<h5><strong>Why compromise between performance and price when you can have both?</strong></h5><p><strong>With Thermo Scientific factory-certified, pre-owned </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products?category=5&amp;manufacturerItems=3"><strong>mass spectrometers</strong></a><strong>, you can access legendary LC-MS technology—trusted around the world—at a fraction of the cost of buying new. Our refurb program delivers the quality, precision, and reliability you expect from Thermo Fisher Scientific, while helping you stay within budget and on top of your analytical goals.</strong></p><h3><strong>Factory-Certified for confidence</strong></h3><p>Every certified pre-owned system goes through a <strong>rigorous factory reconditioning process</strong>. From updated hardware and software to comprehensive performance testing, each instrument is restored to meet the same high standards as our new products.</p><h4><strong>What’s included?</strong></h4><p>When you choose a certified LC-MS system, you get more than just an instrument—you get the <strong>complete Thermo Scientific experience</strong>:</p><ul><li><strong>Full 1-year factory warranty</strong> for peace of mind</li><li><strong>29-point inspection checklist</strong>, re-certification, and final quality testing</li><li><strong>Software and hardware updates</strong> to current revisions</li><li>Re-certification using <strong>only genuine Thermo Scientific factory parts</strong></li><li><strong>Professional installation</strong> by Unity Lab Services field engineers</li><li><strong>Optional training and application support</strong> to get you up and running fast</li></ul><h4><strong>What gets replaced?</strong></h4><p>Our reconditioning process is comprehensive. 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Personalized equipment </strong><a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/content/lifetech/global/en/home/products-and-services/services/financial-leasing-services.html"><strong>financing &amp; leasing options</strong></a></h4><p>If upfront capital is limited, our tailored financing and leasing plans offer flexibility that aligns with your lab’s budget and growth plans.</p><h5><strong>Ready to get started?</strong></h5><ul><li><a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/content/lifetech/global/en/home/industrial/mass-spectrometry/mass-spectrometer-price-affordability-programs.html"><strong>Explore our certified systems, trade-in opportunities, and financing solutions.</strong></a></li></ul><p><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong><u>LinkedIn:</u></strong></a><strong>&nbsp;</strong>#affordabiliy #LCMS #sustainability #productivity</p><blockquote><h5><strong>Ema Ruzic</strong></h5><p>Vertical Marketing Manager, Chromatography and Mass Spectrometry Division (CMD)</p></blockquote>

Unlock High-Performance LC-MS with Factory-Certified Systems from Thermo Fisher Scientific

<p><strong>Metalloproteins play essential roles in marine phytoplankton, yet their metalloproteomes remain poorly characterized. This study combines protein modeling, quantitative proteomics, and ICP-MS measurements to assess metal requirements across several phytoplankton species, including chlorophytes, a haptophyte, and a cyanobacterium.</strong></p><p>Results show strong agreement between proteome-inferred metal demands and measured cellular metal quotas, while providing deeper insight into biological functions. Mg-containing proteins were most abundant overall, with Zn, Fe, and Mn as dominant trace cofactors. Distinct differences between prokaryotic and eukaryotic phytoplankton were observed, and strain-level analysis demonstrated how metalloproteomes reflect environmental adaptation and metal limitation strategies.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233"><strong>Unlocking Phytoplankton Metallomes with Comparative Analysis of Metal Quotas, Quantitative Proteomics, and Inferred Metalloproteomes</strong></a></h4><p>Qiong Zhang*, Jiayou Ge, Fengjie Liu, Shabaz Mohammed, Kedong Yin, and Rosalind E. M. Rickaby</p><p>Environ. Sci. Technol. 2025, 59, 50, 27367–27377</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.est.5c11233">https://doi.org/10.1021/acs.est.5c11233</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><p>Many important biological processes of phytoplankton, including photosynthesis, carbon fixation, and nitrogen reduction, rely on enzymes that have metals as cofactors. <a href="javascript:void(0);">(1)</a> It has been estimated that half of all enzymes must be associated with a particular metal to function. <a href="javascript:void(0);">(2)</a> The availability of metals in the environment has changed over geological time and, given imperfections in the selectivity of metal transport systems, proteins have evolved to make the best use of metals that are more available. <a href="javascript:void(0);">(3−5)</a> Depending on their evolutionary histories, different groups of marine phytoplankton may have differences in their metalloprotein compositions and metal transport strategies. The evolving trace metal availability in the environment, thus, may provide a selective pressure to promote the proliferation of different phytoplankton groups in the oceanic environment, affecting the phytoplankton community structure with knock-on effects on the marine food web and carbon sequestration. <a href="javascript:void(0);">(5)</a> It is crucial to understand the utilization of trace metals by different groups of marine phytoplankton that inhabit contrasting niches in the modern ocean, not only by assessing the accumulation of trace metals in cells but also examining the functions of trace metals in different biological pathways.</p><p>In previous studies, the utilization or requirements of trace metals by marine phytoplankton were mostly determined by measuring the elemental stoichiometry in cells (metallome or quota of trace metals). <a href="javascript:void(0);">(6−8)</a> In the field, attempts have also been made to investigate the elements in phytoplankton <a href="javascript:void(0);">(9,10)</a> which have then been compared with profiles in the abiotic environment to understand their relationships. <a href="javascript:void(0);">(11)</a> The discovery of various metal storage proteins and the plasticity in elemental quotas under different environmental conditions raise the question of whether intracellular trace metal quotas reflect true differences in trace metal usage by phytoplankton. <a href="javascript:void(0);">(12,13)</a> In the past few decades, more and more studies have focused on metal–protein partnerships, using approaches such as genome-wide analysis to identify homologues of known metalloproteins and other deduced metal-binding motifs encoded within sequenced genomes. <a href="javascript:void(0);">(5,14)</a> However, this approach has limitations in estimating metal abundance in cells because not all genes predicted in the genome would be translated and expressed as proteins under all environments, and a single gene for a metalloprotein could be highly expressed, such that a translation from genetic presence to a required concentration is not linear and could be environment-dependent. To obtain <i>in situ</i> metal abundance in metalloproteins in cells, native separation of proteins by HPLC or PAGE followed by the detection of metals using ICP-MS <a href="javascript:void(0);">(15,16)</a> has been used. This approach also has limitations in that, without bioinformatics, it cannot identify the function of proteins within which the metals are found, and it may also depend on the composition of the media to which the organism has been exposed and in which it has been growing. An ideal way to solve the problem would be to separate and purify each of the proteins and then identify both the associated metal (<i>e.g.,</i> by ICP-MS) and the protein sequence (<i>e.g.,</i> by mass spectrometry). However, this approach is constrained by the resolution of chromatographic or electrophoretic techniques, making it challenging to establish the metal–protein associations unambiguously; many proteins often co-occur in metal-containing fractions. Additionally, this method requires huge volumes of biomass and is both time-consuming and complex, complicating the reconstruction of the expressed metalloproteome in cells. The techniques and challenges for metalloproteomics have been discussed in detail in previously published review articles (and the references therein). <a href="javascript:void(0);">(17)</a></p><p>In this study, we determined the trace metal utilization (the metallome) of different phytoplankton from their expressed proteome via a protein modeling and homologue identification approach, and then compared the resulting metallome with the metal quota data measured by the traditional inductively coupled plasma mass spectrometry (ICP-MS). This approach allows the building of a link between the truly used trace elements and their biological functions in phytoplankton. We aim to fill the gap between an estimation of metals encoded in the genome and metal analysis by ICP-MS in phytoplankton, which may be more broadly applicable to infer cellular metallomes.</p><h3><strong>Materials and Methods</strong></h3><h4><strong>ICP-MS Analysis</strong></h4><p>All preparation of samples for ICP-MS measurement was undertaken using trace metal clean methods. All plasticware used in this study, including culture flasks, pipette tips, and centrifuge tubes, was precleaned in 10% quartz-distilled HCl and thoroughly rinsed with 18 MΩ cm water in a clean laboratory. Trace elements in the filtered lysates of <i>G. huxleyi</i> (OA1, OA4, OA8, OA15, OA16, OA23, and RCC 1242) and <i>Synechocystis</i> (FACHB898) strains were measured using an ICP-MS. The detailed ICP-MS method and instrumental settings are described in Zhang et al. (2018). <a href="javascript:void(0);">(31)</a></p><h4><strong>Protein Mass Spectrometry</strong></h4><p>The peptides were resuspended in 5% formic acid and 5% DMSO prior to mass spectrometry. They were separated on an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=3&amp;search=Ultimate+3000+UHPLC"><strong>Ultimate 3000 UHPLC </strong></a>system (Thermo Fisher Scientific) and electrosprayed directly into a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/559"><strong>Q-Exactive Mass Spectrometer</strong></a> (Thermo Fisher Scientific) through an EASY-Spray nanoelectrospray ion source (Thermo Fisher Scientific). The peptides were trapped on a C18 PepMap100 precolumn (300 μm i.d. × 5 mm, 100 Å, Thermo Fisher Scientific) using solvent A (0.1% formic acid in water) at a pressure of 500 bar. The peptides were separated on an in-house packed analytical column (75 μm i.d. × 50 cm packed with ReproSil-Pur 120 C18-AQ, 1.9 μm, 120 Å, Dr. Maisch GmbH) using a linear gradient (length: 65 min, 15% to 35% solvent B [0.1% formic acid in acetonitrile], flow rate: 200 nL/min). The raw data were acquired on the mass spectrometer in a data-dependent mode (DDA). Full scan MS spectra were acquired in the Orbitrap (scan range 350–1500 <i>m</i>/<i>z</i>, resolution 70000, AGC target 3e6, maximum injection time 50 ms). After the MS scans, the 10 most intense peaks were selected for HCD fragmentation at 30% of normalized collision energy. HCD spectra were also acquired in the Orbitrap (resolution 17500, AGC target 5e4, maximum injection time 120 ms, isolation window 1.5 <i>m</i>/<i>z</i>) with the first fixed mass at 180 <i>m</i>/<i>z</i>. Charge exclusion was selected for unassigned and 1+ ions. The dynamic exclusion was set to 20 s.</p><h3><strong>Results and Discussion</strong></h3><h4><strong>Trace Elements Determined from the Expressed Proteomes of Different Phytoplankton</strong></h4><p>Based on the expressed proteome sequences, we predicted metal-binding proteins and compared their distribution among various phytoplankton species (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig2">Figure 2</a>). The inference revealed 28 different metals in <i>G. huxleyi</i>, 31 different metals in <i>C. reinhardtii</i>, and 30 different metals in <i>Synechocystis</i>. Although only 6 different metals were identified in <i>O. tauri</i> proteins, it has to be noted that the analysis for <i>O. tauri</i> was only based on the 40 most abundant proteins reported in this organism <a href="javascript:void(0);">(21)</a> and, hence, the listed elements, including Mg, Fe, Mn, Ca, Zn, and Cu, may represent the most essential metals for the species.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Environ_Sci_Technol_2025_59_50_27367_27377_Figure_2_The_number_of_metal_binding_proteins_identified_in_the_expressed_proteome_of_the_haptophyte_G_9b8ac0f004.jpeg" alt="Environ. Sci. Technol. 2025, 59, 50, 27367–27377: Figure 2. The number of metal-binding proteins identified in the expressed proteome of the haptophyte G. huxleyi (a), the chlorophyte C. reinhardtii (b) and O. tauri(c), and the cyanobacteria Synechocystis (d). Pie charts show the percentages of metalloproteins containing specific metals. Original proteome data for G. huxleyi are from Mckew et al. (2013) (24) for C. reinhardtii are from Hsieh et al. (2013) (77) for O.tauriare from Martin et al. (2012) (21) for Synechocystisare from Chen et al. (2018). (22) *Noted that for O. tauri, only the 40 most abundant proteins were included in this analysis. ND: no metal binding was found in the proteins." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Environ_Sci_Technol_2025_59_50_27367_27377_Figure_2_The_number_of_metal_binding_proteins_identified_in_the_expressed_proteome_of_the_haptophyte_G_9b8ac0f004.jpeg 123w," sizes="100vw" width="934" height="1181"></p><p>The number of proteins that bind with different metals varies dramatically in phytoplankton. For metalloproteins, there are variations in the binding affinities of different metals to organic molecules. For example, the affinities of divalent metals to proteins have a tendency to follow a universal order of preference, namely the Irving-Williams series (Mg<sup>2+</sup> and Ca<sup>2+</sup> [weakest binding] &lt; Mn<sup>2+</sup> &lt; Fe<sup>2+</sup> &lt; Co<sup>2+</sup> &lt; Ni<sup>2+</sup> &lt; Cu<sup>2+</sup> &gt; Zn<sup>2+</sup>). <a href="javascript:void(0);">(43)</a> Cells can simultaneously contain proteins having high-affinity-binding metals, such as Cu and Zn, and others that require uncompetitive metals, such as Mg and Ca. One of the least competitive metals for binding with biological chelators, Mg, is even found to be the most widely distributed metal in the metalloproteomes of various phytoplankton species in this study, supporting the observations of high concentrations in the protein fraction of cells (at millimolar concentrations <a href="javascript:void(0);">(31)</a>).</p><p>In all phytoplankton species in our analysis, the Mg-containing proteins are found to have the highest proportion in all metalloproteins identified. About 30% of the metalloproteins in different strains of phytoplankton are found to contain Mg or depend on it for function (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig2">Figure 2</a>), suggesting the important role of Mg in phytoplankton cells. It is generally coordinated in protein complexes by ATP or ADP and has also been found to be largely distributed in the chloroplasts or thylakoids in <i>G. huxleyi</i> and <i>Synechocystis</i>. <a href="javascript:void(0);">(22,24)</a> The essential roles of Mg in plants have been reported in various studies. Mg<sup>2+</sup> is known to be the central atom of the chlorophyll molecule, and its levels in the chloroplast regulate the activity of key photosynthetic enzymes. <a href="javascript:void(0);">(44)</a> It was reported that approximately 15–35% of total Mg is in the chloroplasts of a plant, <a href="javascript:void(0);">(45)</a> and it also serves as an osmotically active ion in the regulation of cells <a href="javascript:void(0);">(46)</a></p><h4><strong>Comparison Between Metallome Measured Directly and Reconstructed from Proteins</strong></h4><p>A large proportion of metals, such as Fe, Mn, and Cu, are found in membrane proteins,and may contribute significantly to total cellular quotas. <a href="javascript:void(0);">(54,55)</a> However, for method development purpose, we endeavored to remove the cell membranes from our samples to focus mostly on the analysis of intracellular metal quotas and metalloproteins in the cytosol fraction in this study. We note that our analysis includes some membrane-bound proteins likely derived from organelles or surface membranes disrupted during sonication.</p><p>The derivation of cellular metal composition, as determined by two different methods, is compared in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>. The abundance of metal in the proteins is determined as the relative abundance of the protein multiplied by the number of metal ions needed for the specific protein. The abundance of the proteins was normalized to ensure that the total intensities from each replicate measurement for the same species were similar. Since the proteomic data used here were generated from different studies using different instruments, we cannot quantify or compare the absolute biomass of proteins used for each species. Therefore, we cannot compare the absolute trace metal abundance between species solely from metal inferences of expressed proteomes. Nevertheless, we can estimate the relative abundance of different metals in the same species. For the elements that are both measured by the ICP-MS and identified in the proteome, there are generally good correlations (<i>r</i><sup>2</sup> = 0.81 in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>a and <i>r</i><sup>2</sup> = 0.74 in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>b) between the two approaches. This indicates that the metal compositions determined from the protein modeling may be reliable and, therefore, can reflect the metal usage in different phytoplankton. This would provide a level of assurance to further investigate the metal binding associated with various proteins, thereby deepening our understanding of the roles that different metals play in phytoplankton.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Environ_Sci_Technol_2025_59_50_27367_27377_Figure_3_Relationship_between_the_abundance_of_metals_determined_by_ICP_MS_analysis_e7b259e376.jpeg" alt="Environ. Sci. Technol. 2025, 59, 50, 27367–27377: Figure 3. Relationship between the abundance of metals determined by ICP-MS analysis (normalized to C, mmol/mol C) and metal abundance determined from the metalloproteome analysis (the unit is arbitrary). To account for strain variations, the ICP-MS data for the cellular metal content of G. huxleyi are average values from 7 G. huxleyi strains isolated from different areas of the ocean, and the proteome-derived metal composition data are average values calculated from 2 of those G. huxleyi strains (OA1 and OA16) isolated previously, and data from Mckew et al., 2013. (24) The ICP-MS data for Synechocystis are from Synechocystis sp. FACHB898 measured in this study, and the proteome data are calculated from Chen et al., 2018. (22) Noted that the abundance of metals from each proteome was calculated by using the metal stoichiometry multiplied by the relative abundance of proteins, which provides only a relative relationship of different trace metals, not absolute abundance. The symbols represent the mean values, and the error bars indicate standard deviations." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Environ_Sci_Technol_2025_59_50_27367_27377_Figure_3_Relationship_between_the_abundance_of_metals_determined_by_ICP_MS_analysis_e7b259e376.jpeg 245w," sizes="100vw" width="1384" height="641"></p><p>Compared to the other metals investigated in this study, Ca and Mg appear to have a much higher relative abundance in the ICP-MS analysis than in the proteomic analysis of <i>G. huxleyi</i> and <i>Synechocystis</i> (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>). These two elements are essential macronutrients for phytoplankton and plants. Ca is the most prominent secondary messenger that plays a crucial role in response to extracellular stimuli in all eukaryotes. Ca<sup>2+</sup> fluxes are transported via Ca channels and transporters, such as Ca-ATPase, regulating a series of important biological functions, including mineral uptake and utilization, K<sup>+</sup> homeostasis adjustment, and regulatory network activity in response to P or N deficiency. <a href="javascript:void(0);">(56)</a> Ca is not always incorporated into protein structures. The Ca abundance determined from the proteins in this study, therefore, is much lower than the actual Ca needed intracellularly. Similarly, the intracellular Mg<sup>2+</sup> and K<sup>+</sup> abundances should also be higher than those determined from the protein structures. Free Mg<sup>2+</sup> and K<sup>+</sup> are known to regulate cation–anion balance and serve as osmotically active ions in the regulation of cells <a href="javascript:void(0);">(46)</a> but free metal ion concentrations cannot be determined through the approach used in this study. Thus, it is not surprising to see much higher relative abundances of Ca and Mg in ICP-MS analysis than in proteomic analysis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>).</p>

Unlocking Phytoplankton Metallomes with Comparative Analysis of Metal Quotas, Quantitative Proteomics, and Inferred Metalloproteomes

<h3><a target="_blank" rel="noopener noreferrer" href="https://www.isc2026.org/"><strong>ISC 2026</strong></a></h3><p><strong>The </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/314"><strong>International Symposium on Chromatography (ISC)</strong></a><strong> represents the oldest conference series on separation science. ISC symposia have been organised since 1956 in each even year. ISC is one of the premier meetings series for discussion of all modes of chromatography and separation science with a broad coverage of techniques and applications.</strong></p><p>The major focus of the symposium will be on the impact of chromatography and separation science to meet the needs of the pharmaceutical, environmental, food and health industry, as well as science and medicine. The symposium programme will reflect these themes and highlight new challenges and emerging opportunities for the science and marketing of separation and detection systems and methods.</p><p>As an integral part of the scientific programme of lectures and poster sessions, an international exhibition and vendor seminars on instrumentation and services for chromatography, separation science and mass spectrometry will be organised. ISC 2026 will provide the perfect forum for attendees from academia, industry and government research institutions for scientific exchange and networking.</p><h3><strong>ISC 2026 SYMPOSIUM KEY DATES</strong></h3><h4><strong>6-10 SEPTEMBER 2026</strong></h4><ul><li><strong>15 January 2026:</strong> Opening of Early-bird Registration &amp; Abstract submission</li><li><strong>11 March 2026: </strong>Deadline for abstract submission (orals)</li><li><strong>21 April 2026: </strong>Sending acceptance letters (orals)</li><li><strong>15 May 2026: </strong>Deadline of early-bird registration and payment &amp; Author registration deadline (orals)</li><li><strong>1 June 2026: </strong>Preliminary detailed program on web</li><li><strong>1 June 2026: </strong>Deadline for abstract submission (posters)</li><li><strong>16 June 2026: </strong>Sending acceptance letters (posters)<ul><li>Authors who submit their abstracts with a poster preference by 5 May 2026 will be notified of the outcome by 12 May 2026 and will have the opportunity to register at the early-bird rate until 15 May 2026.</li></ul></li><li><strong>30 June 2026:</strong> Author registration deadline (posters)</li><li><strong>30 July 2026:</strong> Deadline for abstract submission (late-breaking posters)<ul><li>without the possibility of competing for the Best Poster Award</li></ul></li><li><strong>11 August 2026: </strong>Sending acceptance letters (late-breaking posters)</li><li><strong>18 August 2026:</strong> Author registration deadline (late-breaking posters)</li><li><strong>25 August 2026: </strong>Deadline for late registration &amp; payment&nbsp;</li><li><strong>6-10 September 2026: </strong>Symposium</li></ul><h3><strong>REGISTRATION</strong></h3><blockquote><p class="cke-user_style-important"><strong>👉</strong><a target="_blank" rel="noopener noreferrer" href="https://www.czech-in.org/cmPortalV15/Account/Login?ReturnUrl=%2FcmPortalV15%2FPortal%2FISC26%2Fnormal"><strong>Register HERE for the ISC 2026</strong></a></p></blockquote><h3><strong>ABSTRACT SUBMISSION</strong></h3><blockquote><p class="cke-user_style-important"><strong>👉</strong><a target="_blank" rel="noopener noreferrer" href="https://www.czech-in.org/cmPortalV15/Account/Login?ReturnUrl=%2FcmPortalV15%2FPortal%2FISC26%2Fnormal"><strong>Submit your Abstract HERE</strong></a></p></blockquote><h3><strong>SCIENTIFIC PROGRAM</strong></h3><h4><strong>SHORT COURSES</strong></h4><h5><strong>SC 4 Hydrophilic Interaction Liquid Chromatography</strong></h5><p><strong>🗓️ SUNDAY, 6 SEPTEMBER 2026</strong></p><p><strong>🕗 8:30 – 11:45</strong></p><p>Hydrophilic Interaction Chromatography (HILIC) has become an essential separation mode for the analysis of polar compounds that are poorly retained in reversed-phase LC. This chromatographic mode is more and more widely used in pharmaceutical analysis, biopharmaceutical characterization, and, above all, metabolomics, where enhanced retention, improved MS sensitivity, and complementary selectivity are indispensable. Despite its power, HILIC remains perceived as complex due to its mixed retention mechanisms, sensitivity to experimental conditions, and limited repeatability. A dedicated short course is therefore required to help users understand this technique in a robust and efficient way.</p><p>This course will provide an in-depth and practical overview of HILIC fundamentals, starting with a discussion of the relatively complex retention mechanism. Particular emphasis will be placed on critical operational parameters such as sample diluent effects, which can drastically impact peak shape and retention, and on achieving good repeatability in gradient mode.</p><p>Participants will also learn how coupling HILIC with MS can maximize sensitivity, and how to select both mobile phase components and stationary phases to obtain reliable and reproducible separations. Numerous applications will be covered, including typical small-molecule analyses, comprehensive metabolomic workflows, and the characterization of large biopolymers such as oligonucleotides, peptides, and proteins.</p><p>In the end, this short course will help participants to confidently implement and troubleshoot HILIC in modern analytical laboratories.</p><h4><strong>Lecturers</strong></h4><h5><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/articles?search=Davy+Guillarme"><strong>Davy Guillarme</strong></a></h5><ul><li>Davy Guillarme currently serves as an associate professor at the University of Geneva in Switzerland. With over 350 published journal his expertise spans various techniques, including UHPLC, HILIC, LC−MS, SFC, SFC-MS, multidimensional LC, and application to the characterization of biopharmaceuticals.</li><li>He is an editor of the Journal of Chromatography A and serves on the editorial advisory board of various other journals.</li><li>Davy Guillarme has been honored with the LC-GC Emerging Leader Award in Chromatography (2013), the Jubilee Medal from the Chromatographic Society (2018), the International Award of the Belgian Society of Pharmaceutical Sciences (2022) and the Csaba Horvath memorial award (2025).</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ISC_2026_Davy_Guillarme_c54bb7dd40.jpg" alt="ISC 2026: Davy Guillarme" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ISC_2026_Davy_Guillarme_c54bb7dd40.jpg 156w," sizes="100vw" width="500" height="500"></p>

ISC 2026 Short Course 4 - Hydrophilic Interaction Liquid Chromatography

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The International Symposium on Chromatography (ISC) represents the oldest conference series focussing on separation science. ISC symposia have been organised since 1956 in each even year. ISC is internationally recognised as one of the premier meeting series for discussion of all modes of chromatography and separation science with a broad coverage of techniques and applications.

International Symposium on Chromatography - (ISC)

Thermo Scientific Compound Discoverer software

Compound Discoverer software addresses small molecule identification needs and workflows including untargeted metabolomics, drug metabolism, impurity, E&L, environmental, food & beverage, and forensic research.

Thermo Scientific mzVault offline advanced mass spectral database

mzVault provides you the capabilities to access and search mzCloud’s MS2-level spectral data off-line, or to store your own spectral library information.

<p><strong>Your data has inherent value, as it is the knowledge that you acquire. mzVault provides you the capabilities to access and search mzCloud’s MS<sup>2</sup>-level spectral data off-line, or to store your own spectral library information. Spectral information, and your knowledge, can be automatically sent from </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer</strong></a><strong> into a new, or existing library which can then be searched using Compound Discoverer or</strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong> Mass Frontier.</strong></a></p><div><p>When you need to curate proprietary libraries and ensure the highest quality data, <strong>Mass Frontier</strong> provides you with the same tools used to curate <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a>, meaning that <strong>you can ensure your spectral data has been filtered, recalibrated, averaged and fully structurally annotated, ready to share your knowledge within your organization.</strong></p></div><div><h3><strong>Key benefits</strong></h3><h5><strong>Know more unknowns off-line</strong></h5><p><strong>Sometimes it isn’t possible to be online and access </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a><strong>.</strong> mzVault contains all MS<sup>2</sup>-level spectral data contained within mzCloud to allow for confident unknown identifications.</p><h5><strong>Create and share your knowledge&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p><strong>Create, store and search your own in-house spectral libraries. </strong>Once you have identified unknowns through mzLogic, or you have your proprietary compounds, make sure that this valuable information can be leveraged.</p><h5><strong>Have I seen this unknown before?&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p><strong>Even with extensive online structural databases, and mzLogic to propose a structure or sub-structure, there can be occasions where it remains an unknown.</strong> Store this information and re-use to see if you have previously observed any unknowns.</p><h5><strong>Curate your high-quality data</strong></h5><p><strong>When it is important to curate your valuable data</strong>, the <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/mass-spectrometry/liquid-chromatography-mass-spectrometry-lc-ms/lc-ms-software/mass-spectral-libraries.html?open=curator">Curator</a> tool from Mass Frontier allows you to use the same tools used to populate <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a>, ensuring the creation of your own high-quality mzVault proprietary libraries.</p></div>

Thermo Scientific Metabolika module for easy pathway analysis

Create, edit and search reaction pathways using the new Metabolika module to take your knowledge to the next level. 

<div style="height:auto;" id="metabolika"><div><div><div><div colctrl-id="7-1"><div><div container-id="cq-colctrl-lt8" comp-id="B1"><div><p><strong>Create, edit and search reaction pathways using the new Metabolika module to take your knowledge to the next level. With publication-quality graphical functionality to create and edit reaction pathways within</strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong> Thermo Scientific Compound Discoverer 3.0</strong></a><strong> or greater, and </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Thermo Scientific Mass Frontier Software 8.0</strong></a><strong> or greater, and more than 370 curated and annotated biochemical pathways for a range of organisms, it is easier than ever to share your pathway knowledge.</strong></p><p>The Metabolika Module is also utilized within substructure searching, fragmentation prediction and for <strong>mzLogic</strong>, further increasing the chances of unknown compound identification.</p></div></div></div></div><div><p>When used within the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer software</strong></a>, this module can take your data visualization to a new level with interactive statistical data overlay, including metabolic flux analysis data.</p><div><h3><strong>Key benefits</strong></h3><h5><strong>Create, edit and store reaction pathways&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p>From the included &gt;370 metabolic pathways, through to your own reaction pathways, easily curate and edit your knowledge for future use within both the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Mass Frontier</strong></a> software.</p><h5><strong>Access knowledge of &gt;370 metabolic pathways&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p>The combined knowledge of the included pathways isn’t just restricted to Metabolika, the information is also fully utilized for substructure searching as well as with<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1762"> <strong>mzLogic</strong></a><strong>.</strong></p><h5><strong>Map pathways to your data, as well as visualize your statistical information</strong></h5><p>Pathways can be easily mapped to your detected compounds within the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer software</strong></a>, with highly visual and interactive representation. Additionally, your statistical information from flux analyses can be displayed within Metabolika pathways for easy data visualization.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Metabolika_module_for_easy_pathway_analysis_781f11c926.jpg" alt="Thermo Scientific Metabolika module for easy pathway analysis: An example of Metabolika pathways analysis tool with flux analysis data included, showing qualitative flux analysis of exchange rates from a stable isotope labeling experiment." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Metabolika_module_for_easy_pathway_analysis_781f11c926.jpg 245w," sizes="100vw" width="960" height="500"></p></div></div></div></div></div></div>

Thermo Scientific mzLogic Data Analysis Algorithm

mzLogic solves a key challenge in small molecule identification by enabling the characterization of unknowns when high-quality MSⁿ data yield no matches in spectral libraries.

<div style="height:auto;" id="mzlogic"><div><div style="display:block;"><div><div><div container-id="cq-colctrl-lt8" comp-id="B2"><div><div><div container-id="cq-colctrl-lt8" comp-id="B1"><div><h3><strong>Accelerate unknown small molecule identification with mzLogic</strong></h3></div></div><div container-id="cq-colctrl-lt8" comp-id="B2"><div><p><strong>The mzLogic data analysis algorithm addresses one of the biggest challenges for small molecule characterization and identification-when, despite having sufficient high-quality and high-resolution MS<sup>n</sup> mass spectrometric data, there is no match in any spectral library, meaning you have an unknown.</strong></p><p>mzLogic combines the extensive fragmentation information available within the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a> online advanced mass spectral library with the information in numerous online structural databases. As a result, mzLogic allows you to take thousands of potential structural candidates and automatically rank them based upon spectral similarity and sub-structural information – delivering confident candidates for your true unknowns.</p></div></div></div></div></div></div><div><h3><strong>Key benefits</strong></h3><h5><strong>Combine the benefits of multiple libraries and databases&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p>The ability of mzLogic to combine the extensive, high-quality and high-resolution accurate mass, multi-stage (MS<sup>n</sup>) fragmentation information in <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764">mzCloud</a>, with numerous online structural databases provides the greatest chance to confidently identify unknowns.</p><h5><strong>Take lengthy guesswork out of unknown identification&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p>mzLogic uses the data from <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764">mzCloud </a>and multiple other data sources to identify common sub-structural features from your MS<sup>n</sup> data, explaining as much of your fragmentation data as possible before the next stages of identification.</p><h5><strong>Go from thousands of potential candidates to a handful</strong></h5><p>Using elemental composition to search structural databases can return thousands of potential candidates; mzLogic uses MS<sup>n</sup> data and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764">mzCloud</a> fragmentation database information to explain as much structural information as possible, reducing thousands of potentials to a handful of confident candidates based upon structural similarity.</p><div><div><figure class="image"><img style="aspect-ratio:740/345;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_05478bcf43.jpg" alt="Thermo Scientific mzLogic Data Analysis Algorithm: Take the guesswork out of small molecule unknown identification through the combination of mzLogic algorithm and the high quality, structurally diverse mass spectral fragmentation information contained within mzCloud, to propose and confirm structural identification." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_05478bcf43.jpg 245w," sizes="100vw" width="740" height="345"></figure><h3><strong>How does your data relate to mass spectral libraries?</strong></h3><div style="height:auto;" id="massspectrallibraries"><div><div><div><div><p>Whether you are working to better characterize and understand <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/pharma-biopharma/pre-clinical-and-clinical-drug-testing/metabolite-identification.html">metabolism and drug analytes</a>, <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/food-beverage/food-analytical-testing/food-contact-materials.html">food and environmental samples</a>, <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/forensics/antidoping/doping-control-retrospective-analysis.html">designer drugs</a> or <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/pharma-biopharma/pharma-biopharma-learning-center/pharmaceutical-qa-qc-information/extractables-leachables-information.html">extractables and leachables</a>, the use of mass spectral libraries and online databases can help identify compounds in your samples. However, with increasing crossover between compound classes, new impurities, subtle compound transformations or metabolism and degradation products, sometimes no compelling match is made to the libraries you use.</p><p>Acquiring comprehensive high-resolution accurate- mass MS/MS and MS<sup>n</sup> data has been simplified with data acquisition tools such as <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1763"><strong>AcquireX</strong></a>, and general hardware improvements. Obtaining mass spectral libraries that contain broad chemical diversity, extensive fragmentation and reliable and concise data has been the biggest challenge.</p><p>The<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764">mzCloud</a> mass spectral database is the largest (in terms of total spectra and data per compound) publicly available online mass spectral fragmentation library. It contains high-resolution accurate-mass (HRAM) spectra, including exhaustive high-resolution MS/MS and multi-stage MS<sup>n</sup> spectra. Each entry contains considerable metadata and, most importantly, has been extensively curated (i.e., filtered, recalibrated, averaged, and annotated) to provide absolute confidence in the quality of its contents.</p><figure class="image"><img style="aspect-ratio:908/323;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_2_959e175e53.jpg" alt="Thermo Scientific mzLogic Data Analysis Algorithm: High quality MS, MS/MS and MSn data can be used to interrogate the fully curated and annotated mass-spectral fragmentation library, mzCloud. Common substructural information can be used from the extensive fragmentation information to aid in unknown compound identification using mzLogic algorithm." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_2_959e175e53.jpg 245w," sizes="100vw" width="908" height="323"></figure><h3><strong>How does mzLogic identify unknowns?</strong></h3><div style="height:auto;" id="identifyunknowns"><div><div><div><div><p>Each <strong>mzCloud library</strong> entry contains extensive fragmentation information, which has been acquired using both a range of collision energies and fragmentation techniques (collision induced and higher energy collisional dissociation, CID and HCD). When this information is combined with the broad chemical diversity of library entries, the likelihood that some or all of an unknown structure can be matched against an existing fragment within the library increases.</p><figure class="image"><img style="aspect-ratio:927/394;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_3_b50ae0af70.jpg" alt="Thermo Scientific mzLogic Data Analysis Algorithm: mzLogic reduction of putative candidates using online structural databases and the extensive fragmentation information contained within mzCloud." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_3_b50ae0af70.jpg 245w," sizes="100vw" width="927" height="394"></figure></div></div></div></div></div><div style="height:auto;" id="identifyunknowns"><div><div><div><div><p>As shown in the figure above, mzLogic is available as part of the<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong> Mass Frontier software</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer software</strong></a> packages, and works as follows:</p><ol style="list-style-type:upper-latin;"><li>Online databases, such as <a target="_blank" rel="noopener noreferrer" href="http://www.chemspider.com" aria-label="ChemSpider - open in a new tab" data-uw-rm-ext-link="" uw-rm-external-link-id="http://www.chemspider.com/$chemspider">ChemSpider</a>, which contains more than 70 million structures, can be searched using an elemental composition. Even with the ability to use the high-resolution and accurate mass capabilities of <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products?category=5&amp;search=orbitrap"><strong>Orbitrap mass analyzers</strong></a> to reveal fine isotopic information, many hundreds or even thousands of potential structures could match the elemental composition.</li><li>The high-quality fragmentation information contained within mzCloud is <strong>compared to experimental data.</strong></li><li>mzLogic rapidly identifies structurally similar fragments through forward and reverse searches.</li><li>Based upon the identified sub-structures, the structural candidates from the online search are ranked in order of how much of the structure can be explained through the sub-structural matching.</li><li>This ranking based upon the use of real data, takes many hundreds or thousands of potential candidates and reduces them to a significantly smaller list of putative structures, with visualization tools to explain the ranking and structure accounted for by library fragments.</li></ol><div><div><h3><strong>What is the next step to confirm any potential candidates?</strong></h3><div style="height:auto;" id="potentialcandidates"><div><div><div><div><p>The ranked results from using mzLogic will either show that all the structure can be accounted for in that candidate or that there is still some structural information from the proposed candidate that cannot be accounted for. MS/MS and/or MS<sup>n</sup> fragmentation spectra typically contains substantial amounts of structural information, which can be further investigated using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Mass Frontier software</strong></a>.</p><p>Where a complete, in-depth analysis of MS<sup>n</sup> fragmentation data is required,<strong> </strong>Mass Frontier software provides visualization and understanding of fragmentation pathways using extensive MS<sup>n</sup> data. The<strong> Fragments and Mechanism tool </strong>simulates unimolecular dissociation of the proposed structures, including rearrangements and predicted fragments, and can be used to explain the experimental fragmentation data through fragment annotations to help identify which candidates are indeed plausible. Rather than coded fragmentation algorithms, <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Mass Frontier software</strong></a><strong> bases fragmentation on mechanisms published in more than 95% of all peer-reviewed scientific journals.</strong></p><p>This approach adds greater certainty to putative structure identification through the deep fragmentation and characterization information provided by the high-quality data and extensive spectral trees in <strong>mzCloud.</strong></p><figure class="image"><img style="aspect-ratio:673/324;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_4_1d09064e9e.jpg" alt="Thermo Scientific mzLogic Data Analysis Algorithm: Confident structural elucidation using automated fragmentation annotation of MSn spectral trees. Fragmentation pathways can also be predicted based upon submission of a structure and makes full use of the HighChem Fragmentation Library. This library contains information from more than 52,000 fragmentation schemes, 217,000 individual reactions, 256,000 chemical structures and 216,000 decoded mechanisms from peer reviewed literature." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Logic_Data_Analysis_Algorithm_4_1d09064e9e.jpg 245w," sizes="100vw" width="673" height="324"></figure></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Thermo Scientific AcquireX Intelligent Data Acquisition Workflow

The Thermo Scientific AcquireX workflow enhances LC-MSn data acquisition by automating and connecting experiments for efficient, intelligent small-molecule analysis across five different routines.

Thermo Scientific mzCloud Mass Spectral Library

mzCloud is a high-resolution, accurate-mass MSⁿ spectral library that helps identify unknown compounds when no reference standards are available, especially in complex studies.

<div colctrl-id="1-1"><div><div container-id="cq-colctrl-lt8" comp-id="B1"><div><h3><strong>Confident identification for unknown small molecules</strong></h3></div></div><div container-id="cq-colctrl-lt8" comp-id="B2"><div><p><strong>Mass spectral libraries and databases may be required to identify unknown compounds when reference standards are not available. This is particularly true for studies in areas such as metabolomics, forensic toxicology, food &amp; beverage, environmental emerging contaminants or extractables &amp; leachables.</strong></p></div></div></div></div><div><p>In these situations, a mass spectral library, particularly a high-resolution and accurate-mass MS<sup>n</sup> fragmentation library, such as the mzCloud mass spectral library, can provide the information required to confidently identify unknown compounds.</p><h3><strong>Key benefits</strong></h3><h5><strong>Confidence for unknown identification</strong></h5><p>Comprehensive curation of all library content with extensive, fully annotated and searchable fragmentation spectra to provide confidence in your results.</p><h5><strong>Know more unknowns&nbsp;&nbsp;&nbsp;&nbsp;</strong></h5><p>Identify unknowns with automated deconvolution and library searching against extensive fragmentation spectra covering a wide chemical space, including small molecule applications.</p><h5><strong>From spectra to structure&nbsp;&nbsp;</strong></h5><p>With solutions to cover infusion or LC-MS, nominal or high-resolution data, you can be sure that your MS<sup>n</sup> spectra will provide you with actionable results, even when there is no spectral library match.</p><h5><strong>Flexibility for research and routine applications</strong></h5><p>Search for free online at <a target="_blank" rel="noopener noreferrer" href="http://www.mzcloud.org/" aria-label="mzCloud.org - open in a new tab" data-uw-rm-ext-link="" uw-rm-external-link-id="http://www.mzcloud.org/$mzcloud.org"><span style="white-space:nowrap;">mzCloud.org</span></a>, or directly access through the Thermo Scientific Compound Discoverer and Mass Frontier software packages. Not online? mzVault provides you with the ability to perform offline spectral library searching.</p><figure class="image"><img style="aspect-ratio:1398/1002;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_ecc79fe9bf.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: mzCloud is easily and freely accessed online. Anyone can search, review, and use its extensive information. Note that the numbers above were correct at time of publication. For the most up to date numbers visit mzCloud.org." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_ecc79fe9bf.jpg 218w," sizes="100vw" width="1398" height="1002"></figure><h3><strong>What is in the mzCloud mass spectral library?</strong></h3><div style="height:auto;" id="whatismzcloud"><div><div><div><div><p>mzCloud is an extensively curated, high-quality mass spectral fragmentation library that contains significant amounts of spectra and metadata for each entry. Each entry also includes exhaustive high-resolution <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/mass-spectrometry/liquid-chromatography-mass-spectrometry-lc-ms/lc-ms-software/mass-spectral-libraries/mzcloud-mass-spectral-library.html?open=multi-stage-fragmentation#multi-stage-fragmentation">MS/MS and multi-stage MS<sup>n</sup> spectra</a>, which have been acquired at various collision energies and using different fragmentation techniques.</p><p><strong>Each raw mass spectrum</strong> has been filtered to remove noise, recalibrated to ensure absolute mass accuracy, fully annotated and <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/cz/en/home/industrial/mass-spectrometry/liquid-chromatography-mass-spectrometry-lc-ms/lc-ms-software/mass-spectral-libraries/mzcloud-mass-spectral-library.html?open=content-curation#content-curation">curated</a> to ensure quality and consistency.</p><p>Finally, the contents of the library are <strong>updated weekly</strong> to provide coverage of a wide chemical space, ensuring relevance to all small-molecule application areas.</p></div><div><figure class="image"><img style="aspect-ratio:740/410;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_2_77a6795676.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: Example of the Mass Frontier software utilizing the contents of mzCloud to identify an unknown compound through a sub-structural search; the experimental fragmentation spectrum (top left) is searched against the mzCloud mass spectral database, with corresponding spectral hits shown in a given spectral tree (top, middle), with supporting spectral information (bottom left) and the identified precursor structure from the matched fragmentation spectra (bottom right), and the library compound structure from which the fragment originated (top right)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_2_77a6795676.jpg 245w," sizes="100vw" width="740" height="410"></figure></div><div><p>Distinguishing among types of databases is important, as the contents and quality of the contents typically differs significantly and may have an impact upon the reliability of the data and the confidence in any results obtained.</p><ul><li><strong>Chemical database</strong>: A collection of chemical information with, at minimum, a name and a formula. It may also include structures, elemental composition, retention time information, and additional biological or chemical metadata.</li><li><strong>Accurate-mass (AM) database</strong>: An AM database contains accurate mass formulas.</li><li><strong>Accurate-mass retention-time (AMRT) database</strong>: An AMRT database contains accurate mass and retention time(s) for specific analytical methods.</li><li><strong>Library</strong>: A library is a database (AM or AMRT) that, in addition to the above, also contains reference mass spectral data, MS/MS, and/or MS<sup>n</sup> data on compounds.</li></ul><h3><strong>Multi-stage fragmentation in the mzCloud mass spectral library</strong></h3><div style="height:auto;" id="multistagefragmentation"><div><div><div><div><figure class="image"><img style="aspect-ratio:740/420;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_3_792a9d9a59.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: A schematic representation of a spectral tree within mzCloud. The MS spectra are acquired for a given compound in multiple polarities (ESI +/-), and for a range of adducts. Each precursor is exhaustively fragmented using different fragmentation techniques (CID, HCD) and at multiple collision energies to produce collections of fragmentation spectra at each fragmentation level (MS2, MS3, MS4 etc.), generating a comprehensive spectral tree of information for each library entry." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_3_792a9d9a59.jpg 245w," sizes="100vw" width="740" height="420"></figure><p>mzCloud is an<strong> all-encompassing mass spectral library </strong>with content based on a wide chemical space (therefore covering all small-molecule application areas), and acquiring high-resolution and accurate-mass data at various collision energies, for multiple adducts, using CID and HCD. Approximately 10–20 collision energies are included for every precursor ion; this multi-stage, multidimensional MS<sup>n</sup> spectral data are arranged into spectral trees, which are both extensive and comprehensive, typically containing many hundreds to thousands of spectra for each compound, with many exceeding MS<sup>4</sup> fragmentation steps.</p><p>The extensive data for each library entry is critical for accurate compound identifications, matching experimentally obtained data to that of the library contents, with fit confidence and data visualization <strong>provided in the</strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong> Compound Discoverer</strong></a><strong> and </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Mass Frontier</strong></a><strong> data analysis software.</strong> Additional tools in Compound Discoverer and Mass Frontier software, including <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1762"><strong>mzLogic</strong></a>, use the extensive fragmentation information to confidently identify unknowns that cannot be identified based upon the spectral library compound entries alone.</p><h3><strong>Content curation in the mzCloud mass spectral library</strong></h3><div style="height:auto;" id="contentcuration"><div><div><div><div><figure class="image"><img style="aspect-ratio:740/342;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_4_c7064c2ca2.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: An example of the mass spectral content curation tool available within the Mass Frontier software. It contains all the functionality used to manually curate the content contained within mzCloud. The power of mzCloud lies in both the extent and high quality of its content, which helps make confident compound identifications." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_4_c7064c2ca2.jpg 245w," sizes="100vw" width="740" height="342"></figure><p>Despite the fact that <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products?category=5&amp;manufacturerItems=3&amp;search=orbitrap"><strong>Thermo Scientific Orbitrap-based mass analyzers</strong></a> routinely deliver sub 3-ppm mass errors, there is a small amount of inaccuracy in any experimental data used to search against a library; these errors would be compounded if the library itself also contained data with mass errors. The compounded errors would mean that any identifications could be harder to make or have lower confidence due to match scores being higher.</p><p>Curating the content within mzCloud guards against error and variability in the reference spectra against which data is compared. <strong>The process of curation involves:</strong></p><ul><li>Averaging multiple, individually acquired spectra</li><li>The removal of mass spectral noise</li><li>Recalibration of the mass spectra based upon the predicted formulas for the fragment ion elemental compositions, based upon the known elemental composition and structure of the precursor ion</li><li>Annotation of all fragment ions with the fragment structure</li><li>Addition of large amounts of metadata, including the source of the data and all original raw data files</li></ul><p>This curation process is performed <strong>for every spectra</strong> - every collision energy, every fragmentation type, every MS<sup>n</sup> level and for each precursor ion. As such, the spectral data in mzCloud is of <strong>exceedingly high quality </strong>and offers significant advantages over crowd-sourced libraries due to the high levels of control.</p><figure class="image"><img style="aspect-ratio:740/350;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_5_0c3fdc4c6c.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: A recalibrated fragmentation spectrum showing no error on the highlighted peak at m/z 213.05462, along with all of the annotation that is provided for each spectra, at each collision energy, for each fragmentation type at each MSn level." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_5_0c3fdc4c6c.jpg 245w," sizes="100vw" width="740" height="350"></figure><div><div><div container-id="cq-colctrl-lt8" comp-id="B1"><div><h3><strong>How can I use the mzCloud mass spectral library?</strong></h3><p>Accelerate your small molecule unknown identification studies with <strong>mzCloud</strong>, <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1762"><strong>mzLogic</strong></a>, and the other data analysis and mass spectral prediction tools available in<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer</strong></a> software and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1757"><strong>Mass Frontier</strong></a><strong> </strong>software.</p><p><img style="aspect-ratio:860/261;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_7_a8cefb0028.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: Connectivity of mzCloud and mzVault to Mass Frontier." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_7_a8cefb0028.jpg 245w," sizes="100vw" width="860" height="261"></p><p>The content within mzCloud is accessible through Compound Discoverer and Mass Frontier software packages, provided you have an internet connection. No internet? No problem – <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1760"><strong>mzVault</strong></a>, provides you with the MS and MS/MS content of mzCloud in an offline format.</p><div style="height:auto;" id="accessmzcloud"><div><div><div><div colctrl-id="3-1"><div><div container-id="cq-colctrl-lt8" comp-id="B1"><div><p><img style="aspect-ratio:860/242;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_6_ae3c0a28e1.jpg" alt="Thermo Scientific mzCloud Mass Spectral Library: Connectivity of mzCloud and mzVault to Compound Discoverer." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_6_ae3c0a28e1.jpg 245w," sizes="100vw" width="860" height="242"></p><p>Due to security concerns or local firewalls, not everyone can connect processing PCs to the internet. With that in mind, the contents of mzCloud are combined into an offline version twice a year. The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1760"><strong>mzVault</strong></a><strong> </strong>software application helps you access this information. In addition to accessing the offline version of mzCloud, the mzVault application can store and search your high-quality custom in-house (offline) MS/MS spectral libraries.</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Thermo Scientific Proteome Discoverer Software

Identify and quantify peptides and proteins in complex biological samples using Thermo Scientific™ Proteome Discoverer™ software. 

<h3><strong>Comprehensive, extensible, and intelligent platform</strong></h3><p><strong>Thermo Scientific Proteome Discoverer Software is the ultimate toolbox for protein research, offering customizable workflows tailored to the complexities of modern proteomics. It simplifies the identification and quantification of proteins in complex biological samples, supporting a wide range of workflows, including peptide and protein identification, post-translational modifications (PTM) analysis, isobaric mass tagging, and label-free quantitation (LFQ). It handles data from diverse acquisition methods, such as data-independent acquisition (DIA), data-dependent acquisition (DDA), and wide window acquisition (WWA), ensuring comprehensive coverage.</strong></p><p><strong>Advanced tools </strong>like INFERYS™ Rescoring and the CHIMERYS™ intelligent search algorithm by MSAID significantly increase identification rates, protein coverage, and the discovery of unique peptides and PTMs. The software enhances protein quantitation for isobaric mass tags and LFQ, supporting multiple database search algorithms and dissociation techniques. Whether analyzing glycopeptides, top-down proteomics, proteoforms, or MS-based structural biology like chemical cross-linking (XL-MS), Proteome Discoverer Software enables scientists to extract deeper biological insights from their data.</p><figure class="image"><img style="aspect-ratio:1131/598;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteome_Discoverer_Software_7_2221d76acd.jpg" alt="Thermo Scientific Proteome Discoverer Software: Proteome Discoverer software in peer reviewed articles." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteome_Discoverer_Software_7_2221d76acd.jpg 245w," sizes="100vw" width="1131" height="598"></figure><h3><strong>Key benefits</strong></h3><h5><strong>Customize your data analysis</strong></h5><p>Use the node-based workflow editor to customize your data analysis for maximum coverage and confidence. Integrate database search results from multiple search engines such as SEQUEST™ HT, Mascot, MSAmanda, Byonic™ from Protein Metrics, and<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1756"><strong>Thermo Scientific ProSightPD</strong></a> software. Increase confidence in peptide identification and quantification using INFERYS Rescoring and enable a deeper mining of your DIA, DDA, or WWA data using the CHIMERYS intelligent search algorithm.</p><h5><strong>Perform relative quantitation</strong></h5><p>Measure and report the relative expression levels of isotopically labeled peptides for:</p><ul><li>TMT SPS MS3</li><li>Glycopeptide identification and quantification</li><li>Phosphopeptide identification and quantification</li><li>Top-down proteomics</li><li>Cross-linking</li></ul><p>Confidently and efficiently interpret your data with integrated statistical and visualization tools for a faster time to meaningful results.</p><h5><strong>Extensible workflow tools</strong></h5><p>Utilize third-party nodes and build in customization with the scripting node, while maintaining full integration into the Proteome Discoverer software framework to leverage visualization, statistical analysis, and biological interpretation tools to take your analysis to the next level.</p><figure class="image"><img style="aspect-ratio:1160/533;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteome_Discoverer_Software_4_4d8ae8fcd2.jpg" alt="Thermo Scientific Proteome Discoverer Software: Extensibility - Connect to external tools via the Scripting Node; Integration with MSstatsTMT via custom script." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteome_Discoverer_Software_4_4d8ae8fcd2.jpg 245w," sizes="100vw" width="1160" height="533"></figure><h3><strong>Comprehensive tools for proteomic studies</strong></h3><p>With a wide range of database search options and the ability to combine the output from multiple algorithms, Proteome Discoverer software increases confidence in results and decision making through cross-validation. Augment searches with intelligent<strong> INFERYS Rescoring</strong> to increase confidence in peptide identification and quantitation. Whether you acquire your data in <strong>DIA, DDA, or WWA mode, CHIMERYS</strong> <strong>intelligent search algorithm </strong>helps you dig deeper into your data to substantially increase the number of unique peptide identifications, improve protein coverage, extend quantitation capabilities, and uncover new insights.</p><p>Complete sequence coverage and confident identification of post-translational modifications (PTMs) is realized with support for multiple dissociation techniques including collision-induced dissociation (CID), higher-energy collision-induced dissociation (HCD) and electron-transfer dissociation (ETD) in tandem with built-for-purpose search engines.</p><h3><strong>Customizable data analysis workflows</strong></h3><p><strong>Automate and simplify data analysis</strong> through customizable workflows including full support for multiple quantitative workflows. Enjoy experimental flexibility for quantitation by employing isobaric mass tagging with TMT and TMTpro reagent or other isotopic labeling strategies or utilize label-free quantitation techniques. Map quantitative data to biological information through study management and leverage fast, robust algorithms for peak selection and peptide quantification to extract the maximum possible information from quantitative proteomics studies.</p><p>Refine acquisition strategies by generating inclusion and exclusion lists that can be directly imported into instrument methods. Confidently and easily facilitate data comparison, exchange, and verification in compliance with data standards developed by the HUPO Proteomics Standards Initiative (PSI).</p><figure class="image"><img style="aspect-ratio:1232/459;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteomics_Software_Solution_98e62449c5.jpg" alt="Thermo Scientific Proteome Discoverer Software: The workflow system in Proteome Discoverer allows for customizable workflows to analyze complex proteomics data. The workflow system is composed of nodes that can connect in linear or branched pathways. While these workflows are highly customizable, pre-defined workflows for common workflows such as TMT, LFQ, PTM identification and cross-linked peptide ID are included." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteomics_Software_Solution_98e62449c5.jpg 245w," sizes="100vw" width="1232" height="459"></figure><h5><strong>Interactive enrichment table from graphical results to find overrepresented pathways</strong></h5><figure class="image"><img style="aspect-ratio:1344/924;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteome_Discoverer_Software_3_c01db3165a.jpg" alt="Thermo Scientific Proteome Discoverer Software: Interactive enrichment tables allow for the selection of up- or down-regulated proteins or peptides in any view, including volcano plots, PCA plots, and heat maps, and the visualization of corresponding Reactome pathways from the checked proteins to help derive biological interpretation of results. In addition to Reactome pathways, KEGG and Wikipathways as well as gene ontology terms and protein families can be visualized in the enrichment table." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteome_Discoverer_Software_3_c01db3165a.jpg 227w," sizes="100vw" width="1344" height="924"></figure><h5><strong>Pathway maps</strong></h5><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteome_Discoverer_Software_5_c087bb9d6f.jpg" alt="Thermo Scientific Proteome Discoverer Software: Pathways can also be directly visualized, providing biological context and background literature references using pathway maps." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteome_Discoverer_Software_5_c087bb9d6f.jpg 245w," sizes="100vw" width="1119" height="584"></p><h5><strong>Interactive data visualization</strong></h5><figure class="image"><img style="aspect-ratio:973/879;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Proteome_Discoverer_Software_6_2b32110442.jpg" alt="Thermo Scientific Proteome Discoverer Software: Interactive data visualization." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Proteome_Discoverer_Software_6_2b32110442.jpg 173w," sizes="100vw" width="973" height="879"></figure>

Thermo Scientific™ SimGlycan™ Software

SimGlycan software processes and interprets the multi-stage/sequential (MSn) data produced by Thermo Scientific™ Mass Spectrometers, a capability essential to determining glycan heterogeneity and isomeric forms.

<p><strong>Speed the characterization of complex glycans using SimGlycan™ software from PREMIER Biosoft. SimGlycan software processes and interprets the multi-stage/sequential (MS<sup>n</sup>) data produced by Thermo Scientific™ Mass Spectrometers, a capability essential to determining glycan heterogeneity and isomeric forms.</strong></p><p>The software automatically matches experimental mass spectra against a comprehensive database and generates a scored list of candidate structures.</p><h3><strong>Comprehensive Analyses</strong></h3><ul><li>Supports all Thermo Scientific ion trap and Orbitrap™-based instruments performing glycan characterization</li><li>Processes MS<sup>n</sup> data to resolve glycan heterogeneity, branching patterns, and isobaric structures. Up to seven levels of MS fragmentation can be needed to differentiate between glycan structural isomers</li><li>Includes a database of over 22500 glycans to process and verify structures</li><li>Provides a wealth of relevant biological information for the probable glycan structure, including glycan class, reaction, pathway, and enzyme</li><li>Searches for glycans with various chemical derivatives used for reducing end modifications, even if the derivative is not available in the database</li><li>Characterizes Na, Li, Mg, K, and formate adducts, and adduct combinations such as Na + H, Li + H, etc.</li><li>Identifies complex glycosaminoglycan structures, even when modified with substituents such as sulfate, phosphate, and ethanolamine</li><li>Determines cross-ring and double glycosidic cleavages, through a combination of permethyl derivatization and MS<sup>n</sup> data</li></ul><h3><strong>Powerful Reporting</strong></h3><ul><li>Creates reports that include glycan characteristics such as ID, sequence, name, composition, mass, precursor ion <i>m/z</i>, class, reaction, pathway, glycan image and theoretical fragments with corresponding mass and <i>m/z</i> values</li><li>Exports images of glycan structures, fragments, and spectra as JPEG or PNG files</li></ul>

Thermo Scientific LC-MS Data Processing Software

 Thermo Scientific LC-MS software streamlines data analysis with application-specific tools for -omics, pharma, and quant. Gain reliable insights to support decisions.

Thermo Scientific Ardia Platform

Built using cloud technology, the Ardia Platform centralizes information, including scientific data and results, maximizes instrument utilization, and accelerates data analysis to help scientists get closer to the truth.

<h3><strong>Bring your laboratory into a new era of connectivity with the Ardia Platform</strong></h3><p data-start="64" data-end="714"><strong>Digital transformation is a journey driven by the desire to fundamentally improve laboratory working practices by leveraging the latest advances in IT. The Thermo Scientific™ Ardia™ Platform allows the laboratory to harness the same technology.&nbsp;</strong></p><p data-start="64" data-end="714">In an era where laboratories are uncompromising in their pursuit of efficiency, the demand for software that seamlessly connects data, instruments, and scientists is on the rise.</p><p data-start="64" data-end="714">Built using cloud technology, the Ardia Platform centralizes information, including scientific data and results, maximizes instrument utilization, and accelerates data analysis to help scientists get closer to the truth.</p><figure class="image"><img style="aspect-ratio:1440/1127;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_2_4c83f21ef8.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_2_4c83f21ef8.jpg 200w," sizes="100vw" width="1440" height="1127"></figure><h5><strong>Centralize</strong></h5><p>Revolutionize data management by bringing together all your data sources, formats, and applications into one platform. With centralized data, you gain unprecedented control, accessibility, and efficiency, enabling you to make data‑driven decisions with confidence.</p><h5><strong>Unify</strong></h5><p>Say goodbye to the complexities of managing data scattered across various systems and locations. The Ardia Platform integrates with a growing list of software tools and applications for direct data access and automated data transfer, allowing you to harness the power of a unified platform and help eliminate data silos.</p><h5><strong>Streamline</strong></h5><p>Eliminate time‑consuming manual data transfers with automated workflows via the Ardia Platform’s Data Sync tool. Automatically transfer data to and from your repository for applications that are not yet connected so users can focus on what matters most.</p><h5><strong>Collaborate</strong></h5><p>Collaboration goes beyond just centralizing data and integrating software. With a single platform, you can easily share, access, and collaborate on data. Real‑time data updates, shared dashboards, and collaborative tools facilitate efficient teamwork, accelerating project timelines and driving innovation</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_57590fecf7.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_57590fecf7.jpg 245w," sizes="100vw" width="1022" height="450"></p><h3><strong>Data management</strong></h3><p>Securing, managing, and effectively utilizing large volumes of scientific data stored across multiple devices in different formats can be challenging and time-consuming.<br>The Ardia Platform offers robust data management capabilities that address these challenges. With automated central data storage, including backup and archival capabilities, and comprehensive access controls, users can securely access, view, and organize information from various applications more effectively.</p><blockquote><p><strong>webinar: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/4962"><strong>Take control of your data and instruments</strong></a></p></blockquote><div><div data-message-author-role="assistant" data-message-id="ba34c04b-e6ae-4d15-ac9e-9e3606bb4933" dir="auto" data-message-model-slug="gpt-4o"><div><div><h4><strong>Centralize your data and enable accessibility and security</strong></h4><h5><strong>Manage</strong></h5><p data-start="64" data-end="990">The Ardia Platform provides secure, single‑point data management with automated transfer of data and results from <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/76"><strong>Thermo Scientific™ Chromeleon™ Chromatography Data System</strong></a><strong>, </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1758"><strong>Xcalibur™</strong></a><strong>,</strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong> Compound Discoverer™</strong></a><strong>, </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1782"><strong>Proteome Discoverer™</strong></a><strong>,</strong> and<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1837"><strong>BioPharma Finder™ software</strong></a>, as well as third‑party application data via the Ardia Platform’s Data Sync functionality.<br>With single‑point data storage, users can enhance data accessibility, improve data organization and discovery, and reduce or eliminate data duplication.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_3_0ea16b74db.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_3_0ea16b74db.jpg 245w," sizes="100vw" width="1440" height="544"></p><h5><strong>Secure</strong></h5><p data-start="64" data-end="990">Keep data secure and controlled with user login access, system‑generated audit trails, and embedded user and data management tools, customizable to your organization’s specific needs. Streamline your operations and ensure disaster resilience through built‑in capabilities, such as tracking actions and simplifying data backup and archiving.</p></div></div></div></div><h3><strong>Ardia Platform’s Data Viewer</strong></h3><p>The intuitive, web‑based Ardia Platform’s Data Viewer tool provides a <strong>single location</strong> for review of chromatography and mass spectrometry data, delivering consistency across software products integrated with the Ardia Platform.<br>With a new user interface, it’s easy to display chromatograms and spectra, quickly create extracted ion chromatograms, perform peak integration, export spectral data to the<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud™</strong></a> library for easy compound annotation, and view diagnostic channels like pump pressure for troubleshooting.<br>Expedite data review with user‑friendly features that include the ability to import a mass list, export plots in .svg format for high‑resolution visualizations, and quickly display linked data‑dependent acquisitions.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_4_9d3c486827.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_4_9d3c486827.jpg 245w," sizes="100vw" width="1918" height="1012"></p><h3><strong>Instrument management</strong></h3><p>Managing a set of individual instruments is often a manual, time-consuming task. Bringing them together in one place, the Ardia Platform’s Instrument application enables monitoring and management of all connected instruments to maximize utilization and eliminate paper records.<br>This can significantly improve productivity by minimizing downtime, reducing delays, and improving lab efficiency.</p><h4><strong>Effective instrument management to drive laboratory productivity</strong></h4><h5><strong>Monitor</strong></h5><p>Easily view all connected systems from a central location with instrument cards providing real‑time status and data acquisition information for a holistic laboratory view to enable fast, informed decisions.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_5_f985768d28.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_5_f985768d28.jpg 245w," sizes="100vw" width="1692" height="809"></p><h5><strong>Record</strong></h5><p>Digitize, standardize, and centralize instrument logbooks with automated event logging, plus manual entry tools to record maintenance activities, custom notes, and images. Automatic tracking of instrument module movements between systems assists laboratories in maintaining accurate and complete records, helping to ensure instruments are controlled and working properly, instilling confidence in result reliability. Instrument support is accelerated via in‑app service ticket and support package generation for immediate delivery to Thermo Fisher Scientific technical support.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_6_1a2b159f68.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_6_1a2b159f68.jpg 200w," sizes="100vw" width="873" height="680"></p><h5><strong>Schedule</strong></h5><p>Increase laboratory efficiency by optimizing instrument utilization. The Ardia Platform’s Instruments Scheduler tool provides a single point to plan work, view system availability, reserve time, and set maintenance windows on all connected instruments to minimize downtime.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_7_01ca77bc6d.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_7_01ca77bc6d.jpg 245w," sizes="100vw" width="1483" height="548"></p><h5><strong>Utilize</strong></h5><p>The Ardia Platform’s Data Insights application provides out‑of‑the‑box dashboards for key laboratory insights on resource availability, instrument status, and instrument performance in a centralized location. Track and monitor system metrics such as injection quantity, time, volume, type or status, and % utilization across systems and geographical locations. With interactive dashboards that can be filtered by system, system type, location, project, or time, you can easily focus on the metrics that matter most.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_Ardia_Platform_8_3a6b276497.jpg" alt="Thermo Scientific Ardia Platform." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_Ardia_Platform_8_3a6b276497.jpg 245w," sizes="100vw" width="1920" height="937"></p>

Products from Thermo Fisher Scientific - page 15

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