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

Scientific article

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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Shimadzu Corporation

Two years have passed since we hosted our first microplastics symposium.
Since then, the microplastic landscape has witnessed significant developments—the impending release of the first ISO standard and ongoing advancements in SOPs. We are pleased that we can bring you together with experts in our field.
This digital conference aims to explore various crucial topics related to the analysis of microplastics, covering areas such as sampling, sample preparation, analysis, and evaluation.
<h3>Highlights – Why you should attend</h3>
<h5>Stay updated on microplastic analysis</h5>
Gain insight into the latest advancements and challenges in microplastic analysis. This seminar covers essential aspects such as sampling, sample preparation, and analysis techniques like spectroscopy (ICP-MS) and chromatography (pyr/TED-GC/MS). 
<h5>Explore diverse applications</h5>
Discover the wide range of applications beyond microplastic analysis that can be addressed with a QCL-based IR imaging system like the LDIR 8700. Get an overview of its potential in areas such as materials, bio, and pharmaceuticals.
<h5>Take part in a live demo</h5>
Witness a live demonstration of an automatic microplastic analysis workflow. Experience firsthand how these techniques and technologies come together to address real-world challenges. Engage with Agilent experts who will answer any questions you may have.
<h5>Showcase your expertise</h5>
Actively participate by presenting your work and contributions in techniques like TED-GC/MS, pyr-GC/MS, and ICP-MS, which are crucial for microplastic analysis. Alternatively, highlight your knowledge of the versatile LDIR 8700 system, showcasing its applications in pharmaceuticals, material analysis, or bio sectors.
<h3>Agenda</h3>
<h5>09:00 Welcome Introduction &amp; Video of Geoff Winkett , Agilent Technologies</h5>
<h5>9:10 The World of Microplastics Up to Date an Overview</h5>
<ul>
<li>Andreas Kerstan (Agilent Technologies)</li>
</ul>
<h5>09:30 Hot news on Agilent LDIR, new developments, and future perspective</h5>
<ul>
<li>Wesam Alwan , Darren Robey (Agilent Technologies)</li>
</ul>
<h5>09:50 Release of Plastic Additives and Microplastic Particles from Different Consumer Products into Water under Accelerated UV Weathering Conditions</h5>
<ul>
<li>Lars Hildebrandt (Scientist, Helmholtz Zentrum Hereon)</li>
</ul>
Photodegradation of plastic products is known to accelerate weathering and the resulting release of chemical additives and particles to the environment, however these processes are complex. Here, eight different plastic consumer products were leached in double distilled water under exposure to strong ultraviolet (UV) light for ten days, and the chemical composition of the leachates was compared to their respective dark controls. The leachates and plastic particles were investigated with a wide battery of chemical analytical tools to broadly characterize the underlying processes and possible hazards. These covered (a) metal(loid) analysis, (b) microplastic analysis, (c) analysis of &gt;70 organic target analytes and (d) nontargeted screening of the extracts.
<h5>10:10 Identification of Polymers Using Machine Learning</h5>
<ul>
<li>Xin Tian (Scientific Researcher, KWR NL)</li>
</ul>
Microplastics and other polymers are found in the environment. For this reason, it is important to have reliable methods to identify them. Methods used to detect nano- and microplastics in the environment include Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, laser-directed infrared (LDIR) spectroscopy and thermogravimetric analysis (TGA)/pyrolysis. These measurement techniques can provide a lot of information, but sometimes require a database with a lot of high-quality data to compare measurement results. Machine learning (especially classification models) can help improve data processing and accuracy.
Recent research has looked at how machine learning can help improve the accuracy of identification with infrared spectroscopy. Different computer models were tested and examined to see if the accuracy increases and if it does not require an unreasonable amount of computing power and time. This research focused on finding an effective method for identifying polymers in the environment based on their mid-infrared spectroscopic signals.
Polymers are identified by infrared spectroscopy by comparing their spectra with spectra in a database/library. This works well for new polymers, which are clean and barely degraded. Since polymers from the environment are actually degraded, comparing their infrared spectra with spectra in the library is difficult. This is because the spectra in the library often have large deviations from the spectra of the measured polymers. Increasing the number of spectra in the library is not possible because the number of spectra of environmentally degraded polymers is almost infinite. The study therefore looked at whether the problem of small data sets can be addressed using machine learning. The research presents a data enrichment technique to generate spectra of degraded polymers from single spectra of a limited number of samples. Four models were tested using these spectra to identify polymers. The study shows that all the models achieve high success rates, thereby facilitating the identification of polymers from environmental samples. Moreover, the research shows that it is not necessarily the most advanced computer model (particularly deep neural network models) that yields the best results.
<h5>10:30 From the River to the Sea: Microplastics in Sediments of the Thames River</h5>
<ul>
<li>Friederike Strock (Postdoc, German Federal Institute of Hydrology)</li>
</ul>
Microplastics have been investigated for over 45 years especially in the marine environment, but only in the past years research has started to focus on freshwater environments. In the frame of the H2020 LABPLAS project, sediments along the course of the Thames river in its freshwater and estuarune part were studied in order to better understand the sources, transport, distribution and impacts of plastic pollution and to detect the amount of plastics transport via the rivers into the sea.
In the frame of the project, a winter and a summer campaign were conducted 2022 and samples taken from 6 sites within the study area. Sediment samples were taken with a Van Veen grabber from the edge of the river, wet sieved into different compartments (10 100 µm, 100 1000 µm, &gt;1000 µm), density separated and the organic matter digested. The plastics from the sediments were characterized with a Laser Direct Infrared (LDIR). The preliminary results reveal that microplastics are present in all samples. The amount of particles varies significantly between the sampling sites showing the importance of industrial emissions and cities.
<h5>10:50 Good Laboratory Practices to Characterize Microplastics Using Quantum-Cascade Laser Reflectance Absorbance Spectrometry</h5>
<ul>
<li>Jose Manuel Andrade Garda (Professor Analytical Chemistry, University of A Corunna)</li>
</ul>
The nowadays broad societal interest in microplastic pollution demands urgent responses and actions. For these be possible politicians must set rules which, in turn, are not possible at all without sound scientific data. Unfortunately, there is a general feeling that the experimental results obtained so far are not still fully comparable and, further, that the monitoring field where hundreds or samples are taken is not being fully considered. Scientific studies and future regulations depend critically on a reliable identification of the polymers (if any) that constitute the suspicious particles under study. Out of the various analytical techniques to characterize them a novel one based on reflectance-absorbance spectrometry, commercialized as LDIR, outstands. It uses a tuneablemid-IR quantum cascade laser (QCL) to imaging a reflective microscopy slide or a metal-coated filter in a remarkable small timeframe. This communication is meant to present best practice guides to overcome some obstacles/difficulties in routine measurements, and open a path for field monitoring; among them: the adequacy of the spectral range, the variation of the peak&#39;s intensities with the size of the particles; the speed of the analysis as a function of the instrumental setup; the criterion to identify unknown spectra (a tiered approach is finally suggested); and how to differentiate fibers and fragments semiautomatically. Also, an empirical dependence of the depth of penetration of the QCL laser in common plastic particles is approached first time.
<h5>11:10 Chemical Characterization of Microplastics using Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC-MS)</h5>
<ul>
<li>Soledad Muniategui-Lorenzo (Pull Professor of Analytical Chemistry, University of A Corunna)</li>
</ul>
The implementation of monitoring programs for Microplastics requires reliable and standardisedmethods. Fourier Transform Infrared (FTIR) and Raman spectroscopy techniques are the most commonly used for Microplastics analysis. However, thermal analytical techniques are currently gaining popularity. This presentation focuses on the potential of mass-based thermal analytical techniques, in particular, Pyrolysis coupled with Gas Chromatography-Mass Spectrometry (Py-GC-MS), for the accurate qualitative and quantitative analysis of microplastics in environmental matrices. It outlines some advantages and good laboratory practices of this approach, the importance of method normalisation, and how it can provide detailed information on polymers and plastic additives.
<h5>11:20 Analysis of Fibrous Microplastics Using Laser Direct Infrared Imaging</h5>
<ul>
<li>Monique Greiner (Research Associate, Hohenstein Laboratories)</li>
</ul>
In the research field of microplastics the identification of their source is important in order to develop strategies to minimize the pollution. A major percentage of microplastics originates from textiles. One pathway into the environment are washing procedures because the textiles release fibers during the process. Therefore our aim was to find a fast and easy way to identify fibers. In our presentation we want to give insights in our approach to the analysis of fibrous microplastics with the LDIR 8700. We will talk about our strategies, the results we achieved and difficulties we faced.
<h5>11:40 Looking beyond the Polymer: Using Thermal Desorption GC MS to expand our understanding of Microplastics</h5>
<ul>
<li>Jan Peter Mayser (Market Specialist, Markes International)</li>
</ul>
Detecting and analysingmicroplastics in the environment is challenging. The method must be able to detect and distinguish between a large variety of polymers. Additives, such as hardeners, flame retardants and preservatives, used during the manufacturing process and other compounds, that can adhere to the surfaces of microplastics from their environment, can affect their toxicity assessment. These additives could be used to link the microplastics found in the environment to their original use or potentially even back to the manufacturer.
In this study, various salts were sampled and filtered and analyzed for their microplastic content. TD–GC–MS was used to identify and measure which concentration of the plastic PS, PET, PVC and Nylon 6 had been incorporated into the crystalline structure of the salt during evaporation. By using direct desorption and backflushing technology, a large sample size could be easily isolated from the lab environment during analysis while ensuring a large range of volatile organic compounds (VOCs) including the marker compounds for four polymers could be trapped and analyzed.
The VOC-profile of the microplastics not only gave information about the polymer and its concentration within the sample, but further information about the toxicity could be extracted. This enabled the determination and tentative identification of additional compounds in the samples, such as dimethyl ether, acrolein and cyclopentane. These are used in the process of manufacturing plastics, so could assist with identifying the source of the plastics. For the four analysed polymers distinct marker compounds could be identified and calibration curves determined for each polymer. In all of the real-world salt samples microplastics were identified, highlighting the ubiquitous nature of the microplastic contamination.
This further information about the origin of the polymer, as well as the origin of the microplastic particles can be gathered by investigating the full VOC-profile obtained by TD-GC-MS. This allows both additional polymer information and particle source characterization.
<h5>12:00 Tiny Problems</h5>
<ul>
<li>Roxana Sühring (Assistant Professor in Analytical Environmental Chemistry, Toronto Metropolitan University)</li>
</ul>
Microplastics have been on the front page of newspapers, a dominant topic for environmental research (and funding), and a recent focus for regulatory action across the globe. Their potential impacts have been classed as a planetary boundary threat and new studies are published daily, reporting microplastics virtually anywhere on the planet. But despite numerous publications, there are still a lot of open questions on how to effectively and reproducibly characterize microplastics. How can microplastic characterization be automized? What is the impact of additives or weathering on the characterization accuracy?
In this presentation I will provide an overview and the first results of a research collaboration between Agilent technologies and the Emerging contaminants lab at Toronto Metropolitan University that works on addressing some of these questions. Our research aims to create a versatile microplastic library using weathered and new plastics commonly found in the environment. This library will additionally be used as a training set for developing automated particle characterization for the LDIR.
<h5>12:20 Identification of Microplastic Particles in Soil Using LDIR</h5>
<ul>
<li>Martine Graf, PhD (Student &amp; Senior Technician, Bangor University)</li>
</ul>
The use of agricultural plastic has become increasingly concerning in an environmental setting in recent years; in Europe alone, an estimated 2.5 million tones of plastic mulch films are used each year. The use of mulch films for crop production has been promoted by governments worldwide due to its many benefits, however the removal of these films from the soil can be difficult due to their poor mechanical strength and fragmentation, and barriers such as poor incentives for farmers and underdeveloped infrastructure for collection and disposal. The latter often leading to the films being discarded or incinerated along field margins, or ploughed back into the fields, leading to an accumulation of plastic legacy in soil. To evaluate the microplastic pollution levels in agricultural soils, we are i ) conducting a global soil survey in all partner countries; ii) assessing the degradation and fragmentation of conventional and biodegradable plastic mulch films in soil, and measuring the resulting microplastic production rate; and iii) measure the degradation and movement of microplastic in soil after repeated application. Microplastics are extracted from soil using targeted methods for different polymer types, and analysed using fluorescent microscopy, FTIR spectroscopy, and LDIR spectroscopy.
<h5>12:40 Wrap up and open discussion</h5>

Agilent Technologies: Agilent Microplastics Virtual Symposium 2023

Agilent Microplastics Virtual Symposium 2023

Explore various crucial topics related to the analysis of microplastics, covering areas such as sampling, sample preparation, analysis, and evaluation.

Calling all food safety analysts! Gear up for an exciting session with us on Digital Classrooms into the heart of food safety analysis, focusing on 3 crucial aspects: organic contaminants identification, elemental analysis, and the pressing issue of PFAS.
Our dedicated expert, Qi An, will kick off the session by introducing Shimadzu’s innovative FTIR analysis workflow that identifies organic contaminants in just seconds to boost your productivity at work. Besides, explore the flexibility offered by various FTIR configurations tailored to analyze different contaminant sizes and uncover the capabilities of <a href="https://icpms.cz/products/849">Shimadzu LabSolutions IR software</a>, particularly on its Food Additive Identification and Contaminant Analysis Macro programs for robust data analysis.
Following that, our seasoned expert Mangesh will delve into elemental analysis, demonstrating how Shimadzu’s ICP-MS is ushering in a new era without compromise. Whether it&#39;s the nourishing minerals in milk or the potentially harmful elements in fruit juice, Shimadzu&#39;s ICPMS accurately quantifies both micro and macro elements present in our daily diet.
Lastly, our specialist, Elton, will address the emerging food safety concern of PFAS in food. Gain valuable insights into the evolving regulatory landscape, explore the current EFSA and FDA guidelines, and discover measures to manage this complex issue. Specifically, Elton will introduce how Shimadzu&#39;s LC-MS/MS solutions can effectively address PFAS concerns in food.
Don&#39;t take any chances with food safety – Make it your priority. Level up your approach in contaminant analysis with us today. Register now!
Learning Objectives
<ul>
<li>Learn how Shimadzu’s FTIR analysis can enable quick characterization of organic contaminants
</li>
<li>Understand how LabSolutions IR software can effectively translate spectral data into actionable insights
</li>
<li>Discover the capabilities of Shimadzu’s ICP-MS to detect harmful elements in food
</li>
<li>Explore how Shimadzu’s LC-MS/MS solutions can effectively address PFAS concerns in food
</li>
</ul>
<blockquote>
Presenter: Tan Qi An (Application Specialist, Shimadzu (Asia Pacific) Pte Ltd)
</blockquote>
<blockquote>
Qi An is a highly skilled professional with a bachelor&#39;s degree in Chemistry and Biological Chemistry from Nanyang Technological University, Singapore. His passion for food science led him to pursue a concurrent second major in Food Science and Technology from Wageningen University. With over two years of experience as an Application Specialist for spectroscopy and TOC instruments at Shimadzu Asia Pacific, Qi An has successfully conducted pre-sales demonstrations, sample analysis, and provided application support across diverse industries. His expertise and commitment to delivering high-quality solutions make him a valuable asset to the field of analytical chemistry.
</blockquote>
<blockquote>
Presenter: Elton Goh (Senior Product Specialist (GCMS), Shimadzu (Asia Pacific) Pte Ltd)
</blockquote>
<blockquote>
Elton is a dedicated and experienced Food Market Specialist at Shimadzu, bringing over nine years of expertise in food safety and analytical chemistry to his role. His career began at the Singapore Food Regulatory Board, where he spent seven years honing his skills and developing a profound understanding of regulatory standards and testing protocols. With a passion for knowledge and innovation, Elton transitioned to the private sector, contributing significantly to the advancement of analytical techniques and the development of novel food safety solutions during his two-year tenure at a research and development centre.
</blockquote>
<blockquote>
Now at Shimadzu, Elton continues to excel, leveraging his expertise to develop cutting-edge analytical methods for detecting and quantifying various compounds in food products. His commitment to food science is evident in his efforts to enhance safety standards, build consumer trust, and make meaningful contributions to the global food industry.
</blockquote>
<blockquote>
Presenter: Mangesh Pawar (Deputy Manager - CSC, Shimadzu Analytical (India) Pvt Ltd)
</blockquote>
<blockquote>
Mangesh S. Pawar is a seasoned professional with a master&#39;s degree in physical chemistry from Mumbai University. With nearly nine years of expertise in the pharmaceutical sector, Mangesh has a rich background, having worked for reputable companies such as Teva Pharmaceuticals, Inventia Healthcare, and Cipla Ltd. Over the past nine years, he has been an integral part of the Shimadzu team in India, accumulating a total of eighteen years of experience.
</blockquote>
<blockquote>
Mangesh specializes in elemental, thermal, and spectroscopic techniques at Shimadzu, where he plays a crucial role in assisting clients throughout India both before and after-sales. In order to fulfil Shimadzu&#39;s ultimate objective of offering a complete solution and ensuring customer satisfaction, pre-sale interactions with customers, instrumental trainings, and troubleshooting during routine analysis are of Mangesh’s particular focus of interests.
</blockquote>

Shimadzu: For the Love of Food! Solutions for Contaminants From PFAS to Heavy Metals

For the Love of Food! Solutions for Contaminants From PFAS to Heavy Metals

Analysis of Food Contaminants From PFAS to Heavy Metals

As part of the global effort to reduce CO₂ emissions, biofuels are becoming an increasingly important source of green energy.
Quality control testing of biofuels is therefore crucial to ensure the efficiency and reliability of biogas, biodiesel, and fuel ethanol. 
In this webinar you will learn about the latest laboratory testing techniques that are used to ensure the quality, efficiency, and sustainability of modern biofuels to enable producers to confidently meet international regulatory requirements and to promote their widespread adoption in both industry and the wider society at large. 
Experts from Agilent Technologies will introduce a wide range of analytical testing solutions covering multiple technologies that are routinely used to detect organic and inorganic impurities in biodiesel and enable the stringent quality control of fuel ethanol, biogas and biogas blends to be achieved. The expert panel will be available to answer questions from the audience at the end of the presentation. 
<blockquote>
Presenter: Danny van Oevelen (LC Product Specialist, Agilent Technologies)
</blockquote>
<blockquote>
Presenter: Luca Godina (GC &amp; GC/MS Application Specialist, Agilent Technologies)
</blockquote>
<blockquote>
Presenter: Sebastien Sannac (Spécialiste produit spectroscopie atomique, Agilent Technologies)
</blockquote>
<blockquote>
Presenter: Donald Inglis (Product Specialist EMEAI for FTIR, Agilent Technologies)
</blockquote>
<blockquote>
Presenter: Remko van Loon (GC &amp; GC/MS Product Specialist, Agilent Technologies)
</blockquote>

Agilent Technologies: Comprehensive Quality Control Testing of Biofuels to Ensure a Greener, more Sustainable Future

Comprehensive Quality Control Testing of Biofuels to Ensure a Greener, more Sustainable Future

Learn about the latest laboratory testing techniques that are used to ensure the quality, efficiency, and sustainability of modern biofuels.

Comprehensive Quality Control Testing of Biofuels

How well do you know FTIR and ICP-MS? Join us for an engaging Digital Classrooms session, where our experts will provide practical insights and explore the real-world applications of these essential analytical techniques.Discover how Shimadzu’s advanced FTIR and latest ICP-MS technologies enable precise molecular and elemental analysis across a variety of samples. Through compelling case studies, you’ll see how Shimadzu's solutions are transforming workflows including environmental monitoring, pharmaceuticals analysis, and materials science studies.This session offers a unique opportunity to deepen your understanding of the core principles, extensive applications, and distinct advantages of FTIR and ICP-MS. Engage with professionals, explore the best practices, and gain the practical knowledge to effectively elevate your analytical capabilities.Don’t miss this chance to enhance your expertise. Register now to secure your spot!<h5>Learning Objectives:</h5><ul><li>Develop an advanced understanding of the core principles, operational mechanisms, and key components of FTIR and ICP-MS</li><li>Explore a wide range of applications for FTIR and ICP-MS across industries, and learn how to effectively apply these techniques in lab work</li><li>Gain insights into best practices from sample preparation to analysis and data reporting&nbsp;</li></ul><blockquote>Presenter: Tan Qi An (Product Specialist (Spectroscopy), Shimadzu (Asia Pacific) Pte Ltd)Qi An is a highly skilled professional with a bachelor's degree in Chemistry and Biological Chemistry from Nanyang Technological University, Singapore. His passion for food science led him to pursue a concurrent second major in Food Science and Technology from Wageningen University. With over three years of experience in Spectroscopy and TOC instruments at Shimadzu Asia Pacific, Qi An has successfully conducted pre-sales demonstrations, sample analysis, and provided application support across diverse industries. His expertise and commitment to delivering high-quality solutions make him a valuable asset to the field of analytical chemistry.Presenter: Nancy Tan Ning Xin (Application Specialist (Spectroscopy), Shimadzu (Asia Pacific) Pte Ltd)Nancy holds a bachelor's degree in Chemistry and Biology from Liverpool John Moores University in the United Kingdom. With over ten years of experience in laboratory and instrumentation processes, she has developed a strong background in testing, research and development. As an Application Specialist for Spectroscopy and TOC instruments, she leverages her expertise to conduct pre-sales demonstrations, perform sample analyses, and provide application support across a variety of industries.</blockquote>

Shimadzu Corporation: All About ICP-MS And FTIR: Essential Insights And Practical Applications

All About ICP-MS And FTIR: Essential Insights And Practical Applications

Discover how Shimadzu’s advanced FTIR and latest ICP-MS technologies enable precise molecular and elemental analysis across a variety of samples.

ICP-MS & FTIR: Key Insights and Practical Applications

As cosmetic formulations grow more complex and regulations tighten, ensuring product safety, compliance, and sustainability requires advanced analytical solutions. This webinar brings together expert-led sessions and real-world insights that cover three key challenges: raw material testing, nanoparticle characterization, and fragrance allergen analysis.<ul><li>New Standard XP CEN ISO/TS 19590:2024 – Characterization of Nano-Objects Using Single Particle ICP-MS. Application to Cosmetics: Explore the ISO/TS 19590:2024 standard, and hear from guest speaker Mathieu Menta (UT2A) who will present its applications in cosmetics, highlighting both technical and regulatory perspectives.</li><li>Raw Material Testing Through Bags &amp; Closed Containers with the Vaya Handheld Raman System: Discover how innovative spatially offset Raman spectroscopy (SORS) technology &nbsp;allows non-destructive identification &nbsp;through transparent and opaque packaging—eliminating sampling waste, improving productivity, and supporting ISO 22716 GMP compliance and sustainable practices.</li><li>Analysis of Fragrance Allergens: Following European Regulation 2023/1545: Learn how Agilent’s GC/TQ workflow helps cosmetics manufacturers comply with new allergen regulations by reliably identifying and quantifying fragrance allergens—even in complex formulations—while minimizing false results.</li></ul><h5>Key learning objectives:</h5><ul><li>Learn how to verify raw materials directly through packaging using Raman spectroscopy to eliminate sampling and reduce waste</li><li>Apply ISO/TS 19590:2024 for accurate characterization of nanoparticles in cosmetic formulations using single-particle ICP-MS</li><li>Gain practical insights from a customer case on implementing spICP-MS for nano-object analysis under real regulatory and quality constraints</li><li>Quantify fragrance allergens in complex cosmetic matrices with high selectivity and sensitivity using GC/TQ</li><li>Enhance analytical workflows by minimizing sample handling, reducing false identifications, and improving compliance with current regulations</li></ul><h5>Who should attend?</h5><ul><li>QC/QA professionals in cosmetics and pharmaceuticals</li><li>Regulatory and compliance managers</li><li>Analytical scientists, chemists and lab managers</li><li>R&amp;D teams</li><li>Anyone involved in nanoparticle characterization, raw material verification, or cosmetic testing</li></ul><blockquote>Presenter: Hansel Koelblen (Application Engineer - GC &amp; GC/MS, Agilent Technologies)Hansel has worked with GCMS instrument for almost 10 years. He joined Agilent in 2017, first as a Field Service Engineer and now holds the position of France GC &amp; GC/MS Application Engineer.Presenter: Thibault Brule (Product Specialist – Molecular Spectroscopy, Agilent Technologies)Thibault Brule is Molecular Spectroscopy Product Specialist. He joined Agilent Technologies on November 2024. His main role is to provide applicative and technical support to the network on UV-Vis-NIR, FTIR and Raman spectroscopies.Presenter: Yolande Abdelnour (Product Specialist - Atomic Spectroscopy, Agilent Technologies)Yolande Abdelnour holds a Ph.D. in Chemical and Plasma Process Engineering from “Ecole Supérieure de Chimie” in Paris and “University of Paris Sorbonne”. She worked as a research engineer at “Photowatts” for 3 years and then joined Varian in 1997 as European ICP-MS product specialist. Since 2010, she occupies within Agilent Technologies the position of Product Specialist for the Atomic Spectroscopy techniques including Atomic Absorption, Microwave Plasma, Inductively Coupled Plasma coupled to Optical Emission Spectroscopy, Single Quad and Triple Quad Mass Spectrometry.Presenter: Mathieu Menta (Application Engineer, Ultra- Trace Analyses Aquitaine (UT2A) - Pau)Mathieu Menta is Applications Engineer at UT2A since 2011. He is responsible for the physico-chemical characterization of nanomaterials and the speciation of trace elements by elemental mass spectrometry. He is also involved in project management and quality assurance. He has co-authored several scientific publications, notably on the quantification of nanoparticles in food, cometics ans pharmaceutics using spICP-MS and on the rapid and accurate determination of elemental impurities in pharmaceutical products using a combination of standard addition and isotope dilution methods</blockquote>

Agilent Technologies: Characterization in Cosmetics: Nano-Objects ISO 19590:2024, Raw Material & Fragrance Allergens

Characterization in Cosmetics: Nano-Objects ISO 19590:2024, Raw Material & Fragrance Allergens

Ensure safety and compliance in cosmetics with insights on raw materials, nanoparticles, and allergens. Discover cutting-edge tools like ICP-MS and Raman SORS.

ICPMS webinars focusing on ICP/MS - page 1