<p><strong>This study investigates the chemical transformations of Eugenia uniflora essential oil under thermal conditions simulating gas chromatography analysis. GC–MS and NMR revealed that sesquiterpenes of the germacrene type, such as furanodiene, undergo sigmatropic rearrangement to form elemene-type compounds, including curzerene.</strong></p><p>Thermal treatment confirmed the formation of rearrangement products, indicating that bioactive properties historically attributed to curzerene may instead originate from furanodiene. The findings highlight the importance of combining complementary analytical techniques, such as NMR, to avoid misinterpretation of essential oil composition and bioactivity markers.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c08966"><strong>Is Curzerene Responsible for the Bioactive Properties of Eugenia uniflora? A Possible Misinterpretation of Bioactive Markers</strong></a></h4><p>Vinicius Monteiro Schaffka, Raphaela Pereira Guaringue, Larissa Kozan, André Luis Kerek, Cássia Gonçalves Magalhães, Andersson Barison, and Barbara Celânia Fiorin*</p><p>ACS Omega 2025, 10, 48, 59425–59434</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c08966">https://doi.org/10.1021/acsomega.5c08966</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><div><p>Essential oils are a matrix of volatile and complex compounds characterized by strong odors and significant biological activity. In plants, they play a crucial role in defense against bacteria, viruses, and predators. <a href="javascript:void(0);">(1)</a> These biological properties support the extensive use of essential oils in the food, cosmetics, and pharmaceutical industries. <a href="javascript:void(0);">(1,2)</a> <i>Eugenia uniflora</i> L., commonly known as pitangueira, is a native Brazilian tree widely distributed across South America and is well-known for its bioactive essential oil. <a href="javascript:void(0);">(3)</a> Beyond the consumption of its fruits in natura or functional beverages, its leaves are used in infusions, decoctions, and tinctures to treat a variety of diseases, including diarrhea, stomach pain, worm infestations, fever, flu, hyperglycemia, hyperlipidemia, and hypertension. <a href="javascript:void(0);">(4,5)</a> Studies have shown that the composition of secondary metabolites in <i>E. uniflora</i> can vary depending on factors such as fruit color, ripening stage, <a href="javascript:void(0);">(6)</a> and seasonal influences. <a href="javascript:void(0);">(4,7−10)</a></p><p>The essential oil of <i>E. uniflora</i> is predominantly composed of sesquiterpenes, mainly germacrene-type, such as curzerene, germacrene B, germacrone, germacrene D, selina-1,3,7(11)-trien-8-one, and its oxide. Additionally, Elemene-type terpenes are also reported, including furanodiene, β-Elemene, and β-Elemenone. <a href="javascript:void(0);">(11−13)</a></p><p>However, those sesquiterpenes are well-documented for their thermal instability. When heat is applied, germacrene-type sesquiterpenes undergo a [3,3]-sigmatropic rearrangement, known as Cope rearrangement, converting into Elemene-type terpenes as presented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c08966#fig1">Figure 1</a>. <a href="javascript:void(0);">(14−16)</a> This reaction is widely utilized as a synthetic pathway to produce Elemenes from germacrene precursors. <a href="javascript:void(0);">(17,18)</a></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_48_59425_59434_Figure_1_3_3_Sigmatropic_rearrangement_of_Germacrene_type_into_Elemene_type_250708e73c.jpg" alt="ACS Omega 2025, 10, 48, 59425–59434: Figure 1. [3,3]-Sigmatropic rearrangement of Germacrene-type into Elemene-type." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_48_59425_59434_Figure_1_3_3_Sigmatropic_rearrangement_of_Germacrene_type_into_Elemene_type_250708e73c.jpg 245w," sizes="100vw" width="3000" height="984"></p><p>Gas chromatography (GC) is the main technique for characterizing essential oils, often coupled with mass spectrometry (GC-MS) and the retention index determination is used in the identification of the compounds through comparison with databases. <a href="javascript:void(0);">(21)</a> During GC analysis, essential oils are subjected to multiple heating stages. Initially, the sample is exposed to a high inlet temperature, typically around 240 °C, to ensure complete volatilization. It then enters the oven, where the temperature follows a programmed ramp starting at 60 °C, increasing at 3 °C/min, and reaching up to 240 °C. Finally, the sample encounters the elevated temperatures of the mass spectrometry (MS) detector’s source (250 °C) and interface (280 °C). Even in isocratic methods, where the oven temperature remains constant throughout the analysis, the inlet, source, and interface temperatures are maintained at high levels. Although the sample passes through these stages briefly, the elevated temperatures can induce Cope rearrangements in the essential oil, leading to possible changes in its composition. <a href="javascript:void(0);">(22,23)</a></p><p>The accurate characterization of the chemical composition of essential oils is crucial for any study employing them as a biological or analytical matrix, as it supports the interpretation of bioactivity, chemotaxonomic classification, and quality control of samples with economic value added. There are many studies attributing relevant biological activities, classifying specimens, and identifying phenotypic and genetic variations based on the chemical composition of the essential oil of <i>E. uniflora</i> L., which is usually characterized by GC-MS. <a href="javascript:void(0);">(8,9,11,24)</a> As an example of the study carried out by de Jesus, found acute anti-inflammatory effect of a rich in curzerene essential oil. <a href="javascript:void(0);">(5)</a> Similarly, Pascoal, reported distinct essential oil composition patterns among <i>E. uniflora</i> varieties─yellow, red, and purple fruits─primarily driven by variations in β-Elemene and germacrene D content. <a href="javascript:void(0);">(7)</a> These findings highlight metabolic changes during fruit ripening and underscore the influence of genetic diversity among <i>E. uniflora</i> varieties. Such exhibitions are unsatisfactory, because they sustain all their evidence in the characterization of their essential oil only by GC-MS analysis, without considering the Cope rearrangements, a fact that may change the outcome of their research. In this context Nuclear Magnetic Resonance (NMR) spectroscopy is a good alternative for essential oil analysis, since is a robust not destructive technique and able to detect and quantify simultaneously a wide range of metabolites that exceed the concentration of about 5–10 μM. <a href="javascript:void(0);">(25)</a></p><p>In order to highlight analytical concerns about the uses of only GC-MS data to access chemical relevance of <i>E. uniflora</i> essential oil studies, Nuclear Magnetic Resonance (NMR) spectroscopy was employed to evaluate the chemical composition of the essential oil of <i>Eugenia uniflora</i> L. before and after an induced thermal treatment, compared to GC-MS data. The findings provide insights into thermolabile compounds and highlight potential misidentifications of the bioactive properties associated with the sesquiterpenes of <i>E. uniflora</i> present in literature.</p><h4><strong>2. Results and Discussion</strong></h4><h5><strong>2.1. Characterization of the Essential Oil</strong></h5><p>Approximately 60 compounds, mostly sesquiterpenes (Germacrene B) and oxygenated sesquiterpenes (Germacrone), were visualized in the essential oil, with the 9 compounds having a relative area above 2%, as shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c08966#tbl1">Table 1</a>. The identified and most prevalent compounds align with those reported in the literature for <i>E. uniflora</i>. <a href="javascript:void(0);">(4,11,12)</a> It is possible to highlight the significant proportion of Germacrene-type sesquiterpenes compared to Elemene-type, except Curzerene, which was found in high concentration.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_48_59425_59434_Table_1_Main_Components_Identified_in_the_GC_MS_Analysis_of_the_Essential_Oil_from_Leaves_of_E_uniflora_9d59d96bef.jpg" alt="ACS Omega 2025, 10, 48, 59425–59434: Table 1. Main Components Identified in the GC–MS Analysis of the Essential Oil from Leaves of E. uniflora." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_48_59425_59434_Table_1_Main_Components_Identified_in_the_GC_MS_Analysis_of_the_Essential_Oil_from_Leaves_of_E_uniflora_9d59d96bef.jpg 218w," sizes="100vw" width="1076" height="771"></p><p>The variation in the composition of the essential oil from <i>E. uniflora</i> leaves was described in literature, <a href="javascript:void(0);">(9)</a> who classified the specimens into three groups: Group I, containing yellow, dark red, and purple fruits, which showed high concentrations of germacrene B, germacrone, and atractylone; Group II, consisting of light red fruit samples, with high concentrations of curzerene, germacrene D, and germacrene A; and Group III, containing orange-red fruits, with a high content of selina-1,3,7(11)-trien-8-one and oxyselina-1,3,7(11)-trien-8-one. According to this classification, this essential oil fits into Group II.</p><p>Chemical transformations of many components found in the <i>E. uniflora</i> leaves essential oil result from the heating conditions typically applied during GC–MS analysis, which occur through Cope Rearrangement. <a href="javascript:void(0);">(12,19)</a> Cope rearrangement is a stereospecific [3,3]-sigmatropic rearrangement that proceeds via the most stable chairlike transition state of 1,5-cyclodecadiene, from germacrene-type, to give 1,2-divinylcyclohexane, known as Elemene-type. <a href="javascript:void(0);">(14)</a> Some of the Cope rearrangements found in the <i>E. uniflora</i> essential oil are represented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c08966#fig2">Figure 2</a>. <a href="javascript:void(0);">(11,22,23,26)</a></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_48_59425_59434_Figure_2_Cope_Rearrangements_of_sesquiterpenes_7fe9282d75.jpg" alt="ACS Omega 2025, 10, 48, 59425–59434: Figure 2. Cope Rearrangements of sesquiterpenes." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_48_59425_59434_Figure_2_Cope_Rearrangements_of_sesquiterpenes_7fe9282d75.jpg 150w," sizes="100vw" width="1500" height="1566"></p><p>The same essential oil was analyzed using NMR spectroscopy to identify its components. Although NMR identification is considerably more labor-intensive than GC-MS analysis, it offers the advantage of being a cold and nondestructive technique. Since the sample does not undergo heating during the process, its stability is preserved throughout the analysis. The conformational differences observed in germacrene-type compounds further increase the spectrum’s complexity, leading to signal broadening in the <sup>1</sup>H NMR spectra. <a href="javascript:void(0);">(27)</a></p><p>A substantial number of signals were observed in the <sup>1</sup>H spectrum, with the majority concentrated between 0.5 and 3.0 ppm, a region characteristic of terpene compounds. The region between 4.5 and 6.0 ppm also exhibited numerous signals attributed to vinylic protons, observed in sesquiterpenes (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c08966#fig3">Figure 3</a>).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_48_59425_59434_Figure_3_1_H_NMR_400_13_M_Hz_CD_Cl3_spectra_of_the_raw_essential_oil_a46e04574e.jpg" alt="ACS Omega 2025, 10, 48, 59425–59434: Figure 3. 1H NMR (400.13 MHz, CDCl3) spectra of the raw essential oil." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_48_59425_59434_Figure_3_1_H_NMR_400_13_M_Hz_CD_Cl3_spectra_of_the_raw_essential_oil_a46e04574e.jpg 245w," sizes="100vw" width="4175" height="2376"></p><h4><strong>3. Conclusions</strong></h4><p>The investigation of the composition of <i>E. uniflora</i> essential oil by NMR and the thermal treatment performed proved that curzerene may come from furanodiene due to the transformations that occur in the matrix during gas chromatographic analysis. These findings have significant implications for the investigation into the chemical composition of <i>E. uniflora</i> essential oil and the evaluation of the biological properties of its sesquiterpenes. Since each technique has advantages and disadvantages, combining GC-MS analysis with a cold technique, such as NMR is important to guarantee the proper identification of the compound genuinely responsible for any property assigned to <i>E. uniflora</i> essential oil.</p><h4><strong>4. Materials and Methods</strong></h4><h5><strong>4.2. GC-MS Analysis</strong></h5><p>The gas chromatographic analyses of the essential oils (10 mg mL<sup>–1</sup>) were performed using a gas chromatography–mass spectrometry system (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=QP2020"><strong>Shimadzu GCMS-QP2020 Gas Chromatograph</strong></a>). The analyses were conducted on an RTx-5MS capillary column (30 m × 0.25 mm internal diameter × 0.25 μm film thickness), and the analytical conditions were as follows: split ratio of 1/10, injector temperature at 250 °C, ion source at 250 °C, and interface at 280 °C. The temperature program of the oven was set at 60 °C for 5 min, followed by a temperature ramp of 3 °C/min until reaching the final temperature of 240 °C. The components were identified based on the relative retention index, calculated for each constituent by injecting a series of <i>n</i>-alkane standards (C8–C20) under the same sample conditions and comparing them with tabulated values as well as by comparing the obtained mass spectra with the mass spectra database and literature comparisons. <a href="javascript:void(0);">(21)</a></p><h5><strong>4.4. NMR Analysis</strong></h5><p>All NMR spectra were acquired at 298 K on a <strong>Bruker AVANCE III</strong> spectrometer operating at 9.4 T, observing <sup>1</sup>H at 400.13 MHz and <sup>13</sup>C at 100.13 MHz, equipped with a broadband probe. The essential oil was solubilized in CDCl<sub>3</sub> with 0.05% of tetramethylsilane (TMS) used as an internal reference. The <sup>1</sup>H NMR spectra were recorded utilizing 65k time-domain data points across a spectral width of 20.00 ppm. This setup provided a digital resolution of 0.24 Hz. The data were obtained using a single 30° excitation pulse, with a relaxation delay of 1.0 s, and an average of 128 scans. The <sup>13</sup>C NMR spectra was carried out using the <i>zgpg30</i> pulse sequence utilizing 64k time-domain data points across a spectral width of 238 ppm, with an acquisition time of 1.3631 s, providing a digital resolution of 0.7434 Hz and a relaxation delay of 2.0s and an average of 2k scans.</p><p>The HSQC and HMBC experiments were conducted using standard pulse sequences from the Bruker library, with modifications to the number of acquired points to improve resolution, 2048 in F2 and 512 in F1.</p></div>

Is Curzerene Responsible for the Bioactive Properties of Eugenia uniflora? A Possible Misinterpretation of Bioactive Markers

Quantitative Assessment of Chemical Modifications of Macromolecules through Counterion Measurement

<p><strong>In the week of March 30, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><div><div><div><div><div><div><h5><strong>1. Agilent Technologies: Trace the Threat: Py-GC/MS Workflows for Microplastics Characterization</strong></h5><ul><li>Tu, 31.3.2026 06:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6025">Registration</a></li></ul><p>Discover advanced approaches for trace micro- and nanoplastics analysis using Py-GC/MS and explore how the Agilent 5977C GC/MSD enhances sensitivity, robustness, and workflow efficiency.</p><h5><strong>2. Thermo Fisher Scientific: FTIR microscopy: Practical guidance for effective sample analysis</strong></h5><ul><li>Tu, 31.3.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6088">Registration</a></li></ul><p>Join this webinar to gain practical guidance on FTIR microscopy workflows, including measurement modes, sample preparation, parameter optimization and spectral interpretation.</p><h5><strong>3. Bruker: Understanding Polymer Reactions and Degradation with FT-IR and EPR Spectroscopy</strong></h5><ul><li>Tu, 31.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5996">Registration</a></li></ul><p>Discover how FT-IR and EPR spectroscopy reveal polymer curing kinetics and radical-driven mechanisms—enabling real-time monitoring, degree of cure quantification, and stability studies.</p><h5><strong>4. Technology Networks: Advances in Hydrogen Gas Generation for Sustainable Laboratories</strong></h5><ul><li>Tu, 31.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5941">Registration</a></li></ul><p>Discover how modern hydrogen gas generators support high-purity GC performance while reducing costs and environmental impact. Learn how on-site generation improves uptime, efficiency, and lab sustainability.</p><h5><strong>5. C&amp;EN: Overcoming Raman Microscopy Challenges in Microplastics and Life Sciences</strong></h5><ul><li>We, 1.4.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6016">Registration</a></li></ul><p>Learn how O-PTIR spectroscopy overcomes fluorescence limitations in Raman microscopy. Discover simultaneous sub-micron IR and Raman analysis for microplastics, biological samples, and organic materials.</p></div></div></div></div></div></div>

Webinars LabRulezGCMS Week 14/2026

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Mestrelab Mnova MSChrom software

Mnova MSChrom (Formerly MS) provides a common interface for different vendor data and automates all functionality such as data importing and display, integration, background subtraction, display of extracted mass chromatograms, molecule match, enumeration of molecular formulae, etc.

<h3><strong>Process, analyze and report your LC-MS and GC-MS data from your different instruments</strong></h3>
<p>Mnova MSChrom (Formerly MS) provides a common interface for different vendor data and automates all functionality such as data importing and display, integration, background subtraction, display of extracted mass chromatograms, molecule match, enumeration of molecular formulae, etc.</p>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Effortlessly_analyze_and_report_LCMS_and_GCMS_data_from_a_wide_range_of_instruments_b7f5482cde.jpg" alt="Mestrelab Research: Mnova MSChrom - Effortlessly analyze and report LCMS and GCMS data from a wide range of instruments."/></p>
<blockquote>
<h4><a href="http://www2.mestrelab.com/l/271522/2024-03-25/3nwslf"><strong>Visit MestreLab Research MSChrom product page to learn more!</strong></a></h4>
</blockquote>
<h3><strong>MSChrom Highlights</strong></h3>
<ul>
<li><strong>Common interface</strong> to visualize your data from different vendors.</li>
<li><strong>Automate all functionality</strong> such as data importing and display, integration, background subtraction, display of extracted mass chromatograms, molecule match, enumeration of molecular formula, etc.</li>
<li><strong>Verify proposed structures</strong> by automatically matching molecular ion and isotope peaks, and potentially the MS/MS fragmentation peaks.</li>
<li><strong>Predict the isotope clusters</strong> of a molecular formula with various adducts/losses and compare with observed mass spectrum.</li>
<li><strong>Process and report</strong> MS data on your computer, improves the efficiency and save time for more complex problems.</li>
<li><strong>Improve your efficiency</strong> by automating and customizing the analysis and reporting in batch mode or in real-time using Mnova scripts.</li>
<li>Make your <strong>analytical results searchable</strong> using Mnova DB!</li>
<li><strong>Calculate MS peak purity.</strong> The Mnova MS peak purity shows the curves associated to the most abundant mass peaks under the selected chromatogram peak.</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Opens_the_power_of_the_technique_to_all_non_expert_users_9ccef334fa.jpg" alt="Mestrelab Research: Mnova MSChrom - Opens the power of the technique to all non-expert users."/></p>
<h3><strong>Mnova MSChrom Features</strong></h3>
<h4><strong>Background Subtraction</strong></h4>
<ul>
<li>This new feature is designed to facilitate background subtraction in your datasets, offering the capability to apply mass spectra and UV subtraction to lower impurities and noisy common peaks obtained from your analytical system, etc. to achieve more precise data analysis.</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Sample_2_and_blank_1_used_to_apply_MS_Background_Subtraction_and_the_result_3_6a554048a8.jpg" alt="Mestrelab Research: Mnova MSChrom - Sample, 2, and blank, 1, used to apply MS Background Subtraction and the result, 3."/></p>
<h4><strong>New Enhanced Peak Picking Algorithm and Blind Regions</strong></h4>
<ul>
<li><p>Now, MSChrom includes a new <strong>Enhanced Peak Picking Algorithm</strong> providing an alternative to the Classic algorithm used in previous versions of MSChrom. Within <strong>Enhanced</strong> peak picking algorithm new settings are available to reproduce your best results in terms of detection and integration, including Baseline Correction, smoothing features, and a new functionality based on Saturated levels, where users can set an abundance threshold to identify those overloaded peaks due to detector saturation, and perform corrections on them.</p>
</li>
<li><p>Introducing the new <strong>Blind Regions</strong> tool-a highly beneficial addition. This tool enables the selective exclusion of those undesired regions from chromatograms during analytical processes as peak picking or any general data treatment. Blind Regions will remain ignored saving time, resources, providing better reproducible results. It proves especially helpful in cases where challenges arise in specific regions (solvent front in LC, column bleeding in GC, etc.) or, for instance, when opting to discard the limits of the chromatogram.</p>
</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Chromatographic_Peak_Detection_Settings_panel_and_Blind_Regions_table_displayed_after_peak_picking_9f4b2b6def.jpg" alt="Mestrelab Research: Mnova MSChrom - Chromatographic Peak Detection Settings panel and Blind Regions table displayed after peak picking process and applying two blind regions on the chromatogram."/></p>
<h4><strong>Combine NMR and LC-MS or GC-MS Data in the Same Document</strong></h4>
<ul>
<li>Automatically open analytical data from instruments like Agilent, Bruker, JEOL, Thermo, and Waters, along with data in mzData or mzXML formats (<a href="http://www2.mestrelab.com/l/271522/2024-04-10/3p2gs6"><strong>refer to supported formats here</strong></a>).</li>
<li>Integrate peaks in TIC, MS, and UV/ELSD traces, either automatically or manually.</li>
<li>Choose mass spectra based on TIC peaks, with or without background subtraction, and display them in either centroid or profile mode.</li>
<li>Manually co-add mass spectra, and seamlessly analyze and report NMR and MS data together in the same document</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Combine_NMR_and_LC_MS_or_GC_MS_Data_in_the_Same_Document_a575d33699.jpg" alt="Mestrelab Research: Mnova MSChrom - Combine NMR and LC-MS or GC-MS Data in the Same Document."/></p>
<h4><strong>Effortlessly Generate EMC/EIC, UV Traces, and UV Spectra</strong></h4>
<ul>
<li>Create Extracted Mass/Ion Chromatograms (EMC/EIC) within a specified mass range or at a particular m/z value.</li>
<li>Generate UV Traces effortlessly by selecting a wavelength from a DAD trace.</li>
<li>Easily extract UV spectra at chosen retention times from a PDA total absorbance chromatogram.</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Effortlessly_Generate_EMC_EIC_UV_Traces_and_UV_Spectra_e80492edfa.jpg" alt="Mestrelab Research: Mnova MSChrom - Effortlessly Generate EMC/EIC, UV Traces, and UV Spectra."/></p>
<h4><strong>Automatic Molecule Matching for Structure Confirmation</strong></h4>
<ul>
<li>Beyond its extensive NMR structure confirmation tools within the NMR plugin, Mnova MSChrom introduces the molecular match feature, an invaluable resource for verifying structures through LC/GC/MS analysis.</li>
<li>This functionality is exceptionally swift and user-friendly, ensuring accessibility for all users, including those new to the field.</li>
<li>Import chemical structures and let the software automatically confirm matches with your experimental data. Customize match criteria by selecting adducts, losses, mass accuracy, score thresholds, etc.</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Automatic_Molecule_Matching_for_Structure_Confirmation_04d66572d1.jpg" alt="Mestrelab Research: Mnova MSChrom - Automatic Molecule Matching for Structure Confirmation."/></p>
<h4><strong>Isotope Cluster Prediction for Elemental Composition Verification</strong></h4>
<ul>
<li>The feature enables users to propose one or multiple molecular formulas and anticipate their mass peaks using a predefined list of adducts or losses.</li>
<li>Mnova MSChrom generates a list of molecular ion and isotopic peaks, automatically aligning them with experimental peaks, if present.</li>
<li>Customize the display by choosing the desired prediction, along with the corresponding adduct or loss, for comparison on the spectrum.</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Isotope_Cluster_Prediction_for_Elemental_Composition_Verification_7f75f9d6c3.jpg" alt="Mestrelab Research: Mnova MSChrom - Isotope Cluster Prediction for Elemental Composition Verification."/></p>
<h3><strong>Mnova MSChrom Market and Users</strong></h3>
<ul>
<li>Teaching MS and Chromatography to chemistry departments</li>
<li>Research in organic, medicinal and environmental chemistry</li>
<li>Quality control in chemical and pharmaceutical companies</li>
</ul>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_users_507a260da1.jpg" alt="Mestrelab Research: Mnova MSChrom users."/></p>
<h3><strong>Frequently Asked Questions</strong></h3>
<h5><strong>How can I know if my data is compatible with Mnova?</strong></h5>
<p><em>Mnova MS supports most of the different MSChrom data formats. You can check it on the MSChrom supported format table <a href="http://www2.mestrelab.com/l/271522/2024-04-10/3p2gs6"><strong>here</strong></a>. Please let us know if your MSChrom data format is not in the list.</em></p>
<h5><strong>How much does the MSChrom module cost?</strong></h5>
<p><em>You can find the cost of this module in our online store. You can also check out for any combo option if you have or you need Mnova NMR. For any questions about pricing you can always contact us directly at <strong>sales@mestrelab.com</strong></em></p>
<h5><strong>I have Mnova NMR and I am wondering if I could add my MS data to my NMR reports.</strong></h5>
<p><em>Yes. You can open NMR and MS data in the same document, and cut/paste the MSChrom display to the same page of NMR data if needed. Or you can create a display template to automatically format the reports.</em></p>
<h5><strong>Can I use my MSChrom data for verification purposes?</strong></h5>
<p><em>Yes. Run Molecule Match in Mnova MSChrom to verify the elemental composition automatically, or run Mnova Verify to verify a proposed structure against your MS data (Mnova Verify needs a separate license).</em></p>
<h5><strong>Can I use it to process my High Resolution MSChrom data?</strong></h5>
<p><em>Yes. Both high resolution and low resolution MS data can be used by Mnova MSChrom. Just make sure you set the proper mass tolerance parameters when you do Molecular Match.</em></p>
<h5><strong>Can I try Mnova MSChrom?</strong></h5>
<p><em>Yes, you can download a 45-day trial license of any of our products. The Mnova MSChrom module is included within the main Mnova installer. Download Mnova and try it now!</em></p>
<h3><strong>Case Studies</strong></h3>
<h4><strong>Automated analysis and reporting LC/MS and NMR together for compound registration – A case study</strong></h4>
<p>A pharma company does quality control of their compounds using both NMR and LC/MS before registration, and generates the analysis reports in their own format. Based on their requirement, we developed a Mnova script (R_NMR_MS.qs) that does all of this automatically.</p>
<blockquote>
<p><a href="http://www2.mestrelab.com/l/271522/2024-04-10/3p2gs9"><strong>read more</strong></a></p>
</blockquote>
<p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_MS_Chrom_Automated_analysis_and_reporting_LC_MS_and_NMR_together_for_compound_registration_A_case_study_8003aab1ff.jpg" alt="Mestrelab Research: Mnova MSChrom - Automated analysis and reporting LC-MS and NMR together for compound registration – A case study."/></p>


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