Paul Scherrer Institute

About: Paul Scherrer Institute is a facility organization based out in Villigen, Switzerland. It is known for research contribution in the topics: Neutron & Large Hadron Collider. The organization has 9248 authors who have published 23984 publications receiving 890129 citations. The organization is also known as: PSI.

T2 relaxation time in patients with Parkinson's disease

Abstract: Postmortem studies of patients with Parkinson's disease (PD) reveal an increase in iron concentration in the substantia nigra. Iron content in the brain is associated with decreased signal intensity on T2-weighted MRI. We measured in vivo the T2 relaxation time in 30 PD patients and 33 healthy volunteer subjects, using a 1.5-T whole-body MRI system. In comparison with healthy controls, T2 values in PD patients were reduced in the following brain regions: substantia nigra, caudate nucleus, and putamen. Due to the overlap between patients and control subjects, we could not differentiate, in a given patient, healthy from diseased state on the basis of T2 relaxation time. Our findings support the notion of increased iron deposition in the substantia nigra of patients with PD. However, the shortening of T2 values in the substantia nigra did not correlate with disease duration nor with clinical severity.

Direct observation of charge order in an epitaxial NdNiO3 film.

Abstract: The first direct observation of charge order of Ni(3+delta(')) and Ni(3-delta) by resonant x-ray scattering experiments in an epitaxial film of NdNiO3 is reported. A quantitative value of delta+delta(') = (0.45 +/- 0.04)e was obtained. The temperature dependence of the charge order deviates significantly from those of the magnetic moment and crystallographic structure. This might be an indication of a difference in their fluctuation time scales. These observations are discussed in terms of the temperature-driven metal-insulator transition in the RNiO3 family.

Structural determinants of growth factor binding and specificity by VEGF receptor 2

Abstract: Vascular endothelial growth factors (VEGFs) regulate blood and lymph vessel formation through activation of three receptor tyrosine kinases, VEGFR-1, -2, and -3. The extracellular domain of VEGF receptors consists of seven immunoglobulin homology domains, which, upon ligand binding, promote receptor dimerization. Dimerization initiates transmembrane signaling, which activates the intracellular tyrosine kinase domain of the receptor. VEGF-C stimulates lymphangiogenesis and contributes to pathological angiogenesis via VEGFR-3. However, proteolytically processed VEGF-C also stimulates VEGFR-2, the predominant transducer of signals required for physiological and pathological angiogenesis. Here we present the crystal structure of VEGF-C bound to the VEGFR-2 high-affinity-binding site, which consists of immunoglobulin homology domains D2 and D3. This structure reveals a symmetrical 2∶2 complex, in which left-handed twisted receptor domains wrap around the 2-fold axis of VEGF-C. In the VEGFs, receptor specificity is determined by an N-terminal alpha helix and three peptide loops. Our structure shows that two of these loops in VEGF-C bind to VEGFR-2 subdomains D2 and D3, while one interacts primarily with D3. Additionally, the N-terminal helix of VEGF-C interacts with D2, and the groove separating the two VEGF-C monomers binds to the D2/D3 linker. VEGF-C, unlike VEGF-A, does not bind VEGFR-1. We therefore created VEGFR-1/VEGFR-2 chimeric proteins to further study receptor specificity. This biochemical analysis, together with our structural data, defined VEGFR-2 residues critical for the binding of VEGF-A and VEGF-C. Our results provide significant insights into the structural features that determine the high affinity and specificity of VEGF/VEGFR interactions.

Vascular graph model to simulate the cerebral blood flow in realistic vascular networks

Abstract: At its most fundamental level, cerebral blood flow (CBF) may be modeled as fluid flow driven through a network of resistors by pressure gradients. The composition of the blood as well as the cross-sectional area and length of a vessel are the major determinants of its resistance to flow. Here, we introduce a vascular graph modeling framework based on these principles that can compute blood pressure, flow and scalar transport in realistic vascular networks. By embedding the network in a computational grid representative of brain tissue, the interaction between the two compartments can be captured in a truly three-dimensional manner and may be applied, among others, to simulate oxygen extraction from the vessels. Moreover, we have devised an upscaling algorithm that significantly reduces the computational expense and eliminates the need for detailed knowledge on the topology of the capillary bed. The vascular graph framework has been applied to investigate the effect of local vascular dilation and occlusion on the flow in the surrounding network.