The electron ionization (EI) source of the instruments was operated with an electron energy of 70 eV and an emission current of 35 μA for the QTOF and 100 μA for the MS/MS at a temperature of 230 °C. For both instruments, the quadrupole was set at 150 °C. For chemical ionization (CI), an emission current of 10 μA was used, the ion source was operated at 150 °C, and a reagent gas flow of 20% CH4 (corresponding to 1 mL min–1) was employed. (24) The QTOF was operated in TOF-mode with a scan speed of 3.33 Hz and in 2 GHz Extended Dynamic Range mode. The mass accuracy was &lt;2 ppm for the calibration ions and resolution at approximately 8000 RFWHM at m/z 501.9706. Mass spectra were acquired in profile mode and were converted postacquisition to centroid. The GC–MS/MS system was operated with 3.5 Hz, and the resolution was set to widest (corresponding to a mass isolation window of 2.5 m/z) for both mass selective quadrupoles. For data evaluation, MassHunter Quantitative analysis B.08.00 (Agilent Technologies Inc.) was used.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Analytical_Chemistry_Anal_Chem_2020_92_7_4875_4883_Figure_1_Extracted_ion_chromatograms_GC_CI_TOF_of_the_three_biologically_relevant_N_acetylated_hexosamines_i_e_b8d10f631c.jpg" alt="Anal. Chem. 2020, 92, 7, 4875-4883: Figure 1. Extracted ion chromatograms (GC–CI-TOF) of the three biologically relevant N-acetylated hexosamines, i.e., N-acetylglucosamine (GlcNAc), N-acetylgalactosamine (GalNAc), andN-acetylmannosamine (ManNAc), using two different oximation reagents, namely, MOX and ETOX (dotted and dashed lines, respectively). For this purpose, the [M – CH₃]⁺ of the respective cis and trans 4TMS derivative was extracted. (a) Separation using a 60 m Optima 1 MS column is depicted. (b) Separation using a 60 m Optima 5 MS is shown."/></p>
<h3><strong>Conclusions</strong></h3>
<p>A robust and highly selective GC based separation method with mass spectrometric detection for GlcNAc was validated and successfully employed for the analysis of biotechnologically relevant <em>Penicillium chrysogenum</em>  samples. GlcNAc was detectable in all biological sample types. The presence of GlcNAc in the cultivation supernatant underlines the relevance of a separate sampling/preparation procedure for quenching supernatant, washing supernatant, cultivation supernatant, and cell-extract in combination with a robust quantification method for accurate intracellular balancing of GlcNAc in biological samples. In contrast to matrices like urine or blood plasma, the matrix of biotechnological samples can change vastly in the course of a batch or fed-batch experiment. This highly concentrated matrix clearly leads to a rapid degradation of the performance of the GC–MS system, more specifically S/N ratio and sensitivity. This heavy matrix, together with the strong matrix dependence of the derivatization efficiency, renders internal standardization with stable isotope labeling indispensable.</p>
<p>Nevertheless, the present method proved to be robust, since even after more than 50 injections, concentrations of less than 30 nmol L⁻¹ were still possible to be quantified. GC–MS instruments with automated liner exchange and ion source cleaning systems could restore the performance of the system within sequences.</p>
<p>A comparison of MS/MS and TOFMS shows comparable validation results with the exception of the linear range, which is more limited for TOFMS. However, TOFMS shows the advantage of changing data evaluation strategies retrospectively, such as the use of lower abundant isotopologues for peak integration in case of detector saturation. By this means, the full potential of TOFMS for accurate quantitation can be exploited.</p>


Selective and Accurate Quantification of N-Acetylglucosamine in Biotechnological Cell Samples via GC–MS/MS and GC–TOFMS

<p><strong>In the week from August 26, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4></blockquote><blockquote><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>3 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Wasson-ECE Instrumentation: Single Cylinder Sample Heater (New Product)</strong></h5><ul><li>Tu, 27.8.2024 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/4216">Registration</a></li></ul><p>Please join us for an introduction to Wasson's new Single Cylinder Heater/Auto Sampler.</p><h5><strong>2. Thermo Fisher Scientific: Improved EA-IRMS NCS workflow for archaeology and ecology applications</strong></h5><ul><li>We, 28.8.2024 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/4210">Registration</a></li></ul><p>This presentation will describe how we have optimized our Thermo Scientific EA IsoLink System with the new High Performance Kit for sulfur analysis to allow for high precision and accuracy NCS analysis.</p><h5><strong>3. LECO: Non-targeted screening in forensics, a discussion of method development and screening of forensic samples using GCXGC-TOFMS</strong></h5><ul><li>Th, 29.8.2024 14:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/4212">Registration</a></li></ul><p>Non-targeted screening in forensics, a discussion of method development and screening of forensic samples using GCXGC-TOFMS.</p>

Webinars LabRulezGCMS Week 35/2024

<p><strong>In the week of August 26, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p>
<blockquote>
<h4><a href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4>
</blockquote>
<blockquote>
<p><strong>👉 Search and filter in the largest global database</strong>  with over <strong>3 500 GC, LC, MS and spectroscopy webinars</strong>.</p>
</blockquote>
<h5><strong>1. US HUPO: Spotlight on Trainees: US HUPO 2024 Poster Presenters</strong></h5>
<ul>
<li>Tu, 27.8.2024 20:30 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/4189">Registrace</a></li>
</ul>
<p>Missed out on visiting all the posters in Portland? Join us to hear more about the exciting research your fellow trainees are working on! Hosted by US HUPO&#39;s ECR.</p>
<h5><strong>2. Agilent Technologies: Effortless UV-VIS Analysis with Long Pathlength Measurements</strong></h5>
<ul>
<li>Tu, 27.8.2024 21:30 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/3912">Registrace</a></li>
</ul>
<p>The Cary 3500&#39;s flexible sampling options make this concentration analysis more effortless than ever before.</p>
<h5><strong>3. Waters Corporation: Fundamentals and biotherapeutics applications of Multi-Angle and Dynamic Light Scattering</strong></h5>
<ul>
<li>We, 28.8.2024 17:00 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/4190">Registrace</a></li>
</ul>
<p>We will delve into the fundamentals and advantages of SEC-MALS and DLS for the biophysical characterization of monoclonal antibodies (mAbs), conjugated proteins, and adeno-associated viruses (AAVs).</p>
<h5><strong>4. Agilent Technologies: Panel Discussion: The Present &amp; Future of PFAS analysis – will we ever fully characterize PFAS?</strong></h5>
<ul>
<li>We, 28.8.2024 17:00 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/4166">Registrace</a></li>
</ul>
<p>Panel Discussion: The Present &amp; Future of PFAS analysis – will we ever fully characterize PFAS?</p>
<h5><strong>5. Agilent Technologies: Getting the Most from Your Diode Array Detector: From Selection to Optimization</strong></h5>
<ul>
<li>Th, 29.8.2024 17:00 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/3913">Registrace</a></li>
</ul>
<p>We will cover the fundamentals of how your DAD works. From there we will discuss the various options for DAD method optimization.</p>
<h5><strong>6. US HUPO: Spatial Single-Cell Mass Spectrometry in Liver Tissue Slices: Experimental Design and Pipelines for Analysis</strong></h5>
<ul>
<li>Fr, 30.8.2024 17:00 CEST</li>
<li><a href="https://lcms.labrulez.com/webinar/4192">Registrace</a></li>
</ul>
<p>Join the MS Imaging SIG for an interactive discussion with authors on experimental design and data pipelines for analysis.</p>


Webinars LabRulezLCMS Week 35/2024

<p><strong>In the week from August 26, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p>
<blockquote>
<h4><a href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4>
</blockquote>
<blockquote>
<p><strong>👉 Search and filter in the largest global database</strong>  with over <strong>3 500 GC, LC, MS and spectroscopy webinars</strong>.</p>
</blockquote>
<h5><strong>1. Agilent Technologies: Effortless UV-VIS Analysis with Long Pathlength Measurements</strong></h5>
<ul>
<li>Tu, 27.8.2024 21:30 CEST</li>
<li><a href="https://icpms.labrulez.com/webinar/3912">Registrace</a></li>
</ul>
<p>The Cary 3500&#39;s flexible sampling options make this concentration analysis more effortless than ever before.</p>
<h5><strong>2. Thermo Fisher Scientific: Improved EA-IRMS NCS workflow for archaeology and ecology applications</strong></h5>
<ul>
<li>We, 28.8.2024 16:00 CEST</li>
<li><a href="https://icpms.labrulez.com/webinar/4210">Registrace</a></li>
</ul>
<p>This presentation will describe how we have optimized our Thermo Scientific EA IsoLink System with the new High Performance Kit for sulfur analysis to allow for high precision and accuracy NCS analysis.</p>
<h5><strong>3. Mettler-Toledo: The Exciting World of Flash DSC</strong></h5>
<ul>
<li>Th, 29.8.2024 08:00 CEST</li>
<li><a href="https://icpms.labrulez.com/webinar/3914">Registrace</a></li>
</ul>
<p>Advanced Material Characterization by Fast-Scanning Calorimetry.</p>
<h5><strong>4. SelectScience/Andor: The Cellular Itinerary of Renal Aquaporin-2 Shuttling with 4.5x Expansion Microscopy</strong></h5>
<ul>
<li>Th, 29.8.2024 17:00 CEST</li>
<li><a href="https://icpms.labrulez.com/webinar/4191">Registrace</a></li>
</ul>
<p>This webinar will present results showing that newly established 4.5 expansion microscopy is an ideal approach to obtain detailed information regarding the AQP2 vesicle population.</p>


Webinars LabRulezICPMS Week 35/2024

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LabRulez

LECO Training Course CS-744/844 Series & ON/ONH-736/836 Series

SCIEX at SOFT/TIAFT

Waters at SOFT/TIAFT 2026

Automatic ICP-OES Analysis of Lubricating Oils Using SPECTRO GENESIS DSOI and ACAROS Automation

Detection and Identification of Microplastics in Water and Other Matrices Using the Agilent Laser Infrared Spectroscopy Microscope

Unlocking New Analytical Possibilities with Waters APGC Solutions