<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 27th July 2026? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you posters by <strong>Agilent Technologies / ASMS, Shimadzu / ASMS, Thermo Fisher Scientific / ASMS </strong>and<strong> Waters Corporation / ASMS </strong>and application note by<strong> KNAUER!</strong></p><h3><strong>1. Agilent Technologies / ASMS: Down in the Weeds: Automated Fast Screening Workflow for Cannabinoids in Whole Blood Using High Resolution Mass Spectrometry</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_blood_cannabinoids_lc_q_tof_mp_694_asms_2026_en_agilent_02f13ac14e.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Distinguishing psychoactive tetrahydrocannabinol (THC) isomers and their metabolites from nonpsychoactive isobars and novel semi-synthetic cannabinoids like hexahydrocannabinol (HHC) is increasingly important to forensic toxicologists, as is the ability to remain up to date with novel compounds that are introduced into the population. This study describes an automated two-step chromatographic workflow that utilizes an initial fast screen method followed by reinjection with specific chromatography to resolve isobars if a suspect is detected in the fast screen on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=Revident"><strong>Revident LC/Q-TOF</strong></a><strong> </strong>with<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+infinity+II+lc"><strong>1290 Infinity II LC</strong></a> (Figure 1). This allows for a larger number of samples to be screened more quickly while ensuring chromatographic resolution of isomers for confirmation. The data acquisition mode enables laboratories to interrogate data retrospectively to determine if novel compounds were present in any given sample.</p><h4><strong>Conclusions</strong></h4><ul><li>Clear and concise software workflow for quick screening analysis&nbsp;</li><li>Baseline resolution of THC isomers and interferences in longer method to allow for confident identification&nbsp;</li><li>All Ions acquisition method allows for retrospective data interrogation with fragment analysis</li></ul><h3><strong>2. KNAUER: Scaling up LNP formulation using a Reynolds number-based methodology</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/VPH_0084_knauer_scaling_up_lnp_formulation_using_a_reynolds_number_based_methodology_e05e67ca78.pdf"><strong>Full PDF for download</strong></a></li></ul><p>LNPs have become an essential enabling technology for RNA-based therapeutics and next-generation drug delivery systems. As these applications progress from laboratory research [1,2] to commercial manufacturing, process robustness and scalability become increasingly important. Beyond scalability, consistent product quality is critical.&nbsp;</p><p>In pharmaceutical development, predefined critical quality attributes (CQAs) such as particle size, PDI, encapsulation efficiency and active pharmaceutical ingredient (API) integrity define whether a formulation meets its intended performance and regulatory requirements. These CQAs are established during early formulation development and must be maintained throughout scaleup to ensure product consistency, pharmaceutical efficacy and reproducibility.</p><p>LNPs are typically generated by controlled mixing of a lipid phase in ethanol with an aqueous buffer containing the nucleic acid payload. The rapid solvent exchange initiates lipid self-assembly and determines the resulting nanoparticle characteristics. Because particle formation occurs on timescales comparable to the mixing process, the interplay between hydrodynamics and nanoparticle assembly is a key determinant of final product quality. Even minor variations in mixing conditions can influence particle size distribution, encapsulation efficiency, and overall formulation consistency.&nbsp;</p><p>To establish robust and scalable manufacturing processes, the underlying transport phenomena must be described independently of an operating scale. Dimensionless numbers provide a powerful framework for this purpose. The Reynolds number (Re) characterizes the flow regime and mixing intensity by relating inertial and viscous forces, while the Damköhler number (Da) describes the relationship between the characteristic timescales of mixing and nanoparticle formation. Together, these parameters provide a quantitative basis for understanding and controlling LNP self-assembly.</p><h4><strong>RESULTS&nbsp;</strong></h4><h5><strong>R&amp;D Evaluation and Hydrodynamic Characterization&nbsp;</strong></h5><p>The experimental study was initiated on <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=503&amp;search=IJM+NanoScaler"><strong>KNAUERs IJM NanoScaler</strong></a>, where multiple LNP formulations were developed and characterized under defined process conditions. During this phase, formulation parameters such as lipid composition, flow rate ratio (FRR), and total flow rate (TFR) were systematically varied to establish target CQAs, particularly particle size and PDI. In addition to recording volumetric flow parameters, the corresponding hydrodynamic conditions were quantified by calculating Re for each experimental setting, thereby the prevailing flow regime within the impingement zone.&nbsp;</p><h5><strong>Determination of a Critical Reynolds Number&nbsp;</strong></h5><p>Particle size was evaluated to depend on the Re using the <strong>IJM NanoScaler </strong>(Fig. 1). At Re below 500 particle sizes of 100 nm and larger were observed, indicating insufficient mixing and heterogeneous supersaturation conditions. With increasing Re, particle size decreased until reaching a plateau region at around 52 nm. Above a critical Reynolds number of ~ 750, further increases in flow rates did not significantly affect particle size. This plateau defines the hydrodynamic condition required to achieve minimal particle size for the given formulation.</p><h4><strong>CONCLUSION&nbsp;</strong></h4><p>A critical Reynolds number defining stable particle size and PDI was successfully identified on the R&amp;D-scale IJM NanoScaler. Operating above this threshold ensured consistent nanoparticle characteristics within a defined plateau region.</p><p>By transferring these hydrodynamic conditions to the benchtop system, predefined CQAs were reliably maintained across scales. The data demonstrate reproducible particle size and PDI during scale-up while enabling a substantial increase in throughput. These findings highlight that a Reynolds number driven approach provides a robust and scalable framework for predictable LNP manufacturing using IJM technology.</p><h3><strong>3. Shimadzu / ASMS: High-Throughput Ultra-Short-Chain PFAS Analysis in Drinking Water using LC-MS/MS with Automated Sample Preparation</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_125_High_Throughput_Ultra_Short_Chain_PFAS_Analysis_in_Drinking_Water_using_LC_MSMS_with_Automated_Sample_Preparation_69e7985cce.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Ultra-short- and short-chain PFAS are highly mobile and persistent contaminants that are challenging to measure in drinking water due to high polarity, low molecular weight, poor chromatographic retention, and susceptibility to laboratory background contamination. This study evaluates a high-throughput LC–MS/MS workflow with automated sample preparation for targeted quantification of ultra-short and short-chain PFAS in drinking water. Method performance was assessed using native background, matrix spike recovery, precision, LOQ accuracy, calibration performance, and continuing calibration verification.</p><h4><strong>Method</strong></h4><p>Nine target PFAS were evaluated: TFA, TFMS, PFPrA, PFMOAA, PFEtS, PFBA, PFPrS, TFSI, and PFBS. Samples and calibrants were prepared in acidified 50:50 PFAS-grade water/methanol using PFAS-grade water provided by MilliporeSigma and an automated ePrep sample preparation system equipped with PFAS-free accessories.</p><p>Chromatographic separation was performed on a polar-embedded IBD column with a delay column to improve retention and minimize background interference. Analysis was performed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>Shimadzu LCMS-8065XE triple quadrupole system</strong></a> within an 8-minute total cycle time with a 10 µL injection volume (figure 2). Drinking-water samples were collected from seven local household sources and spiked at multiple concentration levels. Samples were ran in replicates to evaluate recovery, precision, and method robustness.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This 8-minute LC–MS/MS method enabled high-throughput analysis of ultrashort- and short-chain PFAS in drinking water. TFA background observed in blanks and unspiked samples emphasized the need for contamination control and matrix-specific background assessment. Practical LOQs were supported at 10 ng/L for most analytes and 50 ng/L for PFMOAA. Recovery and precision were generally acceptable from 100–1000 ng/L, with higher variability at 10 ng/L and for PFMOAA, indicating areas for further optimization. Calibration and CCV performance supported reliable quantification across the reportable range.</p><h3><strong>4. Thermo Fisher Scientific / ASMS: Unlocking the archived proteome: High-throughput, deep FFPE proteome profiling using the Orbitrap Astral Mass spectrometer</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004694_lsms_protein_ffpe_orbitrap_astral_proteomics_po004694_asms2026_na_en_7cd59d64aa.pdf"><strong>Full PDF for download</strong></a></li></ul><p>FFPE tissue specimens are central to clinical pathology and translational cancer research, enabling long-term storage while preserving morphology for histology and molecular analysis. Widely available through biobanks, they support retrospective studies, biomarker discovery, and precision oncology—especially when paired with detailed clinical data. Compared to fresh tissues, FFPE samples are more accessible, scalable, and cost-effective for proteomics.</p><p>However, FFPE proteomics is technically challenging. Formaldehyde-induced crosslinking complicates protein extraction and digestion, while paraffin removal and crosslink reversal add complexity. Traditional workflows are labor-intensive, time-consuming, and prone to variability, limiting reproducibility and throughput. Although recent advances in sample preparation have improved performance, residual contaminants can still affect instrument robustness and scalability.&nbsp;</p><p>To address these challenges, we implemented a streamlined FFPE proteomics workflow that simplifies processing and improves peptide yield and reproducibility. Using FFPE lung tissue and the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2465"><strong>Thermo Scientific OptiSpray Ion source</strong></a> with the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/836"><strong>Orbitrap Astral Mass spectrometer</strong></a><strong> </strong>across two LC platforms, we achieved sensitive detection of low-abundance peptides from 20– 200 ng inputs. Combined with fast LC methods and acquisition rates of 60, 180, and 500 samples per day, this approach enables deep, scalable profiling. The automated OptiSpray Ion source also reduces instrument contamination, supporting robust, high-throughput analysis of archived clinical tissues for biomarker discovery and translational research.</p><h4><strong>Experimental procedure&nbsp;</strong></h4><h5><strong>Sample preparation&nbsp;</strong></h5><p>Lung tumor and lung normal samples were de-paraffinized using xylene and sequential ethanol washes. The optimized protein extraction protocol and Thermo Scientific EasyPep Mini MS sample prep kit was used to prepare the digest samples from FFPE sections of normal and tumor lung samples. Protein concentration was measured using Thermo Scientific Pierce Rapid Gold BCA Protein Assay kit. The peptides were quantified using the Thermo Scientific Pierce Fluorometric Peptide Assay Kit before LC-MS/MS analysis. For <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=291&amp;search=Evosep+ENO"><strong>Evosep ENO</strong></a>, peptides were loaded on EvoTips .&nbsp;</p><h5><strong>LC-MS analysis&nbsp;</strong></h5><p>Samples were injected onto an Thermo Scientific OptiSpray µPAC Neo Cartridge (P/N OS-UPAC050NAN) and Thermo Scientific OptiSpray µPAC Neo High-Throughput Cartridge (P/N OS-UPAC005CAP) and separated using 20 min (60 SPD) and 6.8 min (180 SPD) gradients, respectively, in direct injection mode at 55°C on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Thermo Scientific Vanquish Neo UHPLC System</strong></a>. For 500 SPD (2.3 min) separation, samples were processed on Evosep ENO using an Evosep EV1182 Performance Column at 40 °C. Detailed LC and MS parameters are provided in Tables 1–2.&nbsp;</p><h5><strong>Data analysis Spectronaut® Software&nbsp;</strong></h5><p>The raw DIA files from both the labeled and unlabeled samples were analyzed together using Biognosys Spectronaut® Software in directDIA mode. Exported output files were imported to R Studio (2023.09.0 Build 463) with R (v4.3.1) for downstream data analysis and visualization.</p><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>End-to-end FFPE proteomics is completed in under one day, integrating rapid sample preparation, fast LC–MS, and streamlined data analysis.&nbsp;</li><li>Deep proteome coverage is achieved from FFPE lung tissue, with up to ~8,600 protein groups and &gt;100,000 peptides identified from 200 ng input in 20 min.</li><li>Increasing throughput by up to ~8× (60 to 500 SPD) with moderate loss in depth, retaining ~70% of proteins at 180 SPD and ~45% at 500 SPD.&nbsp;</li><li>Robust quantitative performance is maintained at low sample input (20 ng) and across acquisition speeds, with median CVs ≤10%.&nbsp;</li><li>The workflow enables reliable differential expression and pathway analysis at scale, demonstrating its utility for biological insight into lung tumor and normal tissues.</li></ul><h3><strong>5. Waters Corporation / ASMS: Identification of Novel Per-and-Polyfluoroalkyl Substance (PFAS) Isoform in Textile Using a Multi-Reflecting Time-ofFlight Mass Spectrometer Technology</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009415_0b95241dfd.pdf"><strong>Full PDF for download</strong></a></li></ul><div><div><section><div><div><div><div><div><div><p>The poster presents a non-targeted LC-MS/MS workflow for identifying <strong>per- and polyfluoroalkyl substances (PFAS)</strong> in textile materials using high-resolution mass spectrometry. As concerns over PFAS exposure continue to grow, conventional targeted methods often capture only a limited number of compounds. The authors therefore combined <strong>data-dependent acquisition (DDA)</strong> with high-resolution accurate-mass analysis to characterize PFAS profiles more comprehensively, enabling the identification of novel PFAS isoforms and halogenated contaminants with high confidence.</p><p>The analytical workflow was based on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/191"><strong>Waters ACQUITY Premier UPLC system</strong></a> equipped with a PFAS solution installation kit and an <strong>ACQUITY Premier BEH C18 (2.1 × 50 mm, 1.7 µm) column</strong>, coupled to the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2433"><strong>Waters Xevo MRT P10 multi-reflecting time-of-flight (MRT) mass spectrometer</strong></a>. Textile reference material was extracted according to <strong>EN 17681-1:2025</strong>, and LC-MS/MS data were acquired in <strong>data-dependent acquisition (Top 5 DDA)</strong> mode. Data processing and compound identification were performed using the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1544"><strong>waters_connect™ Software Platform</strong></a>, combining accurate precursor and fragment masses with isotopic information.</p><p>A key innovation of the study was the implementation of <strong>mass defect-directed DDA</strong>. By creating a database of nearly <strong>19,600 unique PFAS-related compounds</strong> and using their characteristic mass defects to guide precursor selection, the workflow reduced the number of non-specific MS/MS spectra by approximately <strong>25%</strong>. This allowed the instrument to focus on PFAS-like compounds more efficiently, increasing the number of informative fragmentation spectra and improving the identification of previously unknown PFAS species. The approach successfully identified compounds such as <strong>N-ethyl perfluorooctane sulfonamidoethanol (N-EtFOSE)</strong> in textile extracts with excellent mass accuracy (1.1 ppm).</p><p>The authors conclude that <strong>mass defect-driven DDA</strong> significantly enhances non-targeted PFAS screening by reducing unnecessary MS/MS acquisitions while increasing the number of confidently identified PFAS and PFAS-like compounds. They also suggest that this strategy can be extended beyond PFAS analysis to other classes of persistent environmental contaminants, including <strong>polychlorinated biphenyls (PCBs)</strong> and <strong>polybrominated biphenyls (PBBs)</strong>, making it a promising approach for broader environmental and materials analysis.</p></div></div></div></div></div></div></section></div></div>

News from LabRulezLCMS Library - Week 31, 2026

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2026 AOAC INTERNATIONAL Annual Meeting & Exposition

Bruker at the 7th European Symposium on Single Cell Proteomics

Shimadzu at 2026 AOAC Annual Meeting & Exposition

ICP-MS for Hybrid Photoelectrode Characterization

Modern Methods for Faster Microbial Analysis

Addressing LC Method Optimization - Scaling For Efficiency, Throughput And Reproducibility