The Global Exportation of the U.S. Bayh-Dole Act

Special issue: Intellectual Property and Technolog

Modeling the drug release from hydrogel-based matrices

In this work the behavior of hydrogel-based matrices, the most widespread systems for oral controlled release of pharmaceuticals, has been mathematically described. In addition, the calculations of the model have been validated against a rich set of experimental data obtained working with tablets made of hydroxypropyl methylcellulose (a hydrogel) and theophylline (a model drug). The model takes into account water uptake, hydrogel swelling, drug release, and polymer erosion. The model was obtained as an improvement of a previous code, describing the diffusion in concentrated systems, and obtaining the erosion front (which is a moving boundary) from the polymer mass balance (in this way, the number of fitting parameters was also reduced by one). The proposed model was found able to describe all the observed phenomena, and then it can be considered a tool with predictive capabilities, useful in design and testing of new dosage systems based on hydrogels

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

A machine learning (ML) methodology that uses a histogram of interaction energies has been applied to predict gas adsorption in metal–organic frameworks (MOFs) using results from atomistic grand canonical Monte Carlo (GCMC) simulations as training and test data. In this work, the method is first extended to binary mixtures of spherical species, in particular, Xe and Kr. In addition, it is shown that single-component adsorption of ethane and propane can be predicted in good agreement with GCMC simulation using a histogram of the adsorption energies felt by a methyl probe in conjunction with the random forest ML method. The results for propane can be improved by including a small number of MOF textural properties as descriptors. We also discuss the most significant features, which provides physical insight into the most beneficial adsorption energy sites for a given application

Protocol for a Multicenter Study

Background: In Parkinson’s disease (PD), alpha-synuclein accumulation in cutaneous autonomic pilomotor and sudomotor nerve fibers has been linked to autonomic nervous system disturbances even in the early stages of the disease. This study aims to assess the association between alpha-synuclein-mediated structural autonomic nerve fiber damage and function in PD, elucidate the role of neuropathy progression during the early disease stages, and test reproducibility and external validity of pilomotor function assessment using quantitative pilomotor axon-reflex test and sudomotor function via quantitative direct and indirect test of sudomotor function. Methods/design: A prospective controlled study will be conducted at four study sites in Europe and the USA. Fifty-two male and female patients with idiopathic PD (Hoehn and Yahr 1–2) and 52 age- and sex-matched healthy controls will be recruited. Axon-reflex-mediated pilomotor erection will be induced by iontophoresis of phenylephrine on the dorsal forearm. Silicone impressions of the response will be obtained, scanned, and quantified for pilomotor muscle impressions by number, impression size, and area of axon-reflex spread. Axon-reflex-mediated sweating following acetylcholine iontophoresis will be quantified for number and size of droplets and axon-reflex spread. Sympathetic skin responses, autonomic and motor symptoms will be evaluated. Tests will be performed at baseline, after 2 weeks, 1, 2, and 3 years. Skin biopsies will be obtained at baseline and after 3 years and will be analyzed for nerve fiber density and alpha-synuclein accumulation. Discussion: We anticipate that progression of autonomic nerve dysfunction assessed via pilomotor and sudomotor axon-reflex tests is related to progression of autonomic symptom severity and alpha- synuclein deposition. Potential applications of the techniques include interventional studies evaluating disease-modifying approaches and clinical assessment of autonomic dysfunction in patients with PD. Clinical trail registration: TRN NCT03043768