Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

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Systemic, local, and imaging biomarkers of brain injury: more needed, and better use of those already established?

Much progress has been made over the past two decades in the treatment of severe acute brain injury, including traumatic brain injury and subarachnoid hemorrhage, resulting in a higher proportion of patients surviving with better outcomes. This has arisen from a combination of factors. These include improvements in procedures at the scene (pre-hospital) and in the hospital emergency department, advances in neuromonitoring in the intensive care unit, both continuously at the bedside and intermittently in scans, evolution and refinement of protocol-driven therapy for better management of patients, and advances in surgical procedures and rehabilitation. Nevertheless, many patients still experience varying degrees of long-term disabilities post-injury with consequent demands on carers and resources, and there is room for improvement. Biomarkers are a key aspect of neuromonitoring. A broad definition of a biomarker is any observable feature that can be used to inform on the state of the patient, e.g., a molecular species, a feature on a scan, or a monitoring characteristic, e.g., cerebrovascular pressure reactivity index. Biomarkers are usually quantitative measures, which can be utilized in diagnosis and monitoring of response to treatment. They are thus crucial to the development of therapies and may be utilized as surrogate endpoints in Phase II clinical trials. To date, there is no specific drug treatment for acute brain injury, and many seemingly promising agents emerging from pre-clinical animal models have failed in clinical trials. Large Phase III studies of clinical outcomes are costly, consuming time and resources. It is therefore important that adequate Phase II clinical studies with informative surrogate endpoints are performed employing appropriate biomarkers. In this article, we review some of the available systemic, local, and imaging biomarkers and technologies relevant in acute brain injury patients, and highlight gaps in the current state of knowledge.We gratefully acknowledge financial support as follows. Research support: the Medical Research Council (MRC, Grant Nos. G0600986 ID79068 and G1002277 ID98489) and the National Institute for Health Research Biomedical Research Centre (NIHR BRC) Cambridge (Neuroscience Theme; Brain Injury and Repair Theme). Authors’ support: Keri Linda H. Carpenter – NIHR BRC Cambridge (Neuroscience Theme; Brain Injury and Repair Theme); Ibrahim Jalloh – MRC (Grant no. G1002277 ID 98489) and NIHR BRC Cambridge; Adel Helmy – MRC/Royal College of Surgeons of England Clinical Research Training Fellowship (Grant no. G0802251) and Raymond and Beverly Sackler Fellowship; Virginia F. J. Newcombe–Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship; Richard J. Shannon–NIHR BRC (Neuroscience Theme; Brain Injury and Repair Theme); Angelos G. Kolias–Royal College of Surgeons of England Research Fellowship, NIHR Academic Clinical Fellowship, and a Raymond and Beverly Sackler Studentship; David Krishna Menon–NIHR Senior Investigator Award; Peter J. Hutchinson – NIHR Research Professorship, Academy of Medical Sciences/Health Foundation Senior Surgical Scientist Fellowship.This is the final published version. It first appeared at http://journal.frontiersin.org/article/10.3389/fneur.2015.00026/full#h13

Pain coping skills training for African Americans with osteoarthritis (STAART): study protocol of a randomized controlled trial

Background: African Americans bear a disproportionate burden of osteoarthritis (OA), with higher prevalence rates, more severe pain, and more functional limitations. One key barrier to addressing these disparities has been limited engagement of African Americans in the development and evaluation of behavioral interventions for management of OA. Pain Coping Skills Training (CST) is a cognitive-behavioral intervention with shown efficacy to improve OA-related pain and other outcomes. Emerging data indicate pain CST may be a promising intervention for reducing racial disparities in OA symptom severity. However, there are important gaps in this research, including incorporation of stakeholder perspectives (e.g. cultural appropriateness, strategies for implementation into clinical practice) and testing pain CST specifically among African Americans with OA. This study will evaluate the effectiveness of a culturally enhanced pain CST program among African Americans with OA. Methods/Design: This is a randomized controlled trial among 248 participants with symptomatic hip or knee OA, with equal allocation to a pain CST group and a wait list (WL) control group. The pain CST program incorporated feedback from patients and other stakeholders and involves 11 weekly telephone-based sessions. Outcomes are assessed at baseline, 12 weeks (primary time point), and 36 weeks (to assess maintenance of treatment effects). The primary outcome is the Western Ontario and McMaster Universities Osteoarthritis Index, and secondary outcomes include self-efficacy, pain coping, pain interference, quality of life, depressive symptoms, and global assessment of change. Linear mixed models will be used to compare the pain CST group to the WL control group and explore whether participant characteristics are associated with differential improvement in the pain CST program. This research is in compliance with the Helsinki Declaration and was approved by the Institutional Review Boards of the University of North Carolina at Chapel Hill, Durham Veterans Affairs Medical Center, East Carolina University, and Duke University Health System. Discussion: This culturally enhanced pain CST program could have a substantial impact on outcomes for African Americans with OA and may be a key strategy in the reduction of racial health disparities.Funded by Patient-Centered Outcomes Research Institute (PCORI) Award (AD-1408-19519)

Ecological Thresholds in the Savanna Landscape: Developing a Protocol for Monitoring the Change in Composition and Utilisation of Large Trees

BACKGROUND: Acquiring greater understanding of the factors causing changes in vegetation structure -- particularly with the potential to cause regime shifts -- is important in adaptively managed conservation areas. Large trees (> or =5 m in height) play an important ecosystem function, and are associated with a stable ecological state in the African savanna. There is concern that large tree densities are declining in a number of protected areas, including the Kruger National Park, South Africa. In this paper the results of a field study designed to monitor change in a savanna system are presented and discussed. METHODOLOGY/PRINCIPAL FINDINGS: Developing the first phase of a monitoring protocol to measure the change in tree species composition, density and size distribution, whilst also identifying factors driving change. A central issue is the discrete spatial distribution of large trees in the landscape, making point sampling approaches relatively ineffective. Accordingly, fourteen 10 m wide transects were aligned perpendicular to large rivers (3.0-6.6 km in length) and eight transects were located at fixed-point photographic locations (1.0-1.6 km in length). Using accumulation curves, we established that the majority of tree species were sampled within 3 km. Furthermore, the key ecological drivers (e.g. fire, herbivory, drought and disease) which influence large tree use and impact were also recorded within 3 km. CONCLUSIONS/SIGNIFICANCE: The technique presented provides an effective method for monitoring changes in large tree abundance, size distribution and use by the main ecological drivers across the savanna landscape. However, the monitoring of rare tree species would require individual marking approaches due to their low densities and specific habitat requirements. Repeat sampling intervals would vary depending on the factor of concern and proposed management mitigation. Once a monitoring protocol has been identified and evaluated, the next stage is to integrate that protocol into a decision-making system, which highlights potential leading indicators of change. Frequent monitoring would be required to establish the rate and direction of change. This approach may be useful in generating monitoring protocols for other dynamic systems

Second law, entropy production, and reversibility in thermodynamics of information

We present a pedagogical review of the fundamental concepts in thermodynamics of information, by focusing on the second law of thermodynamics and the entropy production. Especially, we discuss the relationship among thermodynamic reversibility, logical reversibility, and heat emission in the context of the Landauer principle and clarify that these three concepts are fundamentally distinct to each other. We also discuss thermodynamics of measurement and feedback control by Maxwell's demon. We clarify that the demon and the second law are indeed consistent in the measurement and the feedback processes individually, by including the mutual information to the entropy production.Comment: 43 pages, 10 figures. As a chapter of: G. Snider et al. (eds.), "Energy Limits in Computation: A Review of Landauer's Principle, Theory and Experiments

Animal Perception of Seasonal Thresholds: Changes in Elephant Movement in Relation to Rainfall Patterns

Background: The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal\u2019s behaviour, which contributes to an understanding of species\u2019 responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. Methodology/Principal Findings: We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007\u20132009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. Conclusions/Significance: By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal\u2019s perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions based on convention or common practice

The association between farming activities, precipitation, and the risk of acute gastrointestinal illness in rural municipalities of Quebec, Canada: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Increasing livestock density and animal manure spreading, along with climate factors such as heavy rainfall, may increase the risk of acute gastrointestinal illness (AGI). In this study we evaluated the association between farming activities, precipitation and AGI.</p> <p>Methods</p> <p>A cross-sectional telephone survey of randomly selected residents (n = 7006) of 54 rural municipalities in Quebec, Canada, was conducted between April 2007 and April 2008. AGI symptoms and several risk factors were investigated using a phone questionnaire. We calculated the monthly prevalence of AGI, and used multivariate logistic regression, adjusting for several demographic and risk factors, to evaluate the associations between AGI and both intensive farming activities and cumulative weekly precipitation. Cumulative precipitation over each week, from the first to sixth week prior to the onset of AGI, was analyzed to account for both the delayed effect of precipitation on AGI, and the incubation period of causal pathogens. Cumulative precipitation was treated as a four-category variable: high (≥90^thpercentile), moderate (50^thto <90^thpercentile), low (10^thto <50^thpercentile), and very low (<10^thpercentile) precipitation.</p> <p>Results</p> <p>The overall monthly prevalence of AGI was 5.6% (95% CI 5.0%-6.1%), peaking in winter and spring, and in children 0-4 years old. Living in a territory with intensive farming was negatively associated with AGI: adjusted odds ratio (OR) = 0.70 (95% CI 0.51-0.96). Compared to low precipitation periods, high precipitation periods in the fall (September, October, November) increased the risk of AGI three weeks later (OR = 2.20; 95% CI 1.09-4.44) while very low precipitation periods in the summer (June, July, August) increased the risk of AGI four weeks later (OR = 2.19; 95% CI 1.02-4.71). Further analysis supports the role of water source on the risk of AGI.</p> <p>Conclusions</p> <p>AGI poses a significant burden in Quebec rural municipalities with a peak in winter. Intensive farming activities were found to be negatively associated with AGI. However, high and very low precipitation levels were positively associated with the occurrence of AGI, especially during summer and fall. Thus, preventive public health actions during such climate events may be warranted.</p

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

Building pathway clusters from Random Forests classification using class votes

<p>Abstract</p> <p>Background</p> <p>Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.</p> <p>Results</p> <p>We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster.</p> <p>Conclusion</p> <p>Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.</p