<p><strong>Scientists at IOCB Prague are uncovering new details of gene transcription. They have identified a previously unknown molecular mechanism by which the transcription of genetic information from deoxyribonucleic acid (DNA) into ribonucleic acid (RNA) can be initiated. The researchers focused on a specific class of molecules known as alarmones, which are found in cells across a wide range of organisms and whose levels often increase under conditions of cellular stress. The results were published in the prestigious scientific journal </strong><i><strong>Nature Chemical Biology</strong></i><strong>.</strong></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_bc2bfffa6c.jpg" alt="IOCB Prague/Tomáš Belloň: Research from IOCB Prague reveals a previously unknown mechanism of genetic transcription: Dr. Hana Cahová, head of the Chemical Biology of Nucleic Acids research group." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_bc2bfffa6c.jpg 234w," sizes="100vw" width="2000" height="1335"></p><div><p>Molecules of ribonucleic acid can carry a variety of chemical modifications at one end, known as caps. In eukaryotic organisms, including human cells, the best-known cap plays an important role in RNA stability and in regulating its subsequent fate. In recent years, however, it has become clear that alternative, non-canonical RNA caps also exist, although their formation and the mechanisms by which they are attached to RNA remain only partially understood. These include alarmone caps, formed by dinucleoside polyphosphate molecules, that protect cellular RNA at moments when the cell is under threat.</p><p>In their study,<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://cahova.group.uochb.cz/en"><strong>Dr. Hana Cahová</strong></a> and colleagues examined bacterial RNA polymerase and investigated how this enzyme can initiate transcription using dinucleoside polyphosphates (NpNs) instead of the standard RNA building blocks. For the first time, the scientists described, at the atomic level, how RNA bearing an alarmone cap can be generated directly at the initiation of gene transcription. They also observed that NpNs bind through a different type of base pairing than is typically observed.</p><p>The work was significantly shaped by <strong>Valentina Serianni from Hana Cahová’s team</strong>, who demonstrated the ability of dinucleoside polyphosphates to initiate gene transcription, and by <strong>Jana Škerlová</strong>, who focused on the structural analysis of RNA polymerase. Using cryogenic electron microscopy data, she showed how dinucleoside polyphosphate molecules bind within the active site of RNA polymerase – that is, the core of the enzyme where genetic information is transcribed. Together, their findings help to elucidate the processes that accompany the transcription of genetic information from DNA to RNA.</p><p>Hana Cahová adds: <i>“We’re describing something that truly occurs in cells and that we’re now able to observe directly at the level of individual molecules. This allows us to answer fundamental questions about cellular processes, such as how cells adapt to stress. RNA plays a central role in this, as it carries the cascade of information underlying any cellular response – for example, to threatening conditions caused by nutrient deprivation or temperature shock.”</i></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_2_0fe88ff9e9.jpg" alt="IOCB Prague/Tomáš Belloň: Research from IOCB Prague reveals a previously unknown mechanism of genetic transcription: Dr. Tomáš Kouba, head of the Cryogenic Electron Microscopy core facility." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_2_0fe88ff9e9.jpg 234w," sizes="100vw" width="2000" height="1335"></p><div><p>Cryogenic electron microscopy (cryo-EM) was central to the project. This part of the work was led by<strong> Dr. Tomáš Kouba</strong>, one of the authors of the study. <i>“Cryogenic electron microscopy allows us to freeze biological molecules in a state very close to their natural form and then determine their three-dimensional structure. This makes it possible to look directly into the active centers of enzymes and observe their function down to the atomic level,”</i> he explains.</p><p>Last year, IOCB Prague opened a new <a target="_blank" rel="noopener noreferrer" href="https://cryoem.group.uochb.cz/en"><strong>cryo-EM center</strong></a><strong> </strong>that is unique within the Czech research environment. State-of-the-art cryogenic electron microscopes are housed in a specially designed building and enable the study of biological processes with exceptional structural precision.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_3_4d881e7a58.jpg" alt="IOCB Prague: Research from IOCB Prague reveals a previously unknown mechanism of genetic transcription: This work shows how NpnNs initiate bacterial transcription. Cryo-EM reveals how nucleobases pair with the template: one in canonical and one in reverse Watson–Crick mode, providing a structural basis for their function as non-canonical RNA caps." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Vyzkum_z_UOCHB_odhaluje_dosud_nepoznany_zpusob_prepisu_geneticke_informace_3_4d881e7a58.jpg 245w," sizes="100vw" width="2000" height="1077"></p><blockquote><h4><strong>The Original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41589-025-02134-5"><strong>Molecular insight into 5′ RNA capping with Np<sub>n</sub>Ns by bacterial RNA polymerase</strong></a></h4><p>Valentina M. Serianni, Jana Škerlová, Anna Knopp Dubánková, Anton Škríba, Hana Šváchová, Tereza Vučková, Anatolij Filimoněnko, Milan Fábry, Pavlína Řezáčová, Tomáš Kouba &amp; Hana Cahova&nbsp;</p><p>Nat. Chem. Biol. 21 (2026)</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1038/s41589-025-02134-5">https://doi.org/10.1038/s41589-025-02134-5</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><h4><strong>Abstract</strong></h4><p>RNA capped with dinucleoside polyphosphates has been discovered in bacteria and eukaryotes only recently. The likely mechanism of this specific capping involves direct incorporation of dinucleoside polyphosphates by RNA polymerase as noncanonical initiating nucleotides. However, how these compounds bind into the active site of RNA polymerase during transcription initiation is unknown. Here, we explored transcription initiation in vitro, using a series of DNA templates in combination with dinucleoside polyphosphates and model RNA polymerase from <i>Thermus</i> <i>thermophilus</i>. We observed that the transcription start site can vary on the basis of the compatibility of the specific template and dinucleoside polyphosphate. Cryo-electron microscopy structures of transcription initiation complexes with dinucleoside polyphosphates revealed that both nucleobase moieties can pair with the DNA template. The first encoded nucleotide pairs in a canonical Watson–Crick manner, whereas the second nucleobase pairs noncanonically in a reverse Watson–Crick manner. Our work provides a structural explanation of how dinucleoside polyphosphates initiate RNA transcription.</p></div></div>

Research from IOCB Prague reveals a previously unknown mechanism of genetic transcription

<p><strong>In the week of February 9, 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>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><div><div><div><div><div><div><h5><strong>1. Thermo Fisher Scientific: Process Raman – A Reliable and Versatile Tool for Downstream Process Monitoring and Control for mAb Production</strong></h5><ul><li>Tu, 10.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5808">Registration</a></li></ul><p>The presentation highlights how process Raman spectroscopy offers several advantages over traditional in-line UV-Vis analysis for process monitoring and metabolite production control in mAb manufacturing.</p><h5><strong>2. Wasson-ECE Instrumentation: The Data Driven Plant – How AI Transforms Chemical Manufacturing</strong></h5><ul><li>Tu, 10.2.2026 21:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5744">Registration</a></li></ul><p>Explore how artificial intelligence is applied to improve process efficiency, monitoring, and decision-making in modern chemical manufacturing.</p><h5><strong>3. New Food Magazine: The Science of Next-Gen Ingredients – Fermentation, Formulation and Function</strong></h5><ul><li>We, 11.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5720">Registration</a></li></ul><p>Discover how fermentation-driven innovation is transforming functional food ingredients, with analytical insights to optimize flavour, functionality, and product stability.</p></div></div></div></div></div></div>

Webinars LabRulezGCMS Week 07/2026

<p><strong>This study presents an analytical strategy combining QuEChERS extraction with low-temperature partitioning (LTP) for the determination of multiclass pesticide residues in cocoa beans by GC–MS. Extraction conditions were optimized using a fractional factorial design, resulting in a simple and efficient workflow suitable for complex cocoa matrices.</strong></p><p>The validated method showed satisfactory limits of detection and quantification, recoveries within 70–120%, and good overall performance. Application to cocoa samples from Brazil detected permethrin in several samples, demonstrating that the QuEChERS–LTP approach is an effective and reliable cleanup strategy for routine pesticide residue analysis in cocoa.</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.5c10360"><strong>QuEChERS Combined with Low-Temperature Partitioning and GC–MS as an Analytical Strategy for the Determination of Multiclass Pesticide Residues in Cocoa Beans</strong></a></h4><p>Priscilla M. de Freitas Machado, Madson M. Nascimento, Paulo R. R. Mesquita, Manuela B. Nascimento, Lilian Lefol N. Guarieiro, Gisele O. da Rocha, Jailson B. de Andrade, Raildo M. de Jesus*</p><p>ACS Omega 2025, 10, 51, 63464–63473</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c10360">https://doi.org/10.1021/acsomega.5c10360</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>Cocoa is best known as the primary raw material for chocolate but is also processed into products such as cocoa butter, biscuits, cocoa honey, and cocoa powder. Cocoa powder is derived from roasted, pressed, and milled nibs, containing on average 20% (w/w) lipids on a dry basis and less than 9% moisture. <a href="javascript:void(0);">(3,4)</a></p><p>According to the Brazilian Health Regulatory Agency (ANVISA), pesticides such as atrazine, bifenthrin, cyproconazole, metalaxyl, tebuconazole, trifloxystrobin, and permethrin are approved for use in Brazil. <a href="javascript:void(0);">(13)</a> However, among these, only metalaxyl, trifloxystrobin, and tebuconazole are authorized by the European Union. <a href="javascript:void(0);">(14)</a> Thus, investigating these contaminants in cocoa samples is of utmost importance, as Brazil is one of the largest cocoa exporters, supplying cocoa commodities to South America, the United States, and the European Union. <a href="javascript:void(0);">(2)</a> Furthermore, Organochlorine pesticides, in particular, belong to the class of persistent organic pollutants (POPs). Although banned in many countries, they continue to be used in some developing nations because of their chemical stability, resistance to degradation, volatility, and high lipophilicity, which promote bioaccumulation and neurotoxicity. <a href="javascript:void(0);">(15)</a> Epidemiological evidence also associates their exposure with Parkinson’s disease, certain cancers, diabetes, and endometriosis. <a href="javascript:void(0);">(16)</a></p><p>Residues of pesticides in cocoa have been reported in various studies. <a href="javascript:void(0);">(17)</a> Analyzing pesticide residues in cocoa presents analytical challenges due to the matrix’s complexity, comprising high lipid content, fatty acids and esters, sugars, polyphenols, and caffeine. These components can interfere with extraction efficiency and contaminate analytical instrumentation. <a href="javascript:void(0);">(18)</a> Therefore, efficient sample preparation methods incorporating effective cleanup steps are essential for accurate residue determination.</p><p>Several techniques have been employed for multiresidue pesticide analysis in cocoa. For instance, Idowu et al. <a href="javascript:void(0);">(19)</a> quantified 14 organochlorines using Soxhlet extraction and silica/Na<sub>2</sub>SO<sub>4</sub> cleanup, with GC ECD detection. Okoffo et al. <a href="javascript:void(0);">(20)</a> determined 13 organophosphates and 9 pyrethroids employing SPE cartridges (Envi-carb/LC-NH<sub>2</sub> and Bond Elute C18), acetonitrile extraction, and GC PFPD or GC ECD quantification. Yusiasih et al. <a href="javascript:void(0);">(21)</a> applied dispersive SPE with PSA, Florisil, and MgSO<sub>4</sub> for pyrethroids, followed by GC ECD and GC–MS.</p><p>Therefore, this study aimed to evaluate the effectiveness of a QuEChERS–LTP analytical procedure for the determination of multiclass pesticide residues in cocoa beans. The factors that affect the QuEChERS–LTP procedure efficiency were optimized. After validation, the procedure was employed to investigate the occurrence of 15 multiclass pesticides in cocoa samples.</p><h4><strong>Experimental Section</strong></h4><h5><strong>Instrumental Apparatus</strong></h5><p>Pesticide separation and identification were performed on a Shimadzu <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GC-MS-QP2010SE"><strong>GC-MS-QP2010SE</strong></a> system (Kyoto, Japan) equipped with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=AOC-20i"><strong>AOC-20i autosampler</strong></a>. Separation was achieved using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=DB-5MS"><strong>Agilent DB-5MS capillary column</strong></a> (30 m × 0.25 mm × 0.25 μm) with a stationary phase of 5% phenyl/95% dimethylpolysiloxane. The instrumental conditions were based on Nascimento et al. <a href="javascript:void(0);">(49)</a> and they are summarized in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#tbl4">Table 4</a>.</p><p>For quantification, the base peak was used, while two additional ions were monitored for confirmation (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c10360/suppl_file/ao5c10360_si_001.pdf">Table S2</a>) in accordance with SANTE guidelines. <a href="javascript:void(0);">(50)</a> A GC–MS/SIM chromatogram illustrating the separation of all target pesticides is presented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#fig5">Figure 5</a>.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63464_63473_Figure_5_Extracted_ion_chromatogram_EIC_in_SIM_mode_of_the_target_pesticides_f2461c14f4.jpg" alt="ACS Omega 2025, 10, 51, 63464–63473: Figure 5. Extracted ion chromatogram (EIC) in SIM mode of the target pesticides obtained from the injection of a mixed standard solution at 100 μg L–1. Analytes are listed in order of elution: [1] Molinate (6.18 min); [2] α-HCH (8.15 min); [3] atrazine-d5 (8.69 min); [4] atrazine (8.75 min); [5] diazinon (9.31 min); [6] disulfoton (9.67 min); [7] dimethachlor (10.60 min); [8] metalaxyl (11.25 min); [9] p,p′-DDE (15.82 min); [10] cyproconazole I (16.50 min); [11] cyproconazole II (16.56 min); [12] p,p′-DDD (17.29 min); [13] ethion (17.34 min); [14] trifloxystrobin (18.43 min); [15] tebuconazole (19.13 min); [16] bifenthrin (20.47 min); [17] permethrin I (23.92 min); [18] permethrin II (24.18 min)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63464_63473_Figure_5_Extracted_ion_chromatogram_EIC_in_SIM_mode_of_the_target_pesticides_f2461c14f4.jpg 245w," sizes="100vw" width="2080" height="835"></p><h5><strong>Application of the Proposed Procedure to Real Samples</strong></h5><p>In a 50 mL Falcon tube, 2.0 g of sample was weighed using an analytical balance (AUX320, Shimadzu, Kyoto, Japan). A total of 2.0 g of salt (NaCl and Na<sub>2</sub>SO<sub>4</sub> in a 1:1 w/w ratio) was added, followed by an aliquot of the atrazine-<i>d</i><sub>5</sub> solution (surrogate standard) to yield a final concentration of 250 μg kg<sup>–1</sup>. A mixture of acetonitrile (8.0 mL) and ultrapure water (2.0 mL) was then added. The system was vortexed (K40-10208, Kasvi, São Paulo, Brazil) for 3.0 min at 2500 rpm and centrifuged (MPW-351R, MPW Med. Instruments, Warsaw, Poland) for 10.0 min at 15 °C and 10,000 rpm. After phase separation, approximately 6.0 mL of the supernatant was transferred to a Falcon tube containing 150.0 mg of PSA sorbent. The mixture was vortexed again for 3.0 min at 2500 rpm and centrifuged for an additional 10.0 min under the same conditions. The tubes were then placed in the freezer for 24 h. Once the aqueous phase had frozen, the organic extract containing the analytes was collected, filtered through a Cytiva Whatman MiniUniprep G2 vial with a 0.20 μm membrane filter (Marlborough, Massachusetts, USA), and injected into the GC–MS system (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#fig6">Figure 6</a>).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63464_63473_Figure_6_Schematic_representation_of_the_extraction_procedure_using_the_Qu_E_Ch_ERS_LTP_procedure_for_pesticide_extraction_in_cocoa_powder_samples_ed58549bcf.jpg" alt="ACS Omega 2025, 10, 51, 63464–63473: Figure 6. Schematic representation of the extraction procedure using the QuEChERS–LTP procedure for pesticide extraction in cocoa powder samples." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63464_63473_Figure_6_Schematic_representation_of_the_extraction_procedure_using_the_Qu_E_Ch_ERS_LTP_procedure_for_pesticide_extraction_in_cocoa_powder_samples_ed58549bcf.jpg 223w," sizes="100vw" width="1458" height="1022"></p><h4><strong>Results and Discussion</strong></h4><h5><strong>Evaluation of the Effect of Low and Ultralow Temperatures on the Analytical Response</strong></h5><p>Studies reporting the use of LTP generally employ a conventional freezer, which typically reaches −18 ± 2 °C as the minimum temperature. In this equipment, effective phase separation can require 8 to 24 h. <a href="javascript:void(0);">(35−37)</a> In contrast, ultralow temperature freezers (ultrafreezers) can reach −80 °C, leading to a substantial reduction in partitioning time. In this study, tests performed with the conventional freezer achieved satisfactory partitioning after 24 h, whereas in the ultrafreezer, complete partitioning was observed in only 20 min.</p><p>Considering the analytical response in terms of peak area (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#fig3">Figure 3</a>), higher signals were obtained when LTP was performed in a conventional freezer rather than an ultrafreezer. This behavior can be attributed to the partitioning mechanism. <a href="javascript:void(0);">(32)</a> Partitioning depends on cooling and the subsequent freezing of the aqueous phase. In the conventional freezer, the slower freezing rate provides sufficient time for the system to approach thermodynamic equilibrium, favoring analyte diffusion between phases. Under these conditions, analyte molecules have more time to migrate and distribute optimally before complete solidification. In contrast, the rapid freezing in the ultrafreezer may trap analytes in a nonideal distribution, reducing the efficiency of the partitioning process <a href="javascript:void(0);">(32)</a> (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#fig3">Figure 3</a>). According to these observations, the conventional freezer was selected for subsequent experiments.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63464_63473_Figure_3_Comparison_of_chromatographic_peak_areas_of_pesticides_after_partitioning_in_the_conventional_freezer_versus_the_ultrafreezer_9598bcfec3.jpg" alt="ACS Omega 2025, 10, 51, 63464–63473: Figure 3. Comparison of chromatographic peak areas of pesticides after partitioning in the conventional freezer versus the ultrafreezer." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63464_63473_Figure_3_Comparison_of_chromatographic_peak_areas_of_pesticides_after_partitioning_in_the_conventional_freezer_versus_the_ultrafreezer_9598bcfec3.jpg 175w," sizes="100vw" width="996" height="891"></p><h5><strong>Application to Real Samples</strong></h5><p>Fifteen samples were analyzed in triplicate, comprising two from the State of Pará and 12 from the State of Bahia, located in the North and Northeast regions of Brazil, respectively. Among the 15 pesticides investigated, only permethrin isomers were quantified in four samples (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#tbl3">Table 3</a>). The herbicide molinate was also detected in three samples; however, its concentration was below LOQ. Permethrin isomers concentrations ranged from 17.1 ± 0.3 to 49.6 ± 1.8 μg kg<sup>–1</sup>. These values are below the MRL established by European Union regulation, which is 100 μg kg<sup>–1</sup>. <a href="javascript:void(0);">(42)</a> Although permethrin is not permitted in the European Union, <a href="javascript:void(0);">(42)</a> it remains authorized for use as insecticide in Brazil, particularly in crops such as cotton, rice, coffee, citrus, cabbage, beans, tobacco, maize, soybean, tomato, wheat, and grape. <a href="javascript:void(0);">(13)</a> However, no MRL values have been established for cocoa beans under Brazilian legislation. <a href="javascript:void(0);">(13)</a> <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10360#tbl3">Table 3</a> shows the concentration of detected compounds in the cocoa samples.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63464_63473_Table_3_Mean_Concentrations_mg_kg_1_Standard_Deviation_of_Target_Pesticides_Detected_in_This_Study_2427955699.jpg" alt="ACS Omega 2025, 10, 51, 63464–63473: Table 3. Mean Concentrations (μg kg–1 ± Standard Deviation) of Target Pesticides Detected in This Study" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63464_63473_Table_3_Mean_Concentrations_mg_kg_1_Standard_Deviation_of_Target_Pesticides_Detected_in_This_Study_2427955699.jpg 196w," sizes="100vw" width="1070" height="851"></p><p>To assess method performance for pesticides not detected in the cocoa samples, one of the analyzed samples was fortified with a mixed standard solution at concentrations of 50, 250, and 500 μg kg<sup>–1</sup>. The fortified analytes were subsequently detected in the chromatograms presented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c10360/suppl_file/ao5c10360_si_001.pdf">Figures S2–S4</a>, indicating good response of the proposed method.</p><h4><strong>Conclusions</strong></h4><p>The QuEChERS–LTP procedure was successfully developed for the determination of 16 multiclass pesticide residues in cocoa beans. For the first time, ultralow temperature (−80 °C) was applied to accelerate the low-temperature partitioning process during pesticide extraction from cocoa beans. Nevertheless, conventional freezing at −12 °C proved to be more effective for the extraction of the target analytes.</p><p>Evaluation of the matrix effect demonstrated that matrix-matched analytical curves, constructed in an analyte-free cocoa bean extract, were more effective in compensating for matrix interferences than the use of analyte protectants.</p><p>The pyrethroid permethrin was quantified in four cocoa samples. However, the concentrations did not exceed the MRL established by European Union legislation.</p><p>Overall, the QuEChERS–LTP procedure proved to be a promising approach for pesticide residue determination, as it requires smaller volumes of solvents and reagents, involves fewer cleanup and extraction steps, and shows strong potential for application to other complex matrices.</p>

QuEChERS Combined with Low-Temperature Partitioning and GC–MS as an Analytical Strategy for the Determination of Multiclass Pesticide Residues in Cocoa Beans

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The Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences (IOCB Prague) is a leading scientific institution in the Czech Republic, recognized internationally. Its primary mission is basic research in the fields of chemical biology and medicinal chemistry, organic and material oriented chemistry, chemistry of natural compounds, biochemistry and molecular biology, physical chemistry, theoretical chemistry, and analytical chemistry. 

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Leverage sophisticated multivariate analysis tools such as PCA, PLS, and SIMCA for in-depth data exploration, regression, and classification.

<h4><strong>Advanced Chemometrics for Enhanced Data Analysis</strong></h4><p>Leverage sophisticated multivariate analysis tools such as <strong>PCA, PLS, and SIMCA</strong> for in-depth data exploration, regression, and classification. The user-friendly interface ensures seamless integration of spectral data with analysis results, making it ideal for advanced users seeking powerful chemometric techniques for comprehensive data analysis.</p><h4><strong data-start="641" data-end="654">Benefits:</strong></h4><ul><li><strong>All-in-One Solution</strong>: Offers seamless spectral processing, binning, and analysis with just a few clicks, simplifying workflows and managing complex data efficiently in a single platform.</li><li><strong>Incorporates Recognized Methods:</strong> Includes PCA, PLS, and SIMCA for advanced data analysis and unsupervised chemometrics.</li><li><strong>Powerful and Intuitive Interface:</strong> Provides a user-friendly design for a streamlined analysis experience.</li><li><strong>Improved Classification and Prediction</strong>: Classifies samples with SIMCA and builds predictive models using PLS.</li><li><strong>Noise and Outlier Reduction</strong>: Effectively reduces noise and detects outliers, ensuring accurate and reliable results.</li><li><strong>Expandable Plugin:</strong> Features Higher Order Structure (HOS) capabilities, powered by Mnova BioHOS.&nbsp;</li></ul><h4><strong>Features:</strong></h4><h5><strong>New MCR Tool for Peak Purity Assessment in LCMS Data</strong></h5><p>Introduces an MCR tool based on the MCR-ALS algorithm for peak purity assessment, providing comprehensive tables and plots to streamline LCMS data analysis and enhance decision-making. This tool is available with the Advanced Chemometrics or BioHOS plugins and requires an MSChrom plugin license.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_New_MCR_Tool_for_Peak_Purity_Assessment_in_LCMS_Data_94993e71c3.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - New MCR Tool for Peak Purity Assessment in LCMS Data" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_New_MCR_Tool_for_Peak_Purity_Assessment_in_LCMS_Data_94993e71c3.webp 245w," sizes="100vw" width="1920" height="1200"></p><h5><strong>Enhanced Data Analysis with Partial Least Squares (PLS) Regression</strong></h5><p>Facilitates comprehensive analysis and accurate prediction of dependent variables from independent variables (such as binned spectra), while also providing intuitive graphical evaluation tools for deeper insights.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Enhanced_Data_Analysis_with_Partial_Least_Squares_PLS_Regression_7363eca35a.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Enhanced Data Analysis with Partial Least Squares (PLS) Regression" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Enhanced_Data_Analysis_with_Partial_Least_Squares_PLS_Regression_7363eca35a.webp 211w," sizes="100vw" width="1175" height="870"></p><h5><strong>Advanced Data Classification with SIMCA Modeling</strong></h5><p>Offers a powerful statistical method for supervised classification of data, allowing researchers to categorize and analyze complex datasets with precision.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_Data_Classification_with_SIMCA_Modeling_830f63d8a0.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Advanced Data Classification with SIMCA Modeling" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_Data_Classification_with_SIMCA_Modeling_830f63d8a0.webp 195w," sizes="100vw" width="1026" height="820"></p><h5><strong>Advanced PCA Analysis for In-Depth Data Insights</strong></h5><p>Provides features for comprehensive data exploration and visualization, including quantile plots (1D NMR), comparison tools, plot labels display, enhanced selection and interactivity in scores and loadings plots, and additional distance. calculation options in scores plots. These enhancements enable precise, interactive analysis for deeper data insights.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_PCA_Analysis_for_In_Depth_Data_Insights_32b2644333.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Advanced PCA Analysis for In-Depth Data Insights" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_PCA_Analysis_for_In_Depth_Data_Insights_32b2644333.webp 245w," sizes="100vw" width="1026" height="647"></p>

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