23 research outputs found
The long run relationship between private consumption and wealth : common and idiosyncratic effects
We investigate the long run relationship between private consump- tion, disposable income and wealth approximated by equity and house price indices for a panel of 15 industrialized countries. Consumption, income and wealth are cointegrated in their common components. The impact of house prices exceeds the effect arising from equity wealth. The long run vector is broadly in line with the life cycle permanent income hypothesis, if house prices are allowed to enter the relationship. At the idiosyncratic level, a long run equilibrium is detected between consumption and income, i.e. the wealth variable can be excluded. The income elasticity in the idiosyncratic relationship is significantly less than unity. Hence, the presence of wealth effects in consumption equations arises from the international integration of asset markets and points to the relevance of risk sharing activities of agents. Without sufficient opportunities, an increase in national saving rates would be expected, leading to a lower path of private consumption expenditures.info:eu-repo/semantics/publishedVersio
Mapping Exoplanets
The varied surfaces and atmospheres of planets make them interesting places
to live, explore, and study from afar. Unfortunately, the great distance to
exoplanets makes it impossible to resolve their disk with current or near-term
technology. It is still possible, however, to deduce spatial inhomogeneities in
exoplanets provided that different regions are visible at different
times---this can be due to rotation, orbital motion, and occultations by a
star, planet, or moon. Astronomers have so far constructed maps of thermal
emission and albedo for short period giant planets. These maps constrain
atmospheric dynamics and cloud patterns in exotic atmospheres. In the future,
exo-cartography could yield surface maps of terrestrial planets, hinting at the
geophysical and geochemical processes that shape them.Comment: Updated chapter for Handbook of Exoplanets, eds. Deeg & Belmonte. 17
pages, including 6 figures and 4 pages of reference
Modeling and Analysis of the Molecular Basis of Pain in Sensory Neurons
Intracellular calcium dynamics are critical to cellular functions like pain transmission. Extracellular ATP plays an important role in modulating intracellular calcium levels by interacting with the P2 family of surface receptors. In this study, we developed a mechanistic mathematical model of ATP-induced P2 mediated calcium signaling in archetype sensory neurons. The model architecture, which described 90 species connected by 162 interactions, was formulated by aggregating disparate molecular modules from literature. Unlike previous models, only mass action kinetics were used to describe the rate of molecular interactions. Thus, the majority of the 252 unknown model parameters were either association, dissociation or catalytic rate constants. Model parameters were estimated from nine independent data sets taken from multiple laboratories. The training data consisted of both dynamic and steady-state measurements. However, because of the complexity of the calcium network, we were unable to estimate unique model parameters. Instead, we estimated a family or ensemble of probable parameter sets using a multi-objective thermal ensemble method. Each member of the ensemble met an error criterion and was located along or near the optimal trade-off surface between the individual training data sets. The model quantitatively reproduced experimental measurements from dorsal root ganglion neurons as a function of extracellular ATP forcing. Hypothesized architecture linking phosphoinositide regulation with P2X receptor activity explained the inhibition of P2X-mediated current flow by activated metabotropic P2Y receptors. Sensitivity analysis using individual and the whole system outputs suggested which molecular subsystems were most important following P2 activation. Taken together, modeling and analysis of ATP-induced P2 mediated calcium signaling generated qualitative insight into the critical interactions controlling ATP induced calcium dynamics. Understanding these critical interactions may prove useful for the design of the next generation of molecular pain management strategies
What scans we will read: imaging instrumentation trends in clinical oncology
Oncological diseases account for a significant portion of the burden on public healthcare systems with associated
costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific
morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-
invasively, so as to provide referring oncologists with essential information to support therapy management
decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards
integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/
CT), advanced MRI, optical or ultrasound imaging.
This perspective paper highlights a number of key technological and methodological advances in imaging
instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as
the hardware-based combination of complementary anatomical and molecular imaging. These include novel
detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system
developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing
methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging
in oncology patient management we introduce imaging methods with well-defined clinical applications and
potential for clinical translation. For each modality, we report first on the status quo and point to perceived
technological and methodological advances in a subsequent status go section. Considering the breadth and
dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the
majority of them being imaging experts with a background in physics and engineering, believe imaging methods
will be in a few years from now.
Overall, methodological and technological medical imaging advances are geared towards increased image contrast,
the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall
examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is
complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To
this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis,
including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor
phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-
dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and
analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts
with a domain knowledge that will need to go beyond that of plain imaging