The recent outbreak of severe lung injury is allegedly tied to the presence of Vitamin E Acetate (VEA) in vaping-related products after VEA was found in lung fluid samples of patients with vaping-related lung illness (EVALI). Calling for regulatory control, Washington, Colorado and Ohio have already banned the use of VEA in e-juices at the state level.
The Advion Interchim Scientific expression® Compact Mass Spectrometer (CMS) with the Atmospheric Solids Analysis Probe (ASAP®) provides a highly sensitive screening method for the presence of VEA.
In this Lab Manager webinar, Dr. Daniel Eikel, Advion Director of Product Applications and Customer Service reviews the use of the Advion expression Compact Mass Spectrometer (CMS) for food and beverage analysis.
As an attendee, you will learn more about:
How leading technologies and techniques affect food science researchers
How to establish workflows that optimize the efficiency of your food science lab
New and novel applications in the field of food and beverage science
The discovery of chemical reactions is an inherently unpredictable and time-consuming process. An attractive alternative is to predict reactivity, although relevant approaches, such as computer-aided reaction design, are still in their infancy. Reaction prediction based on high-level quantum chemical methods is complex, even for simple molecules. Although machine learning is powerful for data analysis, its applications in chemistry are still being developed6. Inspired by strategies based on chemists’ intuition, we propose that a reaction system controlled by a machine learning algorithm may be able to explore the space of chemical reactions quickly, especially if trained by an expert. Here we present an organic synthesis robot that can perform chemical reactions and analysis faster than they can be performed manually, as well as predict the reactivity of possible reagent combinations after conducting a small number of experiments, thus effectively navigating chemical reaction space. By using machine learning for decision making, enabled by binary encoding of the chemical inputs, the reactions can be assessed in real time using nuclear magnetic resonance and infrared spectroscopy.
Constructive machine learning aims to create examples from its learned domain which are likely to exhibit similar properties. Here, a recurrent neural network was trained with the chemical structures of known cell‐migration modulators. This machine learning model was used to generate new molecules that mimic the training compounds. Two top‐scoring designs were synthesized, and tested for functional activity in a phenotypic spheroid cell migration assay. These computationally generated small molecules significantly increased the migration of medulloblastoma cells. The results further corroborate the applicability of constructive machine learning to the de novo design of druglike molecules with desired properties.
Analysis was performed by TLC/MS using the Advion expression Compact Mass Spectrometer (CMS) and Plate Express TLC Plate Reader.
USDA Cornell University, Federal University of Viçosa
Abstract
This study assessed and compared the effects of the intra-amniotic administration of various concentrations of soluble extracts from chia seed (Salvia hispanica L.) on the Fe and Zn status, brush border membrane functionality, intestinal morphology, and intestinal bacterial populations, in vivo. The hypothesis was that chia seed soluble extracts will affect the intestinal morphology, functionality and intestinal bacterial populations…This study demonstrated that the intra-amniotic administration of chia seed soluble extracts increased (p < 0.05) the villus surface area, villus length, villus width and the number of goblet cells. Further, we observed an increase (p < 0.05) in zinc transporter 1 (ZnT1) and duodenal cytochrome b (Dcytb) proteins gene expression. Our results suggest that the dietary consumption of chia seeds may improve intestinal health and functionality and may indirectly improve iron and zinc intestinal absorption.
Analysis was performed by LC/MS using the Advion expression Compact Mass Spectrometer (CMS).
Metal-based compounds have found utility in various fields such as clinical, energy, food safety and environmental to name a few. Creating the metal complex is the last step in a synthetic process, but it is critical to have the proper conditions for monitoring air-sensitive compounds to get the desire product and that side products are kept to a minimum to maximize yield.
In this application note, the inert atmospheric solid analysis probe (iASAP) and expression Compact Mass Spectrometer (CMS) was used to quickly sample and measure a modification of a published synthesis by Pfeiffer.
The research in this application note was presented at the 66th Annual Conference of the American Society of Mass Spectrometry (ASMS 2018)
Loughborough University, Translational Chemical Biology Research Group
Abstract
Compact mass spectrometry (CMS) is a versatile and transportable analytical instrument that has the potential to be used in clinical settings to quickly and non-invasively detect a wide range of relevant conditions from breath samples. The purpose of this study is to optimise data preprocessing protocols by three proposed methods of breath sampling, using the CMS. It also lays out a general framework for which data processing methods can be evaluated. Methods.This paper considers data from three previous studies, each using a different breath sampling method. These include a peppermint washout study using continuous breath sampling with a purified air source, an exercise study using continuous breath sampling with an ambient air source, and a single breath sampling study with an ambient air source. For each dataset, different breath selection (data preprocessing) methods were compared and benchmarked according to predictive performance on a validation set and quantitative reliability of m/z bin intensity measurements. Results. For both continuous methods, the best breath selection method improved the predictive model compared to no preselection, as measured by the 95% CI range for Youden’s index, from 0.68–0.86 to 0.86–0.97 for the exercise study and 0.69–0.82 to 1.00–1.00 for the peppermint study. The reliability of intensity measurements for both datasets (as measured by median relative standard deviation (RSD)), was improved slightly by the best selection method compared to no preselection, from 18% to 14% for the exercise study and 7%–5% for the peppermint study. For the single breath samples, all the models resulted in perfect prediction, with a 95% CI range for Youden’s index of 1.00–1.00. The reliability of the proposed method was 38%. Conclusion. The method of selecting exhaled breath from CMS data can affect the reliability of the measurement and the ability to distinguish between breath samples taken under different conditions. The application of appropriate data processing methods can improve the quality of the data and results obtained from CMS. The methods presented will enable untargeted analysis of breath VOCs using CMS to be performed.
Compact Mass Spectrometer (CMS).
Leiden University, Eindhoven University of Technology
Abstract
The structure of the copper complex of the 6-((1-butanethiol)oxy)-tris(2-pyridylmethyl)amine ligand (Cu-tmpa-O(CH2)4SH) anchored to a gold surface has been investigated. To enable covalent attachment of the complex to the gold surface, a heteromolecular self-assembled monolayer (SAM) of butanethiol and a thiol-substituted tmpa ligand was used…These results show that upon immobilization of Cu-tmpa-O(CH2)4SH, the resulting structure is not identical to the homogeneous CuII-tmpa complex. Upon anchoring, a novel CuI species is formed instead. This illustrates the importance of a thorough characterization of heterogenized molecular systems before drawing any conclusions regarding the structure–function relationships.
In this application note, the Advion expression® Compact Mass Spectrometer (CMS) coupled with the Advion AVANT™ UHPLC (LC/CMS) was used to measure the concentration of cannabinoids from commercially available CBD oils for a comparative test against the product labels.
The research in this application note was published in Cannabis Science & Technology Magazine May/June 2019 and presented at the 2019 Cannabis Science Conference East in Baltimore, MD.
Horbaczewskyj, Christopher Stefan (2019) Monitoring, Modelling and Optimisation of Continuous Flow Reactions Using On-line Mass Spectrometry. PhD thesis, University of Leeds.
Abstract
An on-line mass spectrometry method has been developed to monitor, model and optimise continuous flow reactions. This method makes use of dual-piston pumps, tubular reactor block, Vici sample actuator, an Advion expression Compact Mass Spectrometer (CMS) and other analytical systems to investigate a variety of chemical systems based on their need for process improvement. Full reaction automation employed MATLAB, the Snobfit algorithm, along with Modde DoE software. On-line mass spectrometry has advantages over other analytical techniques as it has shorter acquisition times (2-60 s), low chemical sensitivity (~108 mol%) and chemical identity as well as the potential to provide quantitative information. In this work, reaction quantitation has been explored using four chemical systems, where each of them was monitored by a variety of analytical techniques, with the overall aim being to examine if on-line mass spectrometry can be used for quantitative analysis. For all cases investigated, process improvements were made whilst also determining optimal operating conditions to improve conversions, yields or selectivities as well as looking at reaction waste reduction. Flow chemistry and the work conducted has shown how waste can be reduced for certain reactions when compared to more traditional approaches. This method relies on machine learning, full process automation and quick process analytical technology to determine optimum conditions as well as build large reaction data sets. Large data sets were created using a hybrid DoE-kinetic composite circumscribed orthogonal design. Mass spectrometry provided valuable reaction information and has the potential for reaction quantitation depending on the required application, reaction system and ionisation settings. Compound thermal stability can be problematic in APCI+ mode whilst ion suppression is problematic in ESI+ mode. Still a versatile analytical tool, on-line mass spectrometry was found to be inherently quantitative. The continuous-flow-on-line-MS-self-optimisation platform was used to investigate a variety of different reactions to show versatility of the MS system. These reactions are summarized below. 1) An N-Boc deprotection of AZD5634 for optimisation and process scale-up, with achieved conversions >95% and scale-up to pilot and commercial scale using on-line mass spectrometry). 2) An N-Boc deprotection reaction using a hybrid DoE-kinetic model for optimisation and large data set generation, with achieved conversion >90%. 3) An SNAr reaction of AZD4547 for product selectivity and yield improvement, with achieved conversion of ~38% and DP yield of ~30%. 4) The synthesis and optimisation of Fe-N-heterocyclic carbene complexes using an electrochemical method for use in a C-H hydroxylation reaction. Optimum electrochemical conditions of either 7 V and 4 minutes residence time, or 2.5 V and 15 minutes residence were achieved.
