Primary skin fibroblasts as a model of Parkinson's disease

Parkinson's disease is the second most frequent neurodegenerative disorder. While most cases occur sporadic mutations in a growing number of genes including Parkin (PARK2) and PINK1 (PARK6) have been associated with the disease. Different animal models and cell models like patient skin fibroblasts and recombinant cell lines can be used as model systems for Parkinson's disease. Skin fibroblasts present a system with defined mutations and the cumulative cellular damage of the patients. PINK1 and Parkin genes show relevant expression levels in human fibroblasts and since both genes participate in stress response pathways, we believe fibroblasts advantageous in order to assess, e.g. the effect of stressors. Furthermore, since a bioenergetic deficit underlies early stage Parkinson's disease, while atrophy underlies later stages, the use of primary cells seems preferable over the use of tumor cell lines. The new option to use fibroblast-derived induced pluripotent stem cells redifferentiated into dopaminergic neurons is an additional benefit. However, the use of fibroblast has also some drawbacks. We have investigated PARK6 fibroblasts and they mirror closely the respiratory alterations, the expression profiles, the mitochondrial dynamics pathology and the vulnerability to proteasomal stress that has been documented in other model systems. Fibroblasts from patients with PARK2, PARK6, idiopathic Parkinson's disease, Alzheimer's disease, and spinocerebellar ataxia type 2 demonstrated a distinct and unique mRNA expression pattern of key genes in neurodegeneration. Thus, primary skin fibroblasts are a useful Parkinson's disease model, able to serve as a complement to animal mutants, transformed cell lines and patient tissues

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer

Quantum Rings in Electromagnetic Fields

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordThis chapter is devoted to optical properties of so-called Aharonov-Bohm quantum rings (quantum rings pierced by a magnetic flux resulting in AharonovBohm oscillations of their electronic spectra) in external electromagnetic fields. It studies two problems. The first problem deals with a single-electron AharonovBohm quantum ring pierced by a magnetic flux and subjected to an in-plane (lateral) electric field. We predict magneto-oscillations of the ring electric dipole moment. These oscillations are accompanied by periodic changes in the selection rules for inter-level optical transitions in the ring allowing control of polarization properties of the associated terahertz radiation. The second problem treats a single-mode microcavity with an embedded Aharonov-Bohm quantum ring which is pierced by a magnetic flux and subjected to a lateral electric field. We show that external electric and magnetic fields provide additional means of control of the emission spectrum of the system. In particular, when the magnetic flux through the quantum ring is equal to a half-integer number of the magnetic flux quanta, a small change in the lateral electric field allows for tuning of the energy levels of the quantum ring into resonance with the microcavity mode, thus providing an efficient way to control the quantum ring-microcavity coupling strength. Emission spectra of the system are discussed for several combinations of the applied magnetic and electric fields

sFlt Multivalent Conjugates Inhibit Angiogenesis and Improve Half-Life In Vivo

We would like to thank Jonathan Winger and Xiao Zhu for guidance with the insect cell protein expression system and providing reagents. We would like to acknowledge Ann Fischer for help with expressing the sFlt protein in the Tissue Culture Facility at UC Berkeley and Dawn Spelke and Anusuya Ramasubramanian for help optimizing protein purification from insect cells. We are also grateful for the help from Leah Byrne and John Flannery at in the Helen Wills Neuroscience Institute at UC Berkeley for aiding us in the development of the rat intravitreal residence time model and for allowing us to use their facilities.Current anti-VEGF drugs for patients with diabetic retinopathy suffer from short residence time in the vitreous of the eye. In order to maintain biologically effective doses of drug for inhibiting retinal neovascularization, patients are required to receive regular monthly injections of drug, which often results in low patient compliance and progression of the disease. To improve the intravitreal residence time of anti-VEGF drugs, we have synthesized multivalent bioconjugates of an anti-VEGF protein, soluble fms-like tyrosine kinase-1 (sFlt) that is covalently grafted to chains of hyaluronic acid (HyA), conjugates that are termed mvsFlt. Using a mouse corneal angiogenesis assay, we demonstrate that covalent conjugation to HyA chains does not decrease the bioactivity of sFlt and that mvsFlt is equivalent to sFlt at inhibiting corneal angiogenesis. In a rat vitreous model, we observed that mvsFlt had significantly increased intravitreal residence time compared to the unconjugated sFlt after 2 days. The calculated intravitreal half-lives for sFlt and mvsFlt were 3.3 and 35 hours, respectively. Furthermore, we show that mvsFlt is more effective than the unconjugated form at inhibiting retinal neovascularization in an oxygen-induced retinopathy model, an effect that is most likely due to the longer half-life of mvsFlt in the vitreous. Taken together, our results indicate that conjugation of sFlt to HyA does not affect its affinity for VEGF and this conjugation significantly improves drug half-life. These in vivo results suggest that our strategy of multivalent conjugation could substantially improve upon drug half-life, and thus the efficacy of currently available drugs that are used in diseases such as diabetic retinopathy, thereby improving patient quality of life.Yeshttp://www.plosone.org/static/editorial#pee

Status and Trends of Physical Activity Surveillance, Policy, and Research in 164 Countries: Findings From the Global Observatory for Physical Activity—GoPA! 2015 and 2020 Surveys

Background: Physical activity (PA) surveillance, policy, and research efforts need to be periodically appraised to gain insight into national and global capacities for PA promotion. The aim of this paper was to assess the status and trends in PA surveillance, policy, and research in 164 countries. Methods: We used data from the Global Observatory for Physical Activity (GoPA!) 2015 and 2020 surveys. Comprehensive searches were performed for each country to determine the level of development of their PA surveillance, policy, and research, and the findings were verified by the GoPA! Country Contacts. Trends were analyzed based on the data available for both survey years. Results: The global 5-year progress in all 3 indicators was modest, with most countries either improving or staying at the same level. PA surveillance, policy, and research improved or remained at a high level in 48.1%, 40.6%, and 42.1% of the countries, respectively. PA surveillance, policy, and research scores decreased or remained at a low level in 8.3%, 15.8%, and 28.6% of the countries, respectively. The highest capacity for PA promotion was found in Europe, the lowest in Africa and low- and lower-middle-income countries. Although a large percentage of the world’s population benefit from at least some PA policy, surveillance, and research efforts in their countries, 49.6 million people are without PA surveillance, 629.4 million people are without PA policy, and 108.7 million live in countries without any PA research output. A total of 6.3 billion people or 88.2% of the world’s population live in countries where PA promotion capacity should be significantly improved. Conclusion: Despite PA is essential for health, there are large inequalities between countries and world regions in their capacity to promote PA. Coordinated efforts are needed to reduce the inequalities and improve the global capacity for PA promotion