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:Gene expression data was analyzed to map with urine proteomics data gene expression data from kidney biopsies from kidney transplant patients with and without acute rejection, chronic allograft nephropathy and BK virus nephritis was used to study gene expression changes during acute rejection, chronic allograft nephropathy and bk virus nephropathy. Samples labeled STA16, STA22, STA14, and STA18 were included in the CAN vs no-CAN analysis as no-CAN samples as they also qualified as non-CAN samples.
Project description:Current techniques to diagnose and/or monitor critically ill neonates with bronchopulmonary dysplasia (BPD) require invasive sampling of body fluids, which can affect the health status of these frail neonate. We tested our hypotheses 1) it is feasible to use early urine samples from extremely low gestational age newborns at risk for bronchopulmonary dysplasia for proteomics, and 2) urine proteomics can confirm previously identified proteins and biomarkers associated with BPD without invasive sample collection. We developed a robust high throughput urine proteomics methodology that requires only 50 microliters of urine. We validated the methodology on urine collected within 72 hours of birth. Urine samples were collected from extremely low gestational age newborns (ELGANS) (gestational age (26 + 1.2) weeks) admitted to a single Neonatal Intensive Care Unit(NICU); half of whom eventually developed BPD, while the other half served as controls. Our high throughput urine proteomics approach clearly identified several BPD-associated changes in the urine proteome recapitulating expected blood proteome changes. Interestingly, sixteen identified urinary proteins are known targets of drugs approved by the Food and Drug Administration (FDA). Urine proteomics can be used for prediction of BPD risk. In addition to identifying numerous proteins implicated in BPD pathophysiology, previously found in invasively collected blood, tracheal aspirate, and broncho-alveolar lavage, urine proteomics also suggested novel potential therapeutic targets. Ease of access to urine for sequential proteomic evaluations could also allow for longitudinal monitoring of disease progression and impact of therapeutic intervention.
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:MicroRNA (miRNA) biomarkers for fragile X syndrome were searched by urine microRNA (miRNA) profiling using deep sequencing. The urine miRNA profile of twin boys who shared the same environment but one had a FXS full mutation and the other carried a premutation allele was compared based on the similar sequence reads. The urine of twin boys showed 28 differentiatially regulated miRNAs when 219 reliable identified miRNAs were compared.
Project description:This study was designed to investigate to test the effect of exosomes from urine-derived mesenchymal stem cells (USCs) on the survival and viability of aging retinal ganglion cells (RGCs), and explored the preliminary related mechanisms. The sequencing outcomes demonstrated 117 upregulated genes and 186 downregulated genes in normal RGCs group vs aging RGCs group, 137 upregulated ones and 517 downregulated ones in aging RGCs group vs aging RGCs+USCs medium group. These DEGs involves in numerous positive molecular activities to promote the recovery of RGCs function.