Meeting EU Drinking Water Standards: The Critical Role of Sample Prep in Trace Contaminant Analysis

Although modern agriculture needs to be based on accurate real-time data on soil, plant, and environmental conditions, affordable, sufficiently sensitive, and robust monitoring devices for this purpose are currently missing. According to scientists, low-cost sensors based on new smart materials and printing technologies offer a suitable solution. The results of multidisciplinary research thus far and proposals for the development of these devices have been presented by researchers from Czechia, Great Britain, Spain, and the USA in a review article in the prestigious journal <a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41467-026-68778-6#Abs1">Nature Communications</a>.“Sensor technologies for monitoring plant health are still in their infancy. Only simple sensors capable of monitoring basic parameters such as pH, soil moisture, or temperature are commonly available on the market. However, if farmers are to face current challenges, including climate change, and ensure sufficient food for humanity, they need much more effective tools that will enable them to monitor, for example, various pathogens, including bacteria and fungi. In our opinion, a suitable solution is a combination of new smart materials and printing for the production of inexpensive, durable, and scalable materials,” said the article’s first author, David Panáček from CATRIN, who worked on the study during his internship at Imperial College London.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg" alt="CATRIN: David Panáček" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg 208w," sizes="100vw" width="1536" height="1152">Sensors for monitoring plant health, for example, lag behind similar devices used in human medicine. According to the authors, advances in materials science, which will enable the development of scalable sensor technologies, play a key role in this potential shift. “Printing techniques, including inkjet printing, screen printing, aerosol printing, 3D printing, and direct laser writing, offer flexible ways to produce flexible sensors, large-area sensors, and sensors integrated directly into plants. The review article summarizes recent advances in printable low-dimensional materials for agricultural sensors, analyzes their physico-chemical properties in relation to sensor performance, and discusses key challenges and future opportunities requiring interdisciplinary integration,” said one of the corresponding authors, Michal Otyepka.The research brought together materials scientists, chemists, biologists, sensing experts, and printing technology specialists. Materials research and the use of graphene-based smart materials were led by scientists from CATRIN at Palacký University and VŠB-Technical University of Ostrava. Plant biologists from CATRIN contributed their knowledge of plant development, their responses to stress conditions, and the monitoring of their properties. Researchers from Imperial College London took care of the electronics, while representatives from<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/36"> CEITEC – VUT</a> focused on printing technologies. The team also included leading experts in sensing from the Catalan Institute of Nanoscience and Nanotechnology in Barcelona, and Joseph Wang of the University of California San Diego, the “father of sensing and electrochemistry,” also contributed his extensive knowledge.“This is a groundbreaking study on this topic, which has managed to attract some truly big names in their respective fields. Last but not least, the study demonstrates that interdisciplinarity at CATRIN gives rise to completely new and promising research topics, such as plant sensing and its use for studying plant-environment interactions and smart agriculture,” added another corresponding author, Nuria De Diego.

Current sensors are not good enough. Scientists propose a new way to monitor plant health

In this episode of the Concentrating on Chromatography podcast, host David Oliva interviews Ainslie Chen about her cutting-edge research on hemoglobin variant testing using liquid chromatography-high resolution mass spectrometry (LC-HR-MS). Ainslie discusses her novel method for separating and identifying hemoglobin subunits with mass shifts less than 1 Da, overcoming critical limitations in conventional clinical assays.Hear firsthand how her team developed an LC-HR-MS workflow using a C4 reversed-phase column, tackled technical challenges (including why C18 columns fell short), and achieved unprecedented sensitivity for variant detection in both adult and neonatal samples. The conversation touches on the potential of mass spectrometry to revolutionize clinical diagnostics, the importance of reproducibility, barriers to adoption in routine labs, and how teamwork drives scientific innovation.Perfect for analytical chemists, clinical laboratorians, and anyone interested in the future of protein variant analysis, this episode also features Ainslie’s advice for early-career scientists and insights from her first ACS poster presentation.<h4>Key Highlights:</h4><ul><li>Motivation behind improving hemoglobinopathy testing &nbsp;</li><li>Technical advantages of LC-HR-MS over gene sequencing and CE &nbsp;</li><li>The crucial role of the C4 column in resolving challenging samples &nbsp;</li><li>Critical parameters for reproducible LC-HR-MS workflows &nbsp;</li><li>Barriers and outlook for clinical adoption of advanced mass spectrometry &nbsp;</li><li>The value of teamwork and mentorship in scientific research &nbsp;</li><li>Direct insights from recent ACS conference experiences</li></ul><h3>Video transcription</h3>In this interview, Ainslie Chen discusses her research on improving the detection and identification of hemoglobin variants using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). The work addresses limitations of conventional hemoglobinopathy testing, which often struggles to resolve very small mass differences between closely related hemoglobin subunits. Because even a single amino-acid substitution can significantly alter hemoglobin structure and function, high analytical resolution is essential for accurate diagnosis of conditions such as anemia and sickle cell disease.Chen explains why her team selected LC-HRMS over established clinical techniques like capillary electrophoresis and gene sequencing. While sequencing offers excellent accuracy, it is time-consuming, costly, and requires extensive sample preparation, making it impractical for routine clinical workflows. Capillary electrophoresis enables subunit separation but lacks the resolving power needed to distinguish variants differing by less than one Dalton. In contrast, high-resolution mass spectrometry provides both structural specificity and sensitivity, enabling confident identification of subtle hemoglobin variants with minimal sample preparation.A key methodological insight from the project was the use of a C4 reversed-phase LC column instead of the more common C18 column. Chen describes how the shorter carbon chain and larger pore size of C4 columns improved protein elution and reduced denaturation, leading to more reproducible separations. Critical parameters for reproducibility included consistent mobile-phase composition (0.1% formic acid in water and acetonitrile), controlled temperature (60 °C for LC, ~320 °C capillary temperature), and stable chromatographic conditions.Beyond hemoglobin analysis, Chen highlights the broader potential of high-resolution mass spectrometry in proteoform analysis and clinical diagnostics, including emerging applications in cancer detection. She acknowledges current barriers to clinical adoption—such as energy demands and instrument infrastructure—but points to advances like miniaturized mass spectrometers as promising steps toward wider use. The interview concludes with advice for young scientists: don’t hesitate to reach out to mentors, embrace collaboration, and view analytical chemistry as a versatile tool that bridges medicine, biology, environmental science, and beyond.<blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote><blockquote><h4>Concentrating on Chromatography Podcast</h4>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!You can find Concentrating on Chromatography Podcast in podcast apps:<ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL">Spotify</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185">Apple podcast</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography">podscan</a></li></ul>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos">YouTube channel</a></blockquote>

Unlocking Hemoglobin Variant Detection: LC-HR-MS Breakthrough with Ainslie Chen

Article

Video

Environment

Scientific article

Interview

Science and research

The Czech Advanced Technology and Research Institute (CATRIN) at Palacký University is a cutting-edge scientific hub dedicated to advancing research in the fields of nanotechnology, biotechnology, and biomedicine. At its core, CATRIN boasts outstanding scientific teams, featuring international researchers. We emphasize interdisciplinarity, foster global collaborations, and work to translate our research findings into practical applications.

CATRIN

Organomation, founded in 1959, designs and manufactures high-quality nitrogen evaporators and extraction systems. Known for innovation and durability, their lab instruments are used globally for efficient sample preparation with strong customer support.

Organomation

Mestrelab Mnova Advanced Chemometrics software

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

<h4>Advanced Chemometrics for Enhanced Data Analysis</h4>Leverage sophisticated multivariate analysis tools such as PCA, PLS, and SIMCA 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.<h4>Benefits:</h4><ul><li>All-in-One Solution: 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>Incorporates Recognized Methods: Includes PCA, PLS, and SIMCA for advanced data analysis and unsupervised chemometrics.</li><li>Powerful and Intuitive Interface: Provides a user-friendly design for a streamlined analysis experience.</li><li>Improved Classification and Prediction: Classifies samples with SIMCA and builds predictive models using PLS.</li><li>Noise and Outlier Reduction: Effectively reduces noise and detects outliers, ensuring accurate and reliable results.</li><li>Expandable Plugin: Features Higher Order Structure (HOS) capabilities, powered by Mnova BioHOS.&nbsp;</li></ul><h4>Features:</h4><h5>New MCR Tool for Peak Purity Assessment in LCMS Data</h5>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.<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"><h5>Enhanced Data Analysis with Partial Least Squares (PLS) Regression</h5>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.<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"><h5>Advanced Data Classification with SIMCA Modeling</h5>Offers a powerful statistical method for supervised classification of data, allowing researchers to categorize and analyze complex datasets with precision.<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"><h5>Advanced PCA Analysis for In-Depth Data Insights</h5>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.<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">

Products from category LIMS, QMS, DMS, Statistics from SciY/Mestrelab Research - page 1

Related content

Unlocking Hemoglobin Variant Detection: LC-HR-MS Breakthrough with Ainslie Chen

Current sensors are not good enough. Scientists propose a new way to monitor plant health

Meeting EU Drinking Water Standards: The Critical Role of Sample Prep in Trace Contaminant Analysis