A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.

This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

     

Iterative solution of large linear systems with non‐smooth submatrices using partial wavelet transforms and split‐matrix matrix–vector multiplication

The iterative solution of large linear systems with highly irregular matrices cannot be accelerated by wavelet transformation and subsequent sparsification if the transformed matrix is still highly irregular. In this paper we show that if the irregularity of the original matrix is limited to a relatively small known set of rows or columns (as is the case in significant applications), then acceleration can be achieved by a mixed approach in which only the ‘smooth’ submatrix is transformed and iterative solution is implemented using a novel ‘split‐matrix’ form of matrix–vector multiplication. Copyright © 2003 John Wiley & Sons, Ltd.     

Gender and Culture Differences in Emotion.

In this article, the authors report a secondary analysis on a cross-cultural dataset on gender differences in 6 emotions, collected in 37 countries all over the world. The aim was to test the universality of the gender-specific pattern found in studies with Western respondents, namely that men report more powerful emotions (e.g., anger), whereas women report more powerless emotions (e.g., sadness, fear). The authors expected the strength of these gender differences to depend on women's status and roles in their respective countries, as operationalized by the Gender Empowerment Measure (GEM; United Nations Development Programme Human Development Report 2002). Overall, the gender-specific pattern of women reporting to experience and express more powerless emotions and men more powerful emotions was replicated, and only some interactions with the GEM were found. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dopamine Antagonists Do Not Block Conditioned Place Preference Induced by Paced Mating Behavior in Female Rats.

The authors assessed the behavioral effects of dopamine (DA) receptor antagonists, Cis (Z) flupentixol and S(+)-raclopride L-tartrate, on conditioned place preference (CPP) induced by paced mating behavior. Ovariectomized female rats of the Wistar strain were used. The administration of amphetamine (1 ior. mg/kg) induced a clear CPP that was completely blocked by the DA antagonists flupentixol (0.25 mg/kg) or raclopride (0.125 mg/kg). These doses had no effect on motor coordination. Female rats that mated in a pacing chamber developed a clear CPP. Neither flupentixol nor raclopride blocked the reward state induced by paced mating behavior. These results indicate that DA is not involved in the reward state induced by paced mating behavior in female rats. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Periodicity in a class of non-autonomous scalar equations with deviating arguments and applications to population models

We offer sufficient and realistic criteria for the existence of positive periodic solutions for a class of non-autonomous scalar equations with deviating arguments. Both the continuous time case and the discrete time case are discussed. Our approach is based on the theory of coincidence degree and the related continuation theorem. To show the usefulness of the results obtained, we include applications to several famous population models.     

Sample size and power calculations based on generalized linear mixed models with correlated binary outcomes

The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effects. Using GLIMMIX based on these linearization methods, we derived formulas for power and sample size calculations for longitudinal designs with attrition over time. We found that the power and sample size estimates depend on the within-subject correlation and the size of random effects. In this article, we present tables of minimum sample sizes commonly used to test hypotheses for longitudinal studies. A simulation study was used to compare the results. We also provide a Web link to the SAS macro that we developed to compute power and sample sizes for correlated binary outcomes.     

Comparison of the distribution and degradation of plastic debris along shorelines of the Great Lakes,North America

The distribution patterns, compositions and textures of plastic debris along the Lake Erie and St. Clair shorelines were studied in order to determine the roles of potential source locations, surface currents, and shoreline types in the accumulation of plastic litter. The results were compared with those previously determined from Lake Huron, where abundant plastic pellets characterize the southeastern shoreline. Lake Erie and St. Clair shorelines contained some pellets, but were mainly characterized by plastic fragments and intact products, respectively. The potential sources for the pellets include spillage within factories or during transport and off-loading; whereas intact products were derived from urban waste. Once entering the lake environment, low density floating polymers such as polyethylene and polypropylene were degraded by UVB radiation at either the water surface or once deposited on shorelines. Mechanical degradation by wave action and/or sand abrasion fragmented intact products into cm-size particles. Certain textures identified on the surfaces of plastic particles could be related to the nature of the depositional environment. Plastics sampled from infrequently visited muddy, organic-rich shorelines were characterized by more adhering particles and less mechanical pits than those from sandy shorelines. In terms of relative distribution, the Lake St. Clair shoreline contained the least amount of plastic debris of the three lakes. This is a function of the breakwaters and retaining walls built along Lake St. Clair, which replace natural sandy or muddy sinks for floating polymers. This study represents the first detailed record of plastics distribution along multiple, but related fresh water shorelines.     

A restrictive polymorphic ant colony algorithm for the optimal band selection of hyperspectral remote sensing images

ABSTRACT

With hundreds of spectral bands, the rise of the issue of dimensionality in the classification of hyperspectral images is usually inevitable. In this paper, a restrictive polymorphic ant colony algorithm (RPACA) based band selection algorithm (RPACA-BS) was proposed to reduce the dimensionality of hyperspectral images. In the proposed algorithm, both local and global searches were conducted considering band similarity. Moreover, the problem of falling into local optima, due to the selection of similar band subsets although travelling different paths, was solved by varying the pheromone matrix between ants moving in opposite directions. The performance of the proposed RPACA-BS algorithm was evaluated using three public datasets (the Indian Pines, Pavia University and Botswana datasets) based on average overall classification accuracy (OA) and CPU processing time. The experimental results showed that average OA of RPACA-BS was up to 89.80%, 94.96% and 92.17% for the Indian Pines, Pavia University and Botswana dataset, respectively, which was higher than that of the benchmarks, including the ant colony algorithm-based band selection algorithm (ACA-BS), polymorphic ant colony algorithm-based band selection algorithm (PACA-BS) and other band selection methods (e.g. the ant lion optimizer-based band selection algorithm). Meanwhile, the time consumed by RPACA-BS and PACA-BS were slightly lower than that of ACA-BS but obviously lower than that of other benchmarks. The proposed RPACA-BS method is thus able to effectively enhance the search abilities and efficiencies of the ACA-BS and PACA-BS algorithms to handle the complex band selection issue for hyperspectral remotely sensed images.     

Combined Use of Local and Global Hydro Meteorological Data with Hydrological Models for Water Resources Management in the Magdalena - Cauca Macro Basin – Colombia

Water Resources Management - Reanalysis and earth observation data have enormous potential to support water resources management, particularly in river basins where data availability is poor or...     

Riparian vegetation restoration: Does social perception reflect ecological value?

Social‐ecological contexts are key to the success of ecological restoration projects. The ecological quality of restoration efforts, however, may not be fully evident to stakeholders, particularly if the desired aesthetic experience is not delivered. Aesthetically pleasing landscapes are more highly appreciated and tend to be better protected than less appealing landscapes, regardless of their ecological value. Positive public perception of restoration actions may therefore facilitate stakeholder involvement and catalyse recognition of ecological improvement. Here we aim to contrast aesthetical perception and ecological condition in headwater river reaches restored through passive ecological restoration in study areas in Portugal (Alentejo) and France (Normandy). We recorded structural and functional indicators of riparian vegetation to monitor the ecological condition of study sites along a passive restoration trajectory. Aesthetical perception indicators were assessed through stakeholder inquiries developed under a semantic differential approach. We analysed perception responses to changes in the riparian ecosystems resulting from passive ecological restoration across different geographical contexts and social groups. The analysed social groups comprised stakeholders (environmental managers and landowners) and university students (landscape architecture and geography students). Results indicate that (a) visual preferences often do not reflect changes in ecological condition, (b) perception of the restoration process is strongly context dependent, and (c) experience and cultural background affect perception of ecological condition across the different social groups analysed. Clear identification of relevant stakeholder groups (those interested in or directly affected by restoration), effective communication, and stakeholder engagement are therefore essential for assuring the success of river restoration projects.