Neuropathological heterogeneity in Alzheimer's disease:A study of 80 cases using principal components analysis

Three hypotheses have been proposed to explain neuropathological heterogeneity in Alzheimer's disease (AD): the presence of distinct subtypes ('subtype hypothesis'), variation in the stage of the disease ('phase hypothesis') and variation in the origin and progression of the disease ('compensation hypothesis'). To test these hypotheses, variation in the distribution and severity of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in 80 cases of AD using principal components analysis (PCA). Principal components analysis using the cases as variables (Q-type analysis) suggested that individual differences between patients were continuously distributed rather than the cases being clustered into distinct subtypes. In addition, PCA using the abundances of SP and NFT as variables (R-type analysis) suggested that variations in the presence and abundance of lesions in the frontal and occipital lobes, the cingulate gyrus and the posterior parahippocampal gyrus were the most important sources of heterogeneity consistent with the presence of different stages of the disease. In addition, in a subgroup of patients, individual differences were related to apolipoprotein E (ApoE) genotype, the presence and severity of SP in the frontal and occipital cortex being significantly increased in patients expressing apolipoprotein (Apo)E allele ε4. It was concluded that some of the neuropathological heterogeneity in our AD cases may be consistent with the 'phase hypothesis'. A major factor determining this variation in late-onset cases was ApoE genotype with accelerated rates of spread of the pathology in patients expressing allele ε4.

Is neuropathological heterogeneity in Alzheimer’s disease related to apolipoprotein genotype?

The abundance of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in cortical and subcortical regions from 30 patients with Alzheimer’s disease (AD) expressing different apolipoprotein E (apoE) genotypes. Principal components analysis (PCA) was used to identify the most important neuropathological variations between individual patients and to determine whether these variations were related to apoE genotype. The first two principal components (PC) accounted for 60% and 40% of the total variance of the SP and NFT data respectively. The abundance of SP in the frontal and occipital cortex and NFT in the frontal cortex, amygdala and substantia nigra were positively correlated with the first principal component (PC1). Analysis of the SP data revealed that the apoE score of the patient (the sum of the two alleles) was positively correlated with PC1 while analysis of the NFT data revealed no significant correlations between apoE score and the PC. The data suggest that apoE genotype was more closely related to variations in the distribution and abundance of SP than of NFT. In addition, a more rapid spread of SP into the frontal and occipital cortex may occur in patients with a high apoE score.

Neuropathological heterogeneity in frontotemporal lobar degeneration with TDP-43 proteinopathy: a quantitative study of 94 cases using principal components analysis

Studies suggest that frontotemporal lobar degeneration with transactive response (TAR) DNA-binding protein of 43kDa (TDP-43) proteinopathy (FTLD-TDP) is heterogeneous with division into four or five subtypes. To determine the degree of heterogeneity and the validity of the subtypes, we studied neuropathological variation within the frontal and temporal lobes of 94 cases of FTLD-TDP using quantitative estimates of density and principal components analysis (PCA). A PCA based on the density of TDP-43 immunoreactive neuronal cytoplasmic inclusions (NCI), oligodendroglial inclusions (GI), neuronal intranuclear inclusions (NII), and dystrophic neurites (DN), surviving neurons, enlarged neurons (EN), and vacuolation suggested that cases were not segregated into distinct subtypes. Variation in the density of the vacuoles was the greatest source of variation between cases. A PCA based on TDP-43 pathology alone suggested that cases of FTLD-TDP with progranulin (GRN) mutation segregated to some degree. The pathological phenotype of all four subtypes overlapped but subtypes 1 and 4 were the most distinctive. Cases with coexisting motor neuron disease (MND) or hippocampal sclerosis (HS) also appeared to segregate to some extent. We suggest: 1) pathological variation in FTLD-TDP is best described as a ‘continuum’ without clearly distinct subtypes, 2) vacuolation was the single greatest source of variation and reflects the ‘stage’ of the disease, and 3) within the FTLD-TDP ‘continuum’ cases with GRN mutation and with coexisting MND or HS may have a more distinctive pathology.

Productivity in China's high technology industry:regional heterogeneity and R&D

This paper analyzes the impact of Research and Development (R&D) on the productivity of China's high technology industry. In order to capture important differences in the effect of R&D on output that arise from geographic and socioeconomic differences across three major regions in China, we use a novel semiparametric approach that allows us to model heterogeneities across provinces and time. Using a unique provincial level panel dataset spanning the period 2000–2007, we find that the impact of R&D on output varies substantially in terms of magnitude and significance across different regions. Results show that the eastern region benefits the most from R&D investments, however it benefits the least from technical progress, while the western region benefits the least from R&D investments, but enjoys the highest benefits from technical progress. The central region benefits from R&D investments more than the western region and benefits from technical progress more than the eastern region. Our results suggest that R&D investments would significantly increase output in both the eastern and central regions, however technical progress in the central region may further compound the effects of R&D on output within the region.

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instance-level coreference links defined in third-party repositories as background knowledge for schema matching techniques. In our tests of this approach we obtained encouraging results, in particular, a substantial increase in recall in comparison with existing sets of coreference links.

Learning to be different:heterogeneity and efficiency in distributed smart camera networks

In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras. © 2013 IEEE.

A taxonomy of heterogeneity and dynamics in particle swarm optimisation

We propose a taxonomy for heterogeneity and dynamics of swarms in PSO, which separates the consideration of homogeneity and heterogeneity from the presence of adaptive and non-adaptive dynamics, both at the particle and swarm level. It thus supports research into the separate and combined contributions of each of these characteristics. An analysis of the literature shows that most recent work has focussed on only parts of the taxonomy. Our results agree with prior work that both heterogeneity and dynamics are useful. However while heterogeneity does typically improve PSO, this is often dominated by the improvement due to dynamics. Adaptive strategies used to generate heterogeneity may end up sacrificing the dynamics which provide the greatest performance increase. We evaluate exemplar strategies for each area of the taxonomy and conclude with recommendations.

Greater CD8+ TCR heterogeneity and functional flexibility in HIV-2 compared to HIV-1 infection

Virus-specific CD8+ T cells are known to play an important role in the control of HIV infection. In this study we investigated whether there may be qualitative differences in the CD8+ T cell response in HIV-1- and HIV-2-infected individuals that contribute to the relatively efficient control of the latter infection. A molecular comparison of global TCR heterogeneity showed a more oligoclonal pattern of CD8 cells in HIV-1- than HIV-2-infected patients. This was reflected in restricted and conserved TCR usage by CD8+ T cells recognizing individual HLA-A2- and HLA-B57-restricted viral epitopes in HIV-1, with limited plasticity in their response to amino acid substitutions within these epitopes. The more diverse TCR usage observed for HIV-2-specific CD8 T cells was associated with an enhanced potential for CD8+ expansion and IFN- production on cross-recognition of variant epitopes. Our data suggest a mechanism that could account for any possible cross-protection that may be mediated by HIV-2-specific CD8+ T cells against HIV-1 infection. Furthermore, they have implications for HIV vaccine development, demonstrating an association between a polyclonal, virus-specific CD8+ T cell response and an enhanced capacity to tolerate substitutions within T cell epitopes.

Static, dynamic, and adaptive heterogeneity in distributed smart camera networks

We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

It's good to be different:diversity, heterogeneity, and dynamics in collective systems

We identify two different forms of diversity present in engineered collective systems, namely heterogeneity (genotypic/phenotypic diversity) and dynamics (temporal diversity). Three qualitatively different case studies are analysed, and it is shown that both forms of diversity can be beneficial in very different problem and application domains. Behavioural diversity is shown to be motivated by input diversity and this observation is used to present recommendations for designers of collective systems.

Eco-efficiency considering the issue of heterogeneity among power plants

One of the main objectives in restructuring power industry is enhancing the efficiency of power facilities. However, power generation industry, which plays a key role in the power industry, has a noticeable share in emission amongst all other emission-generating sectors. In this study, we have developed some new Data Envelopment Analysis models to find efficient power plants based on less fuel consumption, combusting less polluting fuel types, and incorporating emission factors in order to measure the ecological efficiency trend. We then applied these models to measuring eco-efficiency during an eight-year period of power industry restructuring in Iran. Results reveal that there has been a significant improvement in eco-efficiency, cost efficiency and allocative efficiency of the power plants during the restructuring period. It is also shown that despite the hydro power plants look eco-efficient; the combined cycle ones have been more allocative efficient than the other power generation technologies used in Iran.

Dynamics of spatial heterogeneity in a landfill with interacting phase densities:a stochastic analysis

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear subprocesses that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction-diffusion based approach, focusing on the coupled interactions of four key variables - solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth-decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically "irrelevant" in this (large time) asymptotic limit. The other major implication of incorporation of stochasticity in the landfill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20-30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations.