Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

A conceptual cellular interaction model of left ventricular remodelling post-MI: dynamic network with exit-entry competition strategy

Abstract Background Progressive remodelling of the left ventricle (LV) following myocardial infarction (MI) is an outcome of spatial-temporal cellular interactions among different cell types that leads to heart failure for a significant number of patients. Cellular populations demonstrate temporal profiles of flux post-MI. However, little is known about the relationship between cell populations and the interaction strength among cells post-MI. The objective of this study was to establish a conceptual cellular interaction model based on a recently established graph network to describe the interaction between two types of cells. Results We performed stability analysis to investigate the effects of the interaction strengths, the initial status, and the number of links between cells on the cellular population in the dynamic network. Our analysis generated a set of conditions on interaction strength, structure of the network, and initial status of the network to predict the evolutionary profiles of the network. Computer simulations of our conceptual model verified our analysis. Conclusions Our study introduces a dynamic network to model cellular interactions between two different cell types which can be used to model the cellular population changes post-MI. The results on stability analysis can be used as a tool to predict the responses of particular cell populations

Evaluating the potential for the environmentally sustainable control of foot and mouth disease in Sub-Saharan Africa

Strategies to control transboundary diseases have in the past generated unintended negative consequences for both the environment and local human populations. Integrating perspectives from across disciplines, including livestock, veterinary and conservation sectors, is necessary for identifying disease control strategies that optimise environmental goods and services at the wildlife-livestock interface. Prompted by the recent development of a global strategy for the control and elimination of foot-and-mouth disease (FMD), this paper seeks insight into the consequences of, and rational options for potential FMD control measures in relation to environmental, conservation and human poverty considerations in Africa. We suggest a more environmentally nuanced process of FMD control that safe-guards the integrity of wild populations and the ecosystem dynamics on which human livelihoods depend while simultaneously improving socio-economic conditions of rural people. In particular, we outline five major issues that need to be considered: 1) improved understanding of the different FMD viral strains and how they circulate between domestic and wildlife populations; 2) an appreciation for the economic value of wildlife for many African countries whose presence might preclude the country from ever achieving an FMD-free status; 3) exploring ways in which livestock production can be improved without compromising wildlife such as implementing commodity-based trading schemes; 4) introducing a participatory approach involving local farmers and the national veterinary services in the control of FMD; and 5) finally the possibility that transfrontier conservation might offer new hope of integrating decision-making at the wildlife-livestock interface

Epigenetic deregulation of multiple S100 gene family members by differential hypomethylation and hypermethylation events in medulloblastoma

Deregulated expression of genes encoding members of the S100 family of calcium-binding proteins has been associated with the malignant progression of multiple tumour types. Using a pharmacological expression reactivation approach, we screened 16 S100 genes for evidence of epigenetic regulation in medulloblastoma, the most common malignant brain tumour of childhood. Four family members (S100A2, S100A4, S100A6 and S100A10) demonstrated evidence of upregulated expression in multiple medulloblastoma cell lines, following treatment with the DNA methyltransferase inhibitor, 5′-aza-2′-deoxycytidine. Subsequent analysis revealed methylation of critical CpG sites located within these four genes in an extended cell line panel. Assessment of these genes in the non-neoplastic cerebellum (from which medulloblastomas develop) revealed strong somatic methylation affecting S100A2 and S100A4, whereas S100A6 and S100A10 were unmethylated. Assessed against these normal tissue-specific methylation states, S100A6 and S100A10 demonstrated tumour-specific hypermethylation in medulloblastoma primary tumours (5 out of 40 and 4 out of 35, respectively, both 12%) and cell lines (both 7 out of 9, 78%), which was associated with their transcriptional silencing. Moreover, S100A6 hypermethylation was significantly associated with the aggressive large cell/anaplastic morphophenotype (P=0.026). In contrast, pro-metastatic S100A4 displayed evidence of hypomethylation relative to the normal cerebellum in a significant proportion primary tumours (7 out of 41, 17%) and cell lines (3 out of 9, 33%), which was associated with its elevated expression. In summary, these data characterise complex patterns of somatic methylation affecting S100 genes in the normal cerebellum and demonstrate their disruption causing epigenetic deregulation of multiple S100 family members in medulloblastoma development. Epigenetic events affecting S100 genes have potential clinical utility and merit further investigation as molecular biomarkers for this disease

Does osteoporosis predispose falls? a study on obstacle avoidance and balance confidence

Contains fulltext : 96832.pdf (publisher's version ) (Open Access)BACKGROUND: Osteoporosis is associated with changes in balance and physical performance and has psychosocial consequences which increase the risk of falling. Most falls occur during walking; therefore an efficient obstacle avoidance performance might contribute to a reduction in fall risk. Since it was shown that persons with osteoporosis are unstable during obstacle crossing it was hypothesized that they more frequently hit obstacles, specifically under challenging conditions. METHODS: Obstacle avoidance performance was measured on a treadmill and compared between persons with osteoporosis (n = 85) and the comparison group (n = 99). The obstacle was released at different available response times (ART) to create different levels of difficulty by increasing time pressure. Furthermore, balance confidence, measured with the short ABC-questionnaire, was compared between the groups. RESULTS: No differences were found between the groups in success rates on the obstacle avoidance task (p = 0.173). Furthermore, the persons with osteoporosis had similar levels of balance confidence as the comparison group (p = 0.091). The level of balance confidence was not associated with the performance on the obstacle avoidance task (p = 0.145). CONCLUSION: Obstacle avoidance abilities were not impaired in persons with osteoporosis and they did not experience less balance confidence than the comparison group. These findings imply that persons with osteoporosis do not have an additional risk of falling because of poorer obstacle avoidance abilities

What do parents perceive are the barriers and facilitators to accessing psychological treatment for mental health problems in children and adolescents? A systematic review of qualitative and quantitative studies

A minority of children and adolescents with mental health problems access treatment. The reasons for poor rates of treatment access are not well understood. As parents are a key gatekeeper to treatment access, it is important to establish parents’ views of barriers/facilitators to accessing treatment. The aims of this study are to synthesise findings from qualitative and quantitative studies that report parents’ perceptions of barriers/facilitators to accessing treatment for mental health problems in children/adolescents. A systematic review and narrative synthesis were conducted. Forty-four studies were included in the review and were assessed in detail. Parental perceived barriers/facilitators relating to (1) systemic/structural issues; (2) views and attitudes towards services and treatment; (3) knowledge and understanding of mental health problems and the help-seeking process; and (4) family circumstances were identified. Findings highlight avenues for improving access to child mental health services, including increased provision that is free to service users and flexible to their needs, with opportunities to develop trusting, supportive relationships with professionals. Furthermore, interventions are required to improve parents’ identification of mental health problems, reduce stigma for parents, and increase awareness of how to access services

Functional identification of biological neural networks using reservoir adaptation for point processes

The complexity of biological neural networks does not allow to directly relate their biophysical properties to the dynamics of their electrical activity. We present a reservoir computing approach for functionally identifying a biological neural network, i.e. for building an artificial system that is functionally equivalent to the reference biological network. Employing feed-forward and recurrent networks with fading memory, i.e. reservoirs, we propose a point process based learning algorithm to train the internal parameters of the reservoir and the connectivity between the reservoir and the memoryless readout neurons. Specifically, the model is an Echo State Network (ESN) with leaky integrator neurons, whose individual leakage time constants are also adapted. The proposed ESN algorithm learns a predictive model of stimulus-response relations in in vitro and simulated networks, i.e. it models their response dynamics. Receiver Operating Characteristic (ROC) curve analysis indicates that these ESNs can imitate the response signal of a reference biological network. Reservoir adaptation improved the performance of an ESN over readout-only training methods in many cases. This also held for adaptive feed-forward reservoirs, which had no recurrent dynamics. We demonstrate the predictive power of these ESNs on various tasks with cultured and simulated biological neural networks

Extracting key information from historical data to quantify the transmission dynamics of smallpox

<p>Abstract</p> <p>Background</p> <p>Quantification of the transmission dynamics of smallpox is crucial for optimizing intervention strategies in the event of a bioterrorist attack. This article reviews basic methods and findings in mathematical and statistical studies of smallpox which estimate key transmission parameters from historical data.</p> <p>Main findings</p> <p>First, critically important aspects in extracting key information from historical data are briefly summarized. We mention different sources of heterogeneity and potential pitfalls in utilizing historical records. Second, we discuss how smallpox spreads in the absence of interventions and how the optimal timing of quarantine and isolation measures can be determined. Case studies demonstrate the following. (1) The upper confidence limit of the 99th percentile of the incubation period is 22.2 days, suggesting that quarantine should last 23 days. (2) The highest frequency (61.8%) of secondary transmissions occurs 3–5 days after onset of fever so that infected individuals should be isolated before the appearance of rash. (3) The U-shaped age-specific case fatality implies a vulnerability of infants and elderly among non-immune individuals. Estimates of the transmission potential are subsequently reviewed, followed by an assessment of vaccination effects and of the expected effectiveness of interventions.</p> <p>Conclusion</p> <p>Current debates on bio-terrorism preparedness indicate that public health decision making must account for the complex interplay and balance between vaccination strategies and other public health measures (e.g. case isolation and contact tracing) taking into account the frequency of adverse events to vaccination. In this review, we summarize what has already been clarified and point out needs to analyze previous smallpox outbreaks systematically.</p

A neural signature of the unique hues

Since at least the 17th century there has been the idea that there are four simple and perceptually pure “unique” hues: red, yellow, green, and blue, and that all other hues are perceived as mixtures of these four hues. However, sustained scientific investigation has not yet provided solid evidence for a neural representation that separates the unique hues from other colors. We measured event-related potentials elicited from unique hues and the ‘intermediate’ hues in between them. We find a neural signature of the unique hues 230 ms after stimulus onset at a post-perceptual stage of visual processing. Specifically, the posterior P2 component over the parieto-occipital lobe peaked significantly earlier for the unique than for the intermediate hues (Z = -2.9, p = .004). Having identified a neural marker for unique hues, fundamental questions about the contribution of neural hardwiring, language and environment to the unique hues can now be addressed