This study systematically compares four widely used lysosome enrichment strategies, including density gradient separation, magnetic bead isolation, filter-based enrichment, and subcellular fractionation. Using the THP-1 monocytic cell line, the methods were evaluated for lysosome yield, purity, membrane integrity, reproducibility, scalability, and contamination through complementary analytical techniques and proteomics.The results showed that gradient- and bead-based methods achieved the highest lysosomal purity, while subcellular fractionation yielded larger numbers of lysosomes but with greater contamination and variability. Filter-based enrichment enabled rapid processing but recovered mainly nonintact lysosomes. The findings provide practical guidance for selecting lysosome isolation methods in both research and clinical applications.<blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792">Benchmarking Lysosome Enrichment Methods: A Guide for Research and Clinical Translation</a></h4>Anniek L. de Jager, Sara Kassem, Louis Alesha, Brigitta A.E. Naber, Inge F. de Laat, Bas de Mooij, Kyra van der Pan, Erik Bos, Roman I. Koning, Jacques J.M. van Dongen*, Cristina Teodosio*, and Paula Díez*Anal. Chem. 2026, 98, 6, 4585–4600<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c05792">https://doi.org/10.1021/acs.analchem.5c05792</a><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a></h6></blockquote>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.<div>Since their discovery by De Duve et al. <a href="javascript:void(0);">(1)</a> in 1955, lysosomes have emerged as dynamic organelles critical to cellular homeostasis, regulating processes from nutrient sensing to plasma membrane repair. <a href="javascript:void(0);">(2−5)</a> These acidic, enzyme-packed vesicles <a href="javascript:void(0);">(6,7)</a> are now acknowledged as central players in pathologies far beyond their classical association with lysosomal storage disorders (LSDs). Dysfunctional lysosomes are involved in neurodegenerative diseases (e.g., Alzheimer’s, Parkinson’s), <a href="javascript:void(0);">(8−10)</a> cancer metastasis, <a href="javascript:void(0);">(11−13)</a> and cardiovascular disorders. <a href="javascript:void(0);">(14,15)</a> At the same time, lysosomal proteins like GBA1 and LAMP2 serve as biomarkers and therapeutic targets. <a href="javascript:void(0);">(16−19)</a> Despite their clinical significance, a major challenge in lysosomal research persists since lysosomes constitute less than 5% of cellular volume, <a href="javascript:void(0);">(20,21)</a> requiring precise enrichment for accurate analysis in diagnostic and therapeutic development. <a href="javascript:void(0);">(22,23)</a>Current lysosome isolation methods, including density gradient-based separation, <a href="javascript:void(0);">(24−28)</a> filter-based size exclusion approaches, <a href="javascript:void(0);">(29)</a> magnetic particle phagocytosis, <a href="javascript:void(0);">(30−33)</a> subcellular fractionation (SCF), <a href="javascript:void(0);">(34)</a> and immunoprecipitation strategies, <a href="javascript:void(0);">(35,36)</a> vary widely in yield, purity, structural integrity, and practicality. For instance, density gradient-based methods, which often use Percoll <a href="javascript:void(0);">(37)</a> or sucrose, <a href="javascript:void(0);">(38)</a> while well-established, user-friendly, and cost-effective, coisolate organelles with similar densities, such as endosomes, peroxisomes, and mitochondria, <a href="javascript:void(0);">(39,40)</a> and can be time-consuming, potentially affecting lysosomal protein integrity. Conversely, filter-based size exclusion methods isolate lysosomes based on their size, <a href="javascript:void(0);">(29)</a> offering shorter processing times and straightforward protocols. Nevertheless, these approaches may result in cross-contamination, as various cellular vesicles share similar sizes. <a href="javascript:void(0);">(20,21)</a> Magnetic bead-based methods (e.g., superparamagnetic iron oxide nanoparticles, SPION) involve the endocytic uptake of magnetic beads, <a href="javascript:void(0);">(35,41)</a> offering specificity but altering lysosomal physiology through forced phagocytosis, which hampers functional assays, such as in cancer drug screening. <a href="javascript:void(0);">(42,43)</a> Finally, SCF, which employs sequential lysis steps to enrich specific organelles, including lysosomes, <a href="javascript:void(0);">(34,44)</a> is a rapid, easy-to-use, and cost-effective method; however, significant cross-contamination is linked to this method. <a href="javascript:void(0);">(34,44)</a> Such trade-offs are rarely addressed in single-modality studies, leaving clinicians and researchers without clear guidance for protocol selection. This gap is particularly critical in translational contexts, where diagnostic laboratories that prioritize high-purity lysosomes for biomarker discovery require protocols different from those of therapeutic teams that need lysosomes for drug efficacy testing.Previous comparative studies, such as the proteomic analysis by Singh et al., <a href="javascript:void(0);">(35)</a> have provided valuable insights but primarily focused on yield and purity assessments via proteomic markers, overlooking several key parameters with potentially relevant impacts in translational and clinical applications. Critically, these studies often omit functional and practical metrics: for instance, they typically do not evaluate lysosomal membrane integrity, which is vital for enzyme activity and therapeutic testing, nor do they consider the scalability and feasibility of protocols for contexts where only limited patient samples are available or the potential presence of isolation artifacts. This omission of practical, multimodal assessment represents a critical gap that prevents researchers from selecting a protocol optimized for specific clinical goals.Our study seeks to address these limitations by employing a multimodal framework that evaluates four widely used lysosome isolation methods across several metrics that are critical for clinical applications. We systematically assessed the yield and reproducibility of each method, factors that are essential for biobanking and high-throughput diagnostic workflows. We also examined organelle purity, crucial for avoiding false positives in proteomic biomarker screenings, together with lysosomal membrane integrity, an important consideration for functional studies and drug testing. Finally, we considered the scalability of each method, ensuring that our findings are relevant for studies involving rare or precious patient-derived cells together with the cost and processing time of each technique. Thus, by integrating nanoparticle tracking analysis (NTA), spectral flow cytometry, transmission electron microscopy (TEM), and mass spectrometry (MS)-based proteomics, our study revealed distinct advantages for each method depending on the intended application. With this comprehensive benchmark, we bridged a critical gap between fundamental lysosome biology and clinical implementation, guiding researchers and clinicians in the selection of the most appropriate isolation strategies tailored to their diagnostic or therapeutic goals.<h3>Experimental Section</h3><h4>Liquid Chromatography–Tandem Mass Spectrometry Analysis (LC–MS/MS)</h4>For liquid chromatography–tandem mass spectrometry (LC–MS/MS) studies, a total of 15 μg of proteins were reduced with 10 mM DTT at 45 °C for 30 min, followed by alkylation with 40 mM 2-iodoacetamide (IAA, Sigma-Aldrich) at RT for 30 min. This last reaction was quenched with 20 mM DTT, and protein digestion and peptide recovery were performed using hydrophilic and hydrophobic beads (Sera-Mag Carboxylate-Modified Magnetic Particles, Cytiva, Marlborough, MA/USA) according to the Single-Pot Solid-Phase-enhanced Sample Preparation (SP3) method. <a href="javascript:void(0);">(46,47)</a> In short, samples were incubated twice with beads (1:10 (w/w) protein:bead ratio) in 70% acetonitrile (ACN) for 18 min at RT. After incubation, bead-bound proteins were retained by using a DynaMag-PCR Magnet (Thermo Fisher), and contaminants were washed away three times with 80% ethanol (Sigma-Aldrich). Proteins were digested using a Trypsin/LysC mix (1:25 (w/w) enzyme:protein ratio, Promega, Madison, WI/USA) in 50 mM ammonium bicarbonate at RT overnight. Beads were then washed twice with ACN, after which peptides were eluted in 2% (v/v) dimethyl sulfoxide (DMSO, Thermo Fisher), lyophilized in a freeze-dryer, and stored at −20 °C. Samples were then tagged using the tandem mass tag (TMT) labeling kit (TMTpro 16plex tags, Thermo Fisher) by resuspending the lyophilized peptides in 40 mM HEPES pH 8.4 and labeling with the TMT tags at a 1:5 (w/w) sample:tag ratio for 1 h at RT. The labeling reaction was quenched with 5% hydroxylamine. TMT-labeled lysosome samples were pooled, lyophilized in a freeze-dryer, and stored at −20 °C until LC–MS/MS analysis.<h4>Mass Spectrometry Data Acquisition and Analysis</h4>MT-labeled peptides were dissolved in solvent A (water/formic acid (FA), 100/0.1 (v/v)) and analyzed by online C18 nano-HPLC MS/MS, coupling an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=3&amp;search=UltiMate+3000">UltiMate 3000 gradient HPLC system</a> (Thermo Fisher) and an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/401">Orbitrap Exploris 480 mass spectrometer</a> (Thermo Fisher). A total of 12 fractions were injected onto a precolumn (300 μm × 5 mm; PepMap100 C18 5 μm, Thermo Fisher) equilibrated with solvent A and eluted via a homemade analytical nano-HPLC column (50 cm × 75 μm; ReproSil-Pur C18-AQ 1.9 μm) using solvent B (80/20/0.1 (v/v/v) ACN/water/FA) in a gradient from 5 to 30% in 160 min. The nano-HPLC column was drawn to a tip of ∼5 μm and functioned as an electrospray needle. A Sonation PRSO-V2 column oven was used to maintain the analytical column temperature at 50 °C. The MS1 spectra were recorded in the Orbitrap at a mass-to-charge ratio (m/z) range of 350–1,600, a resolution of 120,000, a maximum injection time of 50 ms, and automatic gain control (AGC) at standard. Dynamic exclusion was applied after n = 1 with an exclusion duration of 45 s and a mass tolerance of 10 ppm. Charge states 2–5 were included. Precursors for MS2 were selected using a TopSpeed method of 3 s at a resolution of 45,000 and fragmented by high-energy collision-induced dissociation (HCD) at a normalized collision energy (NCE) of 36%, with an AGC at 200 and the maximum injection time set to auto. The isolation window for MS/MS was 1.2 Da.Raw data files were converted to the peak list by using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1782">Proteome Discoverer v2.4</a> (Thermo Fisher), followed by protein identification employing the UniProtKB database (Homo sapiens, 20,596 entries) using Mascot v2.2.07 (Matrix Science Inc., Boston, MA/USA) with the following parameters: precursor and fragment mass tolerances of 10 ppm and 0.02 Da, respectively; TMT16plex on N-term and Lys as fixed modifications; oxidation on Met and acetylation of N-term as variable modifications; and full tryptic digestion (no P rule) with up to 2 missed cleavages. A false discovery rate (FDR) of 1% was set for peptide spectrum matches (PSMs), peptides, and proteins.The MS data have been deposited via the PRIDE partner repository to the ProteomeXchange Consortium with the identifier PXD040003.<h3>Results</h3><h4>Quantification and Size Distribution of Isolated Vesicle Fractions</h4>To assess the yield and size distribution of vesicles isolated by different methods, nanoparticle tracking analysis (NTA) was employed. The SCF procedure yielded the highest median number of vesicles per cell (2,356.3 ± 7,461.7; median ± range), followed by gradient-based (1,630.2 ± 1632.3), filter-based (228.2 ± 265.6), and bead-based isolation (27.8 ± 35.2). Both filter- and bead-based approaches resulted in significantly lower yields compared to SCF (p-value = 0.002 and p-value &lt;0.0001, respectively), and the gradient-based method yielded significantly more vesicles than the bead-based approach (p-value = 0.002; <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>A).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4585_4600_Figure_1_Quantification_and_size_analyses_of_isolated_vesicles_2d5c120f05.jpeg" alt="Anal. Chem. 2026, 98, 6, 4585–4600: Figure 1. Quantification and size analyses of isolated vesicles. A) Quantification of isolated vesicles per cell, shown as median with range. Circles represent technical replicates. B) Size distribution of isolated vesicles (in nm), displaying average D10 (red), D50 (blue), and D90 (gray), depicted as median with range. Circles represent technical replicates. C–F) Particle distribution plots showing mean concentration at specific sizes; each line represents a technical replicate. For each method, six technical replicates are shown, except for SCF, which includes 12 replicates. SCF, subcellular fractionation. Statistical significance: p &lt; 0.05 and FDR 5%. For statistical analysis, the nonparametric Kruskal–Wallis test was used and corrected for multiple comparisons using the method of Benjamini and Hochberg." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4585_4600_Figure_1_Quantification_and_size_analyses_of_isolated_vesicles_2d5c120f05.jpeg 126w," sizes="100vw" width="1383" height="1708">Median vesicle size (D50) was comparable across all methods: 159.5 ± 17.2 nm (gradient-based), 169.9 ± 82.7 nm (filter-based), 168.9 ± 42.4 nm (bead-based), and 150.0 ± 55.6 nm (SCF). Similarly, decile 10 (D10) values were consistent, ranging from 87.1 ± 87.3 nm (SCF) to 108.2 ± 3.1 nm (gradient-based). However, filter-based isolation led to higher size heterogeneity of the isolated particles, capturing significantly larger vesicles at the upper end (D90:308.5 ± 110.7 nm) compared to SCF (244.9 ± 112.6 nm, p-value = 0.005), while gradient- and bead-based methods showed intermediate D90 values (250.8 ± 31.7 nm and 273.0 ± 45.9 nm, respectively; <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>B). Notably, greater intra-assay variation in concentration and size distribution was observed with filter-based and SCF methods compared to the other approaches (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>C–F).<h4>Morphology of the Isolated Fractions</h4>Transmission electron microscopy (TEM) of the isolated fractions confirmed the presence of heterogeneously sized vesicles, in line with the size distributions obtained by NTA. Notably, only the gradient-based method yielded relatively pure vesicle preparations. In contrast, filter-based and SCF methods displayed contamination with cellular debris or protein aggregates, while the bead-based approach was associated with the presence of lipid structures (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig2">Figure 2</a>).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4585_4600_Figure_2_Transmission_electron_microscopy_TEM_of_isolated_fractions_f14ddbe180.jpeg" alt="Anal. Chem. 2026, 98, 6, 4585–4600: Figure 2. Transmission electron microscopy (TEM) of isolated fractions. Panels A–D show TEM images of the four isolated fractions. Insets display magnified views of the regions outlined in black squares. Black arrows indicate identified representative isolated vesicles, and white arrows denote areas of contamination." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4585_4600_Figure_2_Transmission_electron_microscopy_TEM_of_isolated_fractions_f14ddbe180.jpeg 145w," sizes="100vw" width="1263" height="1361"><h3>Conclusion</h3>This study provides a systematic benchmarking of four lysosome isolation strategies, revealing inherent trade-offs among yield, integrity, purity, and reproducibility driven by their underlying separation principles. No single method is universally optimal; instead, the method selection must be guided by the intended downstream application. By integrating complementary analytical approaches in a clinically relevant and challenging monocytic model, our work offers a practical framework to support the informed selection of lysosome enrichment strategies, facilitating reliable lysosomal analyses in both research and translational settings.</div>

Benchmarking Lysosome Enrichment Methods: A Guide for Research and Clinical Translation

A Method for the Detection of Tire Wear Microplastics in Zebrafish Guts by Laterally Resolved LA-ICP-MS-Based Elemental Fingerprinting and Chemometrics

This leaflet is intended to help participants in quantitative proficiency testing (PT) schemes to better understand the performance assessment made by the PT provider [1-4].<h3>Performance assessment parameters&nbsp;</h3><h4>Assigned value&nbsp;</h4>In order to assess individual performances, the results reported by participants are compared to the value assigned by the PT provider (xpt). ISO 13528 [1] suggests five different ways to obtain xpt (Figure 1). In this context, the design of the PT scheme must reflect the objectives of the scheme, comparing results either to a predetermined xpt (independent from the participant results), or to a value derived from the reported results. The PT provider is responsible for defining xpt , taking into account the advantages and disadvantages of the various possibilities when establishing metrological traceability or estimating the uncertainty of the assigned value, u(xpt).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_1_e5ef5d1f9c.jpg" alt="Eurachem - Figure 1 Options for obtaining the assigned value, Xpt" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_1_e5ef5d1f9c.jpg 245w," sizes="100vw" width="640" height="382"><h4>Uncertainty of the assigned value&nbsp;</h4>The uncertainty of the assigned value u(xpt) can be estimated in at least five different ways [1], each corresponding to the value assignment strategy illustrated in Figure 1. The different uncertainty evaluation methods are listed in Figure 2. This uncertainty can be reported as a standard uncertainty (u (xpt)), or as an expanded uncertainty U (xpt) with a coverage factor k, where U (xpt) = k . u (xpt). The choice of k will impact the level of confidence (e.g. approximately 95 % for k = 2).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_2_f41ebc0c61.jpg" alt="Eurachem: Figure 2 Options for obtaining the uncertainity of the assigned value, u(Xpt)" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_2_f41ebc0c61.jpg 245w," sizes="100vw" width="727" height="378"><h4>Standard deviation for proficiency assessment&nbsp;</h4>Five possibilities are suggested by ISO 13528 to set the standard deviation for proficiency assessment spt (Figure 3). The chosen approach must comply with the objectives of the PT scheme.&nbsp;<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_3_f09cb3969e.jpg" alt="Eurachem: Figure 3 Options for obtaining the standard deviation for proficiency assesment" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_3_f09cb3969e.jpg 245w," sizes="100vw" width="638" height="355">Two approaches for performance assessments use spt as shown in Table 1.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Table_1_Scoring_for_performance_assessment_3dd03aa3fb.jpg" alt="Eurachem: Table 1 - Scoring for performance assessment." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Table_1_Scoring_for_performance_assessment_3dd03aa3fb.jpg 245w," sizes="100vw" width="1390" height="571"><h3>Performance assessment&nbsp;</h3>All performance assessments are based on the difference between the participant’s results (xi) and the assigned value (xpt) divided by a normalisation factor (Table 1).&nbsp;<ul><li>The percent difference D% is the normalised difference expressed as a percentage of xpt , for which a prescribed maximum relative permissible error (dE% = dE / xpt) is defined by the PT provider.&nbsp;</li><li>The z score (unitless) compares the participant’s deviation from the assigned value with the standard deviation for proficiency assessment (spt). When the uncertainty of the assigned value is significant (u(xpt) &gt; 0.3 spt), the z’ score should be used instead, to include the contribution of u(xpt) in the denominator.&nbsp;</li><li>The zeta (ζ) score (unitless) states whether the laboratory’s result agrees with the assigned value within the respective uncertainty. The denominator is the combined (standard) uncertainty of the assigned value u(xpt) and the (standard) measurement uncertainty reported by the laboratory u(xi). An unsatisfactory zeta score can either be caused by an inappropriate estimation of the measured quantity value (e.g. concentration, content), or of its measurement uncertainty, or both.&nbsp;</li><li>The En score (unitless), unlike the zeta score, uses a combination of expanded uncertainties as the normalisation factor. This combination corresponds to a confidence interval of approximately 95 %. En scores are often used in metrology comparisons among calibration laboratories.</li></ul><h3>Interpretation of performance scores&nbsp;</h3>According to ISO 13528:2022 clause 9.4.2, the conventional interpretation of the z, z’ and ζ scores is as follows:&nbsp;<ul><li>A result that gives |score| ≤ 2.0 is considered to be acceptable, indicating satisfactory performance.&nbsp;</li><li>A result that gives 2.0 &lt; |score| &lt; 3.0 is considered to give a warning signal, indicating questionable performance.&nbsp;</li><li>A result that gives |score| ≥ 3.0 is considered to be unacceptable (or action signal), indicating unsatisfactory performance.&nbsp;</li></ul>Similarly, |En| &lt; 1 and |D%| &lt; dE% indicate successful (acceptable) performance.

Understanding PT performance assessment

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Academy

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Science and research

Eurachem is a European network promoting international traceability of chemical measurements and good analytical practice. It provides expert guidance, supports method validation, uncertainty evaluation, proficiency testing, and facilitates discussion on technical and policy issues in analytical quality.

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Some users have questions on how Microwave Plasma compares to other Spectroscopy Techniques. What is it? Where does it fit? Primary applications for the MP.
This presentation will cover these questions as it compares to AAS and ICP techniques. Learn the advantages of each techniques and which applications are best for each.
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Presenter: Paul Krampitz (Application Scientist, Agilent Technologies, Inc.)
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Paul is a graduate of Bowling Green State University with a Chemistry Bachelor of Science degree. Twenty – five years of Spectroscopy experience mainly Inductively Coupled Plasma (ICP) Spectroscopy as well as ICP-MS and AAS. His experience also includes X-Ray Fluorescence (ED, WD), Laser Ablation, Inorganic Speciation and Microwave Plasma Spectroscopy. Market Segment expertise includes environmental, petrochemical, metallurgical applications.
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Agilnt Technologies: Overview of Atomic Techniques and how Microwave Plasma compares to Atomic Absorption and Inductively Coupled Plasma Spectroscopy Techniques: Which is right for you?

Overview of Atomic Techniques and how Microwave Plasma compares to Atomic Absorption and Inductively Coupled Plasma Spectroscopy Techniques: Which is right for you?

We will cover questions as it compares to AAS and ICP techniques.  Learn the advantages of each techniques and which applications are best for each.

Overview of Atomic Techniques: Which is right for you?

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is widely used throughout industry for its high sensitivity, wide dynamic range, and fast multi-element analysis.
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This webinar series will address the challenges in trace elemental analysis by ICP-MS through best practices and the latest advances in sample digestion, sample automation, and ICP-MS instrumentation to obtain accurate, repeatable results and streamline workflow processes to save time, resources, and increase productivity.
In Part 1 of this webinar series, learn how to set up for success in ICP-MS analysis by reducing systematic errors and streamlining standard and sample preparation processes within the trace elemental analysis workflow. Discover sample preparation innovations from our guest speaker, Michael Howe, Sr. Project Manager at CEM Corporation, who will present on the latest cutting-edge microwave digestion system that accelerates sample digestion from hours to minutes with clear digestions and maximum recovery of analytes.
Key learning objectives
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<li>General best practices for the elemental analysis workflow to reduce systematic errors.
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<li>Tips and tricks for standard solution handling, transfers, and preparation
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<li>Advantages and disadvantages between the most common sample preparation methods for trace elemental analysis.
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<li>Innovations in microwave digestion technology presented by CEM Corporation
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Who should attend
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<li>Laboratories performing trace elemental analysis by ICP-MS, ICP-OES, and AAS.
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<li>Laboratories interested in ways to improve the efficiency of current standard and sample preparation processes.
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<li>Analysts seeking information on systematic errors and how to reduce them for best analytical results.
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Presenter: Sabrina Antonio (Regional Marketing Manager, Trace Elemental Analysis and Inorganic Mass Spectrometry, Thermo Fisher Scientific)
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Sabrina’s extensive background includes senior chemical engineer and project manager at electric utilities, application specialist for atomic spectroscopy, and lead auditor for the US EPA Contract Laboratory Program (CLP) inorganic statement of work. She joined Thermo Fisher Scientific in 2015 as a technical sales specialist before becoming regional marketing manager for the trace elemental analysis product line in 2018.
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Presenter: Andy Fornadel (Product Marketing Manager, Thermo Fisher Scientific)
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Andy Fornadel is a Product Marketing Manager for Thermo Fisher Scientific with a focus on elemental spectroscopy and gas chromatography products. He has spent the past seven years in the analytical instrumentation industry in various product marketing and vertical marketing roles. He holds a PhD and an MS from Iowa State University and a BS from Juniata College.
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Presenter: Michael Howe (Sr. Project Manager, CEM Corporation)
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Michael “Howie” Howe is the Sr. Project Manager for CEM Corporation. In his more than 20 years at CEM, Howie has been instrumental in helping customers solve the ever-changing needs of microwave digestion challenges.
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Thermo Scientific: Set up for success in ICP-MS: Standard and sample preparation best practices and innovations to reduce errors and maximize analyte recovery

Set up for success in ICP-MS: Standard and sample preparation best practices and innovations to reduce errors and maximize analyte recovery

Learn how to set up for success in ICP-MS analysis by reducing systematic errors and streamlining standard and sample preparation processes.

Set up for success in ICP-MS: Standard & sample preparation

Fast, accurate results are essential in today’s busy laboratory, whether environmental, industrial, or contract testing, for compliance monitoring, important decision making, or meeting productivity goals and the bottom line.
Multi-element analysis of high matrix and varied samples performed by these laboratories require robust, easy to operate, and maintain instrumentation with minimum operating cost. However, increasing regulation and product quality and safety standards drive the demand for ultra-trace detection in high matrix samples requiring high sensitivity in addition to robustness and ease of use.
In Part 3 of this webinar series, discover how the new Thermo Scientific® iCAP® RQplus ICP-MS and the new Thermo Scientific® iSC-65 autosampler deliver robust, long-term analysis of high matrix samples for enhanced throughput with data demonstrating performance. Learn about differentiating features for ease of use, industry leading sensitivity, and advanced interference removal. Maximize uptime and reduce downtime with new software features for preemptive maintenance, troubleshooting, and consumable management. Finally, find out how this new system helps laboratories meet their sustainability goals.
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<li>Performing long-term, stable analysis of complex, high matrix samples using next generation Argon Gas Dilution.
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<li>Prevent analytical drift and reduce downtime using new software maintenance and consumable assistant.
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<li>Laboratories performing trace elemental analyses by ICP-MS, ICP-OES, and AAS.
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<li>Laboratories starting up or looking to bring ICP-MS analysis in-house.
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<li>Laboratories performing trace elemental analyses on complex, high matrix samples such as seawater, brines, brackish water, wastewater, soils, sludges, and other challenging industrial samples.
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<li>Analysts and laboratory managers interested in learning about the latest innovations in ICP-MS instrumentation that delivers enhanced robustness, high matrix tolerance, industry leading sensitivity, ease of use, low maintenance, and accelerated productivity.
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Presenter: Sabrina Antonio (Regional Marketing Manager, Trace Elemental Analysis and Inorganic Mass Spectrometry, Thermo Fisher Scientific)
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Sabrina’s extensive background includes senior chemical engineer and project manager at electric utilities, application specialist for atomic spectroscopy, and lead auditor for the US EPA Contract Laboratory Program (CLP) inorganic statement of work. She joined Thermo Fisher Scientific in 2015 as a technical sales specialist before becoming regional marketing manager for the trace elemental analysis product line in 2018.
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Presenter: Jeff Gross (Senior Training Instructor, Trace Elemental Analysis, Thermo Fisher Scientific)
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Jeff Gross is a Senior Training Instructor for both ICP-OES and ICP-MS product lines. Before joining Thermo Fisher Scientific in 2008, Jeff worked in the environmental industry for 10 years. Throughout his commercial laboratory tenure, Jeff has fulfilled many roles including Metals Department Analyst, Department Supervisor as well as Project Manager. Jeff graduated from Southeast Missouri State University with a bachelor’s degree in Secondary Education as well as a bachelor’s degree in chemistry.
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Thermo Scientific: Power your ICP-MS analysis: New solutions to overcome the challenges of high matrix samples and boost productivity

Power your ICP-MS analysis: New solutions to overcome the challenges of high matrix samples and boost productivity

The new Thermo Scientific® iCAP® RQplus ICP-MS and the new Thermo Scientific® iSC-65 autosampler.

Power your ICP-MS analysis: New solutions

Innovations in ICP-MS instrumentation improve robustness, performance, and ease of use, however, obtaining accurate results and addressing sample failures are challenges that cannot be addressed through innovation alone.
Reducing systematic errors and streamlining workflow processes are part of the equation in figuring out how to obtain accuracy and achieving productivity goals. The other part of the equation is developing an optimized analytical method and analyzing data to identify troubleshooting and maintenance measures.
In Part 4 of this webinar series, tips and tricks for method development and daily operation will be discussed including the following topics for successful day-to-day operation of the ICP-MS:
<ul>
<li>Instrument tuning, performance report analysis, and measures to address failed performance specifications
</li>
<li>Pre-analysis inspection routines
</li>
<li>Method optimization with example applications for environmental and industrial samples
</li>
<li>Data analysis and troubleshooting failed results
</li>
<li>Preventive and routine maintenance
</li>
</ul>
Key learning objectives
<ul>
<li>Learn about new software features for easy instrument tuning according to the sample matrices.
</li>
<li>How to address failures in performance report specifications prior to analysis to avoid sample failures.
</li>
<li>Pre-analysis inspection routines to ensure successful analysis.
</li>
<li>How to develop an optimized method including operating parameters, QC protocol, and interference correction techniques.
</li>
<li>Troubleshoot failed sample results and performing routine and preventive maintenance.
</li>
</ul>
Who should attend
<ul>
<li>Laboratories performing trace elemental analyses by ICP-MS, ICP-OES, and AAS.
</li>
<li>Laboratories starting up or looking to bring ICP-MS analysis in-house.
</li>
<li>Analysts seeking information on method development, optimizing instrument configuration and operating parameters.
</li>
<li>Analysts evaluating data and seeking measures to troubleshoot failed sample results.
</li>
<li>Analysts seeking tips and tricks for routine and preemptive maintenance to prevent sample failures and reruns.
</li>
</ul>
<blockquote>
Presenter: Sabrina Antonio (Regional Marketing Manager, Trace Elemental Analysis and Inorganic Mass Spectrometry, Thermo Fisher Scientific)
</blockquote>
<blockquote>
Sabrina’s extensive background includes senior chemical engineer and project manager at electric utilities, application specialist for atomic spectroscopy, and lead auditor for the US EPA Contract Laboratory Program (CLP) inorganic statement of work. She joined Thermo Fisher Scientific in 2015 as a technical sales specialist before becoming regional marketing manager for the trace elemental analysis product line in 2018.
</blockquote>
<blockquote>
Presenter: John Schmelzel (Staff Scienticist, Trace Elemental Analysis, Thermo Fisher Scientific)
</blockquote>
<blockquote>
John Schmelzel is a Staff Scientist at Thermo Fisher Scientific responsible for ICP-OES ICP-MS and Atomic Absorption. He graduated from the University of Colorado Boulder and has been with Thermo Fisher Scientific for nearly 35 years supporting customers and developing the technology.
</blockquote>

Thermo Scientific: Success in ICP-MS analysis: Method optimization, maintenance, and troubleshooting tips and tricks

Success in ICP-MS analysis: Method optimization, maintenance, and troubleshooting tips and tricks

Tips and tricks for method development and daily operation (tuning, inspection, method optimization, data analysis and troubleshooting, maintenance)

ICP-MS analysis: optimization, maintenance, troubleshooting

This will be a three week Food and Cannabis elemental analysis workshop.
We will cover a lot of great information during these three weeks.
Part 1: We will cover the entire Agilent elemental portfolio. Each of the different instruments&#39; strengths and how they meet the challenges that food and cannabis labs have.
Part 2: We will focus on preparing your samples, including microwave digestion. We will also cover how to optimize your system for high matrix samples and a diverse sample set.
Part 3: We will put it all together, with running samples live in the lab. We will also share additional tips and tricks on obtaining excellent analytical results in these difficult matrices.
<blockquote>
Presenter: Jenny Nelson, PhD (Application Scientist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Jenny Nelson received her Ph.D. in Analytical Chemistry from the University of Cincinnati in 2007, and her MBA from Saint Mary’s College of California in 2011. Currently, Jenny is an Application Scientist for the Life Science and Chemical Analysis team at Agilent Technologies, joining in 2012 (with a step away in 2019). Jenny is also an Adjunct Professor in the Department of Viticulture and Enology at the University of California, Davis, since 2013. Jenny has been very active with AOAC and ASTM over the past eight years, serving on expert review panels, chairing committees, and volunteering to develop new methods needed by the industry. Jenny has extensive experience in operating and method development for Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Microwave Plasma Atomic Emission Spectroscopy (MP-AES). Jenny has broad knowledge and experience in different speciation analysis for many sample matrices using GC-ICPMS and LC-ICPMS. As well as vast experience with sp-ICP-MS for many applications.
</blockquote>
<blockquote>
Presenter: Greg Gilleland (Application Scientist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Greg began his spectroscopy career in 1987 in Colorado, working at a series of environmental labs. After 14 years working in the world of commercial environmental labs, he moved on to a spectroscopy instrument manufacturer where he performed service and sales functions over the course of 11 years. He has been with Agilent Technologies, Inc., since 2012 in the role of Application Scientist for ICP-OES, MP-AES and AA products.
</blockquote>
<blockquote>
Presenter: Mark Kelinske (Application Scientist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Mark Kelinske is an Applications Chemist with Agilent Technologies, specializing in advanced ICP-MS and ICP-MS/MS techniques. He received his undergraduate and graduate degrees from Texas A&amp;M University in College Station, TX. Prior to Agilent, Mark was a senior research scientist and research group manager with Southern Research Institute in Birmingham, AL, where he focused on low-level analytical chemistry, method development, and research program management.
</blockquote>
<blockquote>
Presenter: Chris Conklin (Atomic Spectroscopy Product Specialist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
With a degree from the University of Wisconsin – Eau Claire, Chris worked in, and lead, a quality control lab testing fine chemicals ranging from reagent grade to high purity. Over the course of 12 years in that role, Chris has run a variety of atomic elemental instruments and techniques including AA, ICP-OES, and ICP-MS. As a result, he has seen most of the periodic table in its elemental form and overcome the associated interferences. In 2018, Chris brought that knowledge and experience to his current role with Agilent as the Product Specialist for Atomic Spectroscopy supporting AA, MP-AES, and ICP-OES for the Eastern US.
</blockquote>

Agilent Technologies: Food and Cannabis Elemental Analysis Part 1: Elemental Workflows in the Food and Cannabis Lab

Food and Cannabis Elemental Analysis Part 1: Elemental Workflows in the Food and Cannabis Lab

Agilent elemental portfolio. Each of the different instruments' strengths and how they meet the challenges that food and cannabis labs have.

Food and Cannabis Elemental Analysis Part 1

Agilent Applications Scientists will demonstrate on live 8900 Triple Quad ICPMS and 5900 ICPOES instrumentation, the hardware, MassHunter and ICP Expert software as well as tuning and cleanliness strategies used and recommended in semiconductor facilities to reduce contamination, maximize sensitivity and minimize interferences.
<blockquote>
Presenter: Bert Woods (Application Scientist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Joined the Agilent ICP-MS team in 2004, with previous employment in the semiconductor industry with Dominion Semiconductor (IBM/Toshiba) and Micron. Bert is a 1997 Chemistry graduate of Radford University in Virginia and an avid Washington DC Sports fan.
</blockquote>
<blockquote>
Presenter: Emmett Soffey (ICP-MS Product Specialist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Emmett Soffey is an ICP-MS Product Specialist and has been with HP/Agilent for 30 years. He received his undergraduate degree from Cornell University. Prior to Agilent he worked at Brookhaven National Labs studying acid rain in the Adirondack Mountains of northern NY and then went on to work at a number of commercial analytical labs operating GC and GC/MS. Emmett has been part of the Agilent ICP-MS team since 1995. He has worked on the development of new software tools, discrete sampling devices and the GC-ICP-MS interface. In his spare time Emmett spends time hiking in the beautiful Cascade Mountains of Washington State.
</blockquote>
<blockquote>
Presenter: Sima Singha, PhD (ICP-OES Application Scientist, Atomic Spectroscopy, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Sima has over fifteen years of hands on experience as an applications scientist in the field of atomic spectroscopy. Before joining Agilent in 2017, managed an agricultural chemistry laboratory for the analysis of water, soil, and plant tissue digests using ICP-OES for various EPA methods. She received a Ph.D. degree in Chemistry from the University of Illinois at Chicago with numerous peer-reviewed publications.
</blockquote>
<blockquote>
Presenter: Chris Conklin (Atomic Spectroscopy Product Specialist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
With a degree from the University of Wisconsin – Eau Claire, Chris worked in, and lead, a quality control lab testing fine chemicals ranging from reagent grade to high purity. Over the course of 12 years in that role, Chris has run a variety of atomic elemental instruments and techniques including AA, ICP-OES, and ICP-MS. As a result, he has seen most of the periodic table in its elemental form and overcome the associated interferences. In 2018, Chris brought that knowledge and experience to his current role with Agilent as the Product Specialist for Atomic Spectroscopy supporting AA, MP-AES, and ICP-OES for the Eastern US.
</blockquote>

Agilent Technologies: Demonstration of Trace Metals and Electronic Grade Materials Analysis Techniques and Strategies on live Instrumentation.

Demonstration of Trace Metals and Electronic Grade Materials Analysis Techniques and Strategies on live Instrumentation.

8900 Triple Quad ICPMS and 5900 ICPOES instrumentation, the hardware, MassHunter and ICP Expert software as well as tuning and cleanliness strategies.

Demonstration of Trace Metals and Electronic Grade Materials

The precise and accurate measurement of 87Sr/86Sr isotope ratios by quadrupole based ICP-MS presents unique analytical challenges, driven by isobaric interferences, matrix effects, and the need for stable and reproducible operating conditions. &nbsp;Tiple quadrupole ICP-MS (ICP-QQQ) offers effective strategies for addressing these challenges, however method performance is highly dependent on the appropriate selection and optimization of instrumental parameters. &nbsp;In this webinar, we will discuss the practical approaches for simplifying 87Sr/86Sr isotope ratio analysis using the Agilent 8900. &nbsp;The presentation will focus on key method considerations, including reaction cell gas selection, mass‑shift strategies, tuning approaches, and control of instrumental and environmental variables that influence isotopic precision and accuracy. &nbsp;This webinar is intended for users seeking a straightforward, reliable path to high‑quality strontium isotope ratio measurements using Agilent’s 8900 and ICP-QQQ technology.<blockquote>Presenter: Jeff Sayen (ICP-MS Application Scientist)Jeffrey Sayen s an ICP-MS Application Scientist at Agilent Technologies with over 15 years of experience in analytical chemistry. He specializes in atomic spectroscopy techniques, including ICP-MS, ICP-OES, and Flame AA. Jeffrey is passionate about ICP-MS and enjoys delivering product and application overviews at customer sites, seminars, and industry events. Prior to joining Agilent, he held the position of Senior Field Application Scientist at another major instrument manufacturer, where he focused on analytical methodologies across a range of regulated industries. He holds both undergraduate and graduate degrees in Inorganic Chemistry from Michigan State University.</blockquote>

Agilent Technologies: Atomic Spectroscopic webinars

Isotope Ratio made easy: Optimizing Method Conditions in 87Sr/86Sr Ratios with ICP-QQQ

Discover practical ICP-QQQ strategies for accurate 87Sr/86Sr isotope ratio analysis, including reaction gas selection, tuning, and interference control.

ICPMS webinars focusing on ICP/MS/MS - page 1