Gold nanoparticles decorated with oligo(ethylene glycol) thiols:kinetics of colloid aggregation driven by depletion forces

We have studied the kinetics of the phase-separation process of mixtures of colloid and protein in solutions by real-time UV-vis spectroscopy. Complementary small-angle X-ray scattering (SAXS) was employed to determine the structures involved. The colloids used are gold nanoparticles functionalized with protein resistant oligo(ethylene glycol) (OEG) thiol, HS(CH(2))(11)(OCH(2)CH(2))(6)OMe (EG6OMe). After mixing with protein solution above a critical concentration, c*, SAXS measurements show that a scattering maximum appears after a short induction time at q = 0.0322 angstrom(-1) stop, which increases its intensity with time but the peak position does not change with time, protein concentration and salt addition. The peak corresponds to the distance of the nearest neighbor in the aggregates. The upturn of scattering intensities in the low q-range developed with time indicating the formation of aggregates. No Bragg peaks corresponding to the formation of colloidal crystallites could be observed before the clusters dropped out from the solution. The growth kinetics of aggregates is followed in detail by real-time UV-vis spectroscopy, using the flocculation parameter defined as the integral of the absorption in the range of 600-800 nm wavelengths. At low salt addition (<0.5 M), a kinetic crossover from reaction-limited cluster aggregation (RLCA) to diffusion-limited cluster aggregation (DLCA) growth model is observed, and interpreted as being due to the effective repulsive interaction barrier between colloids within the depletion potential. Above 0.5 M NaCl, the surface charge of proteins is screened significantly, and the repulsive potential barrier disappeared, thus the growth kinetics can be described by a DLCA model only.

Classic beta-amyloid deposits cluster around large diameter blood vessels rather than capillaries in sporadic Alzheimer's disease

Various hypotheses could explain the relationship between beta-amyloid (Abeta) deposition and the vasculature in Alzheimer's disease (AD). Amyloid deposition may reduce capillary density, affect endothelial cells of blood vessels, result in diffusion from blood vessels, or interfere with the perivascular clearance mechanism. Hence, the spatial pattern of the classic ('cored') type of Abeta deposit was studied in the upper laminae (I,II/III) of the superior frontal gyrus in nine cases of sporadic AD (SAD). Sections were immunostained with antibodies against Abeta and with collagen IV to study the relationships between the spatial distribution of the classic deposits and the blood vessel profiles. Both the classic deposits and blood vessel profiles were distributed in clusters. In all cases, there was a positive spatial correlation between the clusters of the classic deposits and the larger diameter (>10 microm) blood vessel profiles and especially the vertically penetrating arterioles. In only 1 case, was there a significant spatial correlation between the clusters of the classic deposits and the smaller diameter (<10 microm) capillaries. There were no negative correlations between the density of Abeta deposits and the smaller diameter capillaries. In 9/11 cases, the clusters of the classic deposits were significantly larger than those of the clusters of the larger blood vessel profiles. In addition, the density of the classic deposits declined as a negative exponential function with distance from a vertically penetrating arteriole. These results suggest that the classic Abeta deposits cluster around the larger blood vessels in the upper laminae of the frontal cortex. This aggregation could result from diffusion of proteins from blood vessels or from overloading the system of perivascular clearance from the brain.

A statistical method for the identification and aggregation of regional linguistic variation

This paper introduces a method for the analysis of regional linguistic variation. The method identifies individual and common patterns of spatial clustering in a set of linguistic variables measured over a set of locations based on a combination of three statistical techniques: spatial autocorrelation, factor analysis, and cluster analysis. To demonstrate how to apply this method, it is used to analyze regional variation in the values of 40 continuously measured, high-frequency lexical alternation variables in a 26-million-word corpus of letters to the editor representing 206 cities from across the United States.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.