Supernova explosions and the birth of neutron stars

We report here on recent progress in understanding the birth conditions of neutron stars and the way how supernovae explode. More sophisticated numerical models have led to the discovery of new phenomena in the supernova core, for example a generic hydrodynamic instability of the stagnant supernova shock against low-mode nonradial deformation and the excitation of gravity-wave activity in the surface and core of the nascent neutron star. Both can have supportive or decisive influence on the inauguration of the explosion, the former by improving the conditions for energy deposition by neutrino heating in the postshock gas, the latter by supplying the developing blast with a flux of acoustic power that adds to the energy transfer by neutrinos. While recent two-dimensional models suggest that the neutrino-driven mechanism may be viable for stars from about 8 solar masses to at least 15 solar masses, acoustic energy input has been advocated as an alternative if neutrino heating fails. Magnetohydrodynamic effects constitute another way to trigger explosions in connection with the collapse of sufficiently rapidly rotating stellar cores, perhaps linked to the birth of magnetars. The global explosion asymmetries seen in the recent simulations offer an explanation of even the highest measured kick velocities of young neutron stars.Comment: 10 pages, 8 figures, 19 ps files; to be published in Proc. of Conf. "40 Years of Pulsars: Millisecond Pulsars, Magnetars, and More", August 12-17, 2007, McGill Univ., Montreal, Canada; high-resolution images can be obtained upon request; incorrect panel in fig.8 replace

Reversible exposure of hydrophobic residues on albumin as a novel strategy for formulation of nanodelivery vehicles for taxanes

AG Garro1, DM Beltramo1,2,3, RV Alasino1, V Leonhard1,2, V Heredia1, ID Bianco1,2,41Center of Excellence in Products and Processes of Córdoba; 2National Research Council of Argentina (CONICET); 3School of Chemistry, Catholic University of Córdoba; 4Department of Exact, Physical and Natural Sciences, National University of La Rioja, ArgentinaBackground: We report herein a novel strategy for the preparation of protein-based nanodelivery vehicles for hydrophobic active pharmaceutical ingredients.Methods: The procedure consisted of three steps, ie, exposure of hydrophobic residues of a protein to a pH-induced partial unfolding: interaction between hydrophobic residues on the protein and the hydrophobic active pharmaceutical ingredient, and a final step where the structure of the protein was reversed to a native-like state by returning to neutral pH. As proof of concept, the interaction of paclitaxel with partially unfolded states of human serum albumin was evaluated as a potential method for the preparation of water-soluble complexes of the taxane with albumin.Results: We found that paclitaxel readily binds to pH-induced partially unfolded albumin, leading to the formation of optically clear water-soluble complexes. The complexes thus formed were more stable in solution when the albumin native state was at least partially restored by neutralization of the solution to a pH around 7. It was also observed that the hydrodynamic radius of human serum albumin was only slightly increased after the cycle of pH changes, remaining in a monomeric state with a size according to paclitaxel binding. Furthermore, paclitaxel binding did not affect the overall exposure of charged groups of human serum albumin, as evaluated by its interaction with an ionic exchange resin.Conclusion: The in vitro biological activity of the complexes formed was qualitatively equivalent to that of a Cremophor®-based formulation.Keywords: human serum albumin, paclitaxel, unfolded states, solubilit

Noise enhanced coupling between two oscillators with long-term plasticity

Spike time-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It induces structural changes of synaptic connectivity by regulation of coupling strengths between individual cells depending on their spiking behavior. As a biophysical process its functioning is constantly subjected to natural fluctuations. We study theoretically the influence of noise on a microscopic level by considering only two coupled neurons. Adopting a phase description for the neurons we derive a two-dimensional system which describes the averaged dynamics of the coupling strengths. We show that a multistability of several coupling configurations is possible, where some configurations are not found in systems without noise. Intriguingly, it is possible that a strong bidirectional coupling, which is not present in the noise-free situation, can be stabilized by the noise. This means that increased noise, which is normally expected to desynchronize the neurons, can be the reason for an antagonistic response of the system, which organizes itself into a state of stronger coupling and counteracts the impact of noise. This mechanism, as well as a high potential for multistability, is also demonstrated numerically for a coupled pair of Hodgkin-Huxley neurons

Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

Biogeochemical models, capturing the major feedbacks of the pelagic ecosystem of the world ocean, are today often embedded into Earth system models which are increasingly used for decision making regarding climate policies. These models contain poorly constrained parameters (e.g., maximum phytoplankton growth rate), which are typically adjusted until the model shows reasonable behavior. Systematic approaches determine these parameters by minimizing the misfit between the model and observational data. In most common model approaches, however, the underlying functions mimicking the biogeochemical processes are nonlinear and non-convex. Thus, systematic optimization algorithms are likely to get trapped in local minima and might lead to non-optimal results. To judge the quality of an obtained parameter estimate, we propose determining a preferably large lower bound for the global optimum that is relatively easy to obtain and that will help to assess the quality of an optimum, generated by an optimization algorithm. Due to the unavoidable noise component in all observations, such a lower bound is typically larger than zero. We suggest deriving such lower bounds based on typical properties of biogeochemical models (e.g., a limited number of extremes and a bounded time derivative). We illustrate the applicability of the method with two real-world examples. The first example uses real-world observations of the Baltic Sea in a box model setup. The second example considers a three-dimensional coupled ocean circulation model in combination with satellite chlorophyll a

The Cloud Strikes Back: Investigating the Decentralization of IPFS

Interplanetary Filesystem (IPFS) is one of the largest peer-to-peer filesystems in operation. The network is the default storage layer for Web3 and is being presented as a solution to the centralization of the web. In this paper, we present a large-scale, multi-modal measurement study of the IPFS network. We analyze the topology, the traffic, the content providers and the entry points from the classical Internet. Our measurements show significant centralization in the IPFS network and a high share of nodes hosted in the cloud. We also shed light on the main stakeholders in the ecosystem. We discuss key challenges that might disrupt continuing efforts to decentralize the Web and highlight multiple properties that are creating pressures toward centralization

Metal-Insulator Transition in a Disordered Two-Dimensional Electron Gas in GaAs-AlGaAs at zero Magnetic Field

A metal-insulator transition in two-dimensional electron gases at B=0 is found in Ga(Al)As heterostructures, where a high density of self-assembled InAs quantum dots is incorporated just 3 nm below the heterointerface. The transition occurs at resistances around h/e^2 and critical carrier densities of 1.2 10^11cm^-2. Effects of electron-electron interactions are expected to be rather weak in our samples, while disorder plays a crucial role.Comment: 4 pages, 3 figures, 21 reference

Dendritic Oligoglycerol Regioisomer Mixtures and Their Utility for Membrane Protein Research

Dendrons are an important class of macromolecules that can be used for a broad range of applications. Recent studies have indicated that mixtures of oligoglycerol detergent (OGD) regioisomers are superior to individual regioisomers for protein extraction. The origin of this phenomenon remains puzzling. Here we discuss the synthesis and characterization of dendritic oligoglycerol regioisomer mixtures and their implementation into detergents. We provide experimental benchmarks to support quality control after synthesis and investigate the unusual utility of OGD regioisomer mixtures for extracting large protein quantities from biological membranes. We anticipate that our findings will enable the development of mixed detergent platforms in the future

Higher-order thoughts in action : Consciousness as an unconscious re-description process

Peer reviewedPostprin

Rationalizing the Optimization of Detergents for Membrane Protein Purification

Membrane protein purification by means of detergents is key to isolating membrane-bound therapeutic targets. The role of the detergent structure in this process, however, is not well understood. Detergents are optimized empirically, leading to failed preparations, and thereby raising costs. Here we evaluate the utility of the hydrophilic-lipophilic balance (HLB) concept, which was introduced by Griffin in 1949, for guiding the optimization of the hydrophobic tail in first-generation, dendritic oligoglycerol detergents ([G1] OGDs). Our findings deliver qualitative HLB guidelines for rationalizing the optimization of detergents. Moreover, [G1] OGDs exhibit strongly delipidating properties, regardless of the structure of the hydrophobic tail, which delivers a methodological enabling step for investigating binding strengths of endogenous lipids and their role for membrane protein oligomerization. Our findings will facilitate the analysis of challenging drug targets in the future

Spatio-temporal dynamics of oscillatory brain activity during the observation of actions and interactions between point-light agents

Predicting actions from non-verbal cues and using them to optimise one's response behaviour (i.e. interpersonal predictive coding) is essential in everyday social interactions. We aimed to investigate the neural correlates of different cognitive processes evolving over time during interpersonal predictive coding. Thirty-nine participants watched two agents depicted by moving point-light stimuli while an electroencephalogram (EEG) was recorded. One well-recognizable agent performed either a 'communicative' or an 'individual' action. The second agent either was blended into a cluster of noise dots (i.e. present) or was entirely replaced by noise dots (i.e. absent), which participants had to differentiate. EEG amplitude and coherence analyses for theta, alpha and beta frequency bands revealed a dynamic pattern unfolding over time: Watching communicative actions was associated with enhanced coupling within medial anterior regions involved in social and mentalising processes and with dorsolateral prefrontal activation indicating a higher deployment of cognitive resources. Trying to detect the agent in the cluster of noise dots without having seen communicative cues was related to enhanced coupling in posterior regions for social perception and visual processing. Observing an expected outcome was modulated by motor system activation. Finally, when the agent was detected correctly, activation in posterior areas for visual processing of socially relevant features was increased. Taken together, our results demonstrate that it is crucial to consider the temporal dynamics of social interactions and of their neural correlates to better understand interpersonal predictive coding. This could lead to optimised treatment approaches for individuals with problems in social interactions