Project description:Raw data for our manuscript in prep, titled: "Real time health monitoring through urine analysis: A preliminary observational study."
Project description:Current healthcare practices are reactive and based on limited physiological information collected months or years apart. By enabling patients and healthy consumers access to continuous measurements of health, wearable devices and digital medicine stand to realize highly personalized and preventative care. However, most current digital technologies provide information on a limited set of physiological traits, such as heart rate and step count, which alone offer little insight into the etiology of most diseases. Here we propose to integrate data from biohealth smartphone applications with continuous metabolic phenotypes derived from urine metabolites. This combination of molecular phenotypes with quantitative measurements of lifestyle reflect the biological consequences of human behavior in real time. We present data from an observational study involving two healthy subjects and discuss the challenges, opportunities, and implications of integrating this new layer of physiological information into digital medicine. Though our dataset is limited to two subjects, our analysis (also available through an interactive web-based visualization tool) provides an initial framework to monitor lifestyle factors, such as nutrition, drug metabolism, exercise, and sleep using urine metabolites.
Project description:This trial tests new methods and materials for the real-time chemotherapy-associated side effects monitoring support system (RT-CAMSS) in patients with gastrointestinal cancers undergoing chemotherapy. RT-CAMSS is a monitoring support system that provides patients with evidence-based information and side-effect management and coping skills, emotional support and validation, and proactive care via text messages and questionnaires as they undergo chemotherapy.
Project description:Treatment of MCF7 breast cancer cells by cisplatin leads to a very specific metabolic response and an onset of cell death about 10-11 h after beginning of treatment. For more detailed understanding of the molecular processes underlying the specific metabolic response, mRNA was isolated from MCF7 cells when the specific changes, (i) induction of glycolysis and (ii) onset of cell death, were detected during online measurement in the cell biosensor system.
Project description:While it is well known that cell-free RNA (cfRNA) can be isolated from urine, the diagnostic potential of this urine cfRNA, especially in comparison to plasma cfRNA, remains underexplored. Here, we directly compared the utility of urine cfRNA and plasma cfRNA for the monitoring of systemic and urinary tract related complications. We analyzed 272 matched plasma and urine cfRNA isolates obtained from three cohorts of patients: Hematopoietic Stem Cell Transplant (HSCT) recipients, patients with acute kidney injury (AKI), and healthy volunteers. The data highlight the unique cellular origins and properties of urinary and plasma RNA. Most importantly, we find that although plasma cfRNA is a superior analyte for monitoring immune and systemic complications, urinary cfRNA is more sensitive to complications of the urinary tract, including cell-type specific injury in the kidney. These findings highlight the potential of urine cfRNA as a novel analyte in diagnostic medicine.
Project description:Treatment of MCF7 breast cancer cells by cisplatin leads to a very specific metabolic response and an onset of cell death about 10-11 h after beginning of treatment. For more detailed understanding of the molecular processes underlying the specific metabolic response, mRNA was isolated from MCF7 cells when the specific changes, (i) induction of glycolysis and (ii) onset of cell death, were detected during online measurement in the cell biosensor system. MCF7 breast cancer cells were treated with cisplatin in the BIONAS 2500 cell biosensor chip system, and samples were collected from the biosensor chip module at time points when glycolysis was induced (change of ph; 8-9h) and at the beginning of cell death (change of impedance; 10-11h).
Project description:Communities worldwide have used vaccines and facemasks to mitigate the COVID-19 pandemic. When an individual opts to vaccinate or wear a mask, they may lower their own risk of becoming infected as well as the risk that they pose to others while infected. The first benefit-reducing susceptibility-has been established across multiple studies, while the second-reducing infectivity-is less well understood. Using a new statistical method, we estimate the efficacy of vaccines and facemasks at reducing both types of risks from contact tracing data collected in an urban setting. We find that vaccination reduced the risk of onward transmission by 40.7% [95% CI 25.8-53.2%] during the Delta wave and 31.0% [95% CI 19.4-40.9%] during the Omicron wave and that mask wearing reduced the risk of infection by 64.2% [95% CI 5.8-77.3%] during the Omicron wave. By harnessing commonly-collected contact tracing data, the approach can broadly provide timely and actionable estimates of intervention efficacy against a rapidly evolving pathogen.
Project description:Fermentation monitoring is a powerful tool for bioprocess development and optimisation. On-line metabolomics is a technology that is starting to gain attention as a bioprocess monitoring tool, allowing the direct measurement of many compounds in the fermentation broth at a very high time resolution. In this work, targeted on-line metabolomics was used to monitor 40 metabolites of interest during three Escherichia coli succinate production fermentation experiments every 5 minutes with a triple quadrupole mass spectrometer. This allowed capturing high time resolution biological data that can provide critical information for process optimisation. For 9 of these metabolites, simple univariate regression models were used to model compound concentration from their on-line mass spectrometry peak area. These on-line metabolomics univariate models performed comparably to vibrational spectroscopy multivariate PLS regressions models reported in the literature, which typically are much more complex and time consuming to build. In conclusion, this work shows how on-line metabolomics can be used to directly monitor many bioprocess compounds of interest and obtain rich biological and bioprocess data.