<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 29th June 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application note by <strong>Agilent Technologies, </strong>presentation by <strong>MDCW / William &amp; Mary </strong>and posters by <strong>Shimadzu</strong> and <strong>Thermo Fisher Scientific</strong> <strong>/ ASMS!</strong></p><h3><strong>1. Agilent Technologies: Residual Solvents Analysis Based on the 2025 USP &lt;467&gt; and Chinese Pharmacopoeia (ChP 0861)</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/br_8890b_gc_5994_9205en_agilent_fb5db29527.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p><strong>Using the </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8697"><strong>Agilent 8697 headspace sampler</strong></a><strong> and </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>Agilent 8890B GC system</strong></a></p><p>Residual solvents are routinely introduced during pharmaceutical manufacturing as part of synthesis, purification, or formulation processes. Because these volatile organic compounds may pose toxicological risks, their levels must be carefully monitored to ensure patient safety and regulatory compliance. As a result, residual solvent analysis remains a critical component of quality control throughout the pharmaceutical development and manufacturing lifecycle.&nbsp;</p><p>USP &lt;467&gt; provides a harmonized framework for residual solvent analysis, defining solvent classifications, concentration limits, and analytical requirements.1 In September 2025, USP &lt;467&gt; was revised to reflect updated toxicological evaluations and regulatory expectations. The revised chapter expanded the class 2B solvent list and introduced performance requirements for newly added compounds, including tertiary butyl alcohol and cyclopentyl methyl ether (CPME). These updates increase the analytical scope of residual solvent testing and place greater emphasis on consistent system performance and suitability verification. In China, residual solvent control is governed by General Chapter 0861 of the Chinese Pharmacopoeia (ChP 0861)2 , which adopts a risk based classification system consistent with the International Council for Harmonisation (ICH) Q3C.3 Although the Chinese Pharmacopoeia uses different terminology for analytical procedures, its regulatory intent, solvent classification, and control principles are harmonized with USP &lt;467&gt;.&nbsp;</p><p>Gas chromatography with headspace sampling is widely used for residual solvent determination due to its robustness and suitability for volatile analytes. Alongside evolving regulatory requirements, modern GC systems have increasingly focused on intelligent operation to support method execution and compliance. The Agilent 8890B gas chromatograph incorporates GC Assist to help users perform a performance check of the GC system. When performance criteria are not met, the GC system provides alerts to notify the user. Upon user instruction, the GC can initiate a guided troubleshooting workflow, supporting step-by-step fault diagnosis through autonomous diagnostic functions, helping both experienced and less experienced analysts resolve issues efficiently during routine operation. In this application note, a headspace GC/FID method is presented for the determination of class 1, 2A, and the expanded class 2B residual solvents. This study demonstrates how updated regulatory requirements can be addressed using an intelligent GC platform that supports reliable system performance assessment, simplified troubleshooting, and consistent analytical performance.</p><h4><strong>Experimental</strong></h4><p>The experimental conditions described in this study follow the general chromatographic principles outlined in USP &lt;467&gt; procedures A and B. They are also consistent with the recommended headspace GC methods described in ChP 0861. In this work, the screening and confirmation concepts of procedures A and B were implemented simultaneously through a dual-column, dual-FID/GC configuration. Samples were introduced by an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8697"><strong>Agilent 8697 headspace sampler</strong></a> to an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>8890B GC</strong></a> and equally split to an Agilent DB-Select 624 UI and a DB-WAX UI column for parallel detection, as shown in Figure 1. Comparable chromatographic performance was achieved with both helium and nitrogen carrier gases. Data were acquired using Agilent OpenLab CDS version 2.8, and noise was determined using a peak-to-peak (PtoP) approach for calculation of signal-to-noise ratios for target analytes.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This application note demonstrates a harmonized headspace GC/FID workflow suitable for residual solvent analysis in compliance with both the 2025 revision of United States Pharmacopoeia (USP) &lt;467&gt; and the Chinese Pharmacopoeia (ChP 2025, General Chapter 0861). By implementing a dual‑column, dual-FID configuration on a single inlet, screening and confirmatory analyses can be performed simultaneously, significantly reducing total analysis time compared to traditional sequential approaches while maintaining orthogonal separation selectivity. The integrated Agilent 8697 headspace sampler and 8890B GC platform provides consistent chromatographic performance with both helium and nitrogen carrier gases, supporting flexible laboratory operation without compromising data quality. Beyond analytical performance, the intelligent capabilities of the 8890B GC enhance operational reliability and simplify daily use. Through continuous interaction with the user, the built‑in GC Assist function operates in a guided, wizard‑like manner, leading users step by step through the troubleshooting process for effective fault diagnosis. Together, these features enable a compliant, time-efficient, and user-friendly solution for residual solvent testing under the latest USP &lt;467&gt; and ChP&nbsp;0861 requirements.</p><h3><strong>2. MDCW / William &amp; Mary: Developing a Combined Approach to Green Gunshot Residue Analysis in the Forensic Laboratory</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_24_Saunders_f2c5bcdb20.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>Developing a Combined Approach to Green Gunshot Residue Analysis in the Forensic Laboratory presents a multidisciplinary strategy for improving the forensic analysis of <strong>"green" gunshot residue (GSR)</strong>, which originates from lead-free ammunition. Traditional GSR analysis relies heavily on the detection of lead, barium, and antimony particles using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). However, environmentally friendly ammunition replaces these heavy metals with more common elements, making conventional forensic protocols less effective. The authors therefore propose combining inorganic GSR (IGSR) characterization by SEM-EDS with organic GSR (OGSR) analysis using comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS).</p><p>The presentation first describes the development of a new SEM-EDS characterization strategy tailored to green GSR particles. Instead of relying solely on the elemental composition defined by existing OSAC guidelines, the approach incorporates both particle morphology and elemental complexity. In parallel, the researchers optimized an extraction procedure for organic residues and developed a dedicated GC×GC-MS method. Method optimization focused on key chromatographic parameters such as inlet temperature, modulation period, carrier gas selection, and oven temperature program. Compared with previously published methods, the optimized workflow provided higher peak capacity, improved analyte resolution, and enhanced detection of characteristic OGSR compounds.</p><p>To verify the analytical performance, the optimized GC×GC-MS method was evaluated using several reference standards, including phthalates, nitroaromatic explosives, nitroglycerin, and a multi-component gun surveillance standard. The resulting two-dimensional chromatograms demonstrated excellent separation and clear identification of compounds relevant to firearm discharge residues, confirming that the method can reliably detect a broad range of organic GSR markers. The combination of enhanced chromatographic separation with mass spectrometric detection offers substantially greater resolving power than conventional one-dimensional GC-MS, making it particularly valuable for complex forensic samples.</p><p>The authors conclude that integrating SEM-EDS with GC×GC-MS provides a more comprehensive approach to modern GSR analysis, particularly for lead-free ammunition. The study successfully established a characterization strategy for inorganic green GSR, optimized extraction and chromatographic conditions for organic GSR, and verified the visibility and identification of target analytes using certified standards. Future work will focus on further method validation, incorporating retention indices and sorbent-based extraction techniques, and strengthening the scientific robustness of the approach to support forensic evidence under <strong>Rule 702</strong>, thereby improving the reliability and courtroom acceptance of green GSR analyses.</p><h3><strong>3. Shimadzu / ASMS: Impact of Soil Matrix on Microplastics Analysis by Py-GC/MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_222_Impact_of_Soil_Matrix_on_Microplastics_Analysis_by_Py_GCMS_63fdb8ef7d.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The matrix is not just background—it actively participates in pyrolysis chemistry. Lignin-rich soils can co-pyrolyze, producing compounds that overlap with common PS or PVC markers, complicating interpretation. Matrix variability is substantial, with clear chemical and physical differences between forest soils, agricultural land, river sediments, and landfill cover materials. Soil particles act as sinks and sorbents, interacting with microplastics and altering degradation pathways. Sample preparation can introduce bias, and in some cases does more harm than good.&nbsp;</p><p>In this poster, we present a method to improve quantitative accuracy in Py-GCMS microplastics analysis by assessing the matrix effect, while also addressing key challenges in the qualitative identification</p><h4><strong>Experimental Methods&nbsp;</strong></h4><ul><li>Three soil samples were collected from different locations (Figure 1) and homogenized using a mortar/pestle.&nbsp;</li><li>From each sample, 200g were dried in a vial for 3 hours at 40C and 2mg was weighed into a PY cup.&nbsp;</li><li>Targeted microplastics include PE, PP, PS, ABS, PMMA, PC, PVC, N6, and N66. The percentage distribution of polymers in the MPs-CaCO3 standard, as well as the mass of each analyte in a 4 mg standard within a CaCO3 diluent, is shown in Figure 1.&nbsp;</li><li>These were analyzed using a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Py-GC%2FMS"><strong>PY-GCMS instrument</strong></a>, shown in Figure 2.&nbsp;</li><li>A 5-point calibration curve was prepared, in triplicate, by weighing 0.2mg, 0.4mg, 0.8mg, 2.0mg, and 4.0mg from Frontier’s Low calibration standard mix of microplastics.&nbsp;</li><li>A matrix-matched calibration curve was generated by spiking sample B with the same concentration as the calibration levels.&nbsp;</li><li>Samples were analyzed, and analytes in the sample were quantified in µg, calculated using the calibration curve of known standard concentration.&nbsp;</li><li>Recovery studies were performed in blank samples to evaluate matrix effect for the targeted analytes. For this, a 2mg sample was weighed in triplicate, and 2mg of the standard mix was combined with 2mg of CaCO3 diluent.</li></ul><h4><strong>Conclusions</strong></h4><p>Future work will focus on improving microplastic identification by using multiple markers to reduce false positives, while advancing polymer identification tools and spectral libraries to better handle high-background matrix interferences.</p><p>Sample preparation is an important factor, and it needs to be considered and studied for different sample types, including environmental and clinical samples</p><h3><strong>4. Thermo Fisher Scientific / ASMS: Untargeted analysis of volatile PFAS in indoor air by thermal desorption GC high resolution </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/472"><strong>Orbitrap Mass Spectrometer</strong></a></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004717_lsms_volatile_pfas_air_exploris_gc_efs_po004717_asms2026_na_en_69541bd1e3.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) are persistent “forever chemicals” widely used in consumer products and commonly detected in indoor air. Volatile PFAS can originate from treated materials and degrade into harmful compounds linked to adverse health effects. Thermal desorption (TD) enables efficient air monitoring by preconcentrating volatile compounds for direct GC-MS analysis. Coupling TD with high-resolution Orbitrap GC-MS and advanced data processing allows comprehensive, untargeted screening of PFAS, supporting improved indoor air quality assessment.</p><h4><strong>Materials and methods</strong></h4><h5><strong>Sample preparation&nbsp;</strong></h5><ul><li>PFAS standards prepared in methanol and spiked onto sorbent tubes</li><li>Indoor air sampled (35 L) from carpeted, non-carpeted, and cleaning storage areas&nbsp;</li><li>Air collected using sorbent tubes with pumped sampling (TD-compatible). Test method(s)&nbsp;</li><li>Samples analyzed using thermal desorption (TD)–GC-MS (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/472"><strong>Orbitrap Exploris GC</strong></a>)&nbsp;</li><li>TD preconcentration followed by GC separation and HRAM full-scan acquisition (EI/CI)&nbsp;</li><li>Method enabled untargeted screening of volatile compounds.&nbsp;</li></ul><h5><strong>Data analysis&nbsp;</strong></h5><ul><li>Data processed using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/76"><strong>Thermo Scientific Chromeleon CDS</strong></a>, FreeStyle, and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/1759"><strong>Compound Discoverer Software&nbsp;</strong></a></li><li>Workflow included peak detection, deconvolution, and library matching.</li></ul><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>TD-GC Orbitrap MS enables sensitive, untargeted detection of volatile PFAS in indoor air with minimal sample preparation&nbsp;</li><li>HRAM data combined with advanced software workflows provides confident identification and efficient data filtering&nbsp;</li><li>Higher PFAS levels observed in carpeted and cleaning areas, highlighting indoor sources and exposure risk</li></ul></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 27, 2026

News from LabRulezLCMS Library - Week 27, 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 29th June 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies </strong>and<strong> Thermo Fisher Scientific </strong>and brochure by <strong>Shimadzu!</strong></p><h3><strong>1. Agilent Technologies: Analysis of High Purity Titanium Using an </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=9500"><strong>Agilent 9500 ICP-QQQ</strong></a></h3><p><strong>Ensuring purity and performance of titanium materials used in high-tech industries&nbsp;</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_high_purity_titanium_9500_icp_qqq_5994_9024en_agilent_56ab5e943b.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>Importance of high-purity titanium and the role of ICP-QQQ&nbsp;</strong></h5><p>High-purity titanium (Ti) is a critical material in high-tech industries such as semiconductor manufacturing and aerospace engineering. In semiconductor applications, Ti is widely used as a sputtering target for thin-film deposition, where even trace levels of impurities can negatively affect film uniformity, electrical properties, and device reliability. In aerospace applications, Ti is valued for its high strength-to-weight ratio and corrosion resistance, making it an ideal material for engine components and structural parts. However, any impurities can compromise the mechanical integrity and diminish the long-term performance of components, especially when operating under extreme conditions.</p><p>Ensuring the reliability and functionality of Ti in these demanding environments requires precise quantification of trace impurities in the raw material. Triple quadrupole Inductively Coupled Plasma Mass Spectrometry (ICP-QQQ) provides robust suppression of spectral interferences and ultra-low detection limits (DLs), enabling accurate determination of impurities at or below the 1 mg/kg (ppm) level in the solid. This level of sensitivity is particularly important for quality control (QC) of high-purity Ti, where conventional techniques such as XRF, ICP-OES, and GD-MS lack the sensitivity and DLs.&nbsp;</p><p>For unrivalled interference reduction using reactive cell gases, Agilent ICP-QQQ instruments include two unit mass (1 u) quadrupole mass filters, Q1 and Q2.1 Q1 is positioned before the collision/reaction cell (CRC) to select which ions enter the cell for reaction with the cell gas. Q2 filters ions that exit the cell before they pass to the detector. This tandem mass spectrometer (MS/MS) operation allows for unmatched control of reaction chemistry in the CRC, making the technique useful for handling intense spectral interferences, including polyatomic, doubly charged ion (M++), isobaric, and peak overlap interferences.&nbsp;</p><p>Using the newly developed <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=9500"><strong>Agilent 9500 Triple Quadrupole ICP-MS</strong></a> featuring a Dual-Cell System (DCS) CRC and equipped with an optional m-lens, analysts can confidently analyze Ti matrix samples and verify material purity over extended measurement periods. The m-lens is designed with an optimized geometry that minimizes background signals from easily ionized elements that can deposit on interface components during long runs. This feature enables the instrument to maintain high-power, matrix-tolerant plasma conditions while achieving ultralow background equivalent concentrations (BECs), which is critical for ppt-level impurity analysis. Operating the DCS with a suitable cell gas effectively controls spectral interferences from Ti-based species (Ti²+ and TiO+ ) that impact elements like sodium (Na), magnesium (Mg), copper (Cu), and zinc (Zn). Together with the m‑lens, this approach ensures accurate measurement of trace elemental impurities, enabling compliance within stringent industry standards. The effectiveness of the m‑lens in minimizing background signals and enabling ppt‑level impurity analysis under robust plasma conditions has also been demonstrated in high-matrix applications using ICP‑QQQ.2, 3 In addition to interference control, the 9500 ICP-QQQ system’s robustness and reproducibility make it well suited for routine analysis in both research and production settings. This capability supports the continued advancement of high-tech applications that rely on ultra-clean titanium.</p><p>In this study, a 200 ppm Ti solution prepared from a high-purity Ti powder was used to represent a typical sample encountered in advanced material analysis. The performance of the 9500 ICP-QQQ for quantifying trace impurities, including Na, Mg, Cu, and Zn, in a high Ti matrix was assessed through spike-recovery experiments and long-term stability tests.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study demonstrated the effectiveness of the Agilent 9500 ICP-QQQ with m-lens for the ultra-trace analysis of impurity metals in high-purity titanium. By applying optimized reaction gas conditions and mass-shift techniques, spectral interferences from Ti-based species such as Ti²+ and TiO+ were successfully mitigated, enabling accurate quantification of elements like Mg, Cu, and Zn.&nbsp;</p><p>The method achieved limits of quantification in the sub-ppm range for the undiluted Ti digestion solution and maintained stable ISTD signals over extended measurement periods. Spike recovery tests confirmed high accuracy and reproducibility, with most elements showing recoveries within ±10% and RSDs below 3%.&nbsp;</p><p>These results confirm that the 9500 ICP-QQQ is a robust and reliable tool for quality control of high-purity Ti, supporting its critical applications in semiconductor and aerospace industries where impurity levels must be strictly controlled.</p><h3><strong>2. Shimadzu: Scanning Probe Microscope /Atomic Force Microscope SPM-9700HT Plus</strong></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/c147_e021_4c550d3be3.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The <strong>Shimadzu SPM-9700HT Plus</strong> is a high-throughput <strong>scanning probe microscope (SPM) / atomic force microscope (AFM)</strong> designed for three-dimensional surface imaging and nanoscale characterization of material properties across a broad range of scientific and industrial applications. The system combines high-resolution topographical imaging with multiple AFM measurement modes, including contact, dynamic, phase, lateral force, force modulation, and force-curve measurements, while optional modules extend its capabilities to techniques such as Kelvin probe force microscopy (KPFM), magnetic force microscopy (MFM), conductive AFM, piezoresponse force microscopy (PFM), and scanning tunneling microscopy (STM). A wide selection of interchangeable scanners, environmental accessories, optical microscope units, and specialized sample holders enables the instrument to be configured for diverse analytical requirements.</p><p>A major focus of the brochure is the system's emphasis on automation and ease of use through Shimadzu's <strong>Analytical Intelligence</strong> technology. Features such as <strong>Observation Navigation</strong>, <strong>NanoAssist</strong>, and the optional <strong>Cantilever Master</strong> automate instrument setup, cantilever installation, optimization of imaging parameters, and measurement workflows, allowing operators with varying levels of experience to acquire high-quality, reproducible AFM data. The redesigned control electronics and scanning system also enable high-throughput imaging and rapid physical property mapping while maintaining nanoscale resolution. In addition, the head-slide mechanism simplifies sample exchange without removing the cantilever, increasing productivity during routine measurements.</p><p>Beyond surface topography, the <strong>SPM-9700HT Plus</strong> provides extensive quantitative analysis capabilities through integrated software for roughness measurements, particle analysis, cross-sectional profiling, and morphological characterization. Optional <strong>Nano 3D Mapping Fast</strong> technology extends the instrument to nanoscale mechanical property measurements by performing force-curve mapping, allowing localized evaluation of adhesion, Young's modulus, and other mechanical properties of thin films, polymers, biomaterials, and soft samples. The optional Particle Analysis Software further enables automated extraction, classification, statistical evaluation, and export of particle size and morphology data for large datasets.</p><p>The brochure demonstrates the versatility of the platform through numerous application examples spanning <strong>electronics, semiconductor devices, magnetic materials, life sciences, industrial materials, batteries, polymers, nanomaterials, food science, and chemistry</strong>. Representative studies include magnetic domain imaging, organic thin-film transistor characterization, collagen and DNA visualization, live-cell imaging, lithium-ion battery electrode and separator analysis, photocatalyst surface potential measurements, polymer phase imaging, cellulose nanofiber characterization, and beer yeast morphology. Together, these examples highlight the <strong>Shimadzu SPM-9700HT Plus</strong> as a comprehensive AFM platform capable of combining rapid imaging, advanced nanoscale property mapping, and automated data analysis for both research and routine industrial quality control.</p><h3><strong>3. Thermo Fisher Scientific: Enhancing Monoclonal Antibody Yield and Quality Through Automated Multi-Component Feedback Control Loops Using the MarqMetrix All-In-One Process Raman Analyzer</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/enhancing_monoclonal_antibody_an1506_en_bba763e865.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The application of Raman spectroscopy for real-time monitoring and control of bioreactors marks a significant advancement in bioprocessing technology. Over the past decade, its adoption has enabled tighter control of critical process parameters (CPPs), offering early indicators of process performance to ensure consistency and improve product quality. Raman spectroscopy leverages the unique vibrational signatures of molecules, allowing for highly specific detection even in complex biological matrices. This enables simultaneous, real-time monitoring of multiple CPPs, including nutrient concentrations, metabolic by-products, and cell density. As a result, users gain deep, real-time insights into cellular metabolism and can implement more dynamic, adaptive feeding strategies based on metabolic network understanding.&nbsp;</p><p>Previous studies have demonstrated the negative impact of high lactate on cell health and quantity and quality of titer produced.² In this study, we demonstrate the successful implementation of process Raman analyzer for simultaneous multi-component feedback control of glucose and lactate in a bioreactor. By continuously monitoring both analytes, the feedback control loop dynamically maintained a constant total carbon concentration (glucose + lactate) at a setpoint of 2 g/L.&nbsp;</p><p>This advanced carbon-source-based control strategy ensured that cellular metabolic demands were met while promoting lactate consumption toward the end of the run. As a result, lactate accumulation was significantly reduced, leading to substantial improvements in titer yield, product quality, and cell viability compared to standard bolus feeding strategies (Figure 2).</p><p>The outcomes of this work underscore the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/2233"><strong>Thermo Scientific™ MarqMetrix™ All-In-One Process Raman Analyzer </strong></a>as a key Process Analytical Technology (PAT) tool-enabling real-time, multi-analyte control for any biomanufacturer seeking to engage in intelligent, automated biomanufacturing.</p><h4><strong>Conclusion&nbsp;</strong></h4><h5><strong>1. Unmatched Real-Time Control Capability:&nbsp;</strong></h5><p>Maintaining a constant total carbon concentration (glucose + lactate) of 2 g/L in dynamic bioreactor environments demands precise, simultaneous analyte monitoring. The MarqMetrix All-In-One Process Raman Analyzer delivers near real-time, high-fidelity data every two minutes, empowering advanced control strategies that are simply not feasible with conventional technologies. This makes it an indispensable PAT tool for modern bioprocessing.&nbsp;</p><h5><strong>2. Proven Impact on Product Yield and Quality:&nbsp;</strong></h5><p>The Raman-enabled carbon control strategy resulted in a &gt;10% increase in titer and a reduction in glycation by 83% and 66% compared to continuous and fed-batch glucose control, respectively. These outcomes underscore the analyzer’s transformative impact on both product quantity and quality.&nbsp;</p><h5><strong>3. Versatile Automation Across Bioprocesses:&nbsp;</strong></h5><p>All three bioreactor runs—each employing distinct control logics (Table 2)—were successfully managed through automated feedback using the process Raman analyzer. Its flexible design, including easily swappable probes, supports seamless adaptation to other critical metabolites such as amino acids, making it a universal solution for bioprocess control.&nbsp;</p><h5><strong>4. Foundation for Intelligent Manufacturing:&nbsp;</strong></h5><p>With its real-time, data-rich insights and seamless integration into automated systems, the MarqMetrix All-InOne analyzer is not just a monitoring tool; it is a cornerstone technology for intelligent, AI-driven biomanufacturing. It enables consistent, high-quality production while reducing time, cost, and variability.</p>

News from LabRulezICPMS Library - Week 27, 2026

<p><strong>This study presents an optimized dispersive liquid–liquid microextraction (DLLME) method coupled with GC-FID for the determination of eight priority polycyclic aromatic hydrocarbons in surface waters. Experimental design approaches, including fractional factorial and Box–Behnken designs, were used to optimize extraction conditions and maximize analytical performance.</strong></p><p>The validated method achieved rapid chromatographic separation, low detection limits, good precision, and high enrichment factors while maintaining favorable green analytical characteristics. Successful application to wastewater, lake, river, and drain water samples demonstrates its suitability for routine environmental monitoring of PAHs.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c01489"><strong>Experimental Design-Based Dispersive Liquid–Liquid Microextraction with GC-FID for Determination of Polycyclic Aromatic Hydrocarbons in Surface Water</strong></a></h4><p>Chen Minghong, Song Peiyu, Tien Ping Lee, Garret Chan Zhe Ming, Philip J. Marriott, and Yong Foo Wong*</p><p>ACS Omega 2026, 11, 21, 31418–31431</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.6c01489">https://doi.org/10.1021/acsomega.6c01489</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Polycyclic aromatic hydrocarbons (PAHs) are organic pollutants containing two or more fused benzene rings and are widely associated with carcinogenic, teratogenic, and mutagenic properties. <a href="javascript:void(0);">(1)</a> These hydrophobic substances can bioaccumulate with long environmental half-lives and are classified as high priority ecotoxicants of the first danger class. <a href="javascript:void(0);">(1,2)</a> Anthropogenic activities (e.g., fossil fuel combustion, industrial processes, biomass burning, and others) are predominantly recognized as the primary sources of PAHs in most environmental compartments. <a href="javascript:void(0);">(3−6)</a> In the present work, the hydrophobic nature of PAHs facilitates adsorption onto suspended particulate matter and organic material in aquatic systems, followed by deposition into underlying sediments. <a href="javascript:void(0);">(7)</a> These persistent organic pollutants have been reported in surface waters as well as estuarine and coastal environments and can potentially disrupt ecosystem functioning. <a href="javascript:void(0);">(7,8)</a></p><p>From a public health perspective, PAHs exposure via upon ingestion, has been linked to a spectrum of adverse health effects such as cancer and reduced fertility. <a href="javascript:void(0);">(2,9)</a> Sixteen unsubstituted PAHs have been designated as priority pollutants by the United States Environmental Protection Agency (USEPA). <a href="javascript:void(0);">(10)</a> The International Agency for Research on Cancer (IARC) has classified benzo(a)pyrene (BaP) in Group 1 (carcinogen to humans) and other PAHs in Group 2A (possible human carcinogens). <a href="javascript:void(0);">(10,11)</a> The maximum permissible concentrations of benzo(a)pyrene (0.00001 mg/L) in water intended for drinking water is regulated by the European Union (EU). The EU limits the total content of polyaromatic compounds in drinking water to &lt;0.1 μg/L. <a href="javascript:void(0);">(12)</a> In heavily polluted waterways, PAH concentrations have been reported to reach 10 μg/mL. <a href="javascript:void(0);">(13)</a> Epidemiological evidence also suggests a positive relationship between increased cancer incidence in human populations that are having high exposure to organic ecotoxins. <a href="javascript:void(0);">(14)</a> For these reasons, quantitative assessments of PAH occurrence and distribution in surface waters remain important and fertile research topics. <a href="javascript:void(0);">(15,16)</a></p><p>PAHs in water and environmental matrices are routinely analyzed using either gas chromatography (GC) and/or liquid chromatography (LC) with various detection modalities. <a href="javascript:void(0);">(17,18)</a> The coupling of chromatography to mass spectrometry has been the preferred technique, owing to the distinct selectivity and sensitivity, particularly when operated in selected ion monitoring (SIM) or multiple reaction monitoring (SRM) modes. <a href="javascript:void(0);">(19)</a> Additionally, LC coupled with fluorescence detection is also extensively utilized for PAH analysis. <a href="javascript:void(0);">(20,21)</a> As PAHs typically occur at trace to ultratrace levels in complex real-world matrices, sample pretreatment and/or preconcentration is generally required prior to instrumental analysis. <a href="javascript:void(0);">(22,23)</a> Conventional approaches such as liquid–liquid extraction and solid-phase extraction are widely used but are often solvent-intensive and laborious and generate substantial hazardous waste. More recently, microextraction techniques (e.g., dispersive microsolid phase extraction, dispersive liquid–liquid microextraction (DLLME), solid phase microextraction, etc.) have emerged as attractive alternatives, providing advantages such as speed and simplicity and requiring substantially lower volumes of hazardous solvents. <a href="javascript:void(0);">(24−26)</a></p><p>DLLME has shown good efficiency for extracting and preconcentrating hydrophobic PAHs from aqueous matrixes. <a href="javascript:void(0);">(24,27)</a> Briefly, DLLME involves rapid injection of a small volume of an extraction solvent (immiscible with water) and dispersive solvent into the aqueous sample. <a href="javascript:void(0);">(24)</a> Target analytes partition into the microdroplets and are subsequently recovered in a minimal volume of the organic phase after centrifugation. The large interfacial contact area between the two phases enhances mass transfer, leading to fast attainment of extraction equilibrium with high enrichment factors. <a href="javascript:void(0);">(28,29)</a> DLLME has been applied to a wide range of matrices, including environmental samples, <a href="javascript:void(0);">(25,30)</a> milk and dairy products, <a href="javascript:void(0);">(31)</a> honey, <a href="javascript:void(0);">(32)</a> and others. <a href="javascript:void(0);">(33)</a> Optimization of DLLME conditions for targeted solutes is often performed using a one-factor-at-a-time approach, which is time-consuming, labor-intensive, and may inadequately take into account interaction between or among variables. <a href="javascript:void(0);">(34)</a> In contrast, multivariate experimental design methodologies accommodate simultaneous variation of multiple extraction variables, facilitating identification of interaction effects and development of statistically robust models. <a href="javascript:void(0);">(35−37)</a></p><p>Over the past decade, multivariate design of experiments (DOE) has become an important optimization strategy for process development. Compared with traditional one-factor-at-a-time approaches, DOE can reduce time, effort, and resource consumption while extracting meaningful information from a relatively small number of experimental analyses. <a href="javascript:void(0);">(37−40)</a> Among the DOE frameworks, the Box-Behnken design (BBD), an economical variant of response surface methodology, has been widely used for process optimization, offering high statistical efficiency and good predictive performance when tuning experimental variables in analytical and industrial applications. <a href="javascript:void(0);">(35,39,41−45)</a> This study evaluates the applicability of using RSM to optimize DLLME conditions for selective extraction and preconcentration of acenaphthene, fluorene, anthracene, phenanthrene, fluoranthene, pyrene, benzo(a)anthracene, and benzo(a)pyrene. A fractional factorial design (FrFD) was initially used to screen and identify statistically significant DLLME variables. The selected factors were then optimized using the BBD to construct quadratic models and generate response surface plots for determining optimal extraction conditions. The optimized DLLME-GC-FID method was validated, and AGREEprep and AGREE were used to quantify ‘greenness’ metric scores. Analytical practicability of the validated method was demonstrated by determining the targeted PAHs in several surface water samples.</p><h4><strong>2. Experimental Section</strong></h4><h5><strong>2.4. GC-FID Analysis</strong></h5><p>All experiments were performed using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7890B"><strong>Agilent 7890B GC system</strong></a> equipped with a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7693A"><strong>G4513A autosampler</strong></a> and a split–splitless inlet (Agilent Technologies; Santa Clara, CA, USA). Chromatographic separation was effected by using a <strong>DB-5HT column</strong> (Agilent Technologies, Santa Clara, CA, USA; 30 m × 0.25 mm I.D. × 0.25 μm film thickness). Injection mode and oven temperature programming were optimized to achieve baseline separation of all target PAHs. Helium (99.999%) was used as the carrier gas at a constant flow rate of 1 mL/min. Splitless mode with a splitless time of 2.1 min was used, with a 1 μL injection volume. The injector temperature was maintained at 300 °C. The oven temperature program was 70 °C (hold for 3.3 min) and ramped to 300 °C (hold 5 min) at a rate of 25 °C/min. The FID temperature was set to 300 °C.</p><h4><strong>3. Results and Discussion</strong></h4><p>The initial GC-FID conditions were adopted from Hor et al. for the determination of BAP, BAA, BBF, and chrysene in tocotrienol concentrates. <a href="javascript:void(0);">(52)</a> Under those chromatographic conditions, baseline separation of all the targeted PAHs could not be achieved (Flt, Pyr, BaA, and BaP). Hence, GC conditions, particularly the oven temperature program, were briefly optimized to obtain baseline separation of all the targeted PAHs (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c01489#fig1">Figure 1</a>A).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_21_31418_31431_Figure_1_Chromatograms_of_Ai_standard_mixture_265d7e1014.jpeg" alt="ACS Omega 2026, 11, 21, 31418–31431: Figure 1. Chromatograms of (Ai) standard mixture (100 μg/L) before DLLME; (Aii) standard mixture (100 μg/L) after DLLME; (B) lake water sample spiked with PAHs (10 μg/L); and (C) wastewater sample. 1, Ace; 2, Flu; 3, Ant; 4, Phe; 5, Flt; 6, Pyr; 7, BaA; 8, BaP." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_21_31418_31431_Figure_1_Chromatograms_of_Ai_standard_mixture_265d7e1014.jpeg 234w," sizes="100vw" width="2100" height="1402"></p><h5><strong>3.1. Evaluation of the Type of Extractants and Dispersants for DLLME</strong></h5><p>Extraction performance in DLLME is strongly influenced by the choice of extraction solvent (i.e., that which is sedimented), which controls the solutes’ partitioning behavior between the aqueous and organic phases. <a href="javascript:void(0);">(24)</a> Five extraction solvents of different polarity, namely, dichloromethane (DCM, dielectric constant (ε): 8.93 <a href="javascript:void(0);">(53)</a>), chloroform (ε: 4.81 <a href="javascript:void(0);">(54)</a>), carbon tetrachloride (ε: 2.24 <a href="javascript:void(0);">(55)</a>), chlorobenzene (ε: 5.62 <a href="javascript:void(0);">(56)</a>), and cyclohexane (ε: 2.02 <a href="javascript:void(0);">(57)</a>), were evaluated. Based on the overall response (i.e., peak areas), dichloromethane outperformed the other chlorinated solvents (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c01489#fig2">Figure 2</a>). This might be attributed to the stronger partitioning of PAHs into DCM, which exhibited the highest polarity among the tested extractants. <a href="javascript:void(0);">(58)</a> Therefore, DCM was selected as the extraction solvent. It is known that the dispersive solvent serves as a “bridge” between the aqueous sample and the water-immiscible extractant, and its selection is therefore crucial to DLLME performance. Five dispersive solvents (methanol, ε: 33; <a href="javascript:void(0);">(59)</a> ethanol, ε: 24.5; <a href="javascript:void(0);">(60)</a> isopropanol, ε: 20.1; <a href="javascript:void(0);">(61)</a> acetone, ε: 20.7; <a href="javascript:void(0);">(62)</a> acetonitrile, ε: 36 <a href="javascript:void(0);">(63)</a>) of different polarities were studied. Among these, ACN having the highest polarity provided the highest extraction response. This might be attributed to the reduced interfacial tension, which promotes formation of smaller microdroplets, and increases interfacial area for partitioning process, thereby improving extraction efficiency. <a href="javascript:void(0);">(64)</a> Thus, DCM and ACN were selected as the extractant and dispersant, respectively, for subsequent FrFD and BBD experiments.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_21_31418_31431_Figure_2_Effect_of_A_selection_of_extraction_solvent_B_selection_of_dispersive_solvent_5abd279b17.jpeg" alt="ACS Omega 2026, 11, 21, 31418–31431: Figure 2. Effect of (A) selection of extraction solvent; (B) selection of dispersive solvent." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_21_31418_31431_Figure_2_Effect_of_A_selection_of_extraction_solvent_B_selection_of_dispersive_solvent_5abd279b17.jpeg 135w," sizes="100vw" width="1000" height="1154"></p><h4><strong>4. Conclusion</strong></h4><p>An improved and environmentally friendly DLLME-GC-FID method was described for the quantitative analysis of PAHs in surface water. RSM was applied by first screening influential variables using a fractional factorial design, followed by the Box-Behnken design optimization of the DLLME parameters. In contrast to single-factor experimentation, the fitted model and 3D response surface plots showed factor interactions and their combined effects on extraction performance, facilitating near-optimal conditions to be identified with a limited number of experiments. Using the optimized conditions, low detection limits, good enrichment factors, acceptable reproducibility, and recoveries were achieved. The validated analytical features indicate that the proposed method is robust and cost-effective for the routine screening of PAHs in terrestrial water bodies.</p></div>

Experimental Design-Based Dispersive Liquid–Liquid Microextraction with GC-FID for Determination of Polycyclic Aromatic Hydrocarbons in Surface Water

<p><strong>This study compares a commercial ELISA assay with a validated UHPLC-MS/MS method for determining total ergot alkaloids in wheat and durum samples. In addition to method performance, the authors investigated cross-reactivity and matrix effects to explain differences between immunoassay and chromatographic results.</strong></p><p>While ELISA demonstrated good repeatability and is well suited for high-throughput screening, systematic biases were observed due to compound- and matrix-dependent cross-reactivity. The findings support ELISA as an effective screening tool, whereas UHPLC-MS/MS remains the preferred method for accurate quantification and regulatory confirmation of ergot alkaloids.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234"><strong>Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects</strong></a></h4><p>Chamali Kodikara*, Dainna Drul, Nandika Bandara, and Sheryl A. Tittlemier*</p><p>J. Agric. Food Chem. 2026, 74, 25, 20015–20027</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.jafc.6c05234">https://doi.org/10.1021/acs.jafc.6c05234</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Ergot alkaloids (EAs) are a structurally diverse group of indole-derived mycotoxins produced primarily by phytopathogenic fungi of the genus <i>Claviceps</i>, most notably <i>Claviceps purpurea</i>. These fungi infect the flowering heads of cereal crops, replacing the developing grain with hardened fungal structures (sclerotia) that contain ergot alkaloids. Cereals such as rye, wheat, barley, oats, and triticale are particularly susceptible, with infection severity strongly influenced by environmental conditions during flowering, including rainfall and humidity. <a href="javascript:void(0);">(1−3)</a> Although improvements in agronomic practices and grain cleaning have reduced the prevalence of visible ergot sclerotia, ergot alkaloids can persist in cereals and cereal-based foods even in the absence of detectable sclerotia. This may occur because sclerotia can fragment during harvesting, handling, cleaning, or milling, producing small particles that are not visually detected but may still contribute ergot alkaloids to grain or processed products, continuing to pose food and feed safety concerns. <a href="javascript:void(0);">(4)</a> <a href="javascript:void(0);">(5)</a> Ergot alkaloids share a common tetracyclic ergoline backbone and occur as structurally related compounds, including ergometrine, ergotamine, ergosine, ergocristine, ergocryptine, and ergocornine, together with their corresponding C-8 epimers. These epimers occur as <i>R-</i> and <i>S-</i>configurations, commonly referred to as -ine and -inine forms, respectively. Epimerization at the C-8 position can occur during fungal metabolism and during sample extraction, storage, and analysis, complicating accurate quantification. <a href="javascript:void(0);">(6,7)</a> Although S-epimers were historically considered biologically inactive, recent evidence indicates that they may contribute to overall exposure and toxicity, supporting their inclusion in analytical and regulatory frameworks. <a href="javascript:void(0);">(3)</a></p><p>Dietary exposure to elevated levels of ergot alkaloids has been associated with a range of adverse health effects, collectively referred to as ergotism, including vasoconstriction, ischemia, neurological disturbances, and hallucinations. <a href="javascript:void(0);">(3)</a> These effects arise primarily from interactions with adrenergic, serotonergic, and dopaminergic receptors. <a href="javascript:void(0);">(8−10)</a> In response, regulatory limits for ergot alkaloids in food have been introduced or revised in several jurisdictions. In the European Union, maximum levels have been established for the sum of 12 ergot alkaloids in cereal milling products under Regulation (EU) 2021/1399, which was subsequently consolidated under Regulation (EU) 2023/915. This sum includes ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, and ergocristine together with their corresponding -inine epimers, increasing the demand for reliable analytical methods to support routine monitoring and enforcement. <a href="javascript:void(0);">(1,11)</a></p><p>Liquid chromatography-tandem mass spectrometry (LC-MS/MS), particularly ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), is widely regarded as the reference technique for confirmatory determination of ergot alkaloids due to its sensitivity, selectivity, and ability to resolve epimeric forms. Recent methods routinely achieve low microgram-per-kilogram limits of quantification across a range of cereal matrices. <a href="javascript:void(0);">(12−17)</a> However, LC-MS/MS approaches are resource-intensive and typically confined to centralized laboratories, limiting their suitability for high-throughput screening or rapid decision-making in grain-handling and quality-control settings. Consequently, rapid screening methods, most notably enzyme-linked immunosorbent assays (ELISAs), are commonly employed as complementary tools to chromatographic analysis. <a href="javascript:void(0);">(18−21)</a> ELISAs offer reduced analysis time, simplified workflows, and lower per-sample costs, making them attractive for preliminary screening and sample triage. <a href="javascript:void(0);">(22−24)</a></p><p>In contrast to other regulated mycotoxins, however, the commercial availability of ELISAs for ergot alkaloids is limited. While multiple kits have been evaluated, performance has varied substantially across assays and matrices. <a href="javascript:void(0);">(1)</a> At present, the Randox Food Diagnostics Ergot Alkaloids ELISA is the only widely marketed microplate ELISA that quantifies the sum of 12 major ergot alkaloids, comprising ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, and ergocristine together with their corresponding -inine epimers, consistent with the analyte scope used for EU maximum levels for ergot alkaloids in specified cereal products. <a href="javascript:void(0);">(25)</a></p><p>In addition, cereal matrix effects may influence antibody binding and signal generation, potentially resulting in biased quantification relative to LC-MS/MS reference methods. These limitations are particularly relevant given the compositional variability of ergot alkaloids across cereal species, geographic regions, and growing conditions. <a href="javascript:void(0);">(12)</a> Recent reviews emphasize the need for systematic, matrix-specific evaluation of immunoassay performance before such methods can be confidently integrated into regulatory or industrial monitoring programs. <a href="javascript:void(0);">(1,6,11)</a> However, independent evaluations of commercially available ergot alkaloid ELISAs, particularly those benchmarked against validated UHPLC-MS/MS methods using naturally infested wheat samples, remain limited.</p><p>In this context, we hypothesized that measurements of total ergot alkaloids obtained using a commercially available ELISA are influenced by matrix effects and antibody cross-reactivity, resulting in systematic differences compared to UHPLC-MS/MS, which provides compound-specific quantification. To test this, the objective of the present study was to conduct a comprehensive performance evaluation of a commercially available ELISA for the detection of ergot alkaloids in wheat, using UHPLC-MS/MS as a reference method. Specific aims included assessment of repeatability and intermediate precision, extraction efficiency and extract stability, the influence of test portion mass, method accuracy relative to UHPLC-MS/MS, and characterization of antibody cross-reactivity toward individual ergot alkaloids in both solvent and wheat matrix. The results provide data-driven guidance on the appropriate use of ELISA-based screening within tiered analytical strategies for regulatory monitoring and food safety decision-making.</p><h4><strong>2. Materials and Methods</strong></h4><h5><strong>2.3. UHPLC-MS/MS Reference Method</strong></h5><p>UHPLC-MS/MS analysis of ergot alkaloids was performed using the validated Canadian Grain Commission (CGC) method described by Tittlemier et al. (2015). Briefly, ground grain (10 g) was extracted with 50 mL of acetonitrile/aqueous ammonium carbonate (84:16, v/v; 3.03 mM ammonium carbonate) to provide alkaline extraction conditions, then shaken for 30 min and centrifuged at 2450<i>g</i> for 10 min at room temperature. An aliquot of extract (464 μL) was combined with internal standard solution (dihydroergotamine; 20 μL of 4 ng/μL) and aqueous ammonium carbonate (1536 μL), vortex-mixed, and filtered through a 0.45 μm polytetrafluoroethylene syringe filter before injection into the UHPLC-MS/MS system. As in the validated reference method, dihydroergotamine was added after extraction to correct for postextraction analytical variability; extraction recovery was evaluated during method validation. Chromatographic separation was achieved using a reversed-phase <strong>BEH C18 column</strong> (2.1 × 100 mm, 1.7 μm; Waters, Milford, MA, USA) with the autosampler maintained at 15 °C and the column at 30 °C. Mobile phases consisted of (A) 3.03 mM aqueous ammonium carbonate and (B) acetonitrile. The gradient program was as follows: initial, 75% A/25% B; 1.00 min, 60% A/40% B; 5.00 min, 40% A/60% B; 8.00 min, 22% A/78% B; 10.50–11.00 min, 10% A/90% B; and 13.00–16.00 min, 75% A/25% B, with a total run time of 16 min. Detection was performed using positive electrospray ionization in multiple reaction monitoring mode on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554"><strong>Waters Xevo triple quadrupole mass spectrometer</strong></a> (Waters, Milford, MA, USA). Under the validated chromatographic conditions, dihydroergotamine did not coelute with ergotamine, ergotaminine, or the other target ergot alkaloids. Identification and quantification were based on retention-time criteria and compound-specific MRM transitions, thereby minimizing potential isotopic or coelution interference. Precautions to minimize epimerization, including controlled handling of standards and extracts and reduced light exposure, were followed as described in the reference method. UHPLC-MS/MS quantification was performed using analyte-specific, matrix-matched calibration curves prepared according to the validated CGC reference method, with calibration levels of 0.046, 0.2, 1, 2, 10, and 20 μg/kg. Dihydroergotamine was used as the internal standard, and concentrations were calculated from internal-standard-normalized analyte responses with method dilution factors applied. Total ergot alkaloid concentration was calculated as the arithmetic sum of all quantified ergot alkaloids and epimers included in the validated method. <a href="javascript:void(0);">(26)</a></p><h4><strong>3. Results and Discussion</strong></h4><h5><strong>3.4. Comparison of ELISA and UHPLC-MS/MS Results</strong></h5><p>For method comparison, UHPLC-MS/MS was used as the chemical reference method, providing compound-specific quantification of individual ergot alkaloids and their epimers. A total ergot alkaloid concentration was calculated as the arithmetic sum of all quantified alkaloids included in the method. This summed value represents a chemically defined total based on compound-specific quantification of each analyte, rather than an immunoreactivity-weighted response governed by antibody affinity. As such, the UHPLC-MS/MS total serves as a chemically defined comparator against which the immunoreactivity-weighted ELISA response can be interpreted. Agreement between the commercial ELISA and the validated UHPLC-MS/MS reference method was evaluated using wheat and durum wheat cargo samples (<i>n</i> = 102) collected over multiple crop years (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234#fig5">Figure 5</a>). Linear regression analysis demonstrated a positive association between ELISA and UHPLC-MS/MS results across the full concentration range, indicating that the ELISA was responsive to increasing ergot alkaloid levels. However, the regression slope deviated substantially from unity, with ELISA results systematically lower than UHPLC-MS/MS values, indicating an approximate 2-fold underestimation.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_5_Linear_regression_analysis_comparing_total_ergot_alkaloid_concentrations_determined_by_ELISA_and_UHPLC_MS_MS_5d7b5c5c61.jpeg" alt="J. Agric. Food Chem. 2026, 74, 25, 20015–20027: Figure 5. Linear regression analysis comparing total ergot alkaloid concentrations determined by ELISA and UHPLC-MS/MS for wheat and durum wheat cargo samples (n = 102). Each point represents the mean of duplicate measurements (extracted from the same test portion) ELISA determinations for an individual cargo sample, plotted against the corresponding UHPLC-MS/MS result. Statistical analysis was performed using linear regression." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_5_Linear_regression_analysis_comparing_total_ergot_alkaloid_concentrations_determined_by_ELISA_and_UHPLC_MS_MS_5d7b5c5c61.jpeg 197w," sizes="100vw" width="992" height="784"></p><p>Bland-Altman analysis confirmed this proportional bias, showing a consistent negative mean difference between ELISA and UHPLC-MS/MS results across the concentration range (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234#fig6">Figure 6</a>). Importantly, the magnitude of disagreement did not increase randomly with concentration; rather, it reflected a systematic offset, indicating that the discrepancy was not driven by analytical imprecision or outliers but by fundamental differences in method response characteristics. This pattern indicates method-level bias rather than random analytical variability, which may arise from combined workflow effects including extraction, matrix response, and immunochemical cross-reactivity. The magnitude of the ELISA-UHPLC-MS/MS bias was substantially greater than the intermediate precision observed for the ELISA quality-control material, supporting the interpretation that the disagreement reflects systematic differences in method response rather than insufficient ELISA repeatability. Such behavior is well documented when immunoassays are compared with chromatographic methods for complex mycotoxin mixtures, including ergot alkaloids and other structurally diverse mycotoxins in cereals and feed. <a href="javascript:void(0);">(28,30,33)</a> These studies consistently report matrix- and profile-dependent bias in ELISA relative to LC-MS/MS, arising from differential antibody cross-reactivity and the summed immunoreactivity response of the assay, because ELISA produces an immunoreactivity-weighted total that depends on antibody affinity toward individual alkaloids and their relative abundance in the sample, whereas UHPLC-MS/MS quantifies compound-specific concentrations of each alkaloid and its epimers using compound-specific transitions and response factors, and total ergot alkaloid concentration is calculated as the sum of these targeted analytes. In contrast, ELISA produces an immunoreactivity-weighted total, determined by antibody affinity toward individual alkaloids and their competitive binding behavior within the assay format. Consequently, agreement between ELISA and UHPLC-MS/MS depends not only on total concentration, but also on the relative distribution of individual alkaloids within each sample. Although differences in extraction solvent composition and pH may influence ergot alkaloid recovery, stability, and epimeric distribution, each method was applied according to its intended analytical workflow. The ELISA was performed using the manufacturer-recommended acidic methanol/water extraction, whereas UHPLC-MS/MS was performed using the validated acetonitrile/aqueous ammonium carbonate extraction procedure. Therefore, the comparison reflects the performance of the complete methods as used in practice, rather than an isolated comparison of extraction solvents. The sequential extraction experiment further showed that repeating the ELISA extraction under the same kit conditions did not substantially increase the ELISA-measured response, supporting the adequacy of the kit extraction within the ELISA workflow while recognizing that it does not directly compare acidic and ammonium carbonate-based extraction conditions. Previous ELISA-LC-MS/MS comparison studies for ergot alkaloids have reported both under- and overestimation depending on assay design and matrix, including differences in alkaloid profile, cereal type, and antibody cross-reactivity. Turner et al. observed substantial overestimation of ergot alkaloids by ELISA relative to HPLC in rye field samples, attributed to strong antibody cross-reactivity toward alkaloids prevalent in rye matrices. Similar profile-dependent bias has also been reported in interlaboratory and method-comparison studies, <a href="javascript:void(0);">(33)</a> demonstrating that this behavior is not unique to a single data set.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_6_Bland_Altman_plot_comparing_ELISA_and_UHPLC_MS_MS_measurements_of_total_ergot_alkaloids_1be40cce50.jpeg" alt="J. Agric. Food Chem. 2026, 74, 25, 20015–20027: Figure 6. Bland-Altman plot comparing ELISA and UHPLC-MS/MS measurements of total ergot alkaloids for wheat and durum wheat cargo samples (n = 102)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_6_Bland_Altman_plot_comparing_ELISA_and_UHPLC_MS_MS_measurements_of_total_ergot_alkaloids_1be40cce50.jpeg 230w," sizes="100vw" width="1437" height="977"></p><p>This study provides a comprehensive evaluation of a commercially available ELISA for total ergot alkaloids, using wheat samples as the primary application matrix, and integrates performance metrics with mechanistic insights into method behavior. While the assay demonstrated strong repeatability, calibration stability, and robustness to procedural factors such as test portion mass and extraction conditions, systematic differences relative to UHPLC-MS/MS were consistently observed. By linking these differences to compound-specific antibody cross-reactivity and matrix-dependent signal modulation, this work clarifies that ELISA-derived results reflect an immunochemically weighted response rather than a stoichiometric total. This distinction is critical for the appropriate interpretation of ELISA data and supports its use within tiered analytical strategies as a rapid screening tool, complemented by UHPLC-MS/MS for confirmatory quantification and regulatory decision-making.</p></div>

Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects

<p><strong>This study investigates the antioxidant and anti-inflammatory effects of (−)-epicatechin in an in vitro model of metabolic dysfunction-associated steatotic liver disease (MASLD). Lipid peroxidation, inflammatory, and profibrotic markers were assessed alongside ATR-FTIR spectroscopy to evaluate whether spectral changes reflect disease progression and treatment response.</strong></p><p>Epicatechin reduced lipid peroxidation products, TNF-α, and TGF-β1 in a concentration-dependent manner, with stronger protective effects observed during pretreatment. ATR-FTIR spectral changes closely correlated with biochemical markers, demonstrating its potential as a rapid, non-destructive tool for monitoring oxidative stress, inflammation, and fibrosis in MASLD research.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c09978"><strong>ATR-FTIR Assessment of the Antioxidant and Anti-Inflammatory Effects of (−)-Epicatechin in MASLD</strong></a></h4><p>Marija Hefer, Nikolina Filipović, Stjepan Šarić, Nela Malatesti, Ana Petrović, Elvira Kovač-Andrić*, and Martina Smolić*</p><p>ACS Omega 2026, 11, 23, 33333–33344</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c09978">https://doi.org/10.1021/acsomega.5c09978</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Metabolic dysfunction-associated steatotic liver disease (MASLD) represents one of the most prevalent chronic liver disorders. Due to its predisposition to progress toward metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and even hepatocellular carcinoma (HCC), MASLD has become a significant global health burden and a major challenge for healthcare systems. <a href="javascript:void(0);">(1−4)</a></p><p>The majority of patients with MASLD or MASH are obese and frequently present with additional metabolic comorbidities, most commonly insulin resistance, type 2 diabetes mellitus, and dyslipidemia. <a href="javascript:void(0);">(5−7)</a> Furthermore, most conditions associated with MASLD and MASH are characterized by lipid metabolism impairment, with elevated levels of oxidative stress. Impaired lipid metabolism, together with prolonged oxidative stress, promotes hepatocellular lipotoxicity and mitochondrial dysfunction. These alterations affect the antioxidant defense system and increase reactive oxygen species (ROS) generation, thereby contributing to the onset of MASLD and its progression to MASH, along with more advanced liver diseases. <a href="javascript:void(0);">(8,9)</a></p><p>One of the main results of oxidative stress is lipid peroxidation, in which ROS attack (poly)unsaturated fatty acids within membrane lipids. This initiates a series of structural and functional alterations, where the formation of conjugated dienes (CDs) reflects early double-bond rearrangements in fatty acyl chains, while lipid hydroperoxides (LOOHs) represent key propagation-phase products that destabilize cell membranes and increase oxidative injury. <a href="javascript:void(0);">(10,11)</a> Therefore, determining LOOH and CD levels, along with their overall LOOH/CD ratio, might be useful for determining the lipid peroxidation dynamics and the progression of MASLD.</p><p>Along with oxidative damage to the cell structures, inflammation is also a key regulator of MASLD progression. In this context, tumor necrosis factor-α (TNF-α) is suspected to play a central role as its levels are found to increase alongside MASLD to MASH progression. <a href="javascript:void(0);">(12−14)</a> It has also been found that ROS and TNF-α are closely interconnected, where elevated TNF-α levels could serve as an indicator of oxidative cellular damage and enhanced lipid peroxidation. <a href="javascript:void(0);">(15−17)</a> Often, one of the results of MASLD progression is the development of liver fibrosis, which is usually mediated by transforming growth factor beta 1 (TGF-β<sub>1</sub>) as its levels are frequently elevated in MASH and contribute to the worsening of hepatic steatosis. <a href="javascript:void(0);">(18)</a> <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c09978#fig1">Figure 1</a> summarizes the pathways associated with MASLD to MASH progression, with emphasis on lipid peroxidation (CDs, LOOHs) and inflammatory/fibrogenic signaling (TNF-α, TGF-β<sub>1</sub>).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_23_33333_33344_Figure_1_Schematic_representation_of_lipid_peroxidation_and_its_role_in_MASLD_progression_e6a8e05d3e.jpeg" alt="ACS Omega 2026, 11, 23, 33333–33344: Figure 1. Schematic representation of lipid peroxidation and its role in MASLD progression. Lipid accumulation in MASLD leads to the release of free radicals and ROS, which attack (poly)unsaturated fatty acids within membrane lipids, leading to lipid peroxidation, inflammation (via TNF-α), and fibrotic changes (via TGF-β1), thereby contributing to the transition from MASLD to MASH and further progression to cirrhosis and HCC. In lipid peroxidation, reactive radicals (R·) subtract the hydrogen from the (poly)unsaturated lipid, thereby resulting in the formation of a lipid radical, which undergoes rearrangements to form a CD. The lipid radical then reacts with molecular oxygen to form an unstable lipid peroxyl radical, which further subtracts a hydrogen from another (poly)unsaturated lipid, thereby resulting in the formation of a LOOH. The subtraction of hydrogen from the (poly)unsaturated lipid also results in the formation of a lipid radical, thereby perpetuating the chain reaction. The figure was created with Servier Medical Art (https://smart.servier.com/) and MarvinSketch (ChemAxon, https://chemaxon.com/marvin)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_23_33333_33344_Figure_1_Schematic_representation_of_lipid_peroxidation_and_its_role_in_MASLD_progression_e6a8e05d3e.jpeg 216w," sizes="100vw" width="1834" height="1327"></p><p>However, the exact role of different lipid peroxidation indicators and their contribution to MASLD progression toward MASH have not yet been fully elucidated, with the number of studies addressing this issue remaining limited. Given these limitations in research, attention has increasingly turned toward dietary antioxidants, particularly polyphenols or mixtures of polyphenol-rich plant extracts, as potential modulators of oxidative stress and lipid peroxidation in hepatic steatosis. <a href="javascript:void(0);">(19−23)</a></p><p>Among available polyphenols, we selected (−)-epicatechin (EC) because of its strong antioxidant and radical scavenging capacity, with its documented effects on inflammatory signaling. <a href="javascript:void(0);">(24−26)</a> One study even found that the antifibrotic properties of EC were comparable to those of silymarin, with EC showing even stronger reducing effects on malondialdehyde (MDA) formation in vivo. <a href="javascript:void(0);">(27)</a> Since MDA is a secondary product of LOOH breakdown, <a href="javascript:void(0);">(28)</a> these results could link EC’s potential antifibrotic properties to its ability to attenuate lipid peroxidation, thereby potentially mitigating the progression of MASLD to MASH. Unlike more extensively studied compounds such as epigallocatechin gallate, <a href="javascript:void(0);">(29,30)</a> EC has been less investigated in the context of MASLD, providing an opportunity to explore a novel candidate. At the same time, the growing use of advanced spectroscopic techniques offers new opportunities to monitor biochemical alterations in cells and tissues.</p><p>Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy recently emerged as a promising tool for monitoring such changes. The application of ATR-FTIR spectroscopy and similar techniques for steatosis and lipid quantification, along with determining the lipid peroxidation extent, has been introduced, especially in the context of hepatic steatosis. Determining the intensity of C═O vibrational stretching at ∼1740 cm<sup>–1</sup> (triacylglycerols, cholesteryl esters, lipid oxides), as this type of bond usually occurs in lipid peroxidation, could also be valuable for determining the overall extent of steatosis. <a href="javascript:void(0);">(31−33)</a> Along with lipid peroxidation extent, determining the degree of unsaturation in MASLD models is crucial for understanding the changes in cellular components as the degree of unsaturation is often found to decrease due to steatotic changes in cells and tissues. (Poly)unsaturated fatty acids contribute to membrane fluidity and are essential for maintaining membrane integrity and signaling, while their depletion leads to increased membrane rigidity and impaired cellular function. <a href="javascript:void(0);">(34,35)</a> Given their high susceptibility to peroxidation, a reduction in their levels could indicate either an adaptive response to oxidative stress or a disruption of lipid homeostasis. Therefore, correlating the degree of unsaturation (∼3010 cm<sup>–1</sup> for ═C–H) and the intensity of carbonyl stretching (∼1740 cm<sup>–1</sup> for C═O) with the LOOH/CD ratio and cytokines, TNF-α and TGF-β<sub>1</sub>, could be valuable for the noninvasive monitoring of disease progression.</p><h4><strong>Methods</strong></h4><h5><strong>Experimental Design</strong></h5><p>Two experimental models were introduced for the experiments: EC pretreatment and EC Posttreatment models. In both models, the untreated cells (UT) group was used as a negative (vehicle) control group, while the sodium oleate-treated group (OA) was used as a positive control group, with EC (control) being the highest concentration of EC used as a control for the tested compound. In the Pretreatment model, the cells were pretreated with 10, 30, and 50 μM EC for 4 h, followed by a 24 h posttreatment with 1.5 mM sodium oleate. In the Posttreatment model, the cells were treated with 1.5 mM sodium oleate for 12 h, followed by the addition of the same concentrations of EC in the presence of 0.75 mM sodium oleate. All of the experimental groups were labeled as EC50+OA, EC30+OA, and EC10+OA, according to the concentration used in the experiments. EC concentrations of 10, 30, and 50 μM were chosen based on our previous MTS assay and Oil Red O staining results, where we tested 10–100 μM EC to evaluate its effect on MASLD in the Pretreatment model. <a href="javascript:void(0);">(42)</a> As it was proven effective in the Pretreatment model, the Posttreatment model was added to evaluate whether EC could also mitigate oxidative and inflammatory/fibrotic changes once steatosis was already established. Another important consideration was to assess the potential cytotoxicity of the concentrations used, as EC and other polyphenols are often consumed as dietary supplements with poorly regulated dosages. As these cytotoxic effects are often subtle and overlooked in conventional biochemical assays, combining FTIR spectral analysis with complementary assays could provide a more comprehensive assessment of potential cytotoxicity.</p><h5><strong>ATR-FTIR Assessment of Lipid Peroxidation</strong></h5><p>ATR-FTIR spectroscopy was used to determine the extent of lipid peroxidation and steatosis. The lipid samples were dissolved in chloroform and normalized to a lipid concentration of 20 mg/mL. After the evaporation of the solvent, the ATR-FTIR spectra were recorded using an <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+630"><strong>Agilent Cary 630 FTIR spectrophotometer</strong></a> (Agilent Technologies, Santa Clara, CA, USA), at the Faculty of Biotechnology and Drug Development at the University of Rijeka. All ATR-FTIR spectra were processed using the automatic least-squares baseline correction algorithm implemented in <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=MicroLab+Expert"><strong>Agilent MicroLab Expert v.10.5 software</strong></a> (4000–650 cm<sup>–1</sup>; clean scans: 4; threshold: 0.002; background scans: 2; sample scans: 100; resolution: 16 cm<sup>–1</sup>; apodization: HappGenzel; phase correct: Mertz; method gain: 221). Spectra of pure chloroform were recorded under identical conditions and subtracted from sample spectra to remove any residual solvent contributions. Chloroform was recorded to be excluded in the background, and the data were collected in the spectral range 3200–1600 cm<sup>–1</sup> on an ATR device. To ensure comparability between samples, the spectra were normalized against the asymmetric CH<sub>2</sub> stretching vibration of lipid acyl chains (2925–2922 cm<sup>–1</sup>), which was used as an internal reference band due to its relative stability across treatments and minimal alteration during lipid peroxidation. Baseline correction was applied prior to normalization to minimize background variability. Relative intensities of lipid peroxidation-associated bands (C═O stretching at 1744–1735 cm<sup>–1</sup> and ═C–H stretching at 3010 cm<sup>–1</sup>) were then expressed as a ratio to the CH<sub>2</sub> reference peak, allowing quantitative comparison of the lipid peroxidation extent between experimental groups. The data were presented as percent relative intensities (%<i>I</i><sub>rel</sub>).</p><h4><strong>Results and Discussion</strong></h4><h5><strong>ATR-FTIR Spectroscopy for the Assessment of Lipid Peroxidation and Steatosis Extent</strong></h5><p>To evaluate the overall steatosis and lipid peroxidation extent in HepG2 cells, ATR-FTIR spectroscopy was used. <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c09978#fig5">Figure 5</a> shows the 3200–1600 cm<sup>–1</sup> spectral region, including the key C═O (1744–1735 cm<sup>–1</sup>) and ═C–H (3010 cm<sup>–1</sup>) stretching bands, which correlated with the biochemical parameters measured in this study. The increased intensity of the C═O band in sodium oleate-treated groups corresponds to the accumulation of oxidized lipid species derived from peroxidation of (poly)unsaturated fatty acids. On the other hand, a decrease in the ═C–H stretching band near 3010 cm<sup>–1</sup> indicates a progressive depletion of double bonds which undergo rearrangement to form CDs or further transformations associated with lipid peroxidation.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_23_33333_33344_Figure_5_ATR_FTIR_spectra_of_control_groups_aabfabbdc1.jpeg" alt="ACS Omega 2026, 11, 23, 33333–33344: Figure 5. ATR-FTIR spectra of control groups: UT (blue) and EC (control) (purple); along with experimental groups: OA (yellow), EC50+OA (red), EC30+OA (orange), and EC10+OA (brown) in the wavenumber range 3200–1600 cm–1 for the (a) EC Pretreatment Model and (b) EC Posttreatment Model." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_23_33333_33344_Figure_5_ATR_FTIR_spectra_of_control_groups_aabfabbdc1.jpeg 193w," sizes="100vw" width="1572" height="1272"></p><p>All experimental groups show similar FTIR profiles in the lipid regions; however, to determine the overall extent of lipid peroxidation and steatosis, the relative intensities of ═C–H stretching of unsaturated lipids (3010 cm<sup>–1</sup>) and C═O stretching of esters (1744–1735 cm<sup>–1</sup>) were measured according to the baseline and normalized according to asymmetric CH<sub>2</sub> stretching of lipid chains (2925–2922 cm<sup>–1</sup>) (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c09978#fig6">Figure 6</a>). This approach was chosen as the greatest changes were noticed among the given intensities of the peaks in all groups.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_23_33333_33344_Figure_6_Percent_relative_intensities_e921d53b57.jpeg" alt="ACS Omega 2026, 11, 23, 33333–33344: Figure 6. Percent relative intensities (%Irel) of ═C–H stretching (unsaturated lipids) and C═O stretching of esters for the (a) EC Pretreatment Model and (b) EC Posttreatment Model. The results are presented as mean values of %Irel ± SD." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_23_33333_33344_Figure_6_Percent_relative_intensities_e921d53b57.jpeg 149w," sizes="100vw" width="1000" height="1044"></p><p>Also, as indicated in the literature, the increase in intensities of C═O stretching and a decrease in intensities of ═C–H stretching are mostly associated with an increase in the lipid peroxidation extent. <a href="javascript:void(0);">(33,50)</a> Furthermore, a decrease in ═C–H stretching corresponds to a decrease in the (poly)unsaturated fatty acid content, which is often noted in MASLD/MASH models. <a href="javascript:void(0);">(51,52)</a></p><h4><strong>Conclusion</strong></h4><p>In a sodium oleate-induced hepatic steatosis model, EC showed a concentration-dependent effect on the overall radical scavenging ability of HepG2 cells. However, when EC was given as a posttreatment, these results were not achievable. EC also reduced propagation-phase lipid peroxidation by reducing relative LOOH levels in both models, lowering the LOOH/CD ratio (except for the EC50+OA pretreatment group), and effectively decreasing sodium oleate-induced increases in TNF-α and TGF-β<sub>1</sub> concentrations. ATR-FTIR results were consistent with changes in lipid (per)oxidation and reflected the overall antioxidant and anti-inflammatory effects of EC observed through biochemical assays. Compared with biochemical assays, ATR-FTIR spectroscopy has several advantages, including rapid and nondestructive analysis that requires minimal sample preparation. Considering that it can simultaneously capture multiple molecular changes, this represents a reliable approach for accurate and complementary insights into lipid peroxidation and redox alterations in MASLD. However, it is important to correlate ATR-FTIR spectral changes with biochemical assays to further strengthen its interpretation.</p></div>

ATR-FTIR Assessment of the Antioxidant and Anti-Inflammatory Effects of (−)-Epicatechin in MASLD

<p><strong>In the week of July 6, 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><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Agilent Technologies: Boost Environmental GC/MS Uptime, Productivity and Data Quality</strong></h5><ul><li>We, 8.7.2026 08:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6323">Registration</a></li></ul><p>Maximize your laboratory productivity. Learn how advanced GC/MS column technology improves system uptime, data quality, and trace-level target analysis.</p><h5><strong>2. Wiley: From liquids to solids: expand what your UV-Vis-NIR Spectrometer can do</strong></h5><ul><li>We, 8.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6367">Registration</a></li></ul><p>Discover how the Agilent Cary UV-Vis-NIR spectrometer, together with Specac accessories, enables reliable analysis of liquids, powders, films, pellets, and highly scattering solid samples.</p>

Webinars LabRulezGCMS Week 28/2026

<p><strong>In the week of July 6, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Waters Corporation: Characterizing Next-Generation Antibody Therapeutics: LC Strategies for Multispecifics, ADCs &amp; AOCs</strong></h5><ul><li>Tu, 7.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6317">Registration</a></li></ul><p>In this webinar, we share a pragmatic characterization roadmap using LC-based methods across intact, subunit, and peptide-mapping workflows.</p><h5><strong>2. Separation Science: Advances in Antibiotic Extraction from Water: An Automated SPE Approach</strong></h5><ul><li>We, 8.7.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6319">Registration</a></li></ul><p>Streamline water analysis workflows and gain practical insights for modern environmental monitoring.</p><h5><strong>3. SCIEX: Analysis of per- and polyfluoroalkyl substances (PFAS) in food substances using LC-MS/MS solutions</strong></h5><ul><li>We, 8.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6322">Registration</a></li></ul><p>Master PFAS analysis in food safety. Learn how SCIEX LC-MS/MS solutions and QTRAP workflows overcome analytical challenges to ensure accurate and compliant result confirmation.</p><h5><strong>4. Wiley: From liquids to solids: expand what your UV-Vis-NIR Spectrometer can do</strong></h5><ul><li>We, 8.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6367">Registration</a></li></ul><p>Discover how the Agilent Cary UV-Vis-NIR spectrometer, together with Specac accessories, enables reliable analysis of liquids, powders, films, pellets, and highly scattering solid samples.</p><h5><strong>5. Thermo Fisher Scientific: Advanced tools to maximize your sample throughput with Chromeleon Software and Vanquish UHPLC</strong></h5><ul><li>Th, 9.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6326">Registration</a></li></ul><p>Learn how Chromeleon software and the Vanquish Duo UHPLC system streamline sample analysis, automate routine workflows, increase throughput, and reduce errors through practical demonstrations.</p><h5><strong>6. Bruker: 4D-Metabolomics™ in Action: Real-World Strategies for Deep Discovery and Confident Annotation</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6328">Registration</a></li></ul><p>Explore how next-generation mass spectrometry technologies, ion mobility, and computational tools are helping researchers move from complex datasets to confident insight.</p><h5><strong>7. Waters Corporation: Cracking the Code on Nitrogen Methods</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6327">Registration</a></li></ul><p>Learn the fundamentals of nitrogen analysis for wastewater testing. Explore analytical methods, QA/QC, sample handling, compliance reporting, and troubleshooting for accurate environmental monitoring.</p><h5><strong>8. SelectScience: Next-generation metabolomics: From annotation to discovery at scale</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6281">Registration</a></li></ul><p>Explore how next-generation mass spectrometry, ion mobility, and advanced computational tools accelerate confident small-molecule annotation and discovery in metabolomics.</p><h5><strong>9. SCIEX: LC-MS/HRMS Approaches for Monitoring Organic Micropollutants in Wastewater and Environmental Systems</strong></h5><ul><li>Fr, 10.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6370">Registration</a></li></ul><p>Discover how advanced LC-MS/HRMS workflows enable trace-level detection of organic micropollutants, suspect and non-target screening, and environmental monitoring of wastewater systems.</p>

Webinars LabRulezLCMS Week 28/2026

<p><strong>In the week from July 6, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Thermo Fisher Scientific: Lunch and Learn Tips and Tricks Series: Trace Elemental Analysis (ICP-OES &amp; ICP-MS)</strong></h5><ul><li>Tu, 7.7.2026 12:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5977">Registration</a></li></ul><p>Learn practical tips to optimize ICP-OES and ICP-MS performance, improve data quality, streamline troubleshooting and maintenance, and enhance sample preparation for more efficient elemental analysis.</p><h5><strong>2. SelectScience: Expanding the 4D-STEM Toolbox for Advanced Materials Characterization</strong></h5><ul><li>Tu, 7.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6318">Registration</a></li></ul><p>Explore how Timepix4 detector technology advances 4D-STEM workflows, enabling high-resolution imaging, data-driven acquisition, and new opportunities in electron microscopy.</p><h5><strong>3. Anton Paar: Microwave Digestion: The Foundation of Accurate Trace Metal Analysis</strong></h5><ul><li>We, 8.7.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6321">Registration</a></li></ul><p>Build robust workflows for trace metal analysis. Learn how microwave digestion ensures fast, contamination-free, and complete sample preparation across complex food matrices.</p><h5><strong>4. Wiley: From liquids to solids: expand what your UV-Vis-NIR Spectrometer can do</strong></h5><ul><li>We, 8.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6367">Registration</a></li></ul><p>Discover how the Agilent Cary UV-Vis-NIR spectrometer, together with Specac accessories, enables reliable analysis of liquids, powders, films, pellets, and highly scattering solid samples.</p><h5><strong>5. SelectScience: The next generation ICP-MS designed to wow trace element analysts</strong></h5><ul><li>We, 8.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6320">Registration</a></li></ul><p>Upgrade your trace-element analysis. Discover how the new Agilent 9500 ICP-MS eliminates interferences and simplifies method development for complex matrices.</p><h5><strong>6. LECO: Dry Matter and Ash Determination in Wastewater and Sewage Sludge</strong></h5><ul><li>Th, 9.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6324">Registration</a></li></ul><p>Optimize wastewater analysis. Learn how automated thermogravimetric analysis (TGA) replaces manual drying and ashing steps to determine dry matter and ash in sewage sludge.</p><h5><strong>7. Waters Corporation: Cracking the Code on Nitrogen Methods</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6327">Registration</a></li></ul><p>Learn the fundamentals of nitrogen analysis for wastewater testing. Explore analytical methods, QA/QC, sample handling, compliance reporting, and troubleshooting for accurate environmental monitoring.</p><h5><strong>8. Agilent Technologies: ICP Expert 7.8: Booming ICP-OES Software Innovation</strong></h5><ul><li>Th, 9.7.2026 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6368">Registration</a></li></ul><p>Discover what's new in ICP Expert™ 7.8 and how the latest software innovations can improve data quality, simplify routine operation, and increase day-to-day laboratory efficiency.</p>

Webinars LabRulezICPMS Week 28/2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 6th July 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you brochure by <strong>Agilent Technologies, </strong>presentation by <strong>MDCW / University of Washington </strong>and posters by <strong>Shimadzu / ASMS</strong> and <strong>Thermo Fisher Scientific</strong> <strong>/ ASMS!</strong></p><h3><strong>1. Agilent Technologies: Operational efficiency for your GC and GC/MS labs with the Agilent 8860B gas chromatography system</strong></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/br_8860b_gc_5994_9206en_agilent_7b7b766cd2.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The brochure presents the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8860B"><strong>Agilent 8860B GC system</strong></a> as a routine GC and GC/MS platform focused on operational efficiency, reliable performance, intelligent diagnostics, and sustainability. It is positioned as a next-generation GC workhorse for laboratories that need consistent, high-quality data while increasing throughput and reducing downtime. Key performance features include dual sample injection capabilities, improved repeatability for retention time and peak area, electronic pneumatics control, retention time locking for method transfer, and a built-in oven light to simplify maintenance and column installation.</p><p>A major theme is <strong>instrument intelligence</strong> through the Agilent GC Assist interface. The system provides browser-based access to instrument status, methods, sequences, logs, diagnostics, maintenance information, and help resources. Built-in tools such as early maintenance feedback, system health reporting, automated and user-initiated diagnostics, peak evaluation, and self-guided troubleshooting are designed to help laboratories detect issues early, maintain uptime, and reduce the need for expert-level intervention during routine operation.</p><p>The brochure also emphasizes <strong>sustainability and resource management</strong>. The 8860B GC includes gas and power usage reporting, method-based monitoring, alerts for abnormal gas use, and tools for detecting possible leaks or restrictions. Agilent highlights helium conservation options, including a helium conservation module that can reduce helium consumption by switching to an alternative gas during idle periods, as well as support for hydrogen and nitrogen carrier gases with built-in hydrogen safety features. These functions are presented as ways to reduce operating costs, conserve resources, and protect workflows from helium supply disruptions.</p><p>Finally, the brochure describes the broader <strong>Agilent GC ecosystem</strong> around the 8860B. The system supports multiple inlets, detectors, autosamplers, headspace sampling, single quadrupole GC/MS compatibility, OpenLab CDS, DA Express, MassHunter software, Agilent consumables, columns, and CrossLab services. Together, these elements are presented as a complete workflow for routine laboratories that need flexibility, compliance support, service coverage, method consulting, training, and long-term value from their GC investment.</p><h3><strong>2. MDCW / University of Washington: Implementing Tile-Based Fisher Ratio Analysis of GC×GC-TOFMS Data to Obtain a Master Peak Table of All Detected Analyte Compounds in Many Petroleum-Based Samples</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_9_Halvorsen_136808e314.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The presentation describes the development of a chemometric workflow for advanced fuel sample analysis using GC×GC-TOFMS data. The work was carried out by the University of Washington in collaboration with Chevron Technical Center, with the goal of improving the characterization of complex petroleum-based samples. Moving from conventional GC to comprehensive two-dimensional GC increased peak capacity and chromatographic resolution, but also created the need for more advanced methods to generate reliable peak tables across many chemically diverse fuel samples.</p><p>The key method presented is a tile-based Fisher Ratio approach implemented through <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/348"><strong>ChromaTOF Tile</strong></a><strong>.</strong> This method identifies analytes that show statistically significant concentration differences between sample classes. Instead of relying only on peak detection or manual alignment, the workflow uses chromatographic “tiles” to reduce the impact of retention-time shifting and to capture both major and trace-level components. The study included multiple fuel classes, including hydrobate, reformate, naphtha, FCC gasoline, and blanks.</p><p>Because Fisher Ratio values alone do not directly indicate whether a compound is truly detectable, the authors added a blank-based p-testing strategy. Three blank chromatograms were used to estimate background signal distributions for each tile, and confidence intervals were then applied to determine whether each detected hit was present in individual sample classes. This produced a master peak table covering 719 hits across nine fuel sample classes. The results showed good reproducibility, with only 6.3% of classifications being heterogeneous across replicates.</p><p>Overall, the presentation concludes that the tile-based workflow can generate comprehensive and reproducible peak tables with reduced user intervention, while preserving the ability to recover trace analytes in complex petroleum samples. The approach should be broadly applicable to other complex sample types and could also be adapted using chemometric metrics other than Fisher Ratio, depending on the experimental design and analytical goals.</p><h3><strong>3. Shimadzu / ASMS: Is Your Next Sip Safe? A Simple, Rapid Method for Measuring volatile PFAS in Juices.</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_143_Is_Your_Next_Sip_Safe_A_Simple_Rapid_Method_for_Measuring_volatile_PFAS_in_Juices_a6ed9414c0.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) pollution is a growing global concern due to links with adverse health effects, many of which remain poorly understood. 1 Accurate detection and quantification are therefore essential. While PFAS analysis has traditionally focused on water, attention is rapidly expanding to food and beverages, where testing remains limited despite high stakes and increasing regulations. 2 A recent PFAS lawsuit against a juice manufacturer underscored the heightened public scrutiny of PFAS in juices, placing food safety and brand reputation at risk. 3 This study presents a Headspace Solid-Phase Microextraction– Triple Quadrupole Gas Chromatography/Mass Spectrometry (HS-SPME GC/MS/MS) method for PFAS quantitation in juices. GC/MS enables analysis of volatile PFAS unsuitable for LC/MS, while HS-SPME offers rapid analysis with minimal sample preparation in complex matrices.</p><h4><strong>Methods</strong></h4><p>A volatile PFAS analysis method was developed on a <strong>Shimadzu </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-TQ8040+NX"><strong>GCMS-TQ8040 NX</strong></a> with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=AOC-6000+Plus"><strong>AOC-6000 Plus multifunctional autosampler</strong></a> equipped with a solid phase microextraction (SPME) module (Figure 1).</p><h4><strong>Results&nbsp;</strong></h4><p>The system was deemed free of contaminants and inferences. None of the target PFAS in the method blank were found in quantifiable concentration. In the study, the calibration curve for each target included at least seven calibrators. Calibration curve results showed a good linear fit for all compounds with coefficient of determination (R2 ) ≥ 0.993. The linear range and R2 of each PFAS target are shown in Table 3.</p><h4><strong>Conclusion</strong></h4><p>Overall, these results demonstrate the robustness and reliability of the method for PFAS analysis in two carton apple juices (Brands X and Y), one plastic bottled apple juice (Brand X), and a berry blend carton juice (Brand X). Given the diversity of matrices evaluated, the method may also be suitable for other beverages, including sports drinks and vitamin-enhanced waters</p><h3><strong>4. Thermo Fisher Scientific / ASMS: Enhanced sensitivity for the quantitative analysis of pesticides using a GC Orbitrap MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004706_lsms_pesticides_exploris_gc_efs_po004706_asms2026_na_en_5f51b18742.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Detection of pesticide residues in fruits and vegetables is essential for food safety, but it can be challenging in complex, highly pigmented matrices due to interferences. Orbitrap technology provides high resolution and mass accuracy, enabling confident identification of coeluting and isobaric compounds while reducing false results. Furthermore, the FS-HRAM acquisition enables simultaneous quantitation and screening within a single analysis with the capability of retrospective data analysis, allowing laboratories to reprocess datasets for additional or emerging compounds without re-injecting samples. The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2419"><strong>Orbitrap Exploris GC S mass spectrometer</strong></a><strong> </strong>features the Thermo Scientific NeverVent Advanced Electron Ionization Source (NVAEI) which offers an improved design providing enhanced sensitivity and robustness, allowing for increased instrument uptime and maximized sample throughput for rapid return on investment (ROI).</p><h4><strong>Materials and methods</strong></h4><h5><strong>Data analysis&nbsp;</strong></h5><p>Data was acquired, processed and reported using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/76"><strong>Thermo Scientific Chromeleon Chromatography Data System (CDS) software</strong></a>, which provides integrated instrument control, automated workflows, and an intuitive interface for data analysis, customizable reporting, and compliant data management in accordance with FDA 21 CFR Part 11 and European Commission (EU) Annex 11. Its advanced reprocessing capability streamlines sequence setup, data review, and reporting offering the possibility to easily flag and check compliance with the current regulations.</p><p>Results Compliant analyte identification The use of HRAM-GCMS reduces the matrix interferences ensuring a confident and selective identification of analytes (Figure 1). All target compounds satisfied the SANTE criteria at the default MRL of 10 µg/kg and more than 90% were confirmed at concentrations of 1 µg/kg following the SANTE/11312/2021v2026 guidance criteria of:&nbsp;</p><ul><li>two ions were detected for each pesticide with mass accuracy ≤ 5 ppm with precursor and product ions in the extracted ion chromatograms fully overlapped,&nbsp;</li><li>due to the added value of accurate mass measurement, matching ion ratios is not necessary, however, an ion ratio (IR) deviation within ± 30% (relative) of the average of calibration standards from the same sequence was considered to provide additional support for identification</li><li>retention times (RT) within a tolerance of ± 0.1 minutes</li></ul><p>Sensitivity performance (IDL) and analytical linearity Instrument sensitivity was evaluated using calculated IDLs derived from replicate injections of low-level, matrix-matched standards. The Orbitrap Exploris GC S demonstrated detection limits at levels at or below 0.5 µg/kg for most of the investigated pesticides (Figure 2). Linear dynamic range was evaluated using matrix-matched calibration curves ranging 0.5–200 µg/kg, with each calibration level injected in triplicate. All target analytes demonstrated excellent linearity, with coefficients of determination (R²) &gt; 0.993, response factor (%RSD) values below 20% across the calibration range, and ion ratios (IRs) within ±30% of the average calibration standard values. System suitability for quantitative analysis was confirmed by calculated concentrations within ±20% of expected values and recoveries ranging from 96% to 104%. An example of calibration curve for Aldrin is shown in Figure 3.</p><h4><strong>Conclusions&nbsp;</strong></h4><p>The results obtained in these experiments demonstrate that the Orbitrap Exploris GC S mass spectrometer equipped with NeverVent AEI ion source represents a reliable tool for analysis of pesticides in complex matrices.&nbsp;</p><ul><li>The Orbitrap Exploris GC S offers a simple approach for the multiresidue analysis of pesticides allowing for full-scan acquisition combined with high mass resolving power&nbsp;</li><li>The NeverVent AEI ion source is designed for ultra-trace concentration detection, making it ideal for challenging applications ensuring detection limits at levels at or below 0.5 µg/kg for most of the investigated pesticides&nbsp;</li><li>Confident identification of compounds can be easily achieved through i). high spectral quality, ii). high spectral fidelity, ensuring consistent spectrum independently from concentration, and iii). consistent mass accuracy irrespectively of analyte concentration and time&nbsp;</li><li>System suitability for quantitative analysis was demonstrated with R2 &gt;0.993, RF %RSD across the entire calibration curve &lt; 20, and IRs within ± 30% of the average of calibration standards, calculated amounts within 20% the expected values, and percentage recovery (%) ranging from 96 to 104.</li></ul></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 28, 2026

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Everything from the world of analytical chemistry in one place. We connect people in solving their problems. At Labrulez you will find all the necessary information easily, quickly and clearly. Stop searching and start finding.

News from LabRulezGCMS Library - Week 28, 2026

Webinars LabRulezICPMS Week 28/2026

Webinars LabRulezLCMS Week 28/2026

Webinars LabRulezGCMS Week 28/2026

ATR-FTIR Assessment of the Antioxidant and Anti-Inflammatory Effects of (−)-Epicatechin in MASLD

Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects

Experimental Design-Based Dispersive Liquid–Liquid Microextraction with GC-FID for Determination of Polycyclic Aromatic Hydrocarbons in Surface Water

News from LabRulezICPMS Library - Week 27, 2026

News from LabRulezLCMS Library - Week 27, 2026

News from LabRulezGCMS Library - Week 27, 2026

Upcoming events

SCIEX at SOFT/TIAFT

Bruker at SOFT-TIAFT 2026

Thermo Fisher Scientific at SOFT/TIAFT 2026

Webinars

Strengthening SPE Workflows for Today’s Laboratory

From Crude to Candidate: Scaling Preparative Chromatography with Confidence

How Do You Tackle Sample Prep for Diverse SVOCs?