University of Coimbra

About: University of Coimbra is a education organization based out in Coimbra, Portugal. It is known for research contribution in the topics: Population & Mitochondrion. The organization has 14318 authors who have published 43067 publications receiving 994733 citations. The organization is also known as: UC & Universidade dos Estudos Gerais.

Age-dependent responses of tree-ring growth and intra-annual density fluctuations of Pinus pinaster to Mediterranean climate

Abstract: Dendrochronology generally assumes that climate–growth relationships are age independent once the biological growth trend has been removed. However, tree physiology, namely, photosynthetic capacity and hydraulic conductivity changes with age. We tested whether the radial-growth response to climate and the intra-annual density fluctuations (IADFs) of Pinus pinaster Ait. varied with age. Trees were sampled in Pinhal de Leiria (Portugal), and were divided in two age classes: young ( 115 years old). Earlywood and tree-ring width of young P. pinaster trees were more sensitive to climate influence while the response of latewood width to climate was stronger in old trees. Young trees start the growing season earlier, thus a time window delay occurs between young and old trees during which wood cells of young trees integrate environmental signals. Young trees usually have a longer growing season and respond faster to climate conditions, thus young P. pinaster trees presented a higher frequency of IADFs compared with old trees. Most of the IADFs were located in latewood and were positively correlated to autumn precipitation. The radial-growth response of P. pinaster to climate and the IADFs frequency were age dependent. The use of trees with different age to create a tree-ring chronology for climate studies can increase the resolution of climatic signals. Age-dependent responses to climate can also give important clues to predict how young and old trees react to climate change.

Activation of microglial cells triggers a release of brain-derived neurotrophic factor (BDNF) inducing their proliferation in an adenosine A2A receptor-dependent manner: A2A receptor blockade prevents BDNF release and proliferation of microglia

Abstract: Brain-derived neurotrophic factor (BDNF) has been shown to control microglial responses in neuropathic pain. Since adenosine A2A receptors (A2ARs) control neuroinflammation, as well as the production and function of BDNF, we tested to see if A2AR controls the microglia-dependent secretion of BDNF and the proliferation of microglial cells, a crucial event in neuroinflammation. Murine N9 microglial cells were challenged with lipopolysaccharide (LPS, 100 ng/mL) in the absence or in the presence of the A2AR antagonist, SCH58261 (50 nM), as well as other modulators of A2AR signaling. The BDNF cellular content and secretion were quantified by Western blotting and ELISA, A2AR density was probed by Western blotting and immunocytochemistry and cell proliferation was assessed by BrdU incorporation. Additionally, the A2AR modulation of LPS-driven cell proliferation was also tested in primary cultures of mouse microglia. LPS induced time-dependent changes of the intra- and extracellular levels of BDNF and increased microglial proliferation. The maximal LPS-induced BDNF release was time-coincident with an LPS-induced increase of the A2AR density. Notably, removing endogenous extracellular adenosine or blocking A2AR prevented the LPS-mediated increase of both BDNF secretion and proliferation, as well as exogenous BDNF-induced proliferation. We conclude that A2AR activation plays a mandatory role controlling the release of BDNF from activated microglia, as well as the autocrine/paracrine proliferative role of BDNF.

Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

Abstract: Due to the dynamic nature of vehicular traffic and the road surroundings, vehicle-to-vehicle (V2V) propagation characteristics vary greatly on both small and large scale. Recent measurements have shown that both large static objects (e.g., buildings and foliage) and mobile objects (surrounding vehicles) have a profound impact on V2V communication. At the same time, system-level vehicular ad hoc network (VANET) simulators by and large employ simple statistical propagation models, which do not account for surrounding objects explicitly. We designed Geometry-based Efficient propagation Model for V2V communication (GEMV 2 ), which uses outlines of vehicles, buildings, and foliage to distinguish the following three types of links: line of sight (LOS), non-LOS (NLOS) due to vehicles, and NLOS due to static objects. For each link, GEMV 2 calculates the large-scale signal variations deterministically, whereas the small-scale signal variations are calculated stochastically based on the number and size of surrounding objects. We implement GEMV 2 in MATLAB and show that it scales well by using it to simulate radio propagation for city-wide networks with tens of thousands of vehicles on commodity hardware. We make the source code of GEMV 2 freely available. Finally, we validate GEMV 2 against extensive measurements performed in urban, suburban, highway, and open-space environments.