<p><span><strong>This study establishes an integrated workflow for quantitative whole-animal elemental imaging of </strong></span><i><span><strong>Caenorhabditis elegans</strong></span></i><span><strong> by LA-ICP-TOF-MS. Optimized on-slide preparation using petrolatum improved specimen preservation, while oversampling during laser ablation enabled a spatial resolution of 2 μm.</strong></span></p><p><span>Quantitative elemental maps were generated using matrix-matched gelatin standards designed to mimic tissue ablation depth. The workflow addresses key challenges in sample handling, preservation, spatial resolution, and quantification, expanding the use of LA-ICP-TOF-MS for microscale metal biology and other small model organisms.</span></p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article/98/38/28440/5431951/On-Slide-Preparation-of-Caenorhabditis-elegans"><strong>On-Slide Preparation of Caenorhabditis elegans toward Quantitative, High-Resolution LA-ICP-TOF Mass Spectrometry Imaging</strong></a></h4><p>Aidan J. Reynolds# ; Aaron Sue# ; Keith MacRenaris; Thomas V. O’Halloran* ; Tian Autumn Qiu*</p><p>Anal. Chem. (2026) 98 (38): 28440–28453</p><div><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.6c04271">https://doi.org/10.1021/acs.analchem.6c04271</a></div><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><div><div><div><div><div><p>In this study, we established an integrated workflow consisting of sample preparation, imaging, and quantitative data analysis for whole-animal elemental imaging of <i>C. elegans</i> by LA-ICP-TOF-MS using petrolatum as a preferred embedding medium and achieved 2-μm spatial resolution with laser ablation oversampling. Compared to water-based embedding media, hydrocarbon-based petrolatum showed excellent preservation of <i>C. elegans</i> while retaining sufficient optical transparency for microscopy visualization, possessed the necessary nonvolatility for long-term storage, and was elementally pure for high-quality LA-ICP-MS imaging. With the assistance of a home-designed 3D-printed tool, uniform layer media application tool (ULMAT), embedding medium was applied as a uniform layer on top of charged microscope slides for on-slide embedding, freezing, and subsequent elemental analysis of <i>C. elegans</i>. An optional and additional step was also used to extract embedded worms from the embedding media layer to prepare petrolatum-coated worms. Comparisons between petrolatum-embedded worms and petrolatum-coated worms were also made to evaluate sample integrity and imaging data quality. Through several time-series experiments at ambient conditions, we evaluated sample integrity under different sample preparation approaches to determine optimal imaging time frames such that tissue decay and metal delocalization did not impede the accuracy of elemental imaging. We then characterized LA-ICP-TOF-MS imaging artifacts indicative of the stages of sample desiccation. We applied an oversampling technique in LA-ICP-TOF-MS imaging and achieved a 2-μm spatial resolution, providing high resolution imaging of <i>C. elegans</i> elemental content. Finally, using metal-spiked gelatin standards and ImageJ-based data analysis pipeline, we developed quantitative LA-ICP-TOF-MS imaging workflow and successfully produced quantitative elemental profiling of key biological elements in <i>C. elegans</i>.</p><h4><strong>Experimental Section</strong></h4><h5><strong>Microscopy and LA-ICP-TOF-MS Imaging</strong></h5><p>After sample processing including embedding, freezing and optional desiccation, brightfield, GFP and tdTomato fluorescence imaging of embedded and coated worms were taken using a Zeiss Axio Imager.Z2 upright fluorescence microscope. Embedded and coated worms were then taken for elemental analysis by LA-ICP-TOF-MS imaging using an ESL Bioimage 266 nm laser ablation system coupled to a TofWerk icpTOF S2. Samples were ablated with a laser power of 90% using a 5-μm spot size and a 3-μm overlap. Imaging cup and imaging chamber flow rates were set to 200 mL/min and 250 mL/min, respectively, using helium gas. Laser repetition rate was set to 125 Hz with a washout time of 10 ms. Plasma, auxiliary, and nebulizer gas flow were set to 14.0 L/min, 8.0 L/min, and 0.9–1.0 L/min, respectively. Measurement mode was kinetic energy discrimination (KED) using a helium gas flow of 5 mL/min. Time-of-flight elemental analysis was done using a <i>m</i>/<i>z</i> range of 14–256 at a mass resolving power of 1000. All essential microscopy and LA-ICP-TOF-MS parameters for <i>C. elegans</i> imaging are shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5431951/pdf/ac6c04271_si_001/">Table S2</a> and <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5431951/pdf/ac6c04271_si_001/">Table S3</a>.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Selection of Embedding Media To Preserve C. elegans Structural Integrity</strong></h5><p>Preparation of tissue samples for LA-ICP-MS imaging requires preserving tissue morphology and native distribution of elements over possibly hours of instrumental run time. Traits for an ideal embedding medium should be elementally pure to introduce none-to-little background noise, be optically transparent for microscopy, be capable of preserving <i>C. elegans</i> over hours, and not be difficult for the laser to ablate through. We first evaluate the capability of embedding media and application approach to preserve <i>C. elegans</i> structural integrity postprocessing (i.e., after embedding, freezing, and optional desiccation) (<a href="javascript:;">Figure 2</a>A). Two types of embedding media were tested, including aqueous-based hydrophilic media such as OCT and wax-like hydrophobic media such as petrolatum. An isogenic strain of N2, SJ4144, with GFP fluorescence reporters in intestinal cells, was used to better visualize tissues, and brightfield and fluorescence microscopy were used to evaluate tissue morphology.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_38_28440_28453_Figure_2_Summary_of_three_C_elegans_sample_preparation_and_short_term_visualization_of_processed_C_elegans_74a4294b6d.png" alt="Anal. Chem. (2026) 98 (38): 28440–28453: Figure 2. Summary of three C. elegans sample preparation and short-term visualization of processed C. elegans from different preparation. (A) A combined C. elegans embedding workflow for OCT-embedding, petrolatum-embedding, and petrolatum-coating. A synchronized population of day 1 gravid adult C. elegans was rinsed with M9 and transferred to an unseeded NGM plate to let the extra M9 buffer absorb into nematode growth media prior to the embedding workflows. (B) Appearance of day 1 gravid adult SJ4144 C. elegans embedded in OCT, embedded in petrolatum, and coated in petrolatum observed before and after a 1.5-hour time period, visualizing differences in brightfield, GFP fluorescence, and preservation effectiveness. Brightfield black contrast was set to 0 for all microscopy images. OCT-embedded and petrolatum-coated brightfield white contrast was set to 16 000 and 9000, respectively. Petrolatum-coated brightfield white contrast was set to 6000. Green fluorescence black contrast was set to 150, and white contrast was set to 1500 for all microscopy images. White scale bars in microscopy images represent 100 μm." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_38_28440_28453_Figure_2_Summary_of_three_C_elegans_sample_preparation_and_short_term_visualization_of_processed_C_elegans_74a4294b6d.png 245w," sizes="100vw" width="1289" height="789"></p><p>We found that the tested water-based embedding media were ineffective in preventing embedded <i>C. elegans</i> from desiccation and subsequent structural deformation (<a href="javascript:;">Figure 2</a>B, <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5431951/pdf/ac6c04271_si_001/">Figure S2</a>). In OCT-embedded worms, the morphology and fluorescence reporter were clearly preserved immediately after the slide was taken out of the freezer (hour 0); however, signs of desiccation appeared after 1.5 h (<a href="javascript:;">Figure 2</a>B). Hygroscopic dopants such as glycerol can be added to improve water retention capabilities of these media; however, these molecules typically function as osmolytes (<a href="javascript:;">40</a>) or penetrating cryoprotectants. These additives likely displaced water from tissues, resulting in more rapid tissue desiccation. Compared to OCT, fish gelatin and glycerol-doped CMC showed better preservation of reporter fluorescence and worm body, while the wrinkled appearance of the worm cuticle indicated deformation (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5431951/pdf/ac6c04271_si_001/">Figure S2</a>).</p><h5><strong>Simultaneous Mapping of Multiple Elements by High-Resolution LA-ICP-TOF-MS</strong></h5><div><p>The LA-ICP-TOF-MS technology provides the capability to image most elements on the periodic table simultaneously with the TOF analyzer. Using this technology, we successfully demonstrated simultaneous mapping of biologically relevant elements such as <sup>31</sup>P, <sup>55</sup>Mn, <sup>56</sup>Fe, <sup>63</sup>Cu, and <sup>66</sup>Zn in <i>C. elegans</i>, exceeding previous quadrupole-based LA-ICP-MS studies on <i>C. elegans</i> with one or two elements and their respective isotopes. (<a href="javascript:;">31−33</a>) The metallome of <i>C. elegans</i> consists of Na, Mg, K, Ca, Mn, Fe, Cu, and Zn representing the most abundant metals, and lower-abundance metals such as Co, Mo, and Se. (<a href="javascript:;">53−56</a>) While LA-ICP-TOF-MS as a technology provided simultaneous visualization of all relevant elements in analyzed <i>C. elegans</i>, in this work, we present the five most abundant biologically relevant elements, particularly for later quantitative analysis, for their biological importance.</p></div><div><p>We visualize <sup>31</sup>P, <sup>55</sup>Mn, <sup>56</sup>Fe, <sup>63</sup>Cu, and <sup>66</sup>Zn simultaneously in day 1 gravid adult <i>C. elegans</i> prepared by both petrolatum coating (<a href="javascript:;">Figure 4</a>A) and petrolatum embedding (<a href="javascript:;">Figure 4</a>B). By comparing elemental images with brightfield microscope images, we were able to observe discrete visualization of <i>C. elegans</i> anatomy for the assignment of elemental localization. In petrolatum-coated worms, <sup>31</sup>P was found throughout the worm’s body and most strongly accumulated in the intestinal cells and posterior region of the worm. <sup>31</sup>P is an essential element in biomolecules such as DNA, phospholipids, energy-storage molecules such as ATP, and as such, its abundance can reflect the cell size and activity across regions of tissue. (<a href="javascript:;">57</a>)<sup>55</sup>Mn exhibited the most discrete localization of imaged elements throughout the intestinal tract of <i>C. elegans</i> with a punctate pattern. This defined distribution of <sup>55</sup>Mn has previously only been visualized using synchrotron-XFM technology and was first achieved in this work with LA-ICP-MS imaging. (<a href="javascript:;">52</a>)<sup>56</sup>Fe showed some increased background noise due to the presence of the isobaric interference ArO<sup>+</sup>; however, we used kinetic energy discrimination within the collision cell and improved <sup>56</sup>Fe signals. <sup>56</sup>Fe and <sup>55</sup>Mn showed higher relative abundances in the anterior intestine in likely the grinder, with significant localization to the intestinal cells throughout the worm body. Meanwhile, <sup>56</sup>Fe did not exhibit a punctate distribution like <sup>55</sup>Mn throughout intestinal cells. While an essential element, <sup>63</sup>Cu was found in low abundance throughout <i>C. elegans</i>, potentially due to the organism’s reduced use of the element in biological processes. (<a href="javascript:;">58</a>) Improved imaging of <sup>63</sup>Cu can be achieved by using LA-ICP-QQQ-MS imaging if copper biology is of interest. While <sup>55</sup>Mn and <sup>56</sup>Fe showed enrichment in <i>C. elegans</i>’ anterior intestine, <sup>66</sup>Zn showed little or no enrichment in the anterior region of <i>C. elegans</i> and instead showed increased abundance in the posterior region of imaged worms. Synchrotron-XFM imaging has revealed similar zinc distributions with posterior intestinal cells on day 5 <i>C. elegans</i> possessing high zinc content; (<a href="javascript:;">52</a>) however, our 2-μm spatial resolution is not sufficient to resolve the zinc-rich gonad arms from the intestine. Additionally, the orientation of <i>C. elegans</i> during imaging may confound resolving the gonad arms from the intestine. We also noticed that images from petrolatum-coated worms showed a noisier background compared to others (<a href="javascript:;">Figures 2</a>B and <a href="javascript:;">4</a>A). One likely reason is that the laser was directly ablating the bare glass slides without embedding media on top of it and therefore introduced more interfering signals from glass slides contaminants such as <sup>56</sup>Fe from iron oxide (Fe<sub>2</sub>O<sub>3</sub>) and <sup>66</sup>Zn from zinc oxide (ZnO). Additionally, metal contamination could be introduced during the transfer step in creating petrolatum-coated worms and increased background noises. Metal impurities may be found in adhesives such as glue, (<a href="javascript:;">59, 60</a>) which was used to construct the eyelash tool for transferring worms. Repeated cleaning of the eyelash pick between transfers using 70% ethanol solutions may result in a slow dissolution of the glue, which may have subsequently resulted in leaching of metal impurities onto the glass slide when dragged across the surface during transfer. Further investigations should be made to examine possible sources of metal contamination during sample preparation.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_38_28440_28453_Figure_4_Brightfield_microscopy_and_elemental_imaging_of_day_1_gravid_adult_wildtype_N2_C_elegans_9bdf0f4129.jpg" alt="Anal. Chem. (2026) 98 (38): 28440–28453: Figure 4. Brightfield microscopy and elemental imaging of day 1 gravid adult wildtype N2 C. elegans prepared by petrolatum-based methods. (A) Brightfield microscopy and LA-ICP-TOF-MS imaging of a petrolatum-coated C. elegans. (B) Brightfield microscopy and LA-ICP-TOF-MS imaging of a petrolatum-embedded C. elegans. LA-ICP-TOF-MS imaging was able to perform simultaneous mapping of 31P and essential trace elements including 55Mn, 56Fe, 63Cu, and 66Zn. Lower limits for all elements were set to 0 ppm, and upper limits were set to 99th percentile for all elements except 55Mn which was set to 99.9th percentile. Brightfield black contrast and white contrast were set to 0 and 9000, respectively. White scale bars represent 100 μm." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_38_28440_28453_Figure_4_Brightfield_microscopy_and_elemental_imaging_of_day_1_gravid_adult_wildtype_N2_C_elegans_9bdf0f4129.jpg 221w," sizes="100vw" width="1600" height="1128"></p><p>When comparing petrolatum-coated elemental images (<a href="javascript:;">Figure 4</a>A) to petrolatum-embedded elemental images (<a href="javascript:;">Figure 4</a>B), several notable differences were observed. The background signal was drastically reduced in all ion images of petrolatum-embedded <i>C. elegans</i>. Elemental contaminants are present in glass slides, and with petrolatum serving as a barrier between the laser and the microscope slide, these contaminant signals are not observed through the direct ablation of glass. Additionally, minor differences in elemental localization were observed between petrolatum-embedded and -coated <i>C. elegans</i>. Across petrolatum-embedded replicates, elements that were found to be primarily intestinally localized in petrolatum-coated images showed somewhat broadened localization such as <sup>31</sup>P and <sup>56</sup>Fe. We also observed differences in concentration scaling for <sup>31</sup>P, <sup>55</sup>Mn, <sup>56</sup>Fe, <sup>63</sup>Cu, and <sup>66</sup>Zn across imaged replicates. Such variation could be attributed to embedding media matrix effects altering plume properties and impacting spatial clarity in imaging or could be due to biological variations. Future studies should focus on characterizing the impact of worm orientation, embedding media thickness, and developmental variations on the slight differences in metal distribution.</p></div><h4><strong>Conclusion</strong></h4><p>LA-ICP-MS imaging is an important imaging modality for metal biology research in model animals. Previous studies have performed LA-ICP-MS imaging on <i>C. elegans</i>, but the sample preparation and technological limitations made it challenging to achieve high-resolution, multi-element, and quantitative imaging. (<a href="javascript:;">31−33</a>) We developed an integrated workflow that includes sample preparation, instrumental analysis and data processing to enable high-resolution LA-ICP-TOF-MS imaging with quantification on <i>C. elegans</i>, providing a powerful tool for future metal biology research in this classical biology model. We first developed a 3D-printed tool to create a uniform and a thin layer of viscous embedding media on glass slide for on-slide embedding of <i>C. elegans</i>. Three different sample preparations, OCT-embedded, petrolatum-embedded and petrolatum-coated, were evaluated using microscopy and subsequent LA-ICP-MS imaging. We demonstrated that petrolatum preserved reporter fluorescence, tissue morphology, and elemental distribution for a longer period when compared to conventional embedding media such as OCT. Through oversampling laser shots, we were able to achieve an effective 2-μm spatial resolution in LA-ICP-MS imaging, allowing for resolving cellular elemental compartmentalization that has been previously only observed in XFM studies. (<a href="javascript:;">52, 72</a>) We further established a data analysis pipeline toward quantitative LA-ICP-TOF-MS imaging. With gelatin standards, we demonstrated quantitative imaging of five endogenous elements simultaneously in one sample, allowing colocalization of worm fluorescence reporters, brightfield images and different elements.</p></div></div></div></div></div></div>

On-Slide Preparation of Caenorhabditis elegans toward Quantitative, High-Resolution LA-ICP-TOF Mass Spectrometry Imaging

<p><span><strong>Commercial and public spectral libraries provide broad coverage for LC-MS/MS identification, but they cannot contain every compound that matters to a specific laboratory. Proprietary products, metabolites, intermediates, impurities, degradation products, biomarkers, and internally characterized compounds may be highly relevant even if they are absent from standard reference collections. NIST26 allows laboratories to build their own MS/MS user libraries and integrate them directly into routine search workflows, creating a focused resource tailored to their analytical needs.</strong></span></p><h4><span><strong>Why Create a User MS/MS Library?</strong></span></h4><p><span>User libraries are usually much smaller than commercial or public spectral databases, but their value is not determined by size alone.</span></p><p><span>A laboratory-specific library may contain exactly the compounds most important for a particular application. These can include:</span></p><ul><li><span>proprietary products,</span></li><li><span>known metabolites,</span></li><li><span>synthesis intermediates,</span></li><li><span>impurities,</span></li><li><span>degradation products,</span></li><li><span>biomarkers,</span></li><li><span>compounds associated with specific industrial or environmental samples.</span></li></ul><p><span>Such libraries can therefore provide highly relevant identifications in pharmaceutical development, industrial R&amp;D, medical laboratories, environmental analysis, and other specialized fields. A relatively small collection of carefully characterized compounds may be more useful for a particular laboratory than a much larger general-purpose database.&nbsp;</span></p><h4><span><strong>What Information Can Be Stored with Each Spectrum?</strong></span></h4><p><span>Creating a useful library entry involves more than importing an MS/MS spectrum.</span></p><p><span>A complete record can combine several types of information, including the experimental spectrum, chemical structure, instrumental parameters, ionization information, sample history, and additional user-defined metadata.</span></p><p><span>Spectra can be transferred from vendor software into NIST Library Search, or they can be sent from the Chromatogram tab directly to the Library Search environment in NIST26. Chemical structures can be imported through the Windows clipboard from a molecular drawing program, while standard experimental parameters and sample-history information can be prepared separately and added to the entry.&nbsp;</span></p><p><span>The ability to keep analytical metadata together with the spectrum is particularly important for internally generated libraries because it preserves the context in which the reference spectrum was acquired.</span></p><h4><span><strong>Using Tags to Organize LC-MS/MS Metadata</strong></span></h4><p><span>NIST26 supports a range of structured tags for LC-MS/MS spectra.</span></p><p><span>These can describe parameters such as:</span></p><ul><li><span>spectrum type,</span></li><li><span>compound type,</span></li><li><span>ion name,</span></li><li><span>precursor type,</span></li><li><span>precursor </span><i><span>m/z</span></i><span>,</span></li><li><span>collision energy,</span></li><li><span>instrument type,</span></li><li><span>sample identifier,</span></li><li><span>ionization mode,</span></li><li><span>ion polarity,</span></li><li><span>collision gas,</span></li><li><span>pressure,</span></li><li><span>mass range,</span></li><li><span>maximum intensity,</span></li><li><span>cone voltage,</span></li><li><span>charge,</span></li><li><span>molecular weight,</span></li><li><span>known impurities,</span></li><li><span>related CAS numbers,</span></li><li><span>peptide sequence and peptide modifications.</span></li></ul><p><span>This provides a convenient way to attach searchable and standardized experimental information to spectra rather than leaving all metadata in an unstructured comment field.&nbsp;</span></p><p><span>Tags can be entered individually through the <strong>Additional Info</strong> section in the Librarian interface, but when many spectra are being added, a grouped approach can be considerably faster.&nbsp;</span></p><h4><span><strong>Adding Groups of Tags Efficiently</strong></span></h4><p><span>For repetitive workflows, metadata can be prepared in advance and pasted into NIST26 as a group.</span></p><p><span>The presentation recommends maintaining frequently used tag sets in a simple text document, then copying them into the synonym field and using <strong>Add to List</strong> to convert them into structured information.</span></p><p><span>This is especially useful when the vendor software already transfers some parameters automatically. Users can then add only the missing information, such as ion adduct or polarity, rather than duplicating metadata already imported with the spectrum.&nbsp;</span></p><p><span>Care is required because entering information that is already present may create duplicate metadata.</span></p><p><span>This workflow can substantially accelerate library creation when many spectra share the same instrument configuration or acquisition parameters.</span></p><h4><span><strong>Preserving Sample History</strong></span></h4><p><span>A spectral match is more useful when the origin of the reference spectrum is known.</span></p><p><span>NIST26 therefore allows detailed sample information to be stored in the comment field. For batches of related samples, the text can be prepared in Notepad or another editor and pasted into multiple records.</span></p><p><span>Examples of useful information include sampling location, sampling date and time, analyst name, organization, internal sample identifier, project information, or other relevant context.&nbsp;</span></p><p><span>For environmental, clinical, pharmaceutical, and industrial laboratories, this information can become an important part of data traceability.</span></p><h4><span><strong>Adding Molecular Structures</strong></span></h4><p><span>A user library becomes considerably more useful when spectra are linked to molecular structures.</span></p><p><span>Structures can be created from scratch in a chemical drawing program. Alternatively, a similar structure can be located in NIST Search and sent to the default structure editor, where it can be modified as needed.</span></p><p><span>Once completed, the structure can be copied to the Windows clipboard and inserted into the NIST Librarian spectrum-information window. NIST26 can then calculate the molecular formula and molecular weight from the imported structure.&nbsp;</span></p><p><span>This linkage between spectrum and structure supports more informative library displays and structure-based searching.</span></p><h4><span><strong>Creating Custom User-Defined Tags</strong></span></h4><p><span>In addition to the standard LC-MS/MS tags, laboratories can define their own metadata fields.</span></p><p><span>Examples shown include identifiers such as:</span></p><ul><li><span>chemist,</span></li><li><span>laboratory notebook number,</span></li><li><span>analyst.</span></li></ul><p><span>The information can be prepared in a text editor and added using the appropriate tag syntax. Once configured in the <strong>Comment Field Display</strong> settings, these values are displayed as separate structured lines rather than remaining embedded in the general comments.&nbsp;</span></p><p><span>This flexibility makes the library more suitable for laboratories with established internal documentation systems or quality-management requirements.</span></p><p><span>NIST can also automatically add information such as the InChIKey and an estimated retention index when appropriate structural information is available.&nbsp;</span></p><h4><span><strong>High-Resolution and Low-Resolution Libraries Should Be Kept Separate</strong></span></h4><p><span>User libraries do not have to contain only high-resolution spectra.</span></p><p><span>Low-resolution MS/MS spectra may also be valuable, including spectra generated by:</span></p><ul><li><span>in-source collision on single-quadrupole instruments,</span></li><li><span>triple-quadrupole MS/MS,</span></li><li><span>other nominal-mass workflows.</span></li></ul><p><span>The recommendation is to maintain <strong>separate high-resolution and low-resolution user libraries</strong>, because the appropriate search strategies and handling can differ.&nbsp;</span></p><p><span>Low-resolution spectra can still generate strong library-search results and may be particularly useful when laboratories want to preserve historical data or incorporate spectra from multiple instrument types.</span></p><h4><span><strong>Important Software Considerations When Importing Spectra</strong></span></h4><p><span>The presentation also highlights several practical software issues that users should be aware of.</span></p><p><span>One concerns the <strong>Intensity Threshold</strong> setting in the Spectrum Import Options window. When an intensity threshold is applied during import from vendor software, high-resolution spectral values may be converted to nominal mass rather than preserving the expected decimal precision.</span></p><p><span>For laboratories building high-resolution user libraries, this is an important detail because accurate-mass information is one of the main advantages of HRMS data.</span></p><p><span>Another issue affects some library-search modes after high-resolution spectra are added to a user library.</span></p><h4><span><strong>HiRes No Precursor and Hybrid Search Limitations</strong></span></h4><p><span>After adding high-resolution spectra, certain <strong>HiRes NoPrecursor</strong> and <strong>Similarity Hybrid MS/MS</strong> searches may not function correctly.</span></p><p><span>A workaround involves exporting the affected library using <strong>Lib2NIST</strong> into MSP ASCII files together with the associated molecular structure files, then importing the data back into NIST library format.&nbsp;</span></p><p><span>The presentation specifically warns against attempting the problematic MS/MS Hybrid Search under these conditions because it may cause the software to crash.</span></p><p><span>An EI Normal search can mimic some of the functionality of HiRes No Precursor and may work effectively when high- and low-resolution libraries are searched together. HiRes NoPrecursor can also operate with presearch disabled, although this can make searching considerably slower.&nbsp;</span></p><h4><span><strong>Display Issues in the Chromatogram Window</strong></span></h4><p><span>Another software behavior concerns how spectral values are displayed in the Chromatogram tab.</span></p><p><span>Values from Spectrum Import Options are reflected in the head-to-head spectral display. If settings are adjusted for low-resolution spectra, the displayed masses may appear truncated.</span></p><p><span>Importantly, this visual behavior does <strong>not</strong> affect the results in the accurate-mass deconvolution and library-searching table; it affects only the spectral display at the top of the Chromatogram window.&nbsp;</span></p><p><span>Distinguishing display behavior from actual processing results is important to avoid misinterpreting valid search results as corrupted data.</span></p><h4><span><strong>Updating the Library After Adding New Entries</strong></span></h4><p><span>User-library maintenance does not end when a spectrum has been added.</span></p><p><span>Whenever a new entry containing a molecular structure is introduced, the <strong>structure index should be updated</strong> so that the new compound can be included properly in structure searching.</span></p><p><span>The InChIKey appears to update with the structure, but if duplicate records are not being handled correctly, the InChIKey index may also need to be rebuilt.&nbsp;</span></p><p><span>If a new library folder is added to the NIST26 MSSEARCH directory while the software is already running, users should also update the library list so that the newly added collection becomes available without restarting the entire environment.&nbsp;</span></p><h4><span><strong>Using Lib2NIST to Repair High-Resolution User Libraries</strong></span></h4><p><span>The <strong>Lib2NIST</strong> utility plays an important role in resolving some high-resolution library-search issues.</span></p><p><span>The workflow involves exporting the problematic high-resolution library to an MSP file together with its molecular structure files and then re-importing the data into NIST library format.</span></p><p><span>The corrected library can then be placed back into the NIST26 MSSEARCH directory. It is advisable to preserve the original library under a different name until the repaired version has been tested successfully.&nbsp;</span></p><p><span>The presentation also recommends closing NIST Search while performing Lib2NIST conversions.</span></p><h4><span><strong>Small Libraries Can Deliver High Analytical Value</strong></span></h4><p><span>The central message is straightforward: a user library does not need to contain hundreds of thousands of compounds to be useful.</span></p><p><span>A carefully curated collection of spectra from compounds that repeatedly appear in a laboratory's own samples can dramatically improve identification relevance. This is especially valuable for compounds that are proprietary, newly synthesized, application-specific, or otherwise poorly represented in public and commercial databases.</span></p><p><span>By combining MS/MS spectra with structures, acquisition metadata, sample history, tags, and internally defined information, NIST26 can become more than a search engine for commercial databases. It can serve as a laboratory-specific knowledge base built around compounds that genuinely matter to the user's work.</span></p><p><span>For specialized LC-MS/MS workflows, that may be one of the most valuable ways to extend the capabilities of spectral library searching.</span></p>

Creating MS/MS User Libraries in NIST26

<p><strong>Wiley announces the expansion of its spectral libraries across IR and Raman, adding empirical and computed reference data spanning forensics, pigments and dyes, mineralogy, materials, polymers, and pharmaceuticals. This release adds over a thousand new empirical reference spectra, plus more than 429,000 new SmartSpectra records, across dozens of updated and new databases. This brings the combined collections to over 1.4 million IR spectra and 230,000 Raman spectra.</strong></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Wiley_Wiley_continues_to_expand_its_IR_Raman_and_Smart_Spectra_spectral_libraries_806b34cdc1.jpg" alt="Wiley: Wiley continues to expand its IR, Raman, and SmartSpectra spectral libraries" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Wiley_Wiley_continues_to_expand_its_IR_Raman_and_Smart_Spectra_spectral_libraries_806b34cdc1.jpg 245w," sizes="100vw" width="1600" height="838"></p><p>“<i>Scientific discoveries and business decisions depend on trustworthy analytical results,</i>” said <strong>Graeme Whitley</strong>, senior director, data science solutions at Wiley. “<i>The value of a spectral library expansion is not simply that it adds more records. It gives analysts more relevant reference candidates when they encounter unfamiliar materials, whether they are verifying a polymer, investigating a pharmaceutical sample, examining a mineral, or screening a forensic specimen.</i>”</p><h4><strong>Highlights include:</strong></h4><ul><li><strong>Forensics:</strong> A new Raman forensics database adds reference spectra for colorant and dye identification on textiles, drawn from real fiber-evidence research, useful for investigators working on dye and textile analysis.</li><li><strong>Pigments and dyes:</strong> New Raman and IR data significantly broadens pigment and dye coverage, including historic artists' pigments, supporting art conservation and cultural-heritage authentication work.</li><li><strong>Minerals: </strong>New Raman and IR data extends coverage to minerals from different localities and Martian mineral analogs. This release includes new Raman additions from our ongoing collaboration with the American Museum of Natural History, now cross-referenced with DANA Classification Numbers and Mindat IDs, giving mineralogists and gemologists an easier way to identify entries against established references.</li><li><strong>Materials and semiconductors: </strong>New Raman and IR data covers crystal growth relevant to battery materials, rare-earth-doped magnetic crystals, and flexible and 2D semiconductor materials, useful for researchers in battery, magnetic materials, and electronics work.</li><li><strong>Polymers: </strong>New Raman and IR data spans 3D-printed, MOF-integrated microlattices, environmental plastic aging and recycled PET materials, and food packaging plastics. New Raman reference spectra also cover more than two dozen synthetic polymer types for identifying microplastics in environmental samples.</li><li><strong>Clinical and pharma:</strong> New Raman and IR data covers antibiotic classes, including beta-lactams, and the WHO's essential antibiotic list, plus bone mineralization studies in clinical models. A new IR dataset also adds spectra for common over-the-counter medications, including aspirin, ibuprofen, and paracetamol, helping quality control teams confirm formulations faster.</li><li><strong>SmartSpectra: </strong>Our SmartSpectra IR, Raman, and vapor-phase IR collections continue to grow, adding<strong> 243,000+ IR</strong>, <strong>67,000+ Raman</strong>, and <strong>119,000+ vapor-phase IR</strong> computed reference spectra to support broad, high-throughput identification.</li></ul><blockquote><p class="cke-user_style-important"><a target="_blank" rel="noopener noreferrer" href="https://sciencesolutions.wiley.com/spectral-databases/"><strong>Learn more about Wiley Spectral Databases</strong></a></p><p class="cke-user_style-important"><a target="_blank" rel="noopener noreferrer" href="https://sciencesolutions.wiley.com/how-to-update-knowitall-databases/"><strong>Existing subscribers can find guidance on updating their databases here</strong></a></p></blockquote><h4><strong>Wiley Spectral Databases</strong></h4><p>Wiley's spectral databases are consistently evolving to meet today's research demands, covering multiple spectral techniques across a wide range of applications including polymers, materials, environmental, forensics, toxicology, pharmaceutical, biotech, automotive, aerospace, food, cosmetics, and more. Built on rigorous quality protocols, Wiley delivers industry-leading spectral data and intelligent tools to accelerate analysis and deliver deeper insights — making it the authoritative, trusted source that analytical labs worldwide rely on.&nbsp;</p>

Wiley continues to expand its IR, Raman, and SmartSpectra spectral libraries

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VUV Analytics VGA-100 Gas Chromatography Detector for TRACE 1600 Series GC

The VGA-100 GC detector with VUV technology and TRACE 1600 GC delivers rapid, accurate analysis of isomers and complex mixtures with higher productivity and reliability.

<p><strong>The Thermo Scientific™ VGA-100™ Gas Chromatography Detector (developed by VUV Analytics, Inc.) introduces the next generation of GC detection through revolutionary vacuum ultraviolet (VUV) absorption technology. Delivering unmatched sensitivity, selectivity, and precision, the VGA-100 provides both qualitative and quantitative data with exceptional accuracy.</strong></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_2_e45d1cf5c3.jpg" alt="Thermo Scientific VGA-100 Gas Chromatography Detector." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_2_e45d1cf5c3.jpg 165w," sizes="100vw" width="752" height="710"></p><h3><strong>Key Benefits</strong></h3><ul><li><strong>Seamless integration with TRACE 1600 Series GC</strong> – Together, the VGA-100 and<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/483"><strong> TRACE™ 1600 GC </strong></a>form a powerful, scalable, and intuitive system designed to meet the most demanding laboratory workflows.</li><li><strong>Enhanced productivity and speed</strong> – Faster analysis, higher throughput, and reduced operational costs thanks to automated spectral deconvolution and streamlined data processing.</li><li><strong>Superior selectivity and clarity</strong> – Compound-specific absorption spectra enable confident identification of isomers and co-eluting compounds without baseline separation.</li><li><strong>Universal and mass-sensitive detection</strong> – Provides comprehensive 3D data (time, wavelength, intensity) with library matching for reliable compound identification across a broad range of analytes.</li><li><strong>Ease of use</strong> – No vacuum pumps required, minimal maintenance, intuitive operation, and full compatibility with both R&amp;D and QC environments.</li><li><strong>VUV Analyze™ Software integration</strong> – Push-button workflows, automated Time Internal Deconvolution™ (TID), and ready-to-use spectral libraries deliver fast, reliable, and reproducible results.</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_5_e387eb9360.jpg" alt="Thermo Scientific VGA-100 Gas Chromatography Detector: VUV spectra of hydrocarbons exhibit class-based similarities, simplifying complex fuel mixture analysis." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_5_e387eb9360.jpg 245w," sizes="100vw" width="1170" height="552"></p><h3><strong>Applications</strong></h3><p>The VGA-100 detector addresses critical analytical challenges such as accurate isomer identification, analyte co-elution, long run times, and complex data interpretation. It is especially impactful in:</p><ul><li><strong>Petrochemical analysis</strong> – Simplifies PIONA (paraffins, isoparaffins, olefins, naphthenes, aromatics) characterization in finished fuels, enabling rapid, automated fuel analysis.</li><li><strong>Environmental, food, and pharmaceutical testing</strong> – Reliable quantification of complex mixtures with improved accuracy and reduced calibration complexity.</li><li><strong>Quality control and research labs</strong> – Scalable, intuitive platform supporting compliance, throughput, and robust data integrity.</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_3_ddcbe84bde.jpg" alt="Thermo Scientific VGA-100 Gas Chromatography Detector: Simplified PIONA compound analysis in finished gasoline." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_3_ddcbe84bde.jpg 245w," sizes="100vw" width="956" height="426"></p><h3><strong>Summary</strong></h3><p>The <strong>VGA-100 GC Detector</strong> sets a new benchmark in gas chromatography by combining VUV absorption technology with the robust performance of the TRACE 1600 Series GC. Laboratories gain a powerful “ready-to-use” solution that enhances throughput, accuracy, and confidence across diverse industries.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_4_5595ee9da1.jpg" alt="Thermo Scientific VGA-100 Gas Chromatography Detector." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VGA_100_Gas_Chromatography_Detector_4_5595ee9da1.jpg 139w," sizes="100vw" width="816" height="918"></p>

VUV Analytics VUV Detector for TRACE 1600 Series GC

Thermo Scientific VGA-100 and LUMA VUV detectors for TRACE 1600 GC deliver accurate hydrocarbon speciation, impurity detection, and trace-level analysis with speed and reliability.

<div><div><div><div><div><h4><strong>Precision, clarity, and confidence from VUV spectroscopy in GC</strong></h4></div></div><div><div><p>VUV detectors paired with the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/483"><strong>Thermo Scientific TRACE 1600 Series GC </strong></a>conquer the challenge of complex mixtures, co-eluting compounds, and isomer differentiation&nbsp;for accurate hydrocarbon speciation, impurity detection, and trace-level detection.</p><p>Gas Chromatography (GC) is evolving, and VUV (Vacuum Ultraviolet) technology is at the forefront of this transformation. Now available on the TRACE 1600 Series GC, VUV spectroscopy, through VUV <strong>Analytics VGA-100 </strong>detector and the<strong> LUMA detector</strong>, provides accuracy in hydrocarbon speciation, impurity detection, and trace-level analysis.</p><h5><strong>Greater accuracy, automation, and confidence in your GC analysis</strong></h5><p>Traditional GC detectors struggle with complex mixtures, co-eluting compounds, and isomer differentiation. VUV spectroscopy overcomes these limitations by using absorption-based detection, capturing unique molecular fingerprints for each compound.</p><div><h3><strong>How VUV technology works</strong></h3></div><div><div><div><div><div><p>VUV detection provides qualitative and quantitative spectral information for most gas phase compounds.&nbsp;</p></div></div></div></div><div><div><div><div><div><p><strong>Broad-spectrum absorption:&nbsp;</strong>VUV detectors measure how molecules absorb light in the vacuum ultraviolet range (120–240 nm), revealing unique spectral signatures.</p><p><strong>Automated compound ID:&nbsp;</strong>To reduce errors and improve analysis speed, VUV software automatically deconvolutes overlapping peaks. unlike traditional GC detectors.</p><p><strong>Quantitative and qualitative insights:&nbsp;</strong>VUV enables compound identification and quantification in a single run by analyzing complete spectral data.</p></div></div></div></div></div><div><div><div><div><h4><strong>Principle of operations</strong></h4><div><div><div><div><ol><li><b style="font-size:1.0pc;"><strong>Sample injection in the GC: </strong></b>A sample is injected into the GC system and separated into its components as it travels through the GC column.</li><li><strong>Elution from the analytical column:&nbsp;</strong>The separated components elute from the GC column and enter the VUV detector.</li><li><strong>VUV light source:&nbsp;</strong>A deuterium lamp as VUV light source emits light in the vacuum ultraviolet range (typically 120-200 nm).</li><li><strong>Flow cell:&nbsp;</strong>The eluted components pass through a flow cell where they are exposed to the VUV light.</li><li><strong>Analytes absorption of VUV light:&nbsp;</strong>As components pass through the flow cell, they absorb VUV light at specific wavelengths. Each compound has a unique absorption spectrum in the VUV range.</li><li><strong>Analytes detection:&nbsp;</strong>Photodiode array detector measures the intensity of the transmitted VUV light. The decrease in light intensity corresponds to the absorption by the analytes.</li><li><strong>Data processing:&nbsp;</strong>Detector sends the signal to a data processing system, which converts the absorption data into a chromatogram.</li></ol><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VUV_Detector_for_TRACE_1600_Series_GC_e3f5a229d6.jpg" alt="Thermo Scientific  VUV Detector for TRACE 1600 Series GC." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VUV_Detector_for_TRACE_1600_Series_GC_e3f5a229d6.jpg 245w," sizes="100vw" width="2048" height="1128"></p><div><div><div><h3><strong>VUV for petrochemical and refining</strong></h3><ul><li><strong>PIONA analysis: </strong>Accurately classify paraffins, isomers, olefins, naphthenes, and aromatics with automated deconvolution for fast, confident hydrocarbon speciation and group type analysis in complex fuels.</li><li><strong>Fuel quality control (ASTM D8071):</strong> Ensure compliant, efficient fuel characterization using VUV’s spectral fingerprints, delivering fast, automated analysis for gasoline and other fuel blends.</li><li><strong>Sulfur &amp; nitrogen speciation:</strong> Detect and speciate sulfur and nitrogen compounds at trace levels in fuels, ensuring regulatory compliance and protecting product quality.</li></ul></div></div></div><div><div><div><h3><strong>VUV for pharmaceutical and chemicals</strong></h3><ul><li><strong>Residual solvent analysis: </strong>Faster, more sensitive detection of residual solvents, ensuring compliance with USP &lt;467&gt; and reducing reanalysis with precise, automated detection.</li><li><strong>Impurity profiling in APIs: </strong>VUV absorbance provides greater selectivity and lower detection limits than traditional GC detectors, ensuring reliable impurity profiling in even the most complex APIs.</li><li><strong>Trace-level contamination detection: </strong>Identify unknown contaminants at low levels in pharmaceuticals, chemicals, and environmental samples with enhanced selectivity and sensitivity.</li></ul></div><div><div><div><div><div><h4><strong>Benefits of upgrading to GC-VUV</strong></h4><div><div><div><div><div><p><strong>Hydrocarbon speciation</strong></p><ul><li>Distinguish paraffins, olefins, naphthenes, and aromatics (PONA) effortlessly</li><li>Eliminate misidentification errors common with FID and MS</li><li>Automate peak integration and classification</li></ul><div><div><div><div><div><p><strong>Trace impurity detection</strong></p><ul><li>Detect sulfur, nitrogen, and oxygen compounds at trace levels</li><li>Ensure compliance with regulatory standards in fuels and pharmaceuticals</li><li>Identify unknown contaminants in a single run</li></ul><div><div><div><div><div><p><strong>Analysis and workload</strong></p><ul><li>Decrease complex calibration standards requirement</li><li>Automated spectral deconvolution = less manual processing</li><li>Improved lab efficiency and throughput</li></ul><div><h3><strong>Which detector is right for you?</strong></h3><p>VGA-100 and LUMA detectors integrate seamlessly with the TRACE 1600 Series GC, offering plug-and-play installation, intuitive software, and superior analytical performance.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_VUV_Detector_for_TRACE_1600_Series_GC_2_f6a599c167.jpg" alt="Thermo Scientific  VUV Detector for TRACE 1600 Series GC." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_VUV_Detector_for_TRACE_1600_Series_GC_2_f6a599c167.jpg 245w," sizes="100vw" width="777" height="258"></p><blockquote><ul><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2177"><strong>VGA-100 detector</strong></a></li><li><strong>LUMA detector</strong></li></ul></blockquote></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></div></div></div></div></div></div></div></div></div>

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