Technology improvements in liquid chromatography/mass spectrometry have enhanced the detection and identification of metabolites and lipids from complex biological samples. As metabolomics and lipidomics measurements become increasingly valued, there is a growing need to automate sample preparation workflows.
Specifically, Agilent automation offers intuitive workflows that provide high data reproducibility and increased throughput while reducing hands-on time. In this webinar, we describe key learnings revealed during the automation of several workflows that extract metabolites and/or lipids from plasma and mammalian cell samples.
Genevieve Van de Bittner, Ph.D. R&D Researcher
Agilent Research Laboratories
Agilent Technologies, Inc.
The measurement of trace metals in petroleum feeds and its derivatives provides vital information required for running sustainable and daily petroleum operations around the world. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is used in different petroleum facilities due to its ability to perform multi-element analyses, covering a broad range of concentrations as well as being robust and reliable. ICP-MS is becoming more integrated into petroleum laboratories due to its maturity and versatility.
This talk will cover Agilent’s efforts towards developing an ASTM Jet Fuel method. Many interesting elements that aren’t commonly requested, including Platinum (Pt) and Palladium (Pd), will be discussed with this new ICP-MS method. Preliminary data from the ASTM pilot study will be shared in this talk.
Jenny Nelson, PhD Application Scientist
Agilent Technologies, Inc.
Mark Kelinske Application Scientist
Agilent Technologies, Inc.
Inductively coupled plasma–mass spectrometry (ICP-MS) is a fast, multielement technique used for trace elemental analysis.
But labs that use ICP-MS – or are thinking of installing one – can find it difficult to unlock the true potential of the technique. Unproductive and often unnecessary activities can eat into lab time, reducing productivity, increasing stress, and potentially impacting data quality. Open to all; this workshop will provide insights you can employ to improve efficiency in your laboratory while also reducing pressure on staff and increasing confidence in the results you report.
Bert Woods Application Scientist
Agilent Technologies, Inc.
Joined the Agilent ICP-MS team in 2004, with previous employment in the semiconductor industry with Dominion Semiconductor (IBM/Toshiba) and Micron. Bert is a 1997 Chemistry graduate of Radford University in Virginia and an avid Washington DC Sports fan.
L. Craig Jones ICP-MS Application Scientist
Agilent Technologies, Inc.
Craig has been with Agilent for over 15 years as an ICP-MS applications scientist. He has been involved with multiple types of applications for ICP-MS, including environmental, pharmaceutical, nutraceutical, semiconductor, geologic, and clinical analyses, to name a few. Previous to Agilent, he worked in an environmental lab performing analysis and supervising both the inorganic and organic sections of the laboratory. In his spare time, Craig enjoys volunteering at the local marine science centre, mountain biking, hiking and relaxing at the beach. Craig obtained a bachelor of science degree in chemistry from Fort Lewis College in Durango, CO.
Cancer is a leading cause of death worldwide and there is a great movement globally to develop new treatments and advance how cancer is diagnosed. Technology has been a great help, particularly in recent years, and now there’s new innovation that could take our cancer diagnosis and treatment to a new level.
According to an article published by The Guardian, doctors, scientists and researchers have built an artificial intelligence model that can accurately identify cancer in a development they say could speed up diagnosis of the disease and fast-track patients to treatment. This is but one of many new developments that include AI technology in cancer diagnosis as well as treatment.
In this webinar, we learn the predictive powers of artificial intelligence combined with cutting-edge mass spectrometry to discover clinically relevant biomarkers that can only be revealed by high-resolution analysis of the glycoproteome. This presentation is for all who are interested to learn more about the real-world clinical application of glycoproteomics on cancer diagnosis.
Dr. Low Ley Hian Director of Development
Although there’s a rising demand for honey, the honey bee population is also under threat. Another not-so-sweet issue is the number of products labelled as honey on retail shelves that don’t meet the criteria to be classified as pure honey.
The term “adulterated honey” means any honey to which has been added honeydew, glucose, dextrose, molasses, sugar, sugar syrup, inverted sugar, or any other similar product or products other than the nectar of floral exudations of plants gathered and stored in the comb by honey bees.
Food fraud is a significant concern for consumers and producers, with research indicating that fraud accounts for up to 25% of all globally reported food safety incidents. The growing demand for food authenticity means consumers regularly pay a premium for organic and sustainably produced goods like honey. Fraudsters have been flooding markets with adulterated, low-quality, or mislabeled foodstuffs, damaging the livelihoods of legitimate businesses and potentially risking consumer health.
Consumers have become quite specific in their demand for honey, focusing on unifloral honey or monofloral honey obtained predominantly from bees that feed on a single species of plant flowers. This results in a unique colour, flavour, and fragrance exclusive to each type of unifloral honey. As consumers are willing to pay more for these products, protections must ensure that they purchase what they expect.
According to data from the Food and Agriculture Organization of the United Nations, China, Mexico, Russia, Turkey, and the United States are among the major honey-producing countries accounting for approximately 55 per cent of world production. The most common form of adulteration involves extending or diluting honey with other less expensive sweeteners. Commonly identified extenders are corn, cane, and beet syrups.
Testing for authenticity to mitigate honey fraud
Global e-commerce is placing honey sales outside regulatory oversight more frequently—a trend expected to continue. This, combined with increased fraudulent activities, makes tackling the problem critical. This is why it is important to identify these substances quickly, efficiently, and consistently. The food industry requires analytical instruments and testing techniques to consistently and rapidly analyze food and identify trace chemicals.
Analytical testing is essential for assessing food authenticity, which is important to protect consumers’ health, the brand, and producers’ income. Testing is a necessary part of an overall strategy to mitigate fraud risk, and methods for authenticity testing are rapidly evolving, with innovative technologies now available for developing robust food testing techniques.
For example, it has been demonstrated in recent years that coupling high-performance liquid chromatography with quadrupole time-of-flight (LC/Q-TOF), such as the Agilent 1290 Infinity II LC System with Agilent 6545 LC/Q-TOF, provides a sensitive method to reveal the chemical composition of honey samples. Using this method with a non-targeted approach enables the identification of new types and sources of fraud through the chemical markers in the honey, highlighting which kind of fraudulent activity is occurring. Since this technique evaluates multiple markers in honey to determine authenticity, it is very difficult for fraudsters to cheat by adding one or a few adulterants. This innovative technique is called honey fingerprinting.
Honey fingerprinting is the practice of using a suitable technique to record as much information as possible on the chemical composition of a particular honey sample. In the same way, a human fingerprint is unique to individuals, this fingerprinting method unlocks and records the unique molecular composition of authentic honey samples. This enables the mapping of food components in an unprecedented fashion that will revolutionize how honey is regulated for quality, safety, and authenticity.
Utilizing a non-targeted workflow begins with identifying other compounds, including pesticides, molecules that indicate freshness, like a compound called HMF (which suggests thermal processing or age if present in high numbers), and phenolic compounds, which are related to the floral origin of honey. The advantage of using LC/Q-TOF for this technique is its efficiency: higher molecular/trace information levels can be obtained from just one sample in less time versus targeted methods focusing on just a few parameters.
Standardising honey fingerprinting methods
Although previous work has been done developing case studies for fingerprinting foodstuffs, including honey, the approaches among laboratories have been different regarding sample preparation and instrumental condition. There are also differences in terms of data processing and analysis. As a result, two laboratories analyzing the same sample may obtain slightly different results. Ideally, developing a standardized fingerprinting method that could be used across all LC/MS-based workflows, enabling the same testing technique to be used across multiple laboratories, would be optimal and where future work is aimed.
When addressing the issues of food safety, product quality, and authenticity, each may be governed by separate sets of regulations. For example, looking at the residues of contaminants in honey, such as pesticides, there may be differences globally. Countries may have their own restrictions for the maximum limit for specific compounds. Contaminants are a part of the picture when considering fingerprinting for honey, but permitted levels may vary between countries.
Additionally, as samples come from the field to the lab for testing, there is potential interest in reversing this and bringing the lab out into the field instead. This interesting but not yet recognised capability would enable regulators and the global food industry to respond more quickly to honey contamination and food fraud.
Taking a global approach to ensure honey purity
As the food supply chain becomes increasingly globalized, raising the opportunity for food fraud, experts predict that testing, such as those described above, will become more accessible, increasingly automated, and easier to perform. Fingerprinting methods—in which the entire molecular profile of food can be obtained—will be a feature of future fraud prevention and identification systems.
A positive step forward is the focus on building a library of authentic honey samples and making it an accessible, open database so that honey fingerprinting information is available across multiple stakeholders in the global supply chain. With increased knowledge, more scientists will be able to adopt techniques such as LC/Q-TOF and could also use this testing for other types of food—for example, maple syrup.
The ultimate goal is for food testing laboratories to confidently measure contaminants that threaten the global food chain and tackle food fraud head-on to ensure that consumers can access authentic and safe honey.
(This article has been modified from its original appearance on the Agilent website)