|Sunday, March 18
Time: 4:40 pm
Location: Room 230
ANYL 44: Characterization of metabolic variability in red wines using a highly selective non-targeted acquisition approach
Characterization of food and beverages has in recent years shown analytical trends increasingly using non-targeted approaches to complement quantitative targeted analyses. Application of these techniques to the analysis of wine have been used to assess previously unknown contents of wine lees1, patterns in glycosilated simple phenols across wine grape hybrid varieties2, and metabolic profiling of pest resistant genotypes against their susceptible ancestor vines3. In addition to high quality HRMS data, it is also important to ensure that the known analytes in these types of experiments can be quantified within relevant concentration ranges. Here, we demonstrate the use of a QTof data independent acquisition (DIA) mode in which the quadrupole is set to scan across the defined mass range using a narrow mass window. Following this, the collision cell alternates between passive and elevated collision energies which generate fragments. The end result is highly selective and specific spectra for both low- and high-collision energy states. Preliminary work thus far on store bought red wines have demonstrated qualitative profiling using this acquisition approach coupled with UPLC and ESI- ionization. Differentiation between metabolites and constituents in the various wines was achieved using the multivariate statistics approaches PCA, OPLS-DA and hierarchical cluster analysis. From the same data set, quantitation of selected native phenols was performed with isotopically-labeled standards of resveratrol, catechin and p-coumaric acid. Data presented will highlight utility of this approach for both targeted and non-targeted assessment of metabolite variation in wines across different grapes as well as years of production from a single vineyard.
|Monday, March 19
Time: 8:00 pm
Location: Halls D/E
BMGT 7: Procurement strategies for managing technologies
Waters Corporation values and appreciates the important role academia plays in educating the next generation of scientists and leading research into some of the most complex challenges of our time. We understand that the technical foundations laid in colleges and universities underpin future scientific advancement in industry and enable paradigm-changing research programs in medicine and healthcare, the environment, food security, forensics, materials science, energy, etc. To be successful, professors often require access to next generation technologies, a difficult task due to the challenge of acquiring research grants.
Waters Academic Program may contribute to the foundation of a customer's laboratory. It has been designed to assist in acquiring enabling technologies and support from the leader of analytical sciences through:
● Extending the purchasing power of research grants up to 30% on eligible instrument purchases
● Supports the option to lock in 2 years of service coverage at today's price
● Combining with Waters Lease Protection Plans to keep your laboratory's technologies current
● Providing opportunities to publicize a laboratory's accomplishments
|Wednesday, March 21
Time: 2:00 pm
Location: Room 227
|Forced Degradations in Pharmaceutical Industry
ANYL 415: Evaluation of relative response factors using small scale fraction collection in forced degradation studies
Forced degradation studies allow a greater understanding of the degradation pathway of pharmaceuticals. Mass balance correlates the measured loss of a parent drug to the measured increase in the degradation products, however, given the range of impurities and their chemical and physical properties,
mass balance studies can be challenging. One of the specific challenges includes determining the response factor of an impurity relative to the active pharmaceutical ingredient (API). Incorrectly identifying the relative response factors (RRFs) could lead to over or under quantification of the impurity, which can in turn lead to mass imbalance. However, to determine the RRF of an impurity by UV a pure standard is typically required. This poses a challenge for those impurities that may be unknown or for which there are no standards readily available. Isolation or collection of these impurities provides an opportunity for further characterization of the impurities.
In these studies, a dual detection system consisting of a photodiode array (PDA) and a mass detector in combination with small-scale fraction collector will be used to analyze a stressed drug substance. Fraction collection will be performed on an analytical scale for numerous impurities in the sample, including low-level species. Using these collected samples, calibration curves will be acquired. The relative response factors (RRFs) of these impurities will then be determined by established methodologies, specifically the ratio of the slope of both the API and impurity standard curves. For comparison, the RRFs will also be determined using purchased standards, when applicable, to verify the approach. The subsequent RRFs will then be used to calculate mass balance for the stressed study
|Thursday, March 22
Time: 9:20 am
Location: Room 350
|Accurate Mass/High Resolution Mass Spectrometry for Environmental Monitoring & Remediation
ENVR 734: Comprehensive targeted and non-targeted analysis of indoor dust using LC-HRMS with ion mobility
Analysis of indoor dust has been used to assess human exposure to compound classes such as flame retardants, pesticides and other environmental contaminants. Here, we demonstrate the analysis of dust extracts representing various indoor environments (industrial and domestic) using a comprehensive HRMS approach that incorporates ion mobility to provide additional separation of the complex samples. Non-targeted data acquisition was performed using UPLC-IMS QTof in ESI positive and negative polarities with HRMS-ion mobility enhanced MSE acquisition mode. Following acquisition, identifications were made against a target list based on known values from standards for accurate mass of fragments, RT, and the collisional cross section (CCS) values determined using IMS. Assessment of sample variability was achieved using the multivariate approaches of PCA and OPLS-DA. Significant accurate mass:retention time pairs responsible for these sample variations were then submitted for elemental composition and isotope scoring, followed by a ChemSpider database search. Using the compounds' proposed structures, theoretical fragmentation was performed and high-collision energy spectrum was matched to the fragment structures and scored. The combined targeted and non-targeted processing approach resulted in numerous compounds being tentatively identified in the various house and industrial dust samples, including perfluorinated compounds, flame retardants and pharmaceuticals. Trending of compound groups across the industrial and domestic dust samples was also assessed.