What is the Role of the Bystander Response in Radionuclide Therapies?

Radionuclide therapy for cancer is undergoing a renaissance, with a wide range of radionuclide and clinical delivery systems currently under investigation. Dosimetry at the cellular and sub-cellular level is complex with inhomogeneity and incomplete targeting of all cells such that some tumor cells will receive little or no direct radiation energy. There is now sufficient preclinical evidence of a Bystander response which can modulate the biology of these un-irradiated cells with current research demonstrating both protective and inhibitory responses. Dependence upon fraction of irradiated cells has also been found and the presence of functional gap junctions appears to be import for several Bystander responses. The selection of either high or low LET radionuclides may be critical. While low LET radionuclides appear to have a Bystander response proportional to dose, the dose-response from high LET radionuclides are more complex. In media transfer experiments a "U" shaped response curve has been demonstrated for high LET treatments. However this "U" shaped response has not been seen with co-culture experiments and its relevance remains uncertain. For high LET treatments there is a suggestion that dose rate effects may also be important with inhibitory effects noted with 125I labelling study and a stimulatory seen with 123I labelling in one study.© 2013 Brady, O’Sullivan and Prise.

The temporal priority principle: at what age does this develop?

The temporal priority principle states that all causes must precede their effects. It is widely assumed that children's causal reasoning is guided by this principle from early in development. However, the empirical studies that have examined children's use of the principle, most of which were conducted some decades ago, in fact show inconsistent findings. Some researchers have argued that 3-year-olds reliably use this principle, whereas others have suggested that it is not until 5 years that children properly grasp the inviolability of the principle. To examine this issue, 100 children, 50 three-year-olds, and 50 four-year-olds, took part in a study in which they had to judge which of two causes yielded an effect. In the task, children saw one event (A), an effect (E), and then another event (B). The events A and B involved the rolling of balls down runways, and the effect E was a Jack-in-a-box popping up. The extent to which E left a visible trace was also varied, because comparisons across previous studies suggested that this may affect performance. As a group, 3- and 4-year-olds performed at above-chance levels, but performance improved with age. The nature of the effect did not have a significant impact on performance. Although some previous studies suggested that 3-year-olds may be more likely to choose B rather than A as a cause due to a recency effect, we found no evidence of this pattern of performance in the younger group. Potential explanations of the age-related improvement in performance are discussed. © 2013 Desmet.

Tubular cathode prepared by a dip-coating method for low temperature DMFC

A novel tubular cathode for the direct methanol fuel cell (DMFC) is proposed, based on a tubular titanium mesh. A dip-coating method has been developed for its fabrication. The tubular cathode is composed of titanium mesh, a cathode diffusion layer, a catalyst layer, and a recast Nafion® film. The titanium mesh is present at the inner circumference of the diffusion layer, while the recast Nafion® film is at the outer circumference of the catalyst layer. A DMFC single cell with a 3.5 mgPt cm tubular cathode was able to perform as well, in terms of power density, as a conventional planar DMFC. A peak power density of 9 mW cm was reached under atmospheric air at 25 °C. © 2006 WILEY-VCH Verlag GmbH & Co. KGaA.

The role of semantic interference in limiting memory for the details of visual scenes

Many studies suggest a large capacity memory for briefly presented pictures of whole scenes. At the same time, visual working memory (WM) of scene elements is limited to only a few items. We examined the role of retroactive interference in limiting memory for visual details. Participants viewed a scene for 5?s and then, after a short delay containing either a blank screen or 10 distracter scenes, answered questions about the location, color, and identity of objects in the scene. We found that the influence of the distracters depended on whether they were from a similar semantic domain, such as "kitchen" or "airport." Increasing the number of similar scenes reduced, and eventually eliminated, memory for scene details. Although scene memory was firmly established over the initial study period, this memory was fragile and susceptible to interference. This may help to explain the discrepancy in the literature between studies showing limited visual WM and those showing a large capacity memory for scenes.

Intercepting the First Pass:Rapid Categorization is Suppressed for Unseen Stimuli

The operations and processes that the human brain employs to achieve fast visual categorization remain a matter of debate. A first issue concerns the timing and place of rapid visual categorization and to what extent it can be performed with an early feed-forward pass of information through the visual system. A second issue involves the categorization of stimuli that do not reach visual awareness. There is disagreement over the degree to which these stimuli activate the same early mechanisms as stimuli that are consciously perceived. We employed continuous flash suppression (CFS), EEG recordings, and machine learning techniques to study visual categorization of seen and unseen stimuli. Our classifiers were able to predict from the EEG recordings the category of stimuli on seen trials but not on unseen trials. Rapid categorization of conscious images could be detected around 100?ms on the occipital electrodes, consistent with a fast, feed-forward mechanism of target detection. For the invisible stimuli, however, CFS eliminated all traces of early processing. Our results support the idea of a fast mechanism of categorization and suggest that this early categorization process plays an important role in later, more subtle categorizations, and perceptual processes.

Decoding semantics across fMRI sessions with different stimulus modalities:a practical MVPA study

Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task. We present the same set of living and non-living concepts (land-mammals, or work tools) to a cohort of Japanese participants in two sessions: the first using auditory presentation of spoken words; the second using visual presentation of words written in Japanese characters. Classification accuracies confirmed that these semantic categories could be detected in single trials, with within-session predictive accuracies of 80-90%. However cross-session prediction (learning from auditory-task data to classify data from the written-word-task, or vice versa) suffered from a performance penalty, achieving 65-75% (still individually significant at p « 0.05). We carried out several follow-on analyses to investigate the reason for this shortfall, concluding that distributional differences in neither time nor space alone could account for it. Rather, combined spatio-temporal patterns of activity need to be identified for successful cross-session learning, and this suggests that feature selection strategies could be modified to take advantage of this.

Personalized medicine: Has it started yet? A reconstruction of the early history

Within the last few years the field personalized medicine entered the stage. Accompanied with great hopes and expectations it is believed that this field may have the potential to revolutionize medical and clinical care by utilizing genomics information about the individual patients themselves. In this paper, we reconstruct the early footprints of personalized medicine as reflected by information retrieved from PubMed and Google Scholar. That means we are providing a data-driven perspective of this field to estimate its current status and potential problems.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we present AGWAN (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the AGWAN model to real-world graphs and for generating random graphs from the model. Using the Enron “who communicates with whom” social graph, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to the structure of real-world graphs.

Endothelial progenitor cells in diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of visual impairment worldwide. Patients with DR may irreversibly lose sight as a result of the development of diabetic macular edema (DME) and/or proliferative diabetic retinopathy (PDR); retinal blood vessel dysfunction and degeneration plays an essential role in their pathogenesis. Although new treatments have been recently introduced for DME, including intravitreal vascular endothelial growth factor inhibitors (anti-VEGFs) and steroids, a high proportion of patients (~40-50%) do not respond to these therapies. Furthermore, for people with PDR, laser photocoagulation remains a mainstay therapy despite this being an inherently destructive procedure. Endothelial progenitor cells (EPCs) are a low-frequency population of circulating cells known to be recruited to sites of vessel damage and tissue ischemia where they promote vascular healing and re-perfusion. A growing body of evidence suggests that the number and function of EPCs are altered in patients with varying degrees of diabetes duration, metabolic control, and in the presence or absence of DR. Although there are no clear-cut outcomes from these clinical studies, there is mounting evidence that some EPC sub-types may be involved in the pathogenesis of DR and may also serve as biomarkers for disease progression and stratification. Moreover, some EPC sub-types have considerable potential as therapeutic modalities for DME and PDR in the context of cell therapy. This study presents basic clinical concepts of DR and combines this with a general insight on EPCs and their relation to future directions in understanding and treating this important diabetic complication.

Tools for Finding Inconsistencies in Real-world Logic-based Systems

Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.

Expression pattern of arenicins - the antimicrobial peptides of polychaete Arenicola marina

Immune responses of invertebrate animals are mediated through innate mechanisms, among which production of antimicrobial peptides play an important role. Although evolutionary Polychaetes represent an interesting group closely related to a putative common ancestor of other coelomates, their immune mechanisms still remain scarcely investigated. Previously our group has identified arenicins - new antimicrobial peptides of the lugworm Arenicola marina, since then these peptides were thoroughly characterized in terms of their structure and inhibitory potential. In the present study we addressed the question of the physiological functions of arenicins in the lugworm body. Using molecular and immunocytochemical methods we demonstrated that arencins are expressed in the wide range of the lugworm tissues - coelomocytes, body wall, extravasal tissue and the gut. The expression of arenicins is constitutive and does not depend on stimulation of various infectious stimuli. Most intensively arenicins are produced by mature coelomocytes where they function as killing agents inside the phagolysosome. In the gut and the body wall epithelia arenicins are released from producing cells via secretion as they are found both inside the epithelial cells and in the contents of the cuticle. Collectively our study showed that arenicins are found in different body compartments responsible for providing a first line of defence against infections, which implies their important role as key components of both epithelial and systemic branches of host defence.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we presentAgwan (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the Agwanmodel to real-world graphs and for generating random graphs from the model. Using real-world directed and undirected graphs as input, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to graph structure.