Post-radiation xerostomia therapy with allogeneic mesenchymal stromal stem cells in patients with head and neck cancer: study protocol for phase I clinical trial.

Background: Xerostomia is a common side effect of radiotherapy in patients with head and neck tumors that negatively affects quality of life. There is no known effective standard treatment for xerostomia. Here, we present the study protocol used to evaluate the safety and preliminary efficacy of allogeneic mesenchymal stromal stem cells (MSCs) derived from umbilical cord tissue.

Substrate-dependent inactivation of recombinant paraoxonase 1 during catalytic dihydrocoumarin turnover and the protective properties of surfactants.

Human paraoxonase-1 (PON1) is the most studied member of the paraoxonases (PONs) family and catalyzes the hydrolysis of various substrates (lactones, aryl esters, and paraoxon). Numerous studies link PON1 to oxidative stress-related diseases such as cardiovascular disease, diabetes, HIV infection, autism, Parkinson's, and Alzheimer's, where the kinetic behavior of an enzyme is characterized by initial rates or by modern methods that obtain enzyme kinetic parameters by fitting the computed curves over the entire time-courses of product formation (progress curves). In the analysis of progress curves, the behavior of PON1 during hydrolytically catalyzed turnover cycles is unknown.

Investigation of Paraoxonase-1 Genotype and Enzyme-Kinetic Parameters in the Context of Cognitive Impairment in Parkinson's Disease.

Cognitive impairment is a common non-motor symptom of Parkinson's disease (PD), which often progresses to PD dementia. PD patients with and without dementia may differ in certain biochemical parameters, which could thus be used as biomarkers for PD dementia. The enzyme paraoxonase 1 (PON1) has previously been investigated as a potential biomarker in the context of other types of dementia.

Automated step detection with 6-minute walk test smartphone sensors signals for fall risk classification in lower limb amputees.

Predictive models for fall risk classification are valuable for early identification and intervention. However, lower limb amputees are often neglected in fall risk research despite having increased fall risk compared to age-matched able-bodied individuals. A random forest model was previously shown to be effective for fall risk classification of lower limb amputees, however manual labelling of foot strikes was required.

iFIT: An automated web tool for determining enzyme-kinetic parameters based on the high-curvature region of progress curves.

The area where progress curve exhibits maximum curvature contains the most information about kinetic parameters. To determine these parameters more accurately from progress curves, we propose an iterative approach that calculates the area of maximum curvature based on an estimate of kinetic parameters and then recalculates the parameters based on time-concentration data points within this area. Based on this algorithm, we developed a computer script called iFIT as a free web application at http://www.