Using metabolomics to study the different ways that people digest and process the food that they eat could help researchers to understand the mechanisms behind conditions such as diabetes and cardiovascular disease, say researchers from the Munich Functional Metabolomics Initiative.
Using metabolomics to study the different ways that people digest and process the food that they eat could help researchers to understand the mechanisms behind conditions such as diabetes and cardiovascular disease, say researchers from the Munich Functional Metabolomics Initiative. To do this researchers have begun a study called HuMet, which closely studied 15 metabolically healthy young men for four days. During this time the volunteers underwent four different nutritional interventions, along with physical exercise, while 56 blood plasma samples, 25 urine samples and 32 breath condensate and breath samples were taken. Aliquots of the collected samples were analysed using PTR-MS, LC-MS-MS, GC-MS, GCxGC-MS, FT-ICR-MS and NMR, to yield qualitative and quantitative information on around 400 metabolites.
"In general, all people react similarly to specific nutritional components," says Hannelore Daniel, professor of nutritional physiology, who worked on the study, "but there are big differences in their responses." Beginning with an empty stomach, subjects were given glucose, which caused their blood sugar levels to rise. "Obviously all values will rise", says Daniel. "The blood sugar level must go up. But it is very interesting to observe the differences in the way the levels rise and fall off again. It took four hours for the test subjects' blood sugar levels to come back into alignment with each other."
It is hoped that eventually the study of metabolomics will enable custom-tailored therapies for people with metabolic disorders and nutrition plans for people wanting to lose weight.
This story originally appeared in The Column. Click here to view that issue.
AI and GenAI Applications to Help Optimize Purification and Yield of Antibodies From Plasma
October 31st 2024Deriving antibodies from plasma products involves several steps, typically starting from the collection of plasma and ending with the purification of the desired antibodies. These are: plasma collection; plasma pooling; fractionation; antibody purification; concentration and formulation; quality control; and packaging and storage. This process results in a purified antibody product that can be used for therapeutic purposes, diagnostic tests, or research. Each step is critical to ensure the safety, efficacy, and quality of the final product. Applications of AI/GenAI in many of these steps can significantly help in the optimization of purification and yield of the desired antibodies. Some specific use-cases are: selecting and optimizing plasma units for optimized plasma pooling; GenAI solution for enterprise search on internal knowledge portal; analysing and optimizing production batch profitability, inventory, yields; monitoring production batch key performance indicators for outlier identification; monitoring production equipment to predict maintenance events; and reducing quality control laboratory testing turnaround time.