<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 13th October 2025? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies,</strong> <strong>Shimadzu </strong>and<strong> Waters Corporation </strong>and poster by<strong> Thermo Fisher Scientific / HPLC!</strong></p><h3><strong>1. Agilent Technologies: Expanding Coverage for the Analysis of PFAS in Paper-Based Food Packaging Materials</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_pfas_food_contact_materials_6545_lcqtof_5994_8516en_agilent_0d3cbb1f4d.pdf"><strong>Full PDF for download</strong></a></li></ul><p>PFAS are manufactured chemicals used in food packaging for their grease- and waterproof properties. However, PFAS are persistent in the environment and may pose health risks.2 This study presents a workflow to screen for PFAS in FCMs using LC/Q-TOF. The FluoroMatch software suite was used to automate PFAS data annotation of knowns and unknowns as well as generate an interactive visualization dashboard, enhancing analysis accuracy and coverage.&nbsp;</p><p>The FluoroMatch suite is an open-source set of tools designed to streamline the suspect and nontarget screening of PFAS compounds. It automates several processes, including file conversion, chromatographic peak picking, blank feature filtering, PFAS annotation based on precursor and fragment masses, homologous series detection, compound classification (PFAS versus not PFAS), and reporting annotation confidence. The software library contains 15,643&nbsp;PFAS species and associated fragmentation patterns, with the capability to add more.3&nbsp;</p><p>Various FCM samples, including takeaway containers and microwave popcorn bags, were rigorously extracted and analyzed. Suspect screening was employed for PFAS quantitation, while nontargeted workflows enabled the identification and semi-quantitation of PFAS that were lacking&nbsp;standards.</p><h4><strong>Experimental</strong></h4><h5><strong>LC/MS analysis&nbsp;</strong></h5><p>Extracts were analyzed using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+II+LC"><strong>Agilent 1290 Infinity II LC system</strong></a> coupled with an Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6545+LC%2FQ-TOF"><strong>6545 LC/Q-TOF</strong></a>. An Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=PFC-Free+HPLC+Conversion+kit"><strong>PFC-Free HPLC Conversion kit</strong></a> (part number 5004‑0006) and an Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=InfinityLab+PFC+delay+column"><strong>InfinityLab PFC delay column</strong></a> (part number 5062‑8100) were used to minimize background PFAS levels. Liquid chromatographic separation was performed on a 1.8&nbsp;µm, 2.1 × 100 mm, Agilent ZORBAX RRHD StableBond SB‑C18 column (part number 858700-902) with a corresponding guard column (Agilent part number 821725-902). The mobile phases were (A) water with 20&nbsp;mM ammonium acetate and (B) methanol. The flow rate was 0.4&nbsp;mL/min. The elution gradient was: 5% B (0 to 0.5&nbsp;minutes), linear increase to 40% B (0.5 to 3 minutes), linear increase to 80% B (3 to 16 minutes), hold 80% B (16 to 18 minutes), linear increase to 100% B (18 to 22 minutes), hold 100% B (20 to 22&nbsp;minutes), decrease to 5% B (22 to 22.5 minutes), followed by a 4 minutes post‑run re‑equilibration. The injection volume was 10 μL, and the column temperature was maintained at 50 °C. For the LC/Q‑TOF, the drying gas was set to 4 L/min at 230 °C, the nebulizer to 20 psi, and the sheath gas to 12 L/min at 375 °C.</p><h4><strong>Results and discussion</strong></h4><p>PFAS identification using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=FluoroMatch"><strong>FluoroMatch</strong></a> Using FluoroMatch Visualizer, interactive tools for visualizing PFAS data were generated, including mass defect plots, accurate mass versus retention time plots, MS/MS fragmentation plots, annotation tables, and fragment screening. Individual homologous series were selected based on nominal mass and normalized mass defect, allowing for the observation of patterns and identification of outliers. This interactive cross-filtering simplified the evaluation of PFAS features and enhanced confidence in nontargeted results.&nbsp;</p><p>FluoroMatch was used to annotate a homologous series (C3 to C14) of perfluoroalkyl carboxylic acids (PFCAs), including PFHxA (perfluorohexanoic acid), PFHpA (perfluoroheptanoic acid), PFOA (perfluorooctanoic acid), PFNA (perfluorononanoic acid), PFDA (perfluorodecanoic acid), and PFDoDA (perfluorododecanoic acid). This workflow demonstrated that the suspect screening approach successfully identified common PFAS with available standards, while FluoroMatch was able to annotate additional PFAS that were lacking standards.&nbsp;</p><p>Additionally, FluoroMatch annotated C6 and C8 perfluoroalkyl sulfonic acids (PFSAs), which were not identified by suspect screening. This highlights the value of a hybrid workflow that combines traditional suspect screening with nontargeted tools like FluoroMatch, enhancing confidence in the nontargeted results through their complementary nature. Specifically, FluoroMatch allows for homologous series detection to help annotate incomplete or noisy spectra. FluoroMatch Visualizer evaluation helps incorporate additional lines of evidence to annotation like retention time patterns and Kendrick mass defect to aid in annotation.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study successfully demonstrates the effectiveness of FluoroMatch software in automating the annotation and visualization of PFAS compounds in food packaging materials. The integration of FluoroMatch Visualizer provides a comprehensive approach to identifying both targeted and nontargeted PFAS compounds. The results highlight the prevalence of PFAS in various paper‑based FCMs, with clamshell to-go boxes showing the highest concentrations, particularly PFOA and PFDA, which exceed European Union regulatory limits. As PFAS can migrate into food, especially at higher temperatures, the pervasiveness of PFAS in FCMs raises concerns about potential exposure through hot meals and microwave heating. The widespread detection of PFAS in clamshell to-go boxes and other FCMs indicates a need for stricter regulations to reduce PFAS use in food packaging to protect consumer&nbsp;health.</p><h3><strong>2. Shimadzu: An Ultra-high Sensitivity Analysis of 29 PFAS Compounds in Drinking Water by Direct Injection</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01026_en_dcf554dd6f.pdf"><strong>Full PDF for download</strong></a></li></ul><p>PFAS (Per- and Polyfluoroalkyl Substances) are synthetic fluorinated organic compounds. More than a few thousand compounds exist, each with a varied carbon chain length, functional groups, and structural isomers. Because of its useful qualities, such as their ability to repel water and their nonstickiness, PFAS are found in a wide range of consumer and industrial products, including firefighting foams and coatings. Their high stability and persistence raise concerns about their impact on human health and the environment. In recent years, regulations and studies regarding PFAS have been increasing globally. For example, the U.S. Environmental Protection Agency (EPA) has set a Maximum Contaminant Level (MCL) of 4 ng/L for PFOA and PFOS in drinking water. To improve the analysis of PFAS, more sensitive, accurate and faster methods are needed. This application introduces the ultra-high sensitivity analysis of 29 PFAS in drinking water by direct injection using the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>LCMS-8065XE</strong></a> (Fig. 1) and addresses the demands of testing laboratories for PFAS quantification.</p><h4><strong>Analytical conditions</strong></h4><p>The HPLC and MS analytical conditions are shown in Table 1 and 2. The test compounds used were the 29 compounds included in methods EPA 533 and 537.1 for drinking water analysis. The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>LCMS8065XE</strong></a> is equipped with a new ESI probe (StreamFocus) and a new collision cell (UFsweeper IV), providing more sensitive and accurate results in PFAS analysis. A delay column was installed between the mixer and autosampler to separate PFAS from the HPLC system and those in the sample. To ease the analysis, same type of column is used as delay and analytical columns.</p><h4><strong>Conclusion&nbsp;</strong></h4><ul><li>29 of PFAS in drinking water were measured with high sensitivity (&lt;1 ng/L) by direct injection method using the LCMS-8065XE.&nbsp;</li><li>Good recovery and reproducibility were obtained in drinking water samples, confirming that this analytical method can deliver accurate quantification for PFASsin drinking water.</li></ul><h3><strong>3. Thermo Fisher Scientific / HPLC: Efficient tandem capillary flow LC-MS with short μPAC columns and a single ionization source</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_efficient_tandem_capillary_flow_lc_ms_short_pac_columns_po_en_f38e078c9a.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Nano-flow tandem direct injection (TDI) workflows increase sample throughput and instrument productivity with flow rates below 1 µL/min but need dual-column ESI interfacing to maintain chromatographic performance. At flow rates above 1 µL/min with capillary flow columns, post-column dispersion impacts performance less, allowing low-dispersion switching valves in the fluidic path. We demonstrate the Vanquish Neo UHPLC system TDI workflow for capillary flow LC with a high throughput short pillar array column. This dual-column, single-ESI emitter setup reduces variability, extends emitter life through efficient salt management, and ensures high reproducibility with dedicated gradient pumps and intelligent method design.</p><h4><strong>Materials and methods</strong></h4><h5><strong>Sample Preparation&nbsp;</strong></h5><p>HeLa cell digests were resuspended in 0.1% TFA and 1% ACN to obtain a 200 ng/µL stock solution, sonicated, diluted, and vortexed before use.</p><h5><strong>LC-MS configuration&nbsp;</strong></h5><p>Samples were analyzed using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Vanquish Neo UHPLC</strong></a> instrument that was configured in tandem direct injection mode with an additional pump module and a 10 µL injection loop for maximum throughput. Two µPACM Neo High-Throughput Plus columns were positioned between low-dispersion 6-port switching valves in the column compartment. A 20 µm ID nanoViper line connected the alternating eluents to an ESI emitter with an integrated liquid junction, positioned in a Thermo Scientific EASY-Spray source coupled to a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/402"><strong>Orbitrap Exploris 240 mass spectrometer</strong></a></p><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>Using optimized µPAC Neo HT Plus columns in combination with the Tandem Vanquish Neo UHPLC system heightened the productivity of bottom-up proteomics measurements to 86 - 92% (gradient-dependent)&nbsp;</li><li>At these throughputs, choice of emitter only has a minor effect on identifications, FWHM and TIC. Decreasing the flow rate to 1 uL/min causes peak broadening and increases ionization efficiency which is reflected in higher TICs. In this study, reducing the flow rate only showed a positive effect on protein IDs for the longest gradient (100 SPD).&nbsp;</li><li>With the optimized methods, identifications up to 4713 protein groups for the 180 SPD and 5692 protein groups for the 100 SPD were achieved. The CVs using the same column were between 5-6% and between two columns at around 7-8% (n=6)&nbsp;</li><li>Column reproducibility was showcased for 12 columns across four different production batches. Overall, the ID rate variation between the columns was 1.4%. The median coefficient of variation of the retention times of spiked-in PRTC peptides across the tested 12 columns was 1.8%</li></ul><h3><strong>4. Waters Corporation: Oligo Mapping of sgRNA Digests: Leveraging Xevo MRT Mass Spectrometer Performance and Streamlining Data Analysis</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009009_en_f35f22bebc.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>Benefits&nbsp;</strong></h5><ul><li>Confident characterization of sgRNA digestion products with sub-ppm mass accuracy of oligonucleotide precursors, outstanding MS resolution (~100,000), and sensitivity at high acquisition speed</li><li>A compliance-ready informatics workflow featuring the waters_connect MAP Sequence App (ver 1.0) streamlines oligonucleotide mapping of sgRNA digests</li><li>RapiZyme MC1, a new ribonuclease - offers unique cleavage specificity and the opportunity to generate overlapping digestion products, enabling complete (100%) sequence coverage for sgRNAs</li></ul><p>Single guide RNAs (sgRNAs) were first described in 20121 when two RNA molecules essential for CRISPR-Cas9- mediated DNA cleavage – the trans-activating CRISPR RNA (tracrRNA), which serves as a scaffold for the Cas9 nuclease, and the CRISPR RNA (crRNA), responsible for DNA target recognition - were fused into a single RNA construct. This fusion created the sgRNA, a critical component of the CRISPR-Cas9 gene editing system.<sup>1–2</sup> The sgRNA molecule directs the Cas9 nuclease to introduce precise double-stranded breaks in DNA, enabling targeted genetic modifications.&nbsp;</p><p>Since its discovery, which was honored with the Nobel Prize in Chemistry, CRISPR technology has transformed gene editing applications. Beyond basic research, it has been adapted for rapid diagnostic tools, such as COVID19 tests developed during the 2020 global pandemic<sup>3</sup> , and holds promise for therapeutic interventions in genetic diseases, cancer, and infectious diseases. As sgRNAs are typically synthesized via solid-phase oligonucleotide synthesis, their analytical characterization requires confirmation of both the intact molecular weight<sup>4</sup> and the sequence verification to ensure functional accuracy.<sup>5</sup>&nbsp;</p><p>Traditional LC-MS workflows for sgRNA digest oligo mapping have been labor-intensive and time-consuming, relying heavily on manual data analysis and interpretation. Recently<sup>6</sup> , a UPLC-MS and informatics workflow designed for automated sgRNA sequence mapping was presented following enzymatic digestion with a panel of ribonucleases, including RNase T1, hRNAse 4 and two RNase T2 enzymes: RapiZyme MC1 and Cusativin. This application note extends the effectiveness of this workflow (Figure 1) when implemented on a Xevo MRT Mass Spectrometer (Figure 1), while focusing specifically on MC1 digestion of the Waters™ sgRNA LC-MS standard, where complete unique digested product coverage was obtained.</p><h4><strong>Experimental</strong></h4><h5><strong>LC Conditions</strong></h5><ul><li><strong>LC-MS system:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1148"><strong>Xevo MRT</strong></a> (multi-reflecting time-of-flight) Mass Spectrometer coupled with <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/191"><strong>ACQUITY™ Premier UPLC (Binary) System&nbsp;</strong></a></li><li><strong>Column: </strong>ACQUITY Premier Oligonucleotide BEH™ C18 Column 300 Å, 1.7 µm, 2.1 x 150 mm, (p/n:186010541)</li></ul><h4>Results and Discussion&nbsp;</h4><p>An informatics workflow (Figure 1) featuring the waters_connect MAP Sequence App (version 1.0) was used to facilitate automated data processing of UPLC-MSE datasets acquired following the enzymatic digestion of an sgRNA standard with RapiZyme MC1.6–7 The informatics processing workflow consisted of three steps:&nbsp;</p><ol><li><strong>In-silico digestion:</strong> The mRNA Cleaver MicroApp was used to generate predicted, in-silico digested oligonucleotide digestion products, based on the target RNA sequence.&nbsp;</li><li><strong>Data processing and mass matching:</strong> The waters_connect MAP Sequence App processed the UPLC-MSE data, matching the predicted neutral monoisotopic masses of digested oligonucleotides to the experimentally acquired MS1 data.&nbsp;</li><li><strong>Sequence coverage visualization: </strong>The resulting sequence coverage for the RNA digest was summarized and visualized using the Coverage Viewer MicroApp.</li></ol><h4><strong>Conclusion&nbsp;</strong></h4><ul><li>An informatics workflow, incorporating the waters_connect MAP Sequence App (ver 1.0) was successfully demonstrated for UPLC-MSE digested oligo mapping analysis of sgRNA digests using the Xevo MRT QTOF Mass Spectrometer.&nbsp;</li><li>Confident peak assessments for analysis of sgRNA digests were achieved with the Xevo MRT QTOF Mass Spectrometer, which delivered excellent sensitivity, high resolution MS (100,000), and mass accuracy of less than 1 ppm.</li><li>Complete sgRNA sequence coverage (100%) was achieved by employing RapiZyme MC1, a novel endonuclease introduced by Waters, which provided unique cleavage specificity and predictable missed cleavages to generate longer, unique, overlapping digestion products.</li><li>Oligonucleotide isomeric sequences resulting from enzymatic digestion were effectively differentiated using the waters_connect CONFIRM Sequence App, which matched elevated energy fragment ions patterns to their respective sequences, allowing unambiguous isomer identification.</li></ul>

News from LabRulezLCMS Library - Week 42, 2025

News from LabRulezLCMS Library - Week 44, 2025

<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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