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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Join microwave digestion expert Macy Harris as she reviews sample prep for ICP-OES and ICP-MS analysis of food and cannabis samples.
In this webinar you will learn how microwaves digest samples, recommendations on sample size and acid combinations, what good vs. bad digests look like, and where to go for help when you need it. You will also have the opportunity to ask questions about your samples and processes.
<blockquote>
Presenter: Macy Harris (Applications Chemist, CEM Corporation)
</blockquote>
<blockquote>
Macy Harris graduated from Francis Marion University with a Bachelor of Science degree in Chemistry. She joined CEM shortly after graduating in 2017 where she brought her experience from a leading global plastics manufacturer to assist in the development and testing of the disposable Teflon products for the MARSXpress line. Macy works closely with customers to develop digestion methods for challenging samples, and solve difficult sample preparation issues. She is instrumental in providing supporting to current and potential customers in all industry areas.
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<blockquote>
Macy is an active member of the AAPFCO Methods Forum Group and the American Chemical Society.
</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>

Agilent Technologies: Demystifying Digestions: an Hour to Better Sample Prep

Demystifying Digestions: an Hour to Better Sample Prep

How microwaves digest samples, recommendations on sample size and acid combinations, what good vs. bad digests look like, and where to go for help.

Three-day virtual workshop covering 200.7 and 6010 methods from sample preparation to report generation, all in an environment where you can interact with peers and application experts from Agilent, who will be there to answer all your analytical questions.
You will Learn:
<ul>
<li>EPA Drinking Water, Waste Water, and Soil Analysis
</li>
<li>QC Parameter Setup
</li>
<li>Requirements and Techniques for Measuring Tough Samples
</li>
<li>Tips to Achieve the Highest Sensitivity
</li>
<li>Sample Preparation and Digestion Techniques
</li>
<li>Standard and QC Preparation for Trace Metal Analysis
</li>
<li>Data Analysis &amp; Processing
</li>
<li>Report Generation and Customization
</li>
</ul>
<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: 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: Ana García González (Atomic Spectroscopy Application Scientist, Agilent Technologies)
</blockquote>
<blockquote>
Ana Garcia is the Atomic Spectroscopy Application Scientist at Agilent Technologies. Ana has a broad background in atomic spectroscopy technologies, including international experience developing and validating analytical spectroscopy methods for the geochemical industry. She has also published in the fields of molecular spectroscopy and chemometrics. Ana holds a MSc in plant Biotechnology at CINVESTAV, México, and a Bachelor of Science in Biotechnology Engineering.
</blockquote>

Agilent Technologies: A dive into Sample Preparation and Digestion Techniques as well as Calibration Standard and QC Preparation for Trace Metal Analysis

A dive into Sample Preparation and Digestion Techniques as well as Calibration Standard and QC Preparation for Trace Metal Analysis

200.7 and 6010 methods from sample preparation to report generation.

A dive into Sample Preparation and Digestion Techniques

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is widely used throughout industry for its high sensitivity, wide dynamic range, and fast multi-element analysis.
Applications ranging from environmental compliance to product quality control to industrial and biological monitoring require fast, ultra-trace detection in complex, high matrix samples. The latest advances in instrumentation enhance performance, robustness, and ease of use, however, achieving trace and ultra-trace detection, accurate results, and productivity goals require challenges from the sample matrix and workflow inefficiencies to be addressed in addition to developing an optimized analytical method and maintaining the instrument in peak operating condition.
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
<ul>
<li>General best practices for the elemental analysis workflow to reduce systematic errors.
</li>
<li>Tips and tricks for standard solution handling, transfers, and preparation
</li>
<li>Advantages and disadvantages between the most common sample preparation methods for trace elemental analysis.
</li>
<li>Innovations in microwave digestion technology presented by CEM Corporation
</li>
</ul>
Who should attend
<ul>
<li>Laboratories performing trace elemental analysis by ICP-MS, ICP-OES, and AAS.
</li>
<li>Laboratories interested in ways to improve the efficiency of current standard and sample preparation processes.
</li>
<li>Analysts seeking information on systematic errors and how to reduce them for best analytical results.
</li>
<li>Laboratories interested in learning more about microwave digestion, the latest innovations, and benefits.
</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: Andy Fornadel (Product Marketing Manager, Thermo Fisher Scientific)
</blockquote>
<blockquote>
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.
</blockquote>
<blockquote>
Presenter: Michael Howe (Sr. Project Manager, CEM Corporation)
</blockquote>
<blockquote>
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.
</blockquote>

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

This month-long, five-parts Energy and Chemical application workshop will showcase all Agilent atomic spectroscopy techniques, including ICP-OES and ICP-MS, and MPAES.
Week 1: We will start this series with our experts discussing sample preparation and sample introduction.
Week 2: We first give an overview of all the ASTM methods our atomic spectroscopy applications support, followed by breakout sessions with our experts of each technique for more detailed discussions. Bring your questions and comments to this small group, technique specific discussions.
Week 3: We will focus on applications (besides the ASTM methods discussed last week), both common and unique. We will continue to have breakout sessions for each technique with smaller group size and more detailed discussion for these applications. We look forward to all your comments and questions.
Week 4: We will have a live demo in one of our Center of Excellence (COE) to show you the features in both software and hardware of our ICP-OES and MPAES. We will have real world samples for the analysis and showcase the exceptional results our systems can provide.
Week 5: The workshop&#39;s final week, we will continue the live demo with features in software and hardware of our ICPMS systems, both single quadrupole, and triple quadrupole. We will show the robustness of the systems for all sample types while maintaining ultralow level analyte determination. We will also highlight the ability of the triple quadrupole system to remove interference for certain difficult analytes. In these two weeks&#39; live events, we look forward to interacting with the audience to answer any questions regarding the application or our systems.
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Presenter: Jenny Nelson, PhD (Application Scientist, Agilent Technologies, Inc.)
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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.
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Presenter: Yan Cheung (Applications Chemist, Agilent Technologies, Inc.)
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Yan received her Ph.D. in Analytical Chemistry from Indiana University Bloomington. She joined Agilent Technologies as an Application Scientist in the Life Science and Chemical Analysis team in April 2020. Yan has extensive experience in operating and method development in ICP-MS. Yan also has years of experience working in the oil and gas industry.
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Presenter: Paul Krampitz (Application Scientist, Agilent Technologies, Inc.)
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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. 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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Presenter: Mark Kelinske (Application Scientist, Agilent Technologies, Inc.)
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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.
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Agilent Technologies: Agilent Atomic Spectroscopy in Energy and Chemicals Part 1: Sample Preparation and Sample Introduction in ICP-OES, MP-AES, and ICP-MS

Sample Preparation and Sample Introduction in ICP-OES, MP-AES, and ICP-MS

Discussing sample preparation and sample introduction.

Sample Preparation in ICP-OES, MP-AES, and ICP-MS

As our No. 1 priority remains everyone’s health and safety, please join our Virtual Workshop series of events as we work to do what we can to prevent further spread of the COVID-19 coronavirus.&nbsp;Join our two-hour Virtual Workshop on the analysis of metals in oil, petrochemicals, and edible oils in various semi-volatile and volatile solvents. Subject matter will include standard preparation, method development, internal standardization, and optimization for problematic elements. While you’re working remotely, join us online to learn how to further simplify and automate your organic analysis, from start-up through analysis.Agenda11:30 a.m. – 12:00 p.m.: Lecture &amp; Demo: Microwave Digestion - CEM12:00 p.m. – 12:15 p.m.: ICP-OES Hardware Overview12:15 p.m. – 12:45 p.m.: Live – ICP-OES oil analysis demo12:45 p.m. – 1:00 p.m.: ICP-MS Hardware Overview1:00 p.m. – 1:30 p.m.: Live – ICP-MS oil analysis demo<blockquote>Presenter: Paul Krampitz (Application Scientist, Agilent Technologies, Inc.)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. Experience also includes X-Ray Fluorescence (ED, WD), Laser Ablation, Inorganic Speciation and Microwave Plasma Spectroscopy. Market Segment expertise includes environmental, petrochemical, metallurgical applications.Presenter: Bert Woods (Application Scientist, Agilent Technologies, Inc.)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>

Agilent Technologies: Agilent Webinars On Demand

Virtual Petrochem & Edible Oil Workshop - Agilent Petrochemical Workshop on ICP-OES and ICP-MS

Join our two-hour Virtual Workshop on the analysis of metals in oil, petrochemicals, and edible oils in various semi-volatile and volatile solvents

Agilent Petrochemical Workshop on ICP-OES and ICP-MS

Join us for an insightful webinar in which we'll focus exclusively on the advancements and applications of ICP-OES. Gain in-depth knowledge of how this technique can enhance the workflow efficiency of the analysis of advanced materials samples (including plastic and solid electrolyte) in your laboratory. Don't miss this opportunity to stay ahead in the restriction of hazardous substances (RoHS) compliance and electrolyte testing with the latest innovations.In the first presentation, we will explore the European Union's &nbsp;RoHS directive limits on specific hazardous materials in electrical and electronic equipment (EEE). Compliance with RoHS regulations, especially in testing complex materials, such as plastics, poses challenges for manufacturers, importers, and distributors. ICP-OES provides a robust solution for RoHS compliance testing in terms of measurement of Cd, Cr, Pb, and Hg. The presentation highlights the detailed sample preparation and precise element analysis by ICP-OES, featuring Intelligent Rinse technology.In the second presentation, we will go on to explore solid-state batteries as an emerging battery technology that uses a solid superionic electrolyte material instead of traditional liquid-phase electrolytes. Learn more about this emerging technology as well as how ICP-OES can provide a simple way to accurately determine contaminants and ensure the quality of the final battery.<h5>By attending this presentation, you will learn:</h5><ul><li>Gain a comprehensive understanding of how inductively coupled plasma optical emission spectrometry (ICP-OES) can perform accurate analysis of hazardous substances in EEE for RoHS compliance testing and in electronic waste (e-waste) for monitoring and research purposes, while improving your laboratory’s efficiency and productivity.</li><li>Gain an understanding of solid-state battery technology and discover how to overcome hurdles while analyzing solid electrolyte using ICP-OES.</li></ul><h5>Who should attend:</h5><ul><li>Analytical chemists working in elemental analysis, materials scientists and engineers working with solid-state electrolytes or batteries, environmental scientists interested in RoHS compliance testing, quality assurance, and regulatory compliance, personnel involved in ensuring products meet RoHS or other regulatory standards, researchers in academia, and laboratory technicians and managers.&nbsp;</li></ul><blockquote>Presenter: Aimei Zou, Ph.D (Solution Scientist, Agilent Technologies, Singapore)Aimei joined Agilent in 2018 as a solution scientist based in Singapore. She received her Ph.D in Analytical Chemistry in 2008. Aimei has over 17 years of experience in method development, covering dynamic technologies from atomic spectroscopy, including ICP-MS, ICP-OES, and AAS, to LC and GC mass spectrometry. In her current role with the Global Solution Development Center, Aimei focuses on developing integrated workflow solutions for food, environmental, and emerging markets.Presenter:&nbsp;Ruby Bradford (Application Chemist, Agilent Technologies, Melbourne, Australia)Ruby is an application chemist at Agilent Technologies, having worked in the Atomic Spectroscopy Division since 2020. She works frequently on the analysis of fine chemicals using techniques such as ICP-OES and is experienced in method development and sample preparation techniques in the advanced materials sector. She has a particular passion for the booming lithium-ion battery market and promoting a sustainable future through electrification.</blockquote>

SeparationScience: Advanced ICP-OES Applications: From RoHS Compliance to Solid Electrolyte Analysis

Advanced ICP-OES Applications: From RoHS Compliance to Solid Electrolyte Analysis

Gain insights into how ICP-OES can optimize workflows for the analysis of complex materials.

ICP-OES Applications: Solid Electrolyte Analysis

Mercury has been banned in cosmetics by regulatory agencies, but it persists in some formulations of cosmetic products. Despite the serious health risks associated with its use, mercury is still an attractive ingredient of cosmetic products claiming to lighten skin and remove blemishes. Fraudulent creams and cosmetic products take advantage of mercury's cost-effectiveness and ability to extend shelf life. Because of these properties, mercury in its toxic form, methylmercury, can also be added later to products that have already been manufactured.<h4>The Need for Regulation and Analytical Methods</h4>The identification of such substance is central to the various regulatory frameworks. ISO has addressed this issue by introducing ISO 23674:2022, which emphasizes the use of direct mercury analysis and the ISO 23821:2022 which involves sample preparation and CV-AAS.Together with our guest speaker Dr. Maximilian Orlandi, Chemistry Lab Manager at Complife Group who has deep knowledge of the analysis of cosmetics and the ISO procedures and Iacopo Avolio, Product Specialists at Milestone, we will review the benefits of these methods.This webinar aims to highlight procedure of quantification of mercury traces in cosmetic products that consumers can be exposed to in their usage. These methods describe the determination of mercury traces in cosmetics by using direct solid analysis with no need of digestion or by CV-AAS that requires acid digestion.<blockquote>Speaker: Iacopo Avolio (Product Specialists at Milestone)Speaker: Maximilian Orlandi (Chemistry Lab Manager at Complife Group)</blockquote>

Milestone: Mercury Analysis in Cosmetics: A deep dive into the latest ISO analytical methods for trace metal determination

Mercury Analysis in Cosmetics: A deep dive into the latest ISO analytical methods for trace metal determination

Webinar aims to highlight procedure of quantification of mercury traces in cosmetic products that consumers can be exposed to in their usage.

Mercury Analysis in Cosmetics

Engine coolants are critical to prevent overheating, corrosion, and premature engine wear. Over time, coolant formulations degrade—additives deplete, mixtures become imbalanced, and trace metals from engine components accumulate. Monitoring these changes provides early warning signs of mechanical issues and supports the development of effective maintenance schedules.&nbsp;As a result, many in-service laboratories that already analyze hundreds of engine lubricants are now tasked with coolant analysis as well, creating challenging workloads, increasing consumable costs, and introducing more opportunities for handling errors.&nbsp;ASTM D6130 defines the standard method for determining 12 elements in coolants using ICP-OES. In this work, we demonstrate how pairing the Agilent 5900 ICP-OES with the ADS 2 auto-dilution system simplifies this process while delivering a stable, reproducible, and accurate method for ASTM compliance. By automating both sample and standard preparation, the ADS 2 reduces manual steps, improves consistency, and saves valuable lab time—making it an ideal solution for high-throughput environments.<blockquote>Presenter: Luke Gormley (Pre-Sales Application Engineer, Agilent Technologies, Inc.)Luke earned his Bachelor of Science in Chemistry from Clemson University in South Carolina. He began his career at an environmental contract testing laboratory, where he used EPA methods for routine ICP-OES analysis. Later, he expanded his role by joining the laboratory’s instrument service and repair team, troubleshooting a wide range of analytical instruments and testing equipment. In 2025 Luke joined Agilent Technologies, where he now works as an Application Scientist, supporting the ICP-OES, MP-AES, and AA product lines.</blockquote>

Agilent Technologies: Automation in Trace Metal Analysis of Engine Coolants

Automation in Trace Metal Analysis of Engine Coolants

Agilent 5900 ICP-OES with ADS 2 simplifies ASTM D6130 coolant analysis through automated dilution, improving accuracy, reproducibility, and lab efficiency.

ICPMS webinars focusing on Sample prep - page 1