<p><strong>🎤Dan Reddy </strong>(PhD candidate in the Department of Chemistry at Queen's University and a recipient of the NSERC Vanier Canada Graduate Scholarship. He was recently named one of the top 35 early-career scientists globally in the 2025 CAS Future Leaders program.)</p><p><strong>In this episode, we interview Daniel Reddy, 2025 CAS Future Leader and PhD candidate at Queen's University, about his groundbreaking research on automated mass spectrometry and dried matrix spots (DMS).</strong></p><p>Dan's work combines computer vision, 3D printer automation, and laser micromachining to revolutionize sample preparation—reducing CO₂ emissions by 28-fold and organic solvent use by 21-fold compared to traditional methods.</p><h4><strong>What You'll Learn:</strong></h4><ul><li>How to give a mass spectrometer "sight" and "taste" using computer vision and the LMJ-SSP (Liquid Microjunction Surface Sampling Probe)</li><li>The breakthrough technology behind Surface Energy Traps (SETs) for confining liquid droplets on paper substrates</li><li>Why dried matrix spots eliminate the need for cold-chain shipping and enable analysis of blood, urine, and saliva samples via standard mail</li><li>How DIY chemists are hacking 3D printers to build cost-effective autosamplers (replacing $10K+ systems)</li><li>The role of green chemistry and systems thinking in modernizing analytical methods</li><li>Why interdisciplinary collaboration (chemistry + computer science) is critical to innovation</li></ul><h4><strong>Key Topics:</strong></h4><ul><li>Dried Matrix Spots (DMS) for automated sample prep</li><li>Laser-micromachined Surface Energy Traps</li><li>Direct surface sampling mass spectrometry</li><li>Sustainability in analytical chemistry</li><li>3D printer customization for laboratory automation</li><li>The importance of science communication and community outreach</li></ul><h3><strong>Video Transcription</strong></h3><h4><span><strong>Introduction</strong></span></h4><p>Recent advances in analytical chemistry increasingly focus on simplifying workflows, improving sustainability, and enabling automation. In this context, the work of <span>Dan Reddy</span> centers on the concept of <i>“bringing mass spectrometry to life”</i> through the integration of automated sampling, computer vision, and dried matrix spot (DMS) methodologies.</p><p>The primary objective is to enable efficient and reproducible analysis of biological and liquid samples—such as blood, urine, saliva, or other solutions—by depositing them onto substrates, drying them, and extracting meaningful analytical information directly via mass spectrometry.</p><h4><span><strong>Conceptual Framework: Enabling “Sight” and “Taste” in Mass Spectrometry</strong></span></h4><p>A central innovation in this work is the conceptual transformation of mass spectrometry from a passive analytical tool into an active, semi-autonomous system.</p><ul><li><strong>“Sight”</strong> is introduced through <strong>camera-based computer vision</strong>, allowing the system to identify predefined patterns on a substrate.</li><li><strong>“Taste”</strong> is implemented via a <strong>liquid microjunction surface sampling probe (LMJSSP)</strong>, which enables direct extraction of analytes from surfaces.</li></ul><p>The LMJSSP consists of two concentric capillaries forming a continuously flowing microdroplet. When brought into contact with the sample surface, this droplet facilitates localized extraction, effectively enabling direct surface analysis without traditional chromatographic separation.</p><p>Combined with an automated positioning system (adapted from 3D printer mechanics), the platform can autonomously locate sampling sites and perform reproducible measurements.</p><h4><span><strong>Dried Matrix Spots as an Analytical Platform</strong></span></h4><h5><span><strong>Principle and Advantages</strong></span></h5><p>Dried matrix spots involve depositing a small volume of liquid sample onto a substrate (commonly paper), followed by drying. This approach offers several advantages:</p><ul><li>Reduced need for cold-chain transport</li><li>Simplified sample handling and storage</li><li>Compatibility with remote or decentralized sampling</li><li>Lower solvent consumption</li></ul><p>These features contribute significantly to greener analytical workflows and improved logistical efficiency.</p><h5><span><strong>Sustainability Impact</strong></span></h5><p>The implementation of DMS-based workflows has demonstrated:</p><ul><li>Up to <strong>28-fold reduction in CO₂ emissions</strong></li><li>Up to <strong>21-fold reduction in organic solvent use</strong></li></ul><p>These improvements arise from eliminating cold-chain logistics and minimizing solvent-intensive preparation steps.</p><h4><span><strong>Surface Energy Traps (SCTs): Controlled Micro-Sampling Environments</strong></span></h4><h5><span><strong>Definition and Fabrication</strong></span></h5><p>Surface Energy Traps (SCTs) are microstructured regions on a substrate designed to confine liquid droplets within defined boundaries.</p><p>The fabrication process involves:</p><ol><li>Coating paper with a <strong>hydrophobic layer</strong></li><li>Using <strong>laser ablation</strong> to selectively remove the coating in defined patterns</li><li>Creating <strong>hydrophilic circular regions</strong> (typically ~0.5 mm diameter)</li></ol><p>These patterned regions act as micro-wells that confine droplets spatially and prevent lateral diffusion.</p><h5><span><strong>Analytical Benefits</strong></span></h5><p>SCTs address key limitations of traditional dried matrix spots:</p><ul><li><strong>Improved spatial confinement</strong> of analytes</li><li><strong>Reduced diffusion variability</strong></li><li><strong>Enhanced reproducibility</strong></li><li><strong>Preconcentration effects</strong> due to controlled drying</li></ul><p>Additionally, the SCT diameter is smaller than the sampling probe, enabling near-complete analyte collection during surface extraction.</p><h4><span><strong>Drying Dynamics and Analyte Distribution</strong></span></h4><p>Traditional dried matrix spots often suffer from the <strong>“coffee-ring effect”</strong>, where analytes redistribute unevenly during drying. This leads to variability depending on sampling location.</p><p>The SCT approach mitigates these effects by:</p><ul><li>Limiting diffusion area</li><li>Maintaining analytes near the surface</li><li>Producing more uniform analyte distribution</li></ul><p>Preliminary investigations (e.g., via SEM imaging) indicate improved homogeneity, although further studies are needed to fully characterize drying kinetics and their influence on signal intensity.</p><h4><span><strong>Integration with Automated Sampling Systems</strong></span></h4><h5><span><strong>3D Printer-Based Positioning</strong></span></h5><p>A key engineering innovation is the repurposing of <strong>3D printer hardware</strong> for automated sample positioning:</p><ul><li>Provides cost-effective XYZ motion control</li><li>Enables programmable sampling routines</li><li>Supports integration with analytical instrumentation</li></ul><p>Custom software—developed in collaboration with computer engineers—allows users to define coordinates, dwell times, and sampling parameters.</p><h5><span><strong>Computer Vision Integration</strong></span></h5><p>The addition of computer vision enables:</p><ul><li>Pattern recognition (e.g., alignment markers near SCTs)</li><li>Autonomous targeting of sampling locations</li><li>Reduced operator intervention</li></ul><p>This transforms the system into a semi-autonomous analytical platform.</p><h4><span><strong>Comparison with Conventional Workflows</strong></span></h4><p>Compared to traditional LC-MS or GC-MS workflows, the presented approach offers:</p><div><div><figure class="table"><table><thead><tr><th>Aspect</th><th>Conventional Methods</th><th>SCT + LMJSSP Approach</th></tr></thead><tbody><tr><td>Sample prep</td><td>Multi-step, solvent-intensive</td><td>Minimal, direct surface sampling</td></tr><tr><td>Chromatography</td><td>Required</td><td>Potentially bypassed</td></tr><tr><td>Throughput</td><td>Moderate</td><td>High (automated)</td></tr><tr><td>Sustainability</td><td>Limited</td><td>Significantly improved</td></tr></tbody></table></figure></div></div><p>While chromatographic methods remain essential for many applications, this approach provides a complementary pathway for rapid screening and targeted analyses.</p><h4><span><strong>Green Chemistry and Systems Thinking</strong></span></h4><p>A notable aspect of this work is the integration of <strong>systems thinking</strong> into analytical chemistry. Inspired by engagement with organizations such as the <span>American Chemical Society</span> and green chemistry initiatives, the research emphasizes:</p><ul><li>Environmental impact reduction</li><li>Resource efficiency</li><li>Lifecycle considerations</li></ul><p>This perspective expands the role of analytical chemists beyond method performance to broader societal and environmental implications.</p><h4><span><strong>Future Outlook and Applications</strong></span></h4><p>The research is currently at an early stage but shows strong potential for:</p><ul><li><strong>Decentralized diagnostics</strong> (e.g., remote blood sampling)</li><li><strong>Environmental monitoring</strong></li><li><strong>High-throughput screening workflows</strong></li><li><strong>Field-deployable analytical systems</strong></li></ul><p>Further advancements are expected in:</p><ul><li>Substrate engineering</li><li>Automation robustness</li><li>Integration with advanced MS platforms (e.g., triple quadrupole systems)</li></ul><h4><span><strong>Conclusion</strong></span></h4><p>The integration of dried matrix spots, surface energy traps, and automated surface sampling represents a significant step toward more sustainable, efficient, and accessible analytical workflows.</p><p>By combining innovations in microfabrication, computer vision, and mass spectrometry, the work of <span>Dan Reddy</span> demonstrates how analytical chemistry can evolve toward smarter, greener, and more autonomous systems.</p><blockquote><p><strong>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</strong></p></blockquote><blockquote><h4><strong>Concentrating on Chromatography Podcast</strong></h4><p>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!</p><p>You can find <strong>Concentrating on Chromatography Podcast </strong>in podcast apps:</p><ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL"><strong>Spotify</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185"><strong>Apple podcast</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography"><strong>podscan</strong></a></li></ul><p>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos"><strong>YouTube channel</strong></a></p></blockquote>

Mass Spectrometry, Surface Sampling and Dried Matrix Spots - Greener Chemistry and 3D Printing

<p><strong>This study presents a novel MS/MS filtering tree approach for distinguishing regio- and stereoisomeric bile acids in untargeted LC-MS/MS data. By leveraging intensity ratios of closely related fragment ions, the method overcomes limitations of traditional spectral matching, enabling more accurate isomer annotation.</strong></p><p>A user-friendly web-based application was developed to facilitate implementation without coding expertise. Applied to public datasets, the workflow revealed diet-associated bile acid patterns across mammalian species and enabled identification of previously uncharacterized compounds, demonstrating its potential for large-scale metabolomics studies.</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.analchem.5c05677"><strong>MS/MS Mass Spectrometry Filtering Tree for Bile Acid Regio- and Stereoisomer Annotation</strong></a></h4><p>Ipsita Mohanty, Shipei Xing, Vanessa Castillo, Julius Agongo, Abubaker Patan, Yasin El Abiead, Helena Mannochio-Russo, Wilhan D. Gonçalves Nunes, Jasmine Zemlin, Itzhak Mizrahi, Dionicio Siegel, Mingxun Wang, Lee R. Hagey, and Pieter C. Dorrestein*</p><p>Anal. Chem. 2026, 98, 6, 4571–4584</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c05677">https://doi.org/10.1021/acs.analchem.5c05677</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>Cholesterol-derived steroid molecules, known as bile acids, have been detected in nearly every organ where they have been studied. <a href="javascript:void(0);">(1)</a> Alterations in bile acid composition and dysbiosis have been linked to various health conditions, including neurocognitive developmental disorders, cancer, infections, and metabolic diseases such as diabetes and inflammatory bowel disease (IBD). <a href="javascript:void(0);">(2−8)</a> In the last 5 years, the number of detected bile acids in metabolomics experiments <a href="javascript:void(0);">(1,9−15)</a> has increased by the 1000s and possibly approaching 10,000s - most of which have not yet been fully structurally characterized. <a href="javascript:void(0);">(1,6,16−19)</a> We believe this is only the tip of the iceberg and that in the next 5 years this number will continue to increase. The scale of the bile acid pool and the challenge of accurately detecting and describing their structure truly represent an exciting frontier for analytical and computational scientists who continue to push the boundaries of what is possible.</p><p>In humans, bile acids are predominantly derived from cholesterol through pathways that exist not only in the liver as previously thought but also in many other organs including kidneys and brain. <a href="javascript:void(0);">(16,20,21)</a> These pathways shorten the side chain, producing a carboxyl terminus on the remaining 24-carbon steroid structure, which consists of four interconnected rings and side chain, collectively referred to here as the “core” (colored in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig1">Figure 1</a>a). The core of bile acids undergoes multiple hydroxylations, a process typically associated with the liver but also occurring in other organs such as the brain, kidney, and spleen. <a href="javascript:void(0);">(16)</a> Considering hydroxylation at known carbon positions on bile acids reported from human samples (as starred in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig1">Figure 1</a>a, <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c05677/suppl_file/ac5c05677_si_002.xlsx">Supplementary Table S1</a>) along with stereoisomers and allo versus nonallo A/B ring isomerization at C5, approximately 1,800 candidate mono-, di-, and trihydroxy C<sub>24</sub> bile acid cores are theoretically possible (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig1">Figure 1</a>a). This number further expands exponentially in the gut.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4571_4584_Figure_1_MS_MS_fragmentation_of_bile_acid_isomers_9bfcc8779d.jpg" alt="Anal. Chem. 2026, 98, 6, 4571–4584: Figure 1. MS/MS fragmentation of bile acid isomers. (a) Structure of bile acids highlighting mono-, di-, and trihydroxylated steroid cores, with experimentally observed potential hydroxylation sites on the steroid core indicated by red stars. (b) MS/MS fragmentation spectra of the regioisomers, taurochenodeoxycholic (TCDCA) acid and taurodeoxycholic acid (TDCA), illustrating a low-intensity mass region containing ions unique to each isomer. (c) Enlarged view of the MS/MS fragmentation spectra for taurochenodeoxycholic and taurodeoxycholic acids, emphasizing the ion pair used to calculate relative intensity ratios for differentiating these isomers." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4571_4584_Figure_1_MS_MS_fragmentation_of_bile_acid_isomers_9bfcc8779d.jpg 245w," sizes="100vw" width="2100" height="890"></p><p>Recently, we developed MS/MS fragmentation-based filters using a Mass Spectrometry Query Language (MassQL), a query language that allows filtering of data patterns <a href="javascript:void(0);">(49)</a> to retrieve all MS/MS spectra from the Orbitrap data sets in GNPS/MassIVE repository containing bile acid-specific fragment ions. After merging similar spectra, this resulted in a reference library of 21,549 MS/MS spectra. <a href="javascript:void(0);">(1)</a> This library includes MS/MS spectra of known and many yet-to-be structurally characterized bile acid candidates that have already been detected from public metabolomics data repositories. This also includes MS/MS of multiple ion forms such as different adducts, in-source fragments, and multimers, <a href="javascript:void(0);">(1)</a> which all help in the annotation of bile acids. This MassQL library enables the annotation of the number of hydroxyl groups on the bile acid core, as well as the identification of potential modifications, and ∼ 62% of the atomic compositions are annotated. Other spectral “modifications” that do not have a distinct atomic composition may be different adducts or multiple combinations of adducts, in source fragments, and multimers. However, the diagnostic bile acid MS/MS fragments used to build this reference library do not allow for the differentiation between regio- and stereoisomers. Also, MS/MS spectral matching with the candidate library using the cosine metric often overlooks finer details within fragment ions, as minor peak intensity changes or low-intensity fragment ions have a minimal influence on overall spectral match scores (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig1">Figure 1</a>b).</p><p>Based on our manual inspection of hundreds of bile acid MS/MS spectra, we observed and hypothesized that information in the low-intensity MS/MS fragments, including specific ion pairs, their intensity ratios, and unique ions, could be used to distinguish the steroid core isomers. As proof of concept in leveraging MS/MS data to enable further refinement of the stereo and regiochemistry of the hydroxylations of the bile acids cores, we developed a MassQL-based filtering tree utilizing key marker ions and their intensity ratios within narrow <i>m</i>/<i>z</i> windows to propose regio- and stereoisomer assignments of bile acids solely from MS/MS data. In this study, we focus on bile acid amidates, a class of structures found in humans and other animals.</p><h4><strong>Experimental Section</strong></h4><h5><strong>MS/MS Data Acquisition of Taurine-Conjugated Bile Acids</strong></h5><p>We generated one mM stock solutions of our in-house collection of 48 taurine-conjugated bile acids in 100% MeOH. The standards used in this study were obtained from the bile acid collection of the late Dr. Alan Hofmann’s laboratory at UCSD. The Dorrestein laboratory inherited these standards after his demise. The standard samples were injected (5 μL) into a Vanquish ultrahigh-performance liquid chromatography (UHPLC) system coupled to a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/559"><strong>Q-Exactive quadrupole Orbitrap mass spectrometer</strong></a> (Thermo Fisher Scientific, Waltham, MA). A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1509"><strong>Kinetex polar C18 column</strong></a> (2.1 × 100 mm, 2.6 μm particle size, 100 A pore size; Phenomenex, Torrance) was employed with a SecurityGuard C18 column (2.1 mm ID) at 40 °C column temperature. The mobile phases (0.5 mL/min) were 0.1% formic acid in both water (A) and ACN (B) with the following gradient: 0–0.5 min 5%B, 0.5–1.1 min 5–25%B, 1.1–7.5 min 25–40%B, 7.5–8.5 min 40–99%B, 8.5–10 min 99%B, 10–12 min 5%B. The mass spectrometer was operated in positive heated electrospray ionization with the following parameters: sheath gas flow, 53 AU; auxiliary gas flow, 14 AU; sweep gas flow, 3 AU; auxiliary gas temperature, 400 °C; spray voltage, 3.5 kV; inlet capillary temperature, 269 °C; S-lens level, 50 V. MS1 scan was performed at <i>m</i>/<i>z</i> 150–1500 with the following parameters: resolution, 35,000 at <i>m</i>/<i>z</i> 200; maximum ion injection time, 100 ms; automatic gain control (AGC) target, 1E6. Up to 5 MS/MS spectra per MS1 scan were recorded under the data-dependent mode (dd-MS<sup>2</sup>) with the following parameters: resolution, 17,500 at <i>m</i>/<i>z</i> 200; maximum ion injection time, 150 ms; AGC target, 5.0E5; MS/MS precursor isolation window, <i>m</i>/<i>z</i> 1; isolation offset, <i>m</i>/<i>z</i> 0.5; normalized collision energy (NCE) of 45%; minimum AGC for MS/MS spectrum, 2.5E4; apex trigger, 2 to 5 s; dynamic precursor exclusion, 8 s. Fragmentation was performed in the HCD cell using nitrogen as the collision gas. The data was deposited in GNPS/MassIVE and is publicly available at MSV000092003. The MS/MS spectra are also added now to the GNPS spectral library - BILELIB19 (<a target="_blank" rel="noopener noreferrer" href="https://gnps.ucsd.edu/ProteoSAFe/gnpslibrary.jsp?library=BILELIB19">https://gnps.ucsd.edu/ProteoSAFe/gnpslibrary.jsp?library=BILELIB19</a>)</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Retrospective Bile Acid Isomer Profiling in a Public Data Set of Animals with Different Diets</strong></h5><p>To illustrate the utility of the MassQL multistep filtering trees in retrospectively analyzing data in public repositories, we selected a publicly available data set containing feces from 40 animals (13 mammalian species) from the Zoological Center Tel Aviv-Ramat Gan, Israel. <a href="javascript:void(0);">(62)</a> The data set consisted of 3 herbivores, 23 omnivores, and 13 carnivores (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>a). We selected this data set as we had previously confirmed detection of 6 previously uncharacterized polyamine-conjugated bile acids that we could not confirm with retention times as none of the standards we had synthesized matched, although their MS/MS did. We showed that their levels were higher in carnivores compared to herbivores and omnivores; <a href="javascript:void(0);">(1)</a> however, we were still unable to resolve the regio- and stereochemistry of all possible isomers of polyamine-conjugated bile acids. To further dive into the diversity of bile acids, we matched the MS/MS spectra of this study against the GNPS spectral libraries, including the candidate bile acid MS/MS reference library that we had previously created from the repository scale analysis. <a href="javascript:void(0);">(1)</a> This revealed 993 MS/MS spectral matches to bile acids. We next applied the multistep MassQL queries to resolve the regio- and stereochemistry of the bile acids. The steps described in this section follow the same filtering approach as outlined for the dihydroxy bile acid filtering tree (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig2">Figure 2</a>).&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4571_4584_Figure_2_Development_of_MSMS_fragmentation_based_Mass_QL_filtering_tree_2227b688a9.jpg" alt="Anal. Chem. 2026, 98, 6, 4571–4584: Figure 2. Development of MS/MS fragmentation-based MassQL filtering tree. Sequential MS/MS fragmentation-based filtering tree designed to classify regio- and stereoisomers of dihydroxylated bile acids. Structures at each filtering step are shown, with terminal bins color-coded for clarity." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4571_4584_Figure_2_Development_of_MSMS_fragmentation_based_Mass_QL_filtering_tree_2227b688a9.jpg 183w," sizes="100vw" width="1000" height="852"></p><p>Step 1 excludes MS/MS spectral matches to candidate bile acids where the experimental spectra lacked the two diagnostic MS/MS ions for bile acids. Steroids and lipids often exhibit similar MS/MS spectra to bile acids, sometimes yielding high cosine similarity scores (&gt;0.7), yet they lack key low-intensity diagnostic ions. Due to the low intensity of these ions, their presence or absence typically does not significantly affect spectral matching scores. However, our MassQL isomer filters in Step 1 identified these MS/MS spectra to reveal that 543 MS/MS spectra had the two characteristic fragment ions for mono-, di-, and trihydroxy bile acids (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>a). A portion of the 543 MS/MS spectra are adducts, in-source fragments, and multimers, overall reducing the number of unique bile acid structures. Based on retention time and peak shape correlation analysis in MZmine4, <a href="javascript:void(0);">(63)</a> a strategy that allows the discovery of ion forms associated with a specific molecule, we estimate these to represent 402 bile acids. Even though the data contained evidence for hundreds of unique bile acids, the stereo- and regiochemistry of hydroxylations were yet to be defined.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4571_4584_Figure_4_Filtering_of_bile_acid_isomers_in_an_untargeted_LC_MS_MS_data_set_d7f119b028.jpg" alt="Anal. Chem. 2026, 98, 6, 4571–4584: Figure 4. Filtering of bile acid isomers in an untargeted LC-MS/MS data set. Representative example for using the MassQL filters for identifying bile acid isomers. (a) Overview of study design. Fecal samples from herbivores (n = 3), omnivores (n = 23), and carnivores (n = 13) were analyzed by LC-MS/MS and processed using MZmine4 and FBMN on GNPS2. Stepwise MassQL filtering refined candidate bile acids from 543 features (Step 1) to 96 (Steps 2 and 3) and 49 stereo and regiochemistry assigned MS/MS spectra (Step 4). Differential abundance of bile acids between herbivores/omnivores and carnivores is illustrated in the volcano plots (b) at Step 1 and (c) Step 4 of the dihydroxy filtering tree. The annotation of a previously uncharacterized bile acid was refined from (OH)2-N-acetyl-putrescine to 3,12α-N-acetyl-putrescine." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4571_4584_Figure_4_Filtering_of_bile_acid_isomers_in_an_untargeted_LC_MS_MS_data_set_d7f119b028.jpg 243w," sizes="100vw" width="1819" height="1170"></p><p>The application of our MassQL filtering tree allowed us to further refine structural details within the bile acid core. After Step 2 and Step 3 of the MassQL filtering, we separated the amidated mono-, di-, and trihydroxylated bile acids from their ketones and unconjugated versions to give 96 bile acids (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>a). A univariate analysis at Step 1 of bile acid annotations showed a higher abundance of almost all bile acids in the carnivores compared to herbivores and omnivores combined (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>b). As we move down the MassQL filtering tree to Step 4, we can now hypothesize the regio- and, in many cases, the stereochemistry of their hydroxyl positions. With the current implementation of the tree, we can predict the bile acid cores of 49 MS/MS spectra (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>a). The highest number of spectral matches that could be assigned are dihydroxylated bile acids, symbolized here as (OH)<sub>2</sub> (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05677#fig4">Figure 4</a>c). These were categorized into individual bins of 3,12α-(OH)<sub>2</sub>, 3,7-(OH)<sub>2</sub>; 3,6-(OH)<sub>2</sub>; 3,12β-(OH)<sub>2</sub>; 7,12β-(OH)<sub>2</sub> and 3,6-(OH)<sub>2</sub> isomers following the application of the dihydroxy isomer filtering tree.</p><h4><strong>Conclusion</strong></h4><p>In conclusion, this study introduces the concept of using a MassQL MS/MS fragmentation-based filtering tree approach to enable precise regio- and stereochemical differentiation of bile acid isomers, which were subsequently validated against reference standards. The method expands the ability to annotate bile acids and has led to the discovery of bile acid deoxycholyl-<i>N</i>-acetyl-putrescine, which had previously been detected in the feces of carnivores but not structurally characterized. By making annotated MS/MS spectra publicly available and enabling the MassQL queries, this approach enhances bile acid analysis, offering innovative tools for exploring their metabolic roles and biological significance, including retro-analysis of regio- and stereochemical isomer variations in existing public LC-MS/MS data.</p></div>

MS/MS Mass Spectrometry Filtering Tree for Bile Acid Regio- and Stereoisomer Annotation

<p><strong>In the week of April 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: Fit-for-purpose workflows for inositol stereoisomer profiling in dietary supplements and foods using single and tandem mass spectrometry</strong></h5><ul><li>Tu, 7.4.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6030">Registration</a></li></ul><p>The aim of this webinar is to present analytical procedures capable of simultaneously separating and quantifying free inositol stereoisomers in both simple matrices and complex matrices.</p><h5><strong>2. Thermo Fisher Scientific: Transforming Fuel Testing Performance with Combustion Ion Chromatography</strong></h5><ul><li>We, 8.4.2026 07:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6093">Registration</a></li></ul><p>Join us for an interactive session on how Combustion Ion Chromatography (C-IC) is transforming fuel testing performance in modern laboratories.</p><h5><strong>3. SCIEX: Getting started with LC-MS/MS for PFAS</strong></h5><ul><li>We, 8.4.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6102">Registration</a></li></ul><p>Learn how to build LC-MS/MS methods for PFAS analysis, achieve ultra-low detection limits, and gain practical skills for environmental and food testing in this expert-led webinar.</p><h5><strong>4. Phenomenex: Extraction Face-Off: Choosing Between SLE and SPE</strong></h5><ul><li>We, 8.4.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6092">Registration</a></li></ul><p>Understand how SLE and SPE work and how they are different from each other.</p><h5><strong>5. Waters Corporation: RADIAN™ ASAP Mass Spectrometry for the Detection and Analysis of Explosive Traces</strong></h5><ul><li>We, 8.4.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6031">Registration</a></li></ul><p>Explore how mass spectrometry enables rapid detection of trace explosives. Learn how RADIAN™ ASAP extends forensic and security workflows, supporting future screening technologies and ion-mobility innovation.</p><h5><strong>6. Technology Networks: Label Free Quantitation: New Insights Into High-Throughput Proteomic Workflows</strong></h5><ul><li>Th, 9.4.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5969">Registration</a></li></ul><p>Discover how next-generation LC–MS and the ZenoTOF 8600 enable robust, high-throughput LFQ proteomics, backed by insights from a large multi-laboratory benchmark study.</p>

Webinars LabRulezLCMS Week 15/2026

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Organomation, founded in 1959, designs and manufactures high-quality nitrogen evaporators and extraction systems. Known for innovation and durability, their lab instruments are used globally for efficient sample preparation with strong customer support.

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Waters Corporation

<h4><strong>Virtual event: Pharma conclave series 2024</strong></h4><p>SCIEX offers the platform for the experts to take the stage and drive technological progress</p><p><strong>Welcome to Pharma conclave series 2024</strong> – where our customers’ expertise meets innovation, transforming your knowledge and empowering you to revolutionize your work processes. Join us in discovering techniques that will enhance your skills to accelerate your daily operations in the development of new drugs.</p><p>From the research of new markers to the drug development moving into non and GLP bioanalysis. Confidently plan your next lab expansion with the knowledge gained from industry leaders and pioneers.</p><ul><li>May 16 <strong>Event 1: Pharma omics</strong></li><li>September 17 <strong>Event 2: Impurities</strong></li><li>October 23-24 <strong>Event 3: Pharma</strong></li></ul><p><strong>10:00 a.m.–12:00 p.m. CET</strong></p><h3><strong>Event 3: Pharma</strong></h3><p><strong>The pharma connection</strong></p><p>From discovery to QA/QC. All the process to bring a new treatment to the patients is following a path to connect the different stages until the magic happens.</p><p>Join to see how the scientists are generating the needed tricks to connect the initial though with the final formulation.</p><h3><strong>Day 2</strong></h3><h5><strong>10:00 - 10:30&nbsp;- Metabolomics: From target engagement to metabolic phenotyping. Applications in drug discovery</strong></h5><ul><li>Filippos Michopoulos, Astrazeneca</li></ul><h5><strong>10:30 - 11:00&nbsp;- Development of an LC-MS Method to Quantify Endogenous Urea in Mouse Plasma and BAL.</strong></h5><ul><li>Benjamin Smith, Cyprotex</li></ul><h5><strong>11:00 - 11:30&nbsp;- Optimization of extraction &amp; LC-MS conditions for the bioanalysis of antibody drug conjugates with diverse chemistries</strong></h5><ul><li>John Perkins, KCAS</li></ul><h5><strong>11:30 - 12:00&nbsp;- Preparation of rodent whole blood and plasma microsamples for LC-MS/MS bioanalysis in toxicology studies</strong></h5><ul><li>Birgitte Støvring, Scantox</li></ul><blockquote><p><strong>Presenter:</strong> Bruno Manadas, PhD</p></blockquote><blockquote><p>Dr Manadas is a prominent Cell Biology researcher at CNC-UC since 2017. With expertise in biochemistry, psychology, and biotechnology, he's authored 130+ publications and led multiple projects. As head of CNC's Mass Spectrometry node and Associate Editor for Frontiers, he's contributed significantly to neuroscience and psychiatry. Bruno's research focuses on cell biology mechanisms, translational biomarker research, and MS-based approaches for studying protein oxidation. He played a pivotal role in establishing the hospital biobank and teaches at the Portuguese Catholic University.</p></blockquote><blockquote><p><strong>Presenter:</strong> Dorte Bekker-Jensen</p></blockquote><blockquote><p>Dorte is heading the Applications Development team in Proteomics Research at Evosep. She has long-term experience within proteomics and has focused on technology development by developing simple and automated workflows for high-throughput applications.</p></blockquote><blockquote><p><strong>Presenter:</strong> Stefan Ledinger</p></blockquote><blockquote><p>Stefan has 20 years of experience in the life sciences and diagnostic industries. For the last dozen years, he has been serving various functions within biocrates life sciences ag. Most recently, he has been responsible for the market development for metabolomics solutions in the pharmaceutical and biotech industries. He currently serves as Global Head of Sales. Stefan holds degrees in business administration and bioengineering, combining commercial know-how with a passion for science.</p></blockquote><blockquote><p><strong>Presenter:</strong> Markus Langsdorf</p></blockquote><blockquote><p>Markus has 14 years of experience in life sciences industries. As he joined biocrates in 2010, he worked for 11 years as application support specialist for biocrates’ metabolomics profiling solutions. 3 years ago he changed his position withing the company to his new function as product manager. Markus studied chemistry and graduated with a PhD in Analytical Chemistry.</p></blockquote>

Pharma conclave series 2024: Pharma (Day 2)

From discovery to QA/QC. The process to bring a new treatment to the patients.

<p><span lang="EN-US" xml:lang="EN-US" data-scheme-color="@323130,," data-usefontface="false" data-contrast="none"><strong>Automated lab workflows often require many interactions with pre-existing in-house and commercial software systems. This webinar uses the real example of building a purification factory, to give some insights on how this can be done with Mestrelab tools in conjunction with in-house and commercial software.</strong></span></p><div data-aos-delay="0" data-aos-duration="1000"><div><p><span lang="EN-US" xml:lang="EN-US" data-usefontface="false" data-contrast="none">Join us for an insightful webinar where we’ll demonstrate how to integrate Mestrelab’s tools into a complex IT ecosystem to automate lab workflows. Using a real-world example, we'll show you how to build a purification factory that seamlessly connects in-house and commercial software systems.</span></p><p data-ccp-props="{&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559683&quot;:0,&quot;335559685&quot;:0,&quot;335559731&quot;:0,&quot;335559737&quot;:0,&quot;335562764&quot;:2,&quot;335562765&quot;:1,&quot;335562766&quot;:4,&quot;335562767&quot;:10,&quot;335562768&quot;:4,&quot;335562769&quot;:0}"><span data-usefontface="false" data-contrast="none"><strong>Who Should Attend?</strong></span>​</p><ul style="font-weight:400;"><li data-charcodes="8226" data-font="Arial,Sans-Serif" data-buautonum="8" data-aria-posinset="1" data-aria-level="1"><span data-usefontface="false" data-contrast="none"><strong>Lab Managers and Scientists</strong> looking to automate and enhance lab workflows</span>​</li><li data-charcodes="8226" data-font="Arial,Sans-Serif" data-buautonum="8" data-aria-posinset="2" data-aria-level="1"><span data-usefontface="false" data-contrast="none"><strong>IT and Automation Specialists</strong> in life sciences or chemical industries seeking integration solutions</span>​</li><li data-charcodes="8226" data-font="Arial,Sans-Serif" data-buautonum="8" data-aria-posinset="3" data-aria-level="1"><span data-usefontface="false" data-contrast="none"><strong>Anyone interested</strong> in embedding Mestrelab tools into a powerful, scalable IT infrastructure</span></li></ul><blockquote><p><strong>Presenter:</strong> John Hollerton (Senior Scientific Director, Mestrelab Research)</p><p><span data-teams="true" dir="ltr">John has over 40 years of experience in the scientific and informatics fields at GSK and its predecessor companies. He has managed various analytical functions, including NMR, X-ray crystallography, mass spectrometry, physical chemistry, and chromatography, and has expertise in chemical structure representation and registration. In informatics, he led projects to create a global scientific data management system and wrote software for instrument control, data transformation, and analysis. His team developed software to automate LCMS purification factories in the US and UK.&nbsp;</span></p></blockquote></div></div>

Mestrelab: Building a Purification Factory: Embedding Mestrelab Tools into a Rich IT Infrastructure

Building a Purification Factory: Embedding Mestrelab Tools into a Rich IT Infrastructure

We’ll demonstrate how to integrate Mestrelab’s tools into a complex IT ecosystem to automate lab workflows.

Embedding Mestrelab Tools into a Rich IT Infrastructure

<div data-lineheight="1.5"><p><strong>Food analysis is crucial for consumer safety, authenticity, and pollutant detection. Benchmark analytical methods use complex protocols and organic solvents, and more sustainable alternatives are to be sought out. A recent trend in analytical chemistry leverages raw data from experiments (e.g., chromatographic profiles, spectra) as sample fingerprints, analyzed with multivariate tools to predict characteristics (e.g., origin, composition) and identify adulterations. These approaches reduce analyses, lab work, and resource use, offering greener, more cost-effective alternatives.</strong></p><p>The webinar will show how to combine the two aims, sustainability and data maximization, using an aqueous colloidal system, developing AF4-DAD-MALS-dRI-FLD platforms to separate and characterize components from food matrices:</p></div><ul><li data-lineheight="1.5">Red wine profiling and in-depth analysis of output data can highlight particulate complexity, explain sensory feedback, and lead to cultivar grouping.</li><li data-lineheight="1.5">Milk analysis and multivariate elaboration of fractograms enabled single-run discrimination of factors like thermal treatment, fat content, and even the manufacturing plant’s impact on colloidal content.</li></ul><p>These AF4 method are fast, uses minimal sample preparation, avoid chemical treatments, offering a greener, faster and possibly cheaper alternative. The FFF approach can enhance food quality control and fraud detection processes and is adaptable to other colloidal food samples. Additionally, it underscores the need to increase multivariate analysis in data from FFF platforms.</p><h4>Key Learning Objectives:</h4><ul><li data-lineheight="1.5">Tackle native sample handling</li><li data-lineheight="1.5">Understanding data extraction from multidetection profiling</li><li data-lineheight="1.5">Rationalizing multivariate analysis of FFF data</li></ul><h4>Who Should Attend:</h4><ul><li data-lineheight="1.5">Laboratory managers</li><li data-lineheight="1.5">Chromatographers</li><li data-lineheight="1.5">Scientist in the Food &amp; beverage industry</li></ul><blockquote><p><strong>Presenter:</strong> Valentina Marassi, Ph.D. (University of Bologna, byFlow srl)</p><p>Dr. Marassi is Tenure-Track Researcher and Assistant Professor in Analytical Chemistry at the University of Bologna. She graduated with a B.S. in chemistry, a Master’s in Organic Chemistry and completed a PhD in Analytical Chemistry in the same Institution. Her core research involves separation science and profiling-multidetection applied to nano-bio samples, and developing FFF-chemometrics strategies to model and understand colloidal profiles.</p><p><strong>Presenter:</strong> Prof. Andrea Zattoni (University of Bologna, byFlow srl)</p><p>Andrea Zattoni joined the University of Bologna in 2006 and is currently an Associate Professor. He holds an M.S. in Chemistry and a Ph.D. in Chemical Sciences from the University of Bologna with a research focus on separation science. His main research interests include the fundamental and instrumental development of field-flow fractionation and its combination with highly sensitive and selective detection techniques.</p><p><strong>Presenter:</strong> Udayabagya (Bud) Halim (Waters | Wyatt Technology)</p><p>Bud Halim is a senior marketing analyst at Wyatt Technology. He holds a B.S. and Ph.D. in physical chemistry from the UCLA. Bud started his career as an adjunct professor where he taught courses such as Biochem, Analytical, and Physical Chemistr. Prior to joining Wyatt Technology, Bud worked in the scientific instrumentation field as an applications scientist for three years. His experience spans the characterization of batteries, semiconductors, and the stability of biologics, LNPs, and viral vectors.</p></blockquote>

Waters Corporation: Colloidal Fingerprints of Food and Beverages with multidetector AF4-MALS

Colloidal Fingerprints of Food and Beverages with multidetector AF4-MALS

How to combine sustainability and data maximization, using an aqueous colloidal system, developing AF4-DAD-MALS-dRI-FLD platforms.

Fingerprints of Food and Beverages with AF4-MALS

<p><strong>In this webinar, Dr Stuart Best, Deputy Director, Drug Metabolism and Pharmacokinetics (DMPK), Sygnature Ltd, will provide an overview of analytical approaches in Discovery Bioanalysis CNS measurement, to deliver more information from lower sample volume and align with the 3R principles.</strong></p><p><span name="summary">Drug discovery programs that target the Central Nervous System require bioanalytical measurement of test compounds and neurotransmitter concentrations to establish a pharmacokinetic-pharmacodynamic (PK-PD) relationship. Bioanalytical assessment of unbound compounds in blood, brain tissue, and cerebrospinal fluid describes its distribution for the systemic circulation into the CNS. The inherently high sensitivity and specificity of LC-Triple Quadrupole Mass Spectrometry enables low level detection in small sample volumes, allowing serial sampling from single animals, reducing animal use and inter-animal variability, supporting the 3Rs principles (replacement, reduction, refinement)</span></p><p><span name="summary">The bioanalysis of neurotransmitters such acetylcholine and monoamines, is challenging due to low molecular weight, high polarity, instability, and low endogenous concentrations. At Sygnature, the </span><i><span name="summary">in vivo</span></i><span name="summary"> Pharmacology team employ microdialysis to permit assessment of neurotransmitter changes in specific brain regions. The low endogenous concentrations in brain regions and collection through dialysis probe into artificial CSF lowers further quantitation limits for neurotransmitter detection and lead to the requirements for highly sensitive and specific analytical approaches.</span></p><p><span name="summary">This presentation will describe the above approached to CNS measurement and how LC-Triple Quadrupole Mass Spectrometry enables Sygnature scientists to align to the 3R principles and maximize data output from small samples and relate test compound concentrations to neurotransmitter changes. Truly, achieving on the concept of ‘More from Less’ Stuart will also present further refinement models for assessing test compound impact on acetylcholine and enabling more physiologically relevant measurements.</span></p><h4><span name="summary"><strong>Key Learning Objectives:</strong></span></h4><ul><li><span name="summary"><strong fr-original-style="">Understand the challenges as CNS measurements of test compounds and neurotransmitter concentrations to establish PK-PD relationships</strong></span></li><li><span name="summary"><strong fr-original-style="">Explore the complexities of neurotransmitter bioanalysis in discovery DMPK due to low concentrations and instability</strong></span></li><li><span name="summary"><strong fr-original-style="">Learn the roles of LC-Triple Quadrupole Mass Spectrometry enabling sensitive detection in small samples and alignment to the 3Rs (replacement, reduction, refinement) principles</strong></span></li></ul><div><blockquote><p><strong>Presenter:</strong> Dr Stuart Best (Deputy Director, DMPK, Sygnature Ltd)</p><p><span>Dr Best's expertise spans regulated and discovery bioanalysis and discovery DMPK, from supporting DMPK screening (solubility, log D, metabolic stability, permeability, plasma protein binding, etc) through in vivo assessment of compounds to more detailed profiling to support candidate nomination and human dose prediction, including the assessment of potential risk from drug-drug interactions.</span></p><p><span>During his time in the industry Dr Best has expanded the utilisation of mass spectrometry (specifically triple quadrupole LC-MS/MS) to help solve drug discovery project challenges with a strong focus on maximizing data capture from in vivo samples, refining experimental designs to permit better PD endpoints and expanding LC-MS/MS support for biological screening assays, where a mass spectrometry end-point is required, for the measurement of more challenging endogenous analytes.</span></p></blockquote></div>

More from less: LC-MS/MS an Enabling Technology to Maximize Bioanalytical Data Collection from Small Sample Volumes

An overview of analytical approaches in Discovery Bioanalysis CNS measurement, to deliver more information from lower sample volume.

LC-MS/MS to Maximize Bioanalytical Data Collection

<div><div><div><p><strong>MALDI MS is ideally suited to increase productivity with rapid automated measurements. They provide near instant mass verification and information about impurities and degradants, which is valuable in quality control, assay optimization, and verification of substrates. Learn how the novel neofleX™ MALDI-TOF/TOF system&nbsp;enhances these workflows.</strong></p></div></div></div><div><div><div><h5><strong>Key Learning Objectives:</strong></h5><ul><li><strong>Overview of neofleX™ technology and its benefits to life sciences applications</strong></li><li><strong>Rapid automated analysis of a wide range of analytes including oligonucleotides and peptides</strong></li><li><strong>Software solutions for batch mode post-processing of automated runs</strong></li></ul></div></div></div><div><div><div><h5><strong>Who Should Attend:</strong></h5><ul><li>Characterization team leaders in biopharma companies and CROs</li><li>Mass spectrometry core lab managers</li><li>Anyone who is interested in rapid automated MS analysis</li><li>Researchers who would like to learn about the latest MALDI-TOF/TOF technology</li><li>Anyone who is interested in oligonucleotide and peptide analysis</li></ul><div><div><div><div><blockquote><div><p><strong>Presenter:</strong> Sergei Dikler, Ph.D. (Senior Market Manager, MALDI Technologies, Bruker Scientific LLC, Billerica, MA, USA)</p><p>Sergei Dikler, Ph.D., is a Senior Market Manager focused on promoting MALDI technologies. Dr. Dikler received his Ph.D. degree at Texas A&amp;M University. He is an expert in MALDI application development and high-throughput MS</p><p><strong>Presenter:</strong> Sinduri Vuppala, Ph.D. (Field Applications Specialist, Bruker Scientific LLC, Billerica, MA, USA)</p><p>Sinduri Vuppala, Ph.D., is a Field Applications Specialist for non-imaging MALDI applications at Bruker. Dr. Vuppala received her Ph.D., in Analytical Chemistry at the University of South Florida with focus on method development involving MALDI and CCS technologies.</p></div></blockquote></div></div></div></div></div></div></div>

Bruker: Rapid automated analysis using the novel neofleX™ platform

Rapid automated analysis using the novel neofleX™ platform

MALDI MS is ideally suited to increase productivity with rapid automated measurements. 

<p><span data-bind="expander:{'expandText': moreButtonText(), 'userCollapseText': lessButtonText(), 'text':getWebinarInfo().description}"><strong>With an understanding of selectivity, and using a variety of chromatographic data, we discuss phase design principles and how it is possible to introduce functionality to enhance selectivity through different mechanisms such as hydrophobicity, π-π, dipole-dipole and shape selectivity interactions.</strong></span></p><p><span data-bind="expander:{'expandText': moreButtonText(), 'userCollapseText': lessButtonText(), 'text':getWebinarInfo().description}">This webinar is the second part in a three-part series by Gemma Lo, called "A Systematic UHPLC / HPLC Method Development Strategy with Complementary Stationary Phases to Maximize Selectivity and Resolution."</span></p><p><span data-bind="expander:{'expandText': moreButtonText(), 'userCollapseText': lessButtonText(), 'text':getWebinarInfo().description}">Each part is about 20min long.</span></p><p><span data-bind="expander:{'expandText': moreButtonText(), 'userCollapseText': lessButtonText(), 'text':getWebinarInfo().description}"><strong>Presenter:</strong> Gemma Lo</span></p>

MAC MOD Analytical: Utilizing Stationary Phase Design in Method Development

Utilizing Stationary Phase Design in Method Development

We discuss phase design principles and how it is possible to introduce functionality to enhance selectivity through different mechanisms.

<p><strong>This course is designed to introduce those familiar with analytical-scale HPLC to capillary (or “nano”) liquid chromatography. Although both techniques are based on the same fundamental principles, capillary LC delivers a number of distinct advantages with appropriate use.</strong></p><p>Commercial instrument options, as well as the basics of preparing your own capillary LC columns, will be described. Because one of the most prominent uses of capillary LC is its coupling to mass spectrometry for complex biological sample analysis, special attention will be given to this important area. Both academic and industrial researchers will be able to apply the information gained through this course to successfully use this essential technique.</p><p><strong>After completing this course, participants will be able to:</strong></p><ul><li><strong>Understand the differences between analytical and capillary scale LC</strong></li><li><strong>Describe the fundamentals of capillary LC column preparation</strong></li><li><strong>Determine the best detection modes for a given application</strong></li><li><strong>Explain the advantages of coupling capillary LC with mass spectrometry and how to approach method development using capillary LC-MS</strong></li><li><strong>Identify best practices for the use of capillary LC to solve analytical challenges</strong></li></ul><h5>Who Should Attend?</h5><p>Scientists, chemists, analytical researchers, lab directors and managers, VPs and directors of QC/QA, lab owners</p><blockquote><p><strong>Presenter:</strong> Dr. James Grinias (Professor, Department of Chemistry &amp; Biochemistry, Rowan University)</p><p>James Grinias is a Professor in the Department of Chemistry &amp; Biochemistry at Rowan University in Glassboro, New Jersey, USA. Dr. Grinias has a number of research interests focused on chemical separations and microfluidics, both at the fundamental level and for the analysis of biological systems. He is the recipient of the 2021 American Chemical Society Satinder Ahuja Award for Young Investigators in Separation Science and the 2022 LCGC Emerging Leader in Chromatography. At Rowan, he teaches courses in general, analytical, and bioanalytical chemistry while also conducting research on UHPLC column performance and instrument miniaturization.</p><p><strong>Presenter:</strong> Greg Ward (CEO, Axcend)</p><p>Greg Ward serves as the CEO of Axcend, renowned for its portable high-performance liquid chromatography (HPLC) systems. Greg has over 30 years of experience in the technology and scientific instrumentation sectors. Before joining Axcend, Greg held technical and marketing roles at Hewlett Packard and Agilent Technologies. His leadership at Axcend has been pivotal in advancing the development and commercialization of the Axcend Focus LC®, a compact and eco-friendly HPLC system that has revolutionized the field by offering customers portability, ease of use, and reduced operational costs. Axcend has made significant strides in making high-quality chromatographic analysis accessible and convenient for various industries, including pharmaceuticals, environmental monitoring, and chemical manufacturing. Greg’s vision and dedication continue to push the boundaries of scientific analysis, making him a key leader in the field of compact liquid chromatography.</p></blockquote>

Separation Science: Introduction to Compact Liquid Chromatography

Introduction to Compact Liquid Chromatography

This course is designed to introduce those familiar with analytical-scale HPLC to capillary (or “nano”) liquid chromatography. 

<p id="isPasted"><strong>Biotherapeutics offer targeted therapies for treating a wide range of diseases with greater specificity and efficacy. However, unlike traditional small-molecule drugs, biotherapeutics are typically larger and more complex, requiring advanced techniques for their production, purification, and characterization.</strong></p><p>Therapeutic proteins, first introduced many years ago, have continually advanced in complexity. Since the introduction of monoclonal antibodies, we now have antibody drug conjugates, bispecific antibodies, fragments and fusion proteins, all of which are in various stages of development.&nbsp;</p><p>To keep pace with biotherapeutics advances, analytical techniques must also advance.&nbsp;</p><h5><strong>In this webinar, we will present chromatography findings on:</strong></h5><ul><li><strong>New workflows for intact and peptide mapping characterization of proteins</strong></li><li><strong>Advanced column chemistries for charge variant analysis with pH and salt gradients&nbsp;</strong></li><li><strong>Rapid desalting SEC column for high throughput analysis, ADC analysis with HIC and reversed phase chemistries</strong></li><li><strong>New digestion workflows coupled to a new peptide mapping column for sequence verification and post translation modification analysis</strong></li></ul><p>This live webinar will be an excellent opportunity to boost your R&amp;D capabilities and strengthen your QC analytical methods for the characterization of biotherapeutics and gene therapies. Dr. Ken Cook will be presenting and answering your questions live.</p><p>With over 20 years of innovation, Thermo Fisher Scientific is a leader in biomolecule separation and characterization, supported by a wealth of published research.</p><p id="isPasted"><strong fr-original-style="">Who should attend?&nbsp;</strong></p><ul><li><strong fr-original-style="">Pharmaceutical and Biotech Researchers</strong>: Researchers involved in the development and characterization of biotherapeutics and gene therapies, including those working with therapeutic proteins.</li><li><strong fr-original-style="">Quality Control (QC) Analysts</strong>: Analysts responsible for ensuring the quality and consistency of biotherapeutic products, who will benefit from advanced methods in characterization and validation.</li><li>&nbsp;<strong fr-original-style="">R&amp;D Managers</strong>: Managers who oversee research and development teams working with biotherapeutics, looking to enhance their workflows and methodologies.</li></ul><blockquote><p><strong>Presenter:</strong> Dr. Ken Cook (Application Scientists Manager, Thermo Fisher Scientific)</p><p>Dr. Ken Cook began his career in academia as a Biochemistry lecturer focused on protein chemistry and metabolism. With over 30 years of industry experience at Dionex, and later Thermo Fisher Scientific, his vast knowledge supporting and developing solutions within chromatography has established him as a bio-separations expert.</p><p>Currently, Dr. Cook focuses on supporting and developing solutions for bio-pharmaceutical applications, particularly in the characterization of protein and oligonucleotide-based biotherapeutics. His work involves ongoing collaborations with both the biopharmaceutical industry and academic institutions.</p><p>His expertise includes peptide mapping using LC/HRMS, charged variant analysis with novel MS coupling, glycan analysis, aggregate analysis, and on-line process monitoring. He also has a growing interest and notable success in gene therapy characterization.</p><p>Given his immense experience, it is an honour to have Dr Cook share his knowledge.</p></blockquote>

Thermo Fisher Scientific: Innovations in Protein Characterization

Innovations in Protein Characterization

Boost your R&D capabilities and strengthen your QC analytical methods for the characterization of biotherapeutics and gene therapies.

<h5><strong>Who Should Attend:</strong></h5><ul><li>Any HPLC scientists beginning with method development&nbsp;or working with small molecules in pharmaceutical labs &nbsp;</li></ul><h5><strong>Key Learning Points:</strong></h5><ul><li><strong>Learn about selectivity benefits of phenyl phases during reversed-phase HPLC</strong></li><li><strong>Review mobile-phase optimization when using a phenyl column</strong></li><li><strong>Examine a thorough comparison of different phenyl phases with a C18 phase</strong></li></ul><blockquote><p><strong>Presenter:</strong> Zachary Woodward (Senior Technical Specialist, Phenomenex)</p><p>Zachary Woodward is a Senior Technical Specialist with Phenomenex, Inc, assisting laboratories with method development in the bio-pharma, environmental, and food industries. &nbsp;Zachary spent his formative years developing HPLC and GC methods with a pharmaceutical lab in Albany, NY, after which he developed HPLC and SPE methods in the clinical setting here in Southern California. &nbsp;Zachary received his B.Sci. in Chemistry from the College of William and Mary, was awarded his Master’s in Chemistry at San Diego State University, and is happy to speak with you today!</p></blockquote>

How to Choose a Phenyl Phase

Learn about selectivity benefits of phenyl phases during reversed-phase HPLC. Review mobile-phase optimization when using a phenyl column.

<p><strong>Join us as we dive into a common challenge faced by research facilities: managing the ever-growing mountain of measurement data. As a facility manager, you’re all too familiar with the constant juggling act of handling sample submissions, data collection, and distribution—all while trying to keep your workflows efficient and your focus on the science.</strong></p><p>In today’s data-driven landscape, adhering to the <strong>FAIR principles</strong>—making your data Findable, Accessible, Interoperable, and Reusable—is not just a best practice but a growing requirement for securing public funding. Funding bodies are increasingly looking for research facilities to demonstrate that their data management processes align with these principles.</p><p>That’s why we’re excited to introduce you to <strong>LOGS </strong>for Facilities, our comprehensive software solution tailored specifically for research facilities like yours. Supported by the powerful automation engine Mnova Gears, LOGS streamlines your entire workflow—from sample submission and automatic data processing to data distribution—into a single, seamless platform that adheres to the FAIR principles.</p><p>In today’s session, we’ll explore how LOGS can simplify your data management processes, helping you save time, reduce errors, and get back to what matters most: <strong>advancing your research by making your data findable - wherever you are.</strong></p><blockquote><p><strong>Presenter:</strong> Peter Bellstedt, PhD (Director of Business Development and Product Manager)</p><p>Peter studied Biochemistry at the University of Jena before completing a PhD on the structural characterization of a DNA repair protein using solution and solid-state NMR. He was then appointed as the head of the NMR Spectroscopy Platform in Jena, Germany, where he pioneered the implementation of modern, highly efficient data-driven workflows. After five years, he moved to the University of Zurich, Switzerland, as a principal investigator, where his lab focused on structure-based drug discovery. This year, he brought his wealth of experience to the LOGS by SciY team, focusing on efficient workflow solutions for research labs and facilities on a global scale.</p></blockquote>

Mestrelab Research: Integrating Measurement Requests, Data Collection, and Data Distribution in One Platform

Integrating Measurement Requests, Data Collection, and Data Distribution in One Platform

In today’s session, we’ll explore how LOGS can simplify your data management processes, helping you save time