United States

Hyaluronic acid (HA) is a naturally occurring component in the human body, playing a vital role in maintaining moisture within tissues such as the skin and joints. Its broad functionality has led to widespread use in fields like medicine, cosmetics, and dietary supplements. HA’s unique physicochemical properties, including its strong water-binding capacity and viscoelastic nature, make it well-suited for various biomedical applications, from viscosupplementation to wound healing. However, its complex biopolymeric structure, composed of D-glucuronic acid and N-acetyl-glucosamine units, presents challenges for direct quantification due to its high molecular weight and varying size distribution. This study focuses on accurately measuring HA in different matrices, including supplements, creams, and liquid sodium hyaluronate for equine use. The analysis method involves sample extraction in a Tris-HCl buffer solution, enzymatic digestion with chondroitinase ABC, and subsequent detection using high-performance liquid chromatography with UV analysis. The method proved effective across different sample types, highlighting its reliability and practicality. Overall, this research enhances analytical techniques for HA, a crucial biomolecule with significant biomedical applications.

2025 AOAC INTERNATIONAL Annual Meeting &amp; Exposition

Quantification of Hyaluronic Acid Using HPLC-UV

#### The AOAC INTERNATIONAL Annual Meeting: A Unique Analytical Science Opportunity

The AOAC Annual Meeting & Exposition provides unparalleled professional development, networking, and collaboration in methods-based science. 

* **Businesses**: Meet scientific and regulatory experts and engage with new trends and standards.

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This multi-faceted “idea incubator” focuses on regulatory changes and emerging food safety issues. A plenary and two breakout sessions feature thought-provoking ideas to identify and meet analytical needs.

The 2025 AOAC INTERNATIONAL Annual Meeting & Exposition was held in person in San Diego, USA.

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2025 AOAC INTERNATIONAL Annual Meeting & Exposition

The AOAC Annual Meeting & Exposition provides unparalleled professional development, networking, and collaboration in methods-based science.

Pesticides residues are commonly found in teas, and demand for analytical detection is increasing as global tea consumption increases. We developed a robust analytical method that enables almost 400 both polar and non-polar pesticides to be analyzed under ESI and APCI utilizing a dual source LC-MS/MS. This method eliminates the need for GC-MS/MS analysis by analyzing a list of 50 pesticides using APCI. 
Experiments were carried out using a QSight 420 UHPLC-MS/MS via a divert valve. A simple solvent extraction sample prep procedure with isotopic internal standard dilution was employed. Matrix effects were evaluated using black tea, chamomile, and herbal blend. In total, 690 MRM transitions were monitored for 345 compounds in the ESI method, and 100 MRM transitions were monitored for 50 compounds in the APCI method. A single C18 column was used for both LC methods.
In this work, we demonstrate how a practical simple solvent extraction can be utilized to achieve the analysis of a large multi‑residue panel of pesticides, with low limits of detection (with 319 of 395 analytes displaying LOQs of 5 ng/g or below), minimal matrix effects (94% of compounds with negligible %SSE in black tea), and excellent method performance (93% of compounds with accuracies within 70 ‑ 120% and RSD &lt; 20%). QSight’s Dual Source design allows for APCI analysis on traditionally GC‑only compounds to be included in this LC pesticide panel, reducing instrument workload, and potentially eliminating the need for complementary GC‑MS protocol for multi‑residue pesticide quantification. Simple sample preparation and StayClean ion source instrumentation allows for a robust analytical solution with the potential to analyze hundreds of pesticides in many different matrices.

Dual ESI/APCI StayClean™ Ion Source QSight LC-MS/MS for Analysis of Near 400 Polar and Non-polar Pesticide Residues in Tea

Accurate detection of Mineral Oil Saturated Hydrocarbons (MOSH) and Mineral Oil Aromatic Hydrocarbons (MOAH) is critical for food safety and regulatory compliance. However, inconsistencies in chromatographic integration, baseline corrections, and subjective analyst interpretation create variability, hindering standardization and reproducibility (JRC report: Robouch et al., 2022, JRC129603).
This session introduces a transformative AI-driven solution: Generative Limited Sample Model AI, a novel approach designed to eliminate analytical variability and standardize MOSH/MOAH analysis across laboratories. Unlike conventional deep learning models that require extensive datasets, LSM AI learns from a limited set of expert-annotated samples, providing a scalable, high-precision, and adaptable solution for contaminant detection. This innovation allows laboratories to move beyond subjective, manual data processing and embrace fully automated chromatographic deconvolution, matrix effect correction, and AI-driven regulatory compliance workflows.
Key Innovations and Analytical Advancements

AI-Driven Chromatographic Peak Deconvolution – Eliminates manual bias, ensuring reproducible MOSH/MOAH quantification across GC-FID and GC×GC-TOFMS platforms.
Instrument Variation Compensation – Dynamically corrects for inter-laboratory discrepancies, harmonizing data processing with real-time LSM AI-driven calibration.
MOSH/MOAH Source Attribution – Enhances regulatory compliance by classifying contamination origins (food processing lubricants, recycled packaging, environmental deposition).
Automated Workflows for Non-Specialists – Expands adoption by replacing expert-dependent manual workflows with AI-powered data interpretation and compliance tracking.
Regulatory Alignment & AOAC Standardization – Delivers standardized, reproducible, and bias-free quantification, supporting AOAC and JRC guidelines for method validation.

This breakthrough enables scalable, automated MOSH/MOAH analysis, ensuring regulatory-ready, high-accuracy results without manual inconsistencies.

Applying Generative AI Technology to Overcome MOSH/MOAH Analytical Challenges

The presence of Per- and Polyfluoroalkyl Substances (PFAS) in food has become an increasing concern due to their persistence and bioaccumulation. As regulations tighten with decreasing action limits, the need for a harmonized and accurate method for PFAS determination is critical. Shellfish, as bottom feeders, are particularly susceptible to PFAS contamination from water and sediment. However, their high lipid content presents analytical challenges, and PFAS solvent extraction is inherently difficult due to contamination risks and the low concentrations at which these compounds occur. Traditional extraction methods are often manual, time-consuming, and inefficient. This study evaluates the EDGE PFAS™ system, an automated solvent extraction system, for extracting PFAS from shellfish. This method provides a streamlined process with efficient extraction, minimal sample handling, and high recovery rates with excellent reproducibility. The EDGE PFAS™ system offers a rapid, simple, and effective solution for PFAS testing in shellfish, supporting regulatory compliance and food safety efforts.

Automated Extraction of PFAS from Shellfish: Improving Sample Preparation Efficiency and Reproducibility

Ciguatera Poisoning (CP) has been considered an emerging risk in European subtropical areas of the Atlantic Coast of Europe. The characterization of this emerging risk prompted the interest of the European Health Authorities. This characterization has been carried out over the last eight years under the support of EFSA. The lack of reference materials commercially available has been the main challenge for the method development required for the characterization of the ciguatoxins involved in the contamination. An intensive and challenging work, in the absence of standards commercially available, has been carried out, not only in the optimization of sample pretreatment protocols, but also in the development of analytical methods for screening/quantitation and confirmation. The combination of toxicological assays, such as N2a-MTT cell assay with chemical methods by liquid chromatography coupled to mass Spectrometry (LC-MS) has resulted on a very efficient tool that allowed the characterization of Caribbean ciguatoxins as the responsible of the CP in the areas of study. The analytical tools developed also allowed the preparation of ciguatoxins reference material for laboratory use. The main achievements and challenges on this risk characterization from the analytical chemistry point of view is going to be presented and discussed.

Outcome of the Characterization of the Risk Caused by algal toxins Responsible for ciguatera Poisoning in Coastal Areas of Europe under the Analytical Point of View

Seafood has been identified as the food commodity with the second highest potential for fraud by the European Parliament. Thus, the objective of this project is the development and validation of a DNA metabarcoding method for the identification of seafood in processed foods.Reference sequences of the mitochondrial 16S rDNA marker gene were obtained from the National Centre for Biotechnology. We designed universal primers targeting fragments of 150 bp to 210 bp, and PCR conditions were established. Reference material (202 samples), DNA extract mixtures and processed foods (112 samples) were sequenced on Illumina platforms. Automized data evaluation was achieved by creating customized databases in combination with a Galaxy analysis pipeline. The DNA metabarcoding method was successfully developed and validated. Five primer systems were created that amplify the barcodes of mussels, razor clams, sheath clams, venerids and cockles, oysters and scallops, squids, crustaceans, or marine and terrestrial snails. We correctly identified seafood in reference material, model food samples and processed foods with complex matrices such as prawn butter, linguine with squid ink and nutritional supplements. Most specimens can be classified at species or genus level. The heat stability of the DNA provides an advantage in the analysis of commercial foods. Additionally, this untargeted, standardized method allows the screening of species in complex mixtures, unlike species-specific PCR and DNA barcoding. Establishing this method in official control laboratories directly contributes to improving consumer protection by ensuring the authenticity and safety of food.

Authentication of a Variety of Crustacean and Mollusc Species in Complex Food Matrices - Identification of Seafood in Food Products via DNA Metabarcoding

Recently, the cannabidiol (CBD) products are becoming increasingly available in Japanese food and health markets. In 2024, the Ministry of Health, Labour and Welfare in Japan revised the Cannabis Control Act. This law sets the residual limits of tetrahydrocannabinol (THC) levels in CBD products. Specifically, the residual limits based on Δ9-THC andΔ9- tetrahydrocannabinolic acid (THCA) concentrations were 10 ppm for oil and powder, 1 ppm for various solid samples and 0.1 ppm for liquid samples. In addition, the ministry presents the proposal method for the determination of Δ9-THC and Δ9-THCA based on LC-MS/MS and/or LC-Q/TOF/MS assays. Thus, we investigated that LC-MS/MS assay would be useful, accurate, sensitive and screening evaluation of residual limits of THC levels in common products. Our LC-MS/MS assay of Δ9-THC and Δ9-THCA was developed with reversed-phase short column (running time: 5 min) and ESI-positive/negative mode. Recovery tests with absolute/internal calibrations were good accuracy  and precision of <10%, respectively. In conclusion, our good results were obtained for almost all products, however the recovery rates of water-soluble product were not enough to evaluate these levels using absolute calibrations. On the other hand, we suggest that accurate methods with internal calibration would be useful for the evaluation of residual limits of THC levels in various products.

LC-MS/MS Procedure for the Evaluation of CBD Products from Japanese Markets Based on Official Guidelines

Bovine lactoferrin (bLF) is commonly fortified in infant formula, pediatric and adult nutritional products for its beneficial impacts on immune system development and gut health. The AOAC Method 2010.10 offers a reliable and accurate solution for determining bLF in powdered infant formula and pediatric/adult nutritional formula, using heparin affinity column extraction and reversed-phase high performance liquid chromatography (RP-HPLC) with ultraviolet detection. We evaluated the advantages of the MaxPeak High Performance Surfaces (HPS) for this analytical method by comparing the results from a conventional column with those from the (same) column incorporated with the MaxPeakTM HPS (XBridgeTM Premier Protein BEHTM C4 Column). We observed more symmetric peak shapes and consistent results, when using the XBridge Premier Protein BEH C4 Column. Additionally, a potential co-elution issue was identified and resolved by implementing a modified gradient elution program. 
MaxPeak, XBridge, and BEH are trademarks of Waters Technologies Corporation.

Benefits of an Inert Surface Technology in the Analysis of Bovine Lactoferrin in Infant Formula and Pediatric/Adult Nutritional Formula

Low-Pressure GC (LPGC technique) has been successfully used for the analysis of pesticide residues, monochloropropane diols (MCPDs), phthalates, arylamines, nitrosamines and alkylamines, as examples. In addition to the applications a variety of different stationary phases have been evaluated to include “5-type”, high phenyl-type, trifluoropropyl and cyano-phenyl columns. Applications have demonstrated using both 0.53mm internal diameter columns as well as 0.32mm internal diameter columns can be successfully used for many different applications. The use of Concurrent Solvent Recondensation Large Volume splitless injection (CSR-LVSI) has been used with LPGC injecting up to 25ul with significant increases in sensitivity and minimal peak distortion. The LPGC techniques provided reductions in run times (up to 3.3x faster runs) and helium consumption reduction (up to 81% less helium used), while keeping an acceptable resolution. This presentation will review applications, use of different column dimensions and phases, in addition will review the ability to inject large volumes to increase sensitivity.

Comprehensive Review of Low-Pressure Gas Chromatography Applications.

Accurate prediction of shelf-life is critical for reducing food waste and boosting consumer confidence in the food industry. Conventional methods like gas chromatography-mass spectrometry and microbial analyses are commonly used to monitor changes in food quality and safety and predict shelf-life. These methods, while accurate, are expensive, time-consuming, and impractical for real-time applications. Hence, a more affordable, simple, and real-time analytical method was developed in this study and tested with samples of soymilk, leveraging the volatile compounds (VOCs) released during spoilage. A novel gold-coated surface-enhanced Raman spectroscopy (SERS)-active fiber was inserted into the headspace of soymilk in capped glass vials. The SERS fiber was incubated in the headspace of the samples at 25ºC for 30 minutes. SERS spectra were acquired using a Raman microscope. Samples were monitored for two weeks. The SERS-active fiber could capture VOCs from soymilk, especially dimethyl sulfide, a well-known bacterial spoilage VOC, during spoilage. Using convolutional neural networks (CNN) models, the SERS spectral changes strongly correlated with changes in pH (R=0.89, RMSE=0.30), microbial growth (R=0.91, RMSE=0.69log10CFU/ml), electrical conductivity (R=0.92, RMSE=0.07mS/cm), zeta-potential (R=0.94, RMSE=1.26mV) and remaining shelf-life (R=0.95, RMSE=1.30days) in the training samples. Further, using SERS spectra from the headspace of a separate set of soymilk samples, the CNN models could predict the remaining shelf-life (R=0.80, RMSE=2.54days) and microbial growth (R=0.73, RMSE=1.14log10CFU/ml). Therefore, the SERS fiber combined with CNN can predict soymilk quality and shelf-life in real-time. Further studies are needed to advance the practical application of this method to more food products.

Real-time prediction of shelf-life of soymilk using a surface-enhanced Raman spectroscopy (SERS) fiber and convolutional neural networks

Thistle is a perennial plant belonging to Asteraceae, which has thorns in its leaves and blooms in summer which grows common in Korea. Thistle has been used for traditional medicine of blood coagulation and hepatoprotection because of known to it contains various biologically active substances along centuries. According to recent research, It has reported to have outstanding antioxidant activity and liver function protection effect. Interests have been increased in thistle. In this study, we extract species of thistles (C. japonicum, C. nipponicum) using extraction solvents((Methanol(MeOH), Dichloromethane(MC), n-Butanol(BuOH), Ethyl acetate(EA), Water), then identify antioxidant activity, total polyphenol content, total flavonoid content. DPPH radical scavenging activity of 1 mg/mL of extract is measured the highest activity(89%) of C. nipponicum and ABTS radical scavenging activity of 0.5 mg/mL of extract is measured the highest activity(94%) of C. nipponicum. The total polyphenol content is the highest in 320mg GAE/g from BuOH fraction of C. nipponicum. Also the total flavonoid content is the highest in 600mg QE/g from BuOH fraction of C. nipponicum. In addition, through 13 Polyphenols and Flavonoids HPLC analysis, EA and BuOH fraction have a high polyphenol contents most of which is chlorogenic acid(EA 40 mg/g, BuOH 65 mg/g), and apigenin, sylingic acid are also contained in extract. 

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Dual ESI/APCI StayClean™ Ion Source QSight LC-MS/MS for Analysis of Near 400 Polar and Non-polar Pesticide Residues in Tea

Stay up to date with the latest Underline news!

PRESENTATIONS

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RESOURCES

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