Relationships between beta-amyloid (Abeta) deposits and blood vessels in familial and sporadic Alzheimer's disease

Introduction: The density of diffuse, primitive and classic beta-amyloid (Abeta) deposits and blood vessels was studied in nine cases of sporadic Alzheimer's disease (SAD) and 10 cases of familial Alzheimer's disease (FAD) including two cases with amyloid precursor protein (APP) mutations (APP717, Val - Ile). Materials and Methods: Sections of frontal cortex stained for Abeta12-28 counterstained with collagen type IV antiserum. Densities measured along the upper cortex in 64-128, 1000 x 200 micron continuous sample fields. Results: The density of diffuse and primitive deposits was not correlated with blood vessels in FAD or SAD. The density of the classic deposits was positively correlated with the larger diameter (> 10 micron) blood vessels in all SAD cases and weakly correlated with blood vessel in three non-APP FAD cases. Conclusions: Blood vessels are less important in the formation of classic Abeta deposits in FAD compared with SAD.

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.

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

This paper presents a predictive aggregation rate model for spray fluidized bed melt granulation. The aggregation rate constant was derived from probability analysis of particle–droplet contact combined with time scale analysis of droplet solidification and granule–granule collision rates. The latter was obtained using the principles of kinetic theory of granular flow (KTGF). The predicted aggregation rate constants were validated by comparison with reported experimental data for a range of binder spray rate, binder droplet size and operating granulator temperature. The developed model is particularly useful for predicting particle size distributions and growth using population balance equations (PBEs).

Familial and disease specific abnormalities in the neural correlates of the Stroop Task in Bipolar Disorder

Patients with Bipolar Disorder (BD) perform poorly on tasks of selective attention and inhibitory control. Although similar behavioural deficits have been noted in their relatives, it is yet unclear whether they reflect dysfunction in the same neural circuits. We used functional magnetic resonance imaging and the Stroop Colour Word Task to compare task related neural activity between 39 euthymic BD patients, 39 of their first-degree relatives (25 with no Axis I disorders and 14 with Major Depressive Disorder) and 48 healthy controls. Compared to controls, all individuals with familial predisposition to BD, irrespective of diagnosis, showed similar reductions in neural responsiveness in regions involved in selective attention within the posterior and inferior parietal lobules. In contrast, hypoactivation within fronto-striatal regions, implicated in inhibitory control, was observed only in BD patients and MDD relatives. Although striatal deficits were comparable between BD patients and their MDD relatives, right ventrolateral prefrontal dysfunction was uniquely associated with BD. Our findings suggest that while reduced parietal engagement relates to genetic risk, fronto-striatal dysfunction reflects processes underpinning disease expression for mood disorders. © 2011 Elsevier Inc.

Parametric aggregation in ordered weighted averaging

Incorporating further information into the ordered weighted averaging (OWA) operator weights is investigated in this paper. We first prove that for a constant orness the minimax disparity model [13] has unique optimal solution while the modified minimax disparity model [16] has alternative optimal OWA weights. Multiple optimal solutions in modified minimax disparity model provide us opportunity to define a parametric aggregation OWA which gives flexibility to decision makers in the process of aggregation and selecting the best alternative. Finally, the usefulness of the proposed parametric aggregation method is illustrated with an application in metasearch engine. © 2011 Elsevier Inc. All rights reserved.

Aggregation and caking processes of granular materials:continuum model and simulation with application to sugar

Aggregation and caking of particles are common severe problems in many operations and processing of granular materials, where granulated sugar is an important example. Prevention of aggregation and caking of granular materials requires a good understanding of moisture migration and caking mechanisms. In this paper, the modeling of solid bridge formation between particles is introduced, based on moisture migration of atmospheric moisture into containers packed with granular materials through vapor evaporation and condensation. A model for the caking process is then developed, based on the growth of liquid bridges (during condensation), and their hardening and subsequent creation of solid bridges (during evaporation). The predicted caking strengths agree well with some available experimental data on granulated sugar under storage conditions.

Almost Separable Data Aggregation by Layers of Formal Neurons

Information extraction or knowledge discovery from large data sets should be linked to data aggregation process. Data aggregation process can result in a new data representation with decreased number of objects of a given set. A deterministic approach to separable data aggregation means a lesser number of objects without mixing of objects from different categories. A statistical approach is less restrictive and allows for almost separable data aggregation with a low level of mixing of objects from different categories. Layers of formal neurons can be designed for the purpose of data aggregation both in the case of deterministic and statistical approach. The proposed designing method is based on minimization of the of the convex and piecewise linear (CPL) criterion functions.

Laminar distribution of β-amyloid (Aβ) peptide deposits in the frontal lobe in familial and sporadic Alzheimer's disease

To determine whether genetic factors influence frontal lobe degeneration in Alzheimer's disease (AD), the laminar distributions of diffuse, primitive, and classic β-amyloid (Aβ) peptide deposits were compared in early-onset familial AD (EO-FAD) linked to mutations of the amyloid precursor protein (APP) or presenilin 1 (PSEN1) gene, late-onset familial AD (LO-FAD), and sporadic AD (SAD). The influence of apolipoprotein E (Apo E) genotype on laminar distribution was also studied. In the majority of FAD and SAD cases, maximum density of the diffuse and primitive Aβ deposits occurred in the upper cortical layers, whereas the distribution of the classic Aβ deposits was more variable, either occurring in the lower layers, or a double-peaked (bimodal) distribution was present, density peaks occurring in upper and lower layers. The cortical layer at which maximum density of Aβ deposits occurred and maximum density were similar in EO-FAD, LO-FAD and SAD. In addition, there were no significant differences in distributions in cases expressing Apo E ε4 alleles compared with cases expressing the ε2 or ε3 alleles. These results suggest that gene expression had relatively little effect on the laminar distribution of Aβ deposits in the frontal lobe of the AD cases studied. Hence, the pattern of frontal lobe degeneration in AD is similar regardless of whether it is associated with APP and PSEN1, mutation, allelic variation in Apo E, or with SAD.

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

A comparison of spatial patterns of TDP-43 cellular inclusions in familial and sporadic frontotemporal lobar degeneration with TDP-43 proteinopathy

Abnormal protein aggregates of transactive response (TAR) DNA-binding protein (TDP-43) in the form of neuronal cytoplasmic inclusions (NCI), oligodendroglial inclusions (GI), neuronal internuclear inclusions (NII), and dystrophic neurites (DN) are the pathological hallmark of frontotemporal lobar degeneration with TDP-43 proteinopathy (FTLD-TDP). To investigate the role of phosphorylated TDP-43 (pTDP-43) in neurodegeneration in FTLD-TDP, the spatial patterns of the pTDP-43-immunoreactive NCI, GI, NII, and DN were studied in frontal and temporal cortex in three groups of cases: (1) familial FTLD-TDP caused by progranulin (GRN) mutation, (2) a miscellaneous group of familial cases containing cases caused by valosin-containing protein (VCP) mutation, ubiquitin associated protein 1 (UBAP1) mutation, and cases not associated with currently known genes, and (3) sporadic FTLD-TDP. In a significant number of brain regions, the pTDP-43-immunoreactive inclusions developed in clusters and the clusters were distributed regularly parallel to the tissue boundary. The spatial patterns of the inclusions were similar to those revealed by a phosphorylation-independent anti-TDP-43 antibody. The spatial patterns and cluster sizes of the pTDP-43-immunoreactive inclusions were similar in GRN mutation cases, remaining familial cases, and in sporadic FTLD-TDP. Hence, pathological changes initiated by different genetic factors in familial cases and by unknown causes in sporadic FTLD-TDP appear to follow a parallel course resulting in very similar patterns of degeneration of frontal and temporal lobes.

Familial adrenal hypoplasia syndromes

The adrenal cortex secretes steroid hormones, including glucocorticoids and mineralocorticoids. Glucocorticoids control body homeostasis, stress, and immune responses, while mineralocorticoids regulate the water and electrolyte balance. A spectrum of genetic defects can disrupt the normal adrenal development, causing adrenal hypoplasia and various forms of adrenal insufficiency, which usually present in infancy or childhood with or without mineralocorticoid deficiency and with or without gonadal dysfunction. The genetic causes of adrenal hypoplasia can be broadly categorized into adrenal hypoplasia due to adrenocorticotropic hormone resistance syndromes (i.e., familial glucocorticoid deficiency and triple A syndrome) and adrenal hypoplasia due to primary defects in the development of the adrenal glands (i.e., X-linked adrenal hypoplasia congenita and primary adrenal hypoplasia caused by steroidogenic factor 1 mutations).

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.

Additive and multiplicative properties of scoring methods for preference aggregation

The paper reviews some additive and multiplicative properties of ranking procedures used for generalized tournaments with missing values and multiple comparisons. The methods analysed are the score, generalised row sum and least squares as well as fair bets and its variants. It is argued that generalised row sum should be applied not with a fixed parameter, but a variable one proportional to the number of known comparisons. It is shown that a natural additive property has strong links to independence of irrelevant matches, an axiom judged unfavourable when players have different opponents.