<p><strong>🎤Dr. Steven Weinman </strong>(Associate Professor of Chemical and Biological Engineering at the University of Alabama)</p><p><strong>Steven shares his journey from chemical engineering student to membrane researcher, and explains how membranes are used not only for water purification, but also for sample preparation, pre-treatment, and concentration in analytical workflows. The conversation dives deep into PFAS removal, nanofiltration vs. reverse osmosis, and how chromatography and mass spectrometry are essential for validating membrane performance.</strong></p><h4><strong>Key topics discussed include:</strong></h4><ul><li>How membranes function as separation and concentration tools</li><li>Nanofiltration vs. reverse osmosis for salts and PFAS</li><li>The role of chromatography (LC-MS, GC-MS, ion chromatography) in verifying contaminant removal</li><li>Challenges in scaling academic separation technologies to industry</li><li>Sustainability in membrane manufacturing and PFAS-related regulations</li><li>Training students to balance fundamental science with real-world applications</li></ul><p>Whether you work in environmental analysis, chromatography, mass spectrometry, water quality, or separation science, this episode provides valuable insight into how different separation technologies complement each other—and where the field is heading next.</p><h3><strong>Video Transcription</strong></h3><h4><strong>Introduction</strong></h4><p>Membrane-based separations have become a central part of modern water treatment and resource recovery, offering energy-efficient routes for purification, concentration, and selective contaminant removal. In this discussion, Stephen reflects on his path into chemical engineering and membrane science, then explores how membrane technologies fit within broader separation science, how selectivity is designed into membrane systems, and why translation from academic research to industrial deployment remains challenging.</p><p>His perspective spans both fundamental membrane science and practical engineering, with particular emphasis on water treatment, contaminant removal, sustainable membrane manufacturing, and the realities of research funding and scale-up.</p><h4><strong>From Chemical Engineering to Membrane Research</strong></h4><p>Stephen’s route into membrane science began indirectly. Although his early interests were far removed from chemical engineering, he found himself drawn to chemistry and mathematics during high school, which led him to pursue chemical engineering at the University of Kentucky. His first direct exposure to research came through a cooperative placement with a university-affiliated research institute, where he worked on ceramic membrane systems for coal-fired power plant applications.</p><p>That experience introduced him to bench-scale research, scientific literature, and technical presentation, while also clarifying that research was more appealing to him than traditional industrial internships. He subsequently joined the laboratory of a membrane scientist at the University of Kentucky, where he began working on polymeric membranes for water treatment. This set the direction for graduate study, ultimately leading him to Clemson University, where he pursued PhD research on antifouling membranes using surface chemistry and patterning approaches.</p><p>Although his original career plan had been to join a membrane company after graduate school, that trajectory changed late in his doctoral training. Encouragement from colleagues and family led him to consider academia, where he could define his own research questions and continue mentoring students. He joined the University of Alabama immediately after graduation and has since built a research program focused on water treatment problems using membranes, solvents, and polymer-based sorbents.</p><h4><strong>Membrane Separation in the Broader Context of Analytical and Separation Science</strong></h4><p>Stephen frames membranes as one tool within a broader separation science landscape. Their role depends entirely on the feed composition, the desired product stream, and the ultimate process objective. In some cases, membranes are ideal for concentrating target species or dewatering mixtures. In others, they serve as pretreatment tools, removing particulates, unwanted macromolecules, or selected contaminants before downstream analytical or processing steps.</p><p>This logic parallels broader analytical workflows, including chromatographic and spectrometric methods, where sample preparation and matrix simplification are often critical. Even very routine laboratory operations, such as syringe filtration, rely on membrane principles. In that sense, membranes are already embedded in many analytical workflows, even when they are not the primary focus.</p><p>He also points out that certain membrane-based systems can begin to overlap conceptually with chromatographic approaches, particularly in applications such as protein and biologics purification, where membrane adsorbers and membrane chromatography can provide high-throughput alternatives to conventional packed columns.</p><h4><strong>Membrane Selectivity: Matching the Separation to the Problem</strong></h4><p>A recurring theme in the discussion is that membrane selection is application-specific. The right membrane depends on what must be retained, what must pass through, and whether the goal is purification, concentration, or fractionation.</p><p>Stephen distinguishes between several broad classes of membranes. Microfiltration and ultrafiltration operate largely through size exclusion, although charge effects may still contribute. These are useful when target species differ sufficiently in size. At the more selective end, nanofiltration and reverse osmosis are used for salts, small molecules, and persistent contaminants. Nanofiltration is often well suited for rejecting divalent ions while allowing more monovalent ions to pass, whereas reverse osmosis is required when more complete salt rejection is necessary.</p><p>For contaminants such as PFAS, nanofiltration can reject a substantial fraction of compounds, although shorter-chain and smaller species are more difficult. Reverse osmosis offers broader rejection, but also with higher pressure requirements. This highlights a central engineering tradeoff: tighter selectivity generally requires higher energy input.</p><p>He emphasizes that membrane systems always produce at least two streams: a permeate stream and a retentate or concentrate stream. Designing the separation therefore requires consideration not only of product quality but also of what happens to the reject stream. In many cases this becomes a waste stream; in others, it may represent a concentrated resource that requires additional processing or recovery.</p><h4><strong>Advances in Membrane Materials and System Performance</strong></h4><p>Over the course of more than a decade in membrane science, Stephen has seen important improvements in commercial membrane technology, particularly in the area of lower-pressure reverse osmosis. Traditionally, reverse osmosis has required higher operating pressures than nanofiltration. Recent developments have reduced that burden, allowing similar water productivity at lower pressure or smaller membrane area for a given throughput.</p><p>These advances matter because they reduce either energy demand or plant footprint, both of which are significant in industrial and municipal treatment systems. While pressure recovery devices have also improved overall system efficiency, he distinguishes those engineering gains from the membrane materials themselves.</p><p>On the research side, he highlights the emergence of membrane adsorbers and related hybrid technologies that can support faster, higher-throughput separations than conventional column-based workflows. These have gained particular traction in the purification of proteins and biologics, although he suggests that similar concepts may become increasingly relevant in water treatment and selective ion or molecule recovery.</p><h4><strong>Chromatography and Mass Spectrometry as Tools for Membrane Research</strong></h4><p>Although many membrane processes target relatively simple separations such as desalination, more advanced membrane studies increasingly rely on analytical chemistry for validation and mechanistic insight. Stephen describes how chromatographic and mass spectrometric methods are essential when the separation targets are more complex than salts.</p><p>His group uses ion chromatography for specific ionic analytes, as well as GC-MS and electrospray-based methods for organic compounds and degradation products. One recent example involved a biocatalytic membrane designed to degrade phthalates, where GC-MS was used to detect both the parent phthalate and the resulting breakdown products. In such cases, analytical methods are not merely confirmatory; they are central to demonstrating that the membrane or membrane-coupled system is functioning as intended.</p><p>This reinforces the idea that membrane science and analytical chemistry are closely linked in emerging applications, especially where contaminant transformation, trace-level detection, or selective removal must be verified rigorously.</p><h4><strong>The Difficulty of Scale-Up</strong></h4><p>One of the most substantial barriers in membrane research is translation from academic bench-scale work to industrial or municipal scale. Stephen identifies two major constraints: time and cost.</p><p>Academic demonstrations often rely on reaction steps, modification procedures, or fabrication methods that work well on the laboratory scale but are far too slow for industrial practice. A protocol that takes hours or days in a research setting is rarely attractive to a manufacturer seeking cycle times measured in seconds or minutes. Likewise, materials that seem acceptable at gram scale may be prohibitively expensive at production scale, although the reverse may also be true if bulk pricing is favorable.</p><p>The more fundamental challenge is that academic research is not usually funded to perform pilot-scale development. The mission is often centered on fundamental science and student training, not industrial process engineering. Moving from proof-of-concept to deployable technology requires time, equipment, space, and funding that many university laboratories simply do not have.</p><p>For this reason, Stephen sees academia’s main role as laying the conceptual and technical groundwork. If a technology shows promise, the ideal outcome is that an industrial partner, start-up, or other translational pathway takes it further. In some cases, research can be designed from the start with scalability in mind. He cites current work on reverse osmosis membrane additives as an example, where the goal is not to reinvent membrane fabrication but to introduce a change that could plausibly fit existing manufacturing workflows.</p><h4><strong>Sustainability and Greener Membrane Science</strong></h4><p>Membrane processes themselves are often relatively energy efficient compared with thermal separations, but Stephen notes that membrane manufacturing still has significant room for improvement. Conventional membrane fabrication often relies on hazardous, petroleum-derived solvents, and one area of active research is the substitution of greener or bio-based alternatives.</p><p>Another direction is the use of waste plastics as feedstock for membrane fabrication. The rationale is pragmatic: if such plastics are already present in the environment, converting them into membranes may extend their useful lifetime and partially offset their environmental burden. More biodegradable or less petroleum-dependent polymers are also attractive, but they must still meet cost and performance requirements.</p><p>He also discusses an important regulatory issue involving polyvinylidene fluoride (PVDF), one of the most widely used membrane polymers. Debate over whether it should be treated as a PFAS-related material could have major implications for membrane manufacturing and use. From his perspective, classifying PVDF in that way would create significant disruption, especially given its central role in current membrane systems.</p><h4><strong>Funding, Student Training, and the Academic Mission</strong></h4><p>The final part of the discussion turns to the academic research environment itself. Stephen emphasizes that the most important responsibility of his laboratory is not simply generating new membrane concepts, but training students and ensuring that they can complete their degrees in a supportive research environment.</p><p>Funding uncertainty directly affects that mission. Reduced proposal success rates make it harder to maintain the number of graduate students needed for a healthy research group. This has implications beyond immediate staffing. Laboratories function best when experienced students train newer members, creating continuity in methods, culture, and technical knowledge. If groups shrink too far, that continuity is lost.</p><p>He views graduate research as both education and work experience. Students are not only learning theory; they are learning how to think as researchers, solve open-ended problems, and contribute to technologies that may eventually benefit industry. From that perspective, sustaining student support is one of the most important parts of maintaining a strong academic research ecosystem.</p><h4><strong>Conclusion</strong></h4><p>Stephen presents membrane science as a field that sits at the intersection of chemical engineering, separation science, and analytical chemistry. Membranes are already deeply integrated into both industrial treatment and laboratory workflows, but their future depends on continued progress in selectivity, sustainability, and manufacturability.</p><p>At the same time, the discussion makes clear that technical performance alone is not enough. For membrane technologies to move from the laboratory to practice, they must be scalable, economically realistic, and supported by strong analytical validation. Academic laboratories can provide the foundational science and early demonstrations, but broader adoption depends on partnerships, funding, and translational effort.</p><p>Perhaps most importantly, the conversation highlights that advances in membrane science are inseparable from the students and researchers who carry them forward. In that sense, the future of separations depends not only on materials and methods, but also on sustaining the people who develop them.</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>

Selective Separations: What Membrane Science Can Teach Chromatographers

<p><strong>This study introduces LCMS-Net, a deep learning model designed for direct analysis of raw LC-HRMS data without the need for manual preprocessing. By modeling spatial features of the data, the approach improves reproducibility and detection performance in untargeted metabolomics workflows.</strong></p><p>LCMS-Net demonstrated improved performance in forensic cause-of-death screening and colon cancer detection, outperforming existing methods while reducing batch effects across instruments. Its simplified architecture and lack of pretraining requirements enable faster and more efficient data analysis, highlighting its potential for routine metabolomics and forensic applications.</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.5c05404"><strong>LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening</strong></a></h4><p>Lisa M. Menacher, Liam J. Ward, Fredrik Heintz, Henrik Green, and Oleg Sysoev*</p><p>Anal. Chem. 2026, 98, 9, 6589–6597</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c05404">https://doi.org/10.1021/acs.analchem.5c05404</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>Metabolomics is the study of all low-molecular-weight substances in a biological specimen. <a href="javascript:void(0);">(1)</a> As this is closely linked to cellular functions and biochemical processes, it offers a comprehensive view of the current physiological state of an organism. This makes metabolomics a promising tool for a broad range of applications, including diagnostics, precision medicine, and toxicology. <a href="javascript:void(0);">(1−3)</a> However, large-scale large-scale liquid chromatography-high resolution mass spectrometry (LC-HRMS) studies are difficult due to the complex and labor-intensive data preprocessing. This typically involves peak picking, peak alignment, gap filling, and normalization, to simplify the data structure, extract biologically relevant features, and improve the interpretability for subsequent analyses. <a href="javascript:void(0);">(4−7)</a> Although tools like XCMS or MZmine offer widely used implementations of this workflow, the preprocessing of LC-HRMS data remains challenging, for a number of reasons: (1) The preprocessing of LC-HRMS data can be time-consuming due to computational constraints for large datasets. <a href="javascript:void(0);">(4,8,9)</a> (2) Domain knowledge is necessary to select suitable parameters for the used preprocessing software, and thus to obtain reliable features. <a href="javascript:void(0);">(4,7,8)</a> (3) The reproducibility of the extracted features is often limited across software libraries, especially for low-abundant metabolites. <a href="javascript:void(0);">(4,8)</a> (4) Preprocessing tools may fail to detect some metabolites entirely, resulting in the loss of potentially important information. <a href="javascript:void(0);">(4)</a></p><p>In the past few years, deep learning models have emerged as promising alternatives to the traditional preprocessing workflow for LC-HRMS data. While many publications in this field have been focused on enhancing a particular step of the preprocessing, such as peak identification or peak alignment, end-to-end deep learning has also gained popularity. <a href="javascript:void(0);">(9,10)</a> In end-to-end deep learning, a model is trained to extract useful information directly from raw data without explicit feature engineering. Often, this is less time-consuming than conventional methods and improves the predictive accuracy of the downstream task. This was demonstrated by Cadow et al., who converted raw MS data from prostate biopsies into pseudoimages through binning. They then applied pretrained deep learning models for image processing to extract feature vectors from the pseudoimages and trained a classifier to discriminate between tumor and healthy cases. <a href="javascript:void(0);">(11)</a> A similar approach was also used by Shen et al. to predict the gestational age of pregnant women. To address data scarcity, they proposed a data augmentation strategy that simulates retention time (RT) drifts during the data acquisition. As a result, several pseudoimages can be produced from a single LC-HRMS sample, which substantially increases the size of the training set. <a href="javascript:void(0);">(12)</a> Furthermore, Wang et al. developed an end-to-end deep learning model to detect esophageal squamous cell carcinoma based on raw LC-HRMS data. By decomposing a sample into multiple tiles instead of just one down-scaled pseudoimage, their approach preserves more details of the raw LC-HRMS data. <a href="javascript:void(0);">(13)</a> Most recently, Deng et al. used an ensemble of pretrained image classification models for lung cancer detection. Their approach enables more robust predictions for multiclass classification tasks. Furthermore, model explainability was addressed through the analysis of contributing factors. <a href="javascript:void(0);">(14)</a> Although, these studies collectively highlight the potential of end-to-end deep learning for metabolomics-based analyses, they also show its limitations. For example, the use of pretrained architectures for image classification may be flawed due to the substantially different topology of LC-HRMS data and natural images. Natural images typically contain hierarchically structured objects with geometrical properties such as size or patterns while objects in LC-HRMS pseudoimages are essentially represented as one-dimensional peaks along the retention time axis and are sharply localized in <i>m</i>/<i>z</i>-value. <a href="javascript:void(0);">(6,15)</a> Existing deep learning methods for metabolomics primarily use 2D-convolutions and thus do not take into account such spatial properties of LC-HRMS data. Consequently, there remains a need for more robust methods that are specifically tailored to LC-HRMS data. This is particularly relevant for real-world applications, where batch effects and diverse study populations are common and difficult to mitigate.</p><p>This study presents LCMS-Net, a fully automated end-to-end deep learning model for the analysis of LC-HRMS data. By directly processing the raw data and taking into account its spatial properties by using 1D-convolutions, LCMS-Net mitigates the need for time-intensive, manual feature engineering and improves the classification performance of downstream tasks. This is demonstrated through comprehensive benchmarking for two different applications, forensic CoD screening and colon cancer detection. To the best of our knowledge, it is the first time end-to-end deep learning is applied to post-mortem metabolomics and in the context of forensic science. Furthermore, LCMS-Net achieves robust results even in the presence of severe batch effects, as shown by training and evaluating the CoD screening model with data from different measurement instruments. Lastly, LCMS-Net does not rely on large pretrained deep learning models, and thus requires less computational resources than previous end-to-end learning approaches for the analysis of LC-HRMS data.</p><h4><strong>Methods</strong></h4><h5><strong>Cause-of-Death Screening Dataset</strong></h5><p>The cause-of-death screening study was approved by the Swedish Ethical Review Authority (Dnr 2019–04530 &amp; Dnr 2025–0249–02). All samples were collected from autopsy cases admitted to the Swedish National Board of Forensic Medicine between July 2017 and December 2024, which had undergone routine toxicological screening via HRMS. Screening was performed from femoral whole blood samples, in accordance with standardized procedures reported previously. <a href="javascript:void(0);">(32)</a> Sample separation was performed using gradient elution on a C18 column (150 mm × 2.1 mm, 1.8 μm; <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1952"><strong>Waters Acquity HSS T3 column</strong></a>, Water Sverige AB, Sweden). MS-data was collected in positive mode and the total acquisition time for each sample was 12 min. Samples admitted between July 2017 and November 2020 were run using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6540+Q-TOF"><strong>Agilent 6540 Q-TOF system</strong></a> in MS-mode only, and samples admitted afterward using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6546+Q-TOF"><strong>Agilent 6546 Q-TOF system</strong></a> with data-dependent acquisition mode (autoMSMS). Aside from these differences in acquisition strategy, source settings and TOF parameters (e.g., gas temperatures, voltages, and mass ranges) were kept consistent between platforms. Henceforth, we will refer to the former as <i>Dataset A</i> and the latter as <i>Dataset B</i> for clarity.</p><p>Dataset A was primarily used for the implementation and evaluation of LCMS-Net and includes 4282 autopsy cases processed in over 641 analytical runs. All cases belong to one of the following five CoD groups: acidosis (<i>n</i> = 100), drug intoxication (<i>n</i> = 1385), ischemic heart disease (IHD) (<i>n</i> = 1362), hanging (<i>n</i> = 1200), and pneumonia (<i>n</i> = 235). A detail summary of the inclusion criteria and study population was previously described by Ward et al. <a href="javascript:void(0);">(26)</a> Dataset B was used to evaluate the sensitivity of LCMS-Net to batch effects and includes additional 5485 autopsy cases with the same inclusion criteria and CoD groups as Dataset A.</p><h4><strong>Overview of LCMS-Net</strong></h4><p>LCMS-Net is a end-to-end deep learning model for the analysis of raw LC-HRMS data. First, a data preparation pipeline transforms the raw LC-HRMS data into pseudoimages. Afterward, convolutional neural networks (CNNs) specifically designed to take the spatial properties of LC-HRMS data into account are used to extract relevant features for the downstream task. <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05404#fig1">Figure 1</a> shows an overview of this workflow for CoD screening, as well as the architecture of LCMS-Net.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_9_6589_6597_Figure_1_Overview_of_LCMS_Net_applied_to_Co_D_screening_6db285c40d.jpg" alt="Anal. Chem. 2026, 98, 9, 6589–6597: Figure 1. Overview of LCMS-Net applied to CoD screening. Binning is used to reduce the size of the raw LC-HRMS data and to ensure equally shaped input matrices. Afterward, the input matrices are processed by an ensemble of 1D-CNNs consisting of a depthwise 1D convolutional layer, followed by max pooling and spatial dropout. The results of the CNNs are flattened and dense layers are used to predict the class labels of the input data." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_9_6589_6597_Figure_1_Overview_of_LCMS_Net_applied_to_Co_D_screening_6db285c40d.jpg 238w," sizes="100vw" width="1500" height="986"></p><h4><strong>Results and Discussion</strong></h4><h5><strong>Evaluation of Prediction Performance for CoD Screening</strong></h5><p>First, LCMS-Net was evaluated on the CoD screening dataset (Dataset A). <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05404#fig2">Figure 2</a> shows the results of the model comparison for the CoD screening dataset. With an average accuracy of 70.8%, LCMS-Net outperformed all four benchmark models trained on preprocessed LC-HRMS data. In comparison, our previously published OPLS-DA model for CoD screening achieved only 65.0% accuracy (<i>p</i>-value = 0.0010). Furthermore, LCMS-Net also achieved a better F1-score and sensitivity than these models, while maintaining a high specificity score. The deep learning benchmark model, DeepMSProfiler, achieved a similar accuracy to LCMS-Net. However, LCMS-Net outperformed DeepMSProfiler in terms of both F1-score (<i>p</i>-value = 0.0122) and sensitivity (<i>p</i>-value = 0.0010). This indicates that our method maintains a better balance between true positives and false positives across the five CoD groups, which is especially important for high-stakes applications like forensic science. It should be noted that traditional cross-validation was used for the estimation of p-values, as our purpose was to compare models with fixed hyperparameters. When instead comparing frameworks (e.g., RF vs SVM), nested cross-validation would be more appropriate.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_9_6589_6597_Figure_2_Evaluation_of_Co_D_screening_prediction_performance_of_LCMS_Net_in_comparison_to_benchmark_models_11eef68bb7.jpg" alt="Anal. Chem. 2026, 98, 9, 6589–6597: Figure 2. Evaluation of CoD screening prediction performance of LCMS-Net in comparison to benchmark models. The prediction performance of a classifier is measured by accuracy, macro F1-score, macro sensitivity, and macro specificity over five model runs. The error bars represent the standard deviations between model runs." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_9_6589_6597_Figure_2_Evaluation_of_Co_D_screening_prediction_performance_of_LCMS_Net_in_comparison_to_benchmark_models_11eef68bb7.jpg 245w," sizes="100vw" width="1500" height="709"></p><p>Notably, LCMS-Net achieves its high classification performance without pretraining on natural images. This shows that although transfer learning is often useful, it may fail if the source (e.g., natural images) and target data distribution (e.g., LC-HRMS data) are too different. Such domain mismatch can lead to negative transfer, where features from a pretrained model negatively impact the classification performance of the downstream task, resulting in a lower accuracy than training a simpler model from scratch. <a href="javascript:void(0);">(42)</a> By employing an architecture tailored to LC-HRMS data, LCMS-Net is also computationally more efficient, with fewer than 500,000 trainable parameters compared to over 7 million trainable parameters in DeepMSProfiler. <a href="javascript:void(0);">(14)</a> This makes our method accessible to researchers with limited computational resources.</p><h5><strong>Application for Colon Cancer Detection</strong></h5><p>Lastly, we have tested the potential of LCMS-Net in another application domain, by assessing its prediction performance on the CRC dataset. The cancer detection task has been previously used by Deng et al. to show that DeepMSProfiler can be successfully applied to different application areas, making it a suitable benchmark task. We trained a separate instance of LCMS-Net for the model evaluation on the CRC dataset due to differences in sample preparation, analytical protocols, and instrument setup compared to the CoD screening dataset. The hyperparameter settings remained unchanged, as we assumed similar structural properties for both datasets.</p><p>LCMS-Net outperforms DeepMSProfiler with an F1-score of 97.3% compared to 95.5% on the colon cancer detection task. Furthermore, sensitivity and specificity improvements of 2.8% were observed. These results underline the relevance of LCMS-Net for other application areas than CoD screening. A detailed overview of the evaluation metrics for the colon cancer prediction can be found in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c05404/suppl_file/ac5c05404_si_001.pdf">Supporting Table 7</a>.</p><h4><strong>Conclusion</strong></h4><p>Current preprocessing workflows for untargeted metabolomics are often time-consuming, require extensive domain knowledge, lack reproducibility, or fail to detect some metabolites entirely. LCMS-Net offers an alternative end-to-end approach by operating directly on the raw LC-HRMS data and explicitly modeling its spatial properties. The deep learning model enables faster processing and does not require manual parameter selection. Furthermore, it has been shown through two case studies, CoD screening and cancer detection, that our method extracts a higher amount of relevant information from the raw data and thus outperforms existing models for the analysis of metabolomics data. Specifically, LCMS-Net achieves an average F1-score of 65.5% for CoD screening and 97.3% for colon cancer detection. The previous state-of-the-art models achieved 56.1% (OPLS-DA) and 95.5% (DeepMSProfiler) respectively. The prediction performance of LCMS-Net is consistent even when applied to data from different measurement instruments than those used for the training of the deep learning model, showing its robustness toward batch effects. However, the interpretability of LCMS-Net remains limited and future development is needed to assess which metabolites are learned by the model and which remain undetected. Despite this, LCMS-Net opens up new opportunities for large-scale analyses of LC-HRMS data, potentially driving innovation across numerous application domains.</p></div>

LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening

<p><strong>In the week of April 20, 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. Metrohm: Copper deposition baths: Advanced analytical solutions for development and monitoring</strong></h5><ul><li>Tu, 21.4.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6123">Registration</a></li></ul><p>Discover a multi-method approach to copper plating bath analysis combining titration, CVS, XRF, and pH measurement for improved process control, data reliability, and production quality.</p><h5><strong>2. Bruker: Exploring the Caenorhabditis elegans lipidome in 4D</strong></h5><ul><li>Tu, 21.4.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6106">Registration</a></li></ul><p>Combining chromatography, trapped ion mobility, accurate mass and fragment information enables confident discovery and annotation of novel lipids in this key model organism.</p><h5><strong>3. Technology Networks: Episode 3: PFAS in Food – Addressing Contamination in the Food Supply Chain</strong></h5><ul><li>Tu, 21.4.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6108">Registration</a></li></ul><p>PFAS contamination in food is an emerging analytical and regulatory challenge, especially as testing expands beyond water into complex food and animal protein matrices.</p><h5><strong>4. Agilent Technologies: Getting the Most from Your Agilent LCMS System</strong></h5><ul><li>Tu, 21.4.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5740">Registration</a></li></ul><p>In this webinar, we will discuss best practices and preventative maintenance tips to help maximize your instrument’s uptime.</p><h5><strong>5. Thermo Fisher Scientific: Mass spectrometry strategies to power drug discovery</strong></h5><ul><li>Tu, 21.4.2026 19:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6097">Registration</a></li></ul><p>In this first master class session, explore how advanced mass spectrometry strategies are powering the next generation of drug discovery through chemoproteomics.</p><h5><strong>6. SCIEX: PFAS first steps: A roundtable for new analysts</strong></h5><ul><li>We, 22.4.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6103">Registration</a></li></ul><p>PFAS roundtable webinar for new analysts covering troubleshooting, workflow optimization, and regulatory readiness with expert insights from LC-MS specialists and industry professionals.</p><h5><strong>7. SelectScience: What’s in your hydrogen? Analytical toolkits for fuel purity analysis</strong></h5><ul><li>We, 22.4.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6055">Registration</a></li></ul><p>Join this dual-session webinar on hydrogen impurity testing and ISO 14687 fuel quality. Learn how GC, GC-MS, IC, and FTIR workflows support safe, compliant hydrogen production and fuel-cell applications.</p><h5><strong>8. Separation Science: Testing PFAS in Biosolids: From Sample Preparation to Interference Separation</strong></h5><ul><li>We, 22.4.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6124">Registration</a></li></ul><p>Learn how robust analytical approaches can deliver confident results, even in the most challenging wastewater and biosolid samples.</p><h5><strong>9. Thermo Fisher Scientific: Automated direct mRNA sequence mapping using online partial RNase T1 digestion and 2D LC-MS</strong></h5><ul><li>We, 22.4.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6110">Registration</a></li></ul><p>This webinar highlights a fully automated 2D LC-MS workflow for rapid, high-coverage mRNA characterization.</p><h5><strong>10. SCIEX: Unlocking SCIEX OS software: automating acquisition, analysis, and 21 CFR part 11 compliance reporting</strong></h5><ul><li>We, 22.4.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6125">Registration</a></li></ul><p>Join us to discover how the powerful capabilities of SCIEX OS Software help laboratories improve efficiency, reduce manual steps, and maintain data integrity.</p><h5><strong>11. Thermo Fisher Scientific: From experts to applications: Screening protein-drug interactions with HT-PELSA</strong></h5><ul><li>We, 22.4.2026 19:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6098">Registration</a></li></ul><p>Part 2 of the Chemoproteomics Master Class explores HT-PELSA with Orbitrap Astral MS, showing peptide-level ligand binding analysis for target discovery, specificity, and drug pipeline insights.</p><h5><strong>12. Agilent Technologies: Pesticide Residues &amp; Fumigants Edition</strong></h5><ul><li>Th, 23.4.2026 08:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5955">Registration</a></li></ul><p>Food Safety Webinar Series – Part 2: Pesticide Residues &amp; Fumigants Edition. Explore LC-MS/MS and GC-MS/MS workflows, QuEChERS extraction, and regulatory reporting under Codex and EU frameworks.</p><h5><strong>13. Agilent Technologies: Enhancing Peptide and Oligonucleotide Analysis with Ultra Inert HPLC Technology</strong></h5><ul><li>Th, 23.4.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6134">Registration</a></li></ul><p>Learn how ultra-inert HPLC columns improve LC analysis of peptides and oligonucleotides by minimizing metal interactions and enhancing peak shape, sensitivity, and reproducibility.</p><h5><strong>14. Thermo Fisher Scientific: Chromeleon Admin Console III: Data management and automation</strong></h5><ul><li>Th, 23.4.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6126">Registration</a></li></ul><p>In this practical session, we’ll dive into more Administration Console capabilities that help you manage and standardize your setup at scale.</p><h5><strong>15. Waters Corporation: Informatics series #31 Empower Advanced Custom Fields - Examples</strong></h5><ul><li>Th, 23.4.2026 11:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5923">Registration</a></li></ul><p>Learn how to use Advanced Custom Fields in Empower to streamline calculations, improve reporting, and ensure validation-ready, compliant data processing.</p><h5><strong>16. Waters Corporation: A Multi-Residue Approach - Pesticides, Pharmaceuticals, and Personal Care Products</strong></h5><ul><li>Th, 23.4.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6112">Registration</a></li></ul><p>Navigating challenges and opportunities for environmental testing labs under the revised EU Water Framework Directive.</p><h5><strong>17. Waters Corporation: Analysis of Glyphosate, Glyphosinate and AMPA in water without the need of derivatisation</strong></h5><ul><li>Th, 23.4.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5926">Registration</a></li></ul><p>Learn about required method conditions and instrumentation for Glyphosate, Glyphosinate and AMPA analysis in water without the need of derivatisation.</p><h5><strong>18. Thermo Fisher Scientific: Insights from an IC specialist: Are you using the right eluent?</strong></h5><ul><li>Th, 23.4.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6127">Registration</a></li></ul><p>Join the IC Ask the Experts session to learn practical eluent management strategies, optimize ion chromatography workflows, and get answers to your real-world analytical challenges.</p><h5><strong>19. Waters Corporation: Managing Process Performance in Stage 3 Process Validation: Regulatory Expectations for Continued Process Verification</strong></h5><ul><li>Th, 23.4.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6060">Registration</a></li></ul><p>Join this webinar to gain practical insights into regulatory expectations for CPV and strengthen your approach to maintaining process performance throughout the product lifecycle.</p><h5><strong>20. Thermo Fisher Scientific: High-throughput activity based protein profiling - Systematic mapping of covalent drug-protein interactions on a proteome-wide scale</strong></h5><ul><li>Th, 23.4.2026 19:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6099">Registration</a></li></ul><p>Part 3 of the Chemoproteomics Master Class highlights activity-based proteome profiling and covalent screening to accelerate target identification and drug discovery using scalable MS workflows.</p><h5><strong>21. Agilent Technologies: Advancing and Characterizing Next-Gen Antibody Conjugates: Insights from BBB-Targeting Antibody Platforms</strong></h5><ul><li>Fr, 24.4.2026 08:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6128">Registration</a></li></ul><p>Discover next-generation antibody therapeutics, BBB-targeting platforms, and LC-QTOF workflows for advanced characterization of complex antibody-drug and oligonucleotide conjugates.</p>

Webinars LabRulezLCMS Week 17/2026

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

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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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Agilent Technologies

Phenomenex

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Waters Corporation

<p><strong>Titration is one of the oldest analytical techniques used in the chemical laboratory. Arguably, that is the main reason why so many titrations are performed manually to this day - with all the challenges involved: difficulties to accurately dose the reagent and register the reaction endpoint, poor reproducibility of results, handling delicate glass burets and toxic reagents - you name it.</strong></p><p>In our educational webinar on November 19, Dr. Christian Haider, Head of Competence Center Titration at Metrohm International Headquarters, will give you best practice guidelines on how to replace your manual titrations by automatic procedures using a photometric or a potentiometric sensor, a digital buret, and a modern titrator.</p><h4><strong>Key learnings of this webinar:</strong></h4><ul><li>Why it makes sense to switch from manual to automatic titrations</li><li>How to convert your manual titration procedures to automatic titrations using a photometric or potentiometric sensor</li><li>How a modern titrator can facilitate the validation of your titration methods</li></ul><h4><strong>Who should attend?</strong></h4><ul><li>Laboratory managers, laboratory technicians and anyone regularly performing manual titrations</li></ul><blockquote><p><strong>Presenter:</strong> Dr. Christian Haider (Head of CC Titration, Metrohm International Headquarters)</p><p>Dr. Christian Haider joined Metrohm International Headquarters in 2002 where he started as an Application Specialist Titration. He advanced his career to become Head of Competence Center Titration and this position leads a team of Product Managers, Product Specialists, and Application Chemists for all the different titration techniques, pH and conductivity measurement, titration automation, and software.</p></blockquote>

Metrohm: Best Practice: How to Convert from Manual to Automatic Titration

Best Practice: How to Convert from Manual to Automatic Titration

Make the next step towards higher accuracy and better reproducibility of your titration results.

How to Convert from Manual to Automatic Titration

<div><h4><strong>Elevate Your DLS Knowledge</strong></h4><p><strong>Join us for the last 2 series on DLS and Dynamics! Optimize formulation development and understand particle concentration like never before.</strong></p><p>A focused 4-part series on advanced dynamic light scattering techniques for scientists and researchers.</p><h4><strong>Session Highlights:</strong></h4><ul><li><strong>Part 3 of 4: </strong>Cumulants or Regularization? Choosing the Right DLS Analysis<ul><li>Thursday, November 6&nbsp;</li></ul></li><li><h5><strong>Part 4 of 4: DLS Data Interpretation: Pro Tips and What if’s?</strong></h5><ul><li>Thursday, November 20</li></ul></li></ul><h4><strong>Why Attend:</strong></h4><ul><li>Deepen your understanding of DLS &amp; Dynamics.</li><li>Gain actionable insights for your lab.</li><li>Interact with our expert, Dr. Christian Ackerschott.</li></ul><blockquote><p><strong>Hosted by:</strong> Dr. Christian Ackerschott</p><p>Dr. Christian Ackerschott studied Chemistry at the University of Cologne and finished with his diploma thesis in Biochemistry. He completed his studies with the PhD thesis “Characterization of Recombinant Flagelliform Spider Silk Proteins” at the Technische Universität München, where AF4-MALS was used as an essential characterization method.</p><p>Since 2007, Christian works at Wyatt Technology as Application Scientist and is now Head of Customer Service. His tasks also include customer trainings in Dernbach and onsite as well as education and training of the local Field Application Scientists.</p></blockquote></div>

Waters Corporation: Becoming a DLS and Dynamics Expert

Becoming a DLS and Dynamics Expert: Part 4

Wrap up the series with expert tips on interpreting DLS data, troubleshooting unusual results, and improving confidence in dynamic measurements.

<p><strong>Sustainable Aviation Fuels (SAF) are pivotal in reducing the carbon footprint of aviation, with diverse feedstocks and production routes under active development. Fuel quality and stability must be maintained throughout the process to meet ASTM and ICAO specifications and ensure safe engine performance.</strong></p><p>This session will focus on the role of gas chromatography (GC) and liquid chromatography (LC) in assessing SAF composition. Key areas include hydrocarbon profiling, measurement of aromatics, and detection of oxygenates such as FAME that influence fuel behavior. Case examples will show how analytical workflows support feedstock evaluation, refining optimization, and blend certification.</p><p>By linking analytical control to performance and safety, the session demonstrates how chromatography ensures SAF meets the stringent requirements of aviation applications.</p><blockquote><p><strong>Presenter:&nbsp;</strong> Naoto Hashikita (Product Specialist, Agilent Technologies, Japan)</p><p>Naoto joined Agilent in 2018 as a technical sales specialist specializing in GC and GC/MS. He holds a master’s degree from the University of Tokyo in the field of fuel cells. He has supported customers in the energy and chemical industries, with a focus on promoting green analytical solutions. His motto is: "Contributing to a carbon-neutral society through analytical instruments."</p></blockquote>

Agilent Technologies: Energy Transition Webinar Series

Sustainable Aviation Fuels: Path to Greener Skies

Webinar on Agilent GC/LC for Sustainable Aviation Fuels—analyze composition, certify blends, and ensure compliance with ASTM and ICAO standards.

<div><h4><strong>Strategies to Reduce Risk When Performing LC Method Adjustments</strong></h4><p>As laboratories face evolving materials, instrumentation, and regulatory expectations, understanding the circumstances that justify changing methods is essential. This is especially relevant as more methods are developed on higher performing UHPLC instruments and high-efficiency, sub-2-µm particle columns. These UHPLC methods are suitable for many systems, however, method adjustment may be needed to perform the analysis on HPLC systems. While there are guidelines for performing method adjustments, additional factors, including instrumentation, can impact the performance of the scaled method.</p><p>This three-part webinar series on analytical method adjustment in pharmaceutical analysis is designed to provide practical insights into when and how to adapt validated analytical methods.</p><h5><strong>Topics include:</strong></h5><ul><li>How to assess risk when performing method adjustments and identify some control strategies for more common method and instrument contributors</li><li>How to adapt an analytical method, focusing on the impact of LC instrument characteristics and their impact on scaling from UHPLC to HPLC Columns</li><li>Practical tips and strategies to consider when adjusting LC methods across a variety of instruments</li></ul><p>This series is ideal for analysts, QA professionals, and method developers seeking actionable guidance rooted in real-world lab experience.</p><h4><strong>Session 3: Impact of Instrument Design and Considerations for Implementing Method Adjustment Across Different LC Systems</strong></h4><p>This session will focus on the practical challenges of implementing methods on different types of LC systems across vendors. Attendees will gain an understanding of instrument design differences and their influence on method adjustment. Real-world examples will be shown, illustrating strategies to overcome some of the more common challenges in adjusting methods with a particular focus on controlling for instrument design differences.</p><blockquote><p><strong>Presenter:</strong> Andrew Steere (Evaluation Scientist II, Waters Corporation)</p><p>Andrew Steere is an Evaluation Scientist II at Waters Corporation. He works in the Validation and Competitive Analysis Group within the LC-MS business unit. He graduated from Marist College in 2018 with a degree in Chemistry. Prior to starting at Waters in 2021, he worked in a CRO and primarily focused on LC-TUV/MS and GC-FID/MS instrumentation in cGMP and R&amp;D environments. His current work focuses on evaluating the performance of LC instrumentation across the market through application development and testing.</p></blockquote></div>

Waters Corporation: Strategies to Reduce Risk When Performing LC Method Adjustments

Session 3: Impact of Instrument Design and Considerations for Implementing Method Adjustment Across Different LC Systems

This session will focus on the practical challenges of implementing methods on different types of LC systems across vendors.

LC Method Transfer: Instrument Design & Adjustments

<div><div container-id="cq-colctrl-lt0" comp-id="A1"><div><p><strong>Imaging flow cytometry (IFC) has emerged as a powerful approach for single extracellular vesicle (EV) characterization, yet its broader adoption has been hindered by challenges in assay standardization and data comparability. Join Dr. Wouter W. Woud, Senior Scientist at ExoVectory, as highlights recent methodological advances addressing these limitations. Building on earlier work that established workflows for direct detection and phenotyping of EVs in unprocessed plasma, current efforts focus on developing rigorous calibration strategies for IFC.</strong></p><p>Recent work has introduced bead-based size calibration and fluorescence intensity standardization, enabling instrument-specific signals to be expressed in quantitative units. These approaches markedly improve reproducibility across different platforms and laboratories, thereby supporting cross-study comparability. Standardized IFC data further provide a framework for quantitative analyses in both fundamental EV research and the quality assessment of vesicle-based therapeutics.</p><p>Together, these methodological advances position IFC as a calibrated, quantitative platform for nanoparticle cytometry, with the potential to accelerate both biomarker discovery and translational applications in extracellular vesicle science.</p><h4><strong>Topics discussed in this webinar will include:</strong></h4><ul><li>Advances in EV assay standardization and data comparability</li><li>Development of calibration strategies for IFC</li><li>Introduction of bead-based standardization methodology for quantitative EV analyses</li></ul><h4><strong>Who should attend?</strong></h4><ul><li>Researchers using IFC who are currently or wish to perform small particle analysis</li><li>Anyone interested in flow cytometry applications and small particle analysis</li></ul><h5><strong>Certificate of attendance</strong></h5><ul><li>If you attend the live webinar, you will automatically receive a certificate of attendance, including a learning outcomes summary, for continuing education purposes.</li><li>If you view the on-demand webinar, you can request a certificate of attendance by emailing editor@selectscience.net.</li></ul><blockquote><p><strong>Presenter: </strong>Dr. Wouter W. Woud (Senior Scientist, ExoVectory)</p><p>Dr. Wouter W. Woud is an expert in nanoparticle flow cytometry, with a particular focus on imaging flow cytometry for the study of extracellular vesicles. Wouter obtained his Ph.D. at the Rotterdam Transplant Institute, Erasmus MC, The Netherlands, where he developed an imaging flow cytometry-based method to detect and characterize single vesicles directly in human plasma. His doctoral thesis, “Fantastic vesicles and how to find them” (2023), outlined best practices for instrument calibration, assay design, and data analysis, helping to establish imaging flow cytometry as a reliable tool for vesicle research.</p><p>During his Ph.D. studies, Dr. Woud demonstrated how imaging flow cytometry can uncover clinically relevant vesicle populations without the need for complex pre-isolation steps. More recently, he helped introduce calibration methods that make results comparable across different instruments, an important step toward standardized, reproducible measurements.</p><p>Currently, Dr. Woud is a Senior Scientist at ExoVectory, a company advancing EV-based therapeutics. There, he leads efforts to apply calibrated imaging flow cytometry for product characterization, ensuring quality, potency, and stability. By bridging academic innovation with industry needs, Dr. Woud is helping move EV science toward real-world therapeutic applications.</p><p><strong>Moderator:</strong> Matilde Marques (Life Sciences Assistant Editor, SelectScience)</p></blockquote></div></div></div>

SelectScience: Size and fluorescence calibrated imaging flow cytometry: From arbitrary to standardized units

Size and fluorescence calibrated imaging flow cytometry: From arbitrary to standardized units

Discover new IFC calibration and standardization methods improving reproducibility and quantitative EV analysis across platforms and labs.

Size and fluorescence calibrated imaging flow cytometry

<h4><strong>Key Learning Points</strong></h4><ul><li>Understand Retention Mechanisms and Stationary Phase Behavior in SEC:</li><li>Evaluate the Effect of Mobile Phase Composition on Retentive Interaction</li><li>Learn how to match column pore size to the molecular weight range of the analytes for optimal resolution.</li><li>Implement Strategies to Extend SEC Column Lifetime</li></ul><h4><strong>Who Should Attend</strong></h4><ul><li>Any Biopharma scientists wo are working with big molecular, protein, mRNA, LNP, or AAV.</li></ul><blockquote><p><strong>Speaker:</strong> Mihir Thakar (Product Manager, Phenomenex)</p><p>Mihir holds a master’s degree in Biotechnology. He has over a decade of experience working with various biopharma companies in the characterization of therapeutic peptides, proteins, and oligonucleotides. He has been associated with Phenomenex for more than 7 years, serving in various functions including as a Business Development Manager for Biologics. At present, he has been working as a Global Product Manager for the biopharma segment.&nbsp;</p><p><strong>Speaker: </strong>Kevin Zhao</p><p>Kevin Zhao is the Senior Technical Specisalist with Phenomenex (A Danaher company), located in Torrance, California, USA and has 5 years of experience in biochemistry research; 4 years Protein/Cancer research with CSULA-City of Hope Cancer Collaborative and over 12 years in Phenomenex. Mr. Zhao is a member of a global Technical Support Team, is providing problem solving, troubleshooting, and applications assistance for customers world-wide in the fields of chromatography (liquid and gas) and sample preparation, and also handling Industries supported include – pharmaceutical and biopharmaceutical, clinical research and clinical toxicology, food safety, environmental, fuels and specialty chemicals. Mr. Zhao received his B.S. in Biology at the California State Polytechnic University, Pomona and earned his M.S. in Biochemistry at California State University, Los Angeles, and also earned a MBA at the University of the Incarnate Word.</p></blockquote>

Phenomenex: Chromatography Modes Explained: Sizing up SEC! 

Chromatography Modes Explained: Sizing up SEC! 

Learn SEC best practices for biopharma: optimize retention, match pore size to analytes, adjust mobile phase, and extend column life with Phenomenex experts.

<p><strong>Have an ion chromatography challenge you can’t solve? Submit it now and join Metrohm’s IC experts for a live Q&amp;A session built around your real-world issues. From PFAS and CIC workflows to baseline stability and uptime, our IC pros will tackle the questions you send in—plus the most common troubleshooting pain points labs face today.</strong></p><h4><strong>How it works:</strong></h4><ol><li>Register and share your toughest IC question in the form.</li><li>We’ll prioritize submissions and prepare practical fixes you can apply immediately.</li><li>Join live for additional Q&amp;A and insider tips.</li></ol><p><strong>Bonus: </strong>Attendees receive Getting Peak Performance Out of Your IC—a practical guide to maintenance intervals, troubleshooting tips, and best practices to keep your system running reliably. <strong>PLUS a certificate of attendance</strong>.</p><h4><strong>What You Can Expect:</strong></h4><ul><li>Get practical solutions to common IC challenges submitted by attendees</li><li>Learn troubleshooting strategies to improve data quality, system stability, and method performance</li><li>Discover best practices for instrument maintenance and workflow efficiency</li><li>Explore tips to maximize uptime and extend instrument lifetime</li></ul><blockquote><p><strong>Presenter: </strong>Jay Gandhi. PhD (Vertical Market Manager, Metrohm USA)</p><p>Dr. Gandhi brings 38+ years of proficiency with virtually all analytical instrumentation and the techniques of Environmental, Petrochemical and Pharmaceutical testing and research. Jay is currently involved with the development of «Total Fluorine» analysis using combustion ion chromatography (CIC). Since 2003, Dr. Gandhi is a non-paid adjunct faculty at University of Houston-Clearlake where he enjoys guiding graduate and post-graduate students in their independent study program.</p><p><strong>Presenter: </strong>Bikash Chouhan, PhD (IC Applications Specialist, Metrohm USA)</p><p>Bikash Chouhan is an Applications Specialist for Ion Chromatography at Metrohm USA. He completed his PhD in Analytical Chemistry from the University of Texas at Arlington (UTA). His area of research during his PhD was in Capillary Scale Ion Chromatography. He has worked as a Post Doc at Department of Chemistry and Biochemistry, UTA and as a Senior Scientist in IC at Eurofins, before joining Metrohm USA. He is currently involved in expanding IC applications to more unique and challenging sample matrices.</p><p><strong>Presenter: </strong>Linx Waclaski (IC Product Manager, Metrohm USA)</p><p>Linx Waclaski is the Product Manager for Ion Chromatography at Metrohm USA, in Riverview, Florida. He has years of experience in multiple chromatographic techniques, including ion chromatography, gas chromatography, liquid chromatography, and mass spectrometry, with extensive experience in R&amp;D and applications development. His chromatography applications experience extends across environmental, food safety, and life sciences industries. He has an M.S. in Forensic Science from Duquesne University.</p><p><strong>Presenter: </strong>Jay Sheffer (IC Product Specialist, Metrohm USA)</p><p>Jay Sheffer is a Product Specialist in Ion Chromatography with Metrohm USA. Jay has a BS in chemistry from Elon University and received his master’s degree in analytical chemistry from Emory University. He has been with Metrohm USA for 10 years starting off as an Applications Specialist focusing on ion chromatography and combustion IC and moving into his current IC Product Specialist role in 2017. Jay has over 20 years of experience in developing new products and applications for laboratory analysis. Jay has also been an active member with ASTM for nine years and has developed several test methods using IC and Combustion IC in the petroleum market.</p></blockquote>

Metrohm: Open Office Hours: Your IC Questions, Answered by the Experts

Open Office Hours: Your IC Questions, Answered by the Experts

Have an ion chromatography challenge you can’t solve? Submit it now and join Metrohm’s IC experts for a live Q&A session

IC Questions, Answered by the Experts

<p><strong>Proper care of your HPLC column is essential for consistent, high-quality results. In this webinar, we will cover best practices to maintain your column in optimal condition. Topics include proper connection techniques, mobile phase considerations, column equilibration, cleaning procedures, and correct storage methods. We will also address some common column related issues and offer troubleshooting strategies to help resolve them. &nbsp;Whether you're working with Reverse Phase, HILIC, SEC, or IEX columns, being aware of your column’s technical specifications and applying careful handling can significantly extend the column’s performance and lifetime and have a lasting impact on your chromatography.</strong></p><blockquote><p><strong>Presenter:&nbsp;</strong> Jean Lane (Application Engineer, Agilent Technologies, Inc.)</p><p>Jean has been employed with Agilent since Nov 2010 in technical and applications support and has a primary role supporting Agilent’s full line of LC columns and consumables, which also includes support for Agilent’s GPC/SEC product line. She came to Agilent thru acquisition of Varian and the former Polymer Laboratories. Jean has 20 plus years of technical and applications support for both HPLC and GPC consumable products. In addition to practical chromatography experience in the laboratory, she has had many, many years in her technical role involving customer support providing assistance and troubleshooting for customer chromatography issues.</p></blockquote>

Agilent Technologies: Best Practices for HPLC Column Care and Maintenance

Best Practices for HPLC Column Care and Maintenance

Join Agilent’s webinar to discover how proper care and handling can extend HPLC column life and improve performance across RP, HILIC, SEC, and IEX methods.

<div><div container-id="cq-colctrl-lt0" comp-id="A1"><div><p><strong>Oligonucleotide therapeutics have emerged as promising drug candidates due to their high specificity in targeting various genetic diseases and disorders. Despite advances in LC-MS, the inherent complexity, charge properties, and susceptibility to degradation make oligonucleotide quantitation in biological matrices particularly challenging. Effective sample preparation is essential to mitigate matrix effects, enhance analyte recovery, and ensure data reproducibility.</strong></p><p>This seminar will discuss practical sample preparation strategies to improve matrix cleanup and extraction efficiency for oligonucleotides bioanalysis. We will demonstrate how these strategies achieve consistent recovery and strengthen overall method robustness.</p><h5><strong>By attending this webinar, you will learn:</strong></h5><ul><li>Gain practical insights into effective sample preparation strategies that enhance matrix cleanup, extraction efficiency, and recovery consistency in oligonucleotide bioanalysis, leading to more robust and reproducible LC-MS results.</li></ul><h4><strong>Who should attend?</strong></h4><ul><li>Method development and bioanalytical scientists, laboratory managers, and CRO professionals involved in oligonucleotide drug discovery and quantitation workflows.</li></ul><blockquote><p><strong>Presenter: </strong>Lee Williams (Director of R&amp;D, Analytical Consumables and Applications, Biotage)</p><p>Lee Williams earned his PhD in mass spectrometry from the University of Wales, Swansea, and completed a Post-Doc in the Biochemical Toxicology department at the National Center for Toxicological Research, FDA labs. Lee joined Biotage (formerly Argonaut) to advance the LC/MS capability within the sample preparation arena. Over the 21 years, he has occupied a variety of roles, from senior scientist, group leader, lab manager, and, most recently, as the Director of R&amp;D for Analytical Consumables and Applications.</p></blockquote></div></div></div>

SeparationScience: Overcoming Sample Preparation Challenges in Oligonucleotide LC-MS/MS Analysis

Overcoming Sample Preparation Challenges in Oligonucleotide LC-MS/MS Analysis

Discover sample preparation strategies to improve matrix cleanup and extraction efficiency for oligonucleotides bioanalysis. 

Sample Prep Challenges in Oligonucleotide LC-MS/MS Analysis

<div><p><strong>We are pleased to invite you to join our Virtual PFAS Summit - Leading the Future of PFAS Analysis Together.</strong></p><p>Top scientists and leading experts in the food and environmental sectors met at Waters European headquarter in France on October 21, to explore cutting-edge technologies, share insights, and shape the future of PFAS analytical science.</p><p>The event was fully recorded and we are now pleased to invite you to attend the Online version of the Summit to join in and be part of the PFAS Community: recordings of the panel discussion and highlights of the presentations will give you valuable insights from contract labs and academia on PFAS analysis – tackling regulatory compliance, analytical robustness, and future trends.</p><p>Learn how advanced workflows, harmonized standards, and emerging technologies are shaping the future of PFAS monitoring and compliance</p><h4><strong>Hot Topics:</strong></h4><ul><li><strong>Regulatory Pressure EU </strong>and national frameworks are tightening PFAS monitoring</li><li><strong>Direct Injection LC-MS/MS</strong> for multi-residue and ultra-short chain PFAS in water</li><li><strong>Interlaboratory validation for PFAS quantification</strong> in food of plant origin<br>Innovative remediation technologies achieving &gt;97% PFAS degradation in industrial wastewater</li><li><strong>Future Priorities: </strong>Harmonization of methods, even lower detection limits, untargeted screening, and expanding PFAS lists in textiles, building materials, and air emissions</li></ul><h4><strong>Who Should Attend?</strong></h4><ul><li>Analytical scientists, lab managers, and technical experts working in food safety, environmental monitoring, and regulatory compliance.</li></ul><p><i>Not sure you can attend on November 19? Register today and watch the event on-demand at your convenience</i></p><blockquote><p><strong>Presenter:</strong> Anna Kärrman (Professor in Chemistry, Örebro Universitet - Sweden)</p><p>Anna Kärrman is a professor in chemistry at Örebro University, Sweden. She has studied PFAS since 2002 in Sweden, Japan, and the US within the field of analytical and environmental chemistry, focusing on analytical methods, distribution in the environment, sources, and human exposure. She was part in writing the technical guideline for PFAS determination under the EU Drinking Water Directive and provided input to the Soil Monitoring and Resilience Directive through several European and national research projects. Her main research agenda is to unravel the chemical identity of drivers of toxicity by seeking relevant and sensitive methods including non-targeted methodologies using mass spectrometry, and non-specific methods to determine group of compounds.</p><p><strong>Presenter: </strong>Consolato Schiavone (Research Fellow, INRIM - Italy)</p><p>Dr.ConsolatoSchiavoneholds a PhD in Metrology and is a Research Fellow at INRIM (National Metrology Institute of Italy). He works within the PhysicalChemistry and Nanotechnology Program, part of the Division of Quantum Metrology and Nanotechnologies. His research focus ischemical analysis with metrological approaches for food quality and safety. He spent six months, as a professional delegate, at the European Union reference laboratory for persistent organic pollutants 'EURL-POPs' in Freiburg (Germany), deepening his knowledge on the development of methods for the analysis ofcontaminants in plant matrices at theconcentrations required by new regulations.</p><p><strong>Presenter: </strong>Jenny Davies (Technical Director, Element Materials Technology)</p><p>Jenny has a strong background in environmental analysis. She started her journey nearly 20 years ago in a contract environmental laboratory working in various positions from Laboratory Technician to Lab Manager, managing multiple teams and sites. Recently Jenny worked at Waters as a Principal Applications Chemist in the European demo lab, based in Wilmslow. Now she is back at Element filling in the position of the Technical Director. Having experienced many busy laboratories where productivity is paramount, Jenny understands the importance of having robust, simple methods ideal to be carried out efficiently across multiple sites. She specialises in Persistent Organic Pollutants with a focus on environmental samples in soil, water and air.</p><p><strong>Presenter: </strong>Mickaël Nicolas (Scientific Director, Carso Group - France)</p><p><strong>Presenter: </strong>Caroline Dufour (Laboratory Engineer – HPLC Service, Carso Group - France)</p><p><strong>Presenter: </strong>Nina Huynh (Organic Analysis R&amp;D Engineer, Ineris - France)</p><p>Nina HUYNH holds a PhD in Sciences and environmental techniques and a chemical engineering degree. She is working at Ineris since 2022 as an R&amp;D engineer where her main tasks consist in: (i) the development of targeted and non-targeted analyses performed with high-resolution mass spectrometers and its combination to bioassay, (ii) the development and validation of targeted analysis methods using tandem mass spectrometry for the quantification of organic pollutants in environmental compartment (water, air, soil), (iii) the participation in French and European research and study programs aimed for a better characterization of chemical pollutants in the environment.</p><p><strong>Presenter: </strong>Roman Lyubimenko (Lead Water Analyst / Deputy Head of Process &amp; Analytics Dept., Oxyle - Switzerland)</p><p>Roman Lyubimenkosuccessfully defended his PhD in Chemical Engineering at the Karlsruhe Institute of Technology. Since 2022, he is employed at Oxyle AG, a Swiss cleantech startup that has developed a destruction technology for hazardous PFAS also known as "forever chemicals”.His responsibilities include:i) acting as a Subject Matter Expert in water quality and PFAS analysis in environmental samples;ii) ensuring the smooth running of the analytical laboratory; andiii) leading and mentoring laboratory staff.In today’s talk, he will discuss advances and challenges of PFAS analysis in environmental samples for remediation projects, highlighting the use of user-defined LC-MS methods in a high throughput analytical lab.</p><p><strong>Presenter: </strong>Stephan Lebertz (Operational Laboratory Manager, SGS Institut Fresenius GmbH)</p><p>Chemical Engeneering HS Fresenius - Fokus Analytical Chemistry</p><p>Since 2010 Specialist for traceanalysis of emerging contaminants at SGS INSTITUT FRESENIUS GmbH</p><p>Part of DIN working groups</p><p>As beeing responsible for a interdisciplinary Laboratory focussing into the transfer of emerging topics into other matrix-groups.</p><p><strong>Presenter: </strong>Sara Beverly (Principal Sales Application Chemist, Waters)</p><p>In her current position, Sara is a Principal Sales Application Chemist specializing in food and environmental LC-MS/MS based applications within the Waters UK and Ireland demo laboratory. Sara has worked in F&amp;E analysis with various research interests including the development of both multi-residue HRMS screening and targeted LC/GC MS based methods for the past 25 years in both the government and private sectors. Prior to joining Waters Sara was employed as a Lead Scientist at the Food and Environment Research Agency (FERA, Defra, UK) for 14 years. Sara has participated in EU Food and Veterinary Office (FVO) audit inspections, was an expert on behalf of the International Atomic Energy Agency (IAEA) and a member of the EuroResidue conference scientific committee.</p><p><strong>Presenter: </strong>Claudia Rathmann (Principal F&amp;E Market Development Manager, Waters Corporation)</p><p>Experienced and passionate analytical science professional with over 20 years of technical and strategic expertise in food and environmental applications. Currently serving as Principal Market Development Manager at Waters Corporation, Claudia specializes in connecting customers with product management to deliver innovative solutions for complex analytical challenges. With a strong scientific foundation and a proven track record in both technical and marketing roles, Claudia bridges the gap between customer needs and product innovation across the EMEA region.</p><p><strong>Presenter: </strong>Janitha De-Alwis (JD) (Principal F&amp;E Market Development Manager, Waters Corporation)</p><p>Janitha De-Alwis (known as JD) is an applications chemist in the European demo lab, based in Wilmslow, UK. His main role focuses on application development work for the food and environmental sector. JD takes great pride in speaking to, and advising, many food and environmental customers. His position requires him to be reactive and proactive to the changes in the food industry, such as changing regulations, topical issues and food safety risks.</p></blockquote></div>

Waters Corporation: EMEA PFAS Online Summit 2025

EMEA PFAS Online Summit 2025

Watch Virtual PFAS Summit and learn from global experts about PFAS analysis, harmonized standards, and future trends in food safety and environmental monitoring

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