Can CE-MS be used for Antibody Quantitation in Biological Samples?

Approximately 80% of all cancers are known to be affected by both somatic mutations and copy number changes. Furthermore, recent publications have shown that in certain types of cancers, copy number variations (CNVs) play a more important role than somatic mutations.

COPAN Diagnostics is pleased to release presentations given at an event held during ASM Microbe 2023. During this popular live event guests learned about the benefits of using technology for improved laboratory results and faster turnaround times.

The presentation outlines a case study in establishing the operational space of a Grignard reaction in a series of continuous stirred tank reactors (CSTRs).

Food fraud is estimated to cost the world economy more than $49 billion per year. The 2013 horse meat scandal alone was reported to cost the UK economy more than £1 billion. The effects of food adulteration reach much further than just these serious economic consequences. The Chinese infant formula scandal, which led to multiple mortalities and hundreds of thousands of babies hospitalized, brought into focus the health implications of economically motivated adulteration. Therefore, stakeholders in the food industry should be stepping up to help eliminate this global problem, not only to protect company brand identity but also to safeguard the well-being of consumers. A key aim of the scientific community should be to arm these stakeholders with the appropriate tools to make economically motivated food adulteration a thing of the past. New approaches are needed to help tackle food adulteration. Traditional targeted methods are failing to keep up with the actions of fraudsters, who are numerous and are active at multiple points throughout the globalized supply chain. There is now a general movement toward non-targeted methodologies to detect food adulteration. Instead of looking for individual components or analytes, non-targeted methods work by taking a much more holistic approach. In many ways the aim is to model normality for a commodity, then look for differences present in a suspect sample that is outside of this normal. In this way, if a fraudster changes what they are using to adulterate with, the analyst will still be able to detect an anomaly.