Improving neurophysiological biomarkers for functional myoclonic movements.

INTRODUCTION: Differentiating between functional jerks (FJ) and organic myoclonus can be challenging. At present, the only advanced diagnostic biomarker to support FJ is the Bereitschaftspotential (BP). However, its sensitivity is limited and its evaluation subjective. Recently, event related desynchronisation in the broad beta range (13-45 Hz) prior to functional generalised axial (propriospinal) myoclonus was reported as a possible complementary diagnostic marker for FJ. Here we study the value of ERD together with a quantified BP in clinical practice. METHODS: Twenty-nine patients with FJ and 16 patients with cortical myoclonus (CM) were included. Jerk-locked back-averaging for determination of the 'classical' and quantified BP, and time-frequency decomposition for the event related desynchronisation (ERD) were performed. Diagnostic gain, sensitivity and specificity were obtained for individual and combined techniques. RESULTS: We detected a classical BP in 14/29, a quantitative BP in 15/29 and an ERD in 18/29 patients. At group level we demonstrate that ERD in the broad beta band preceding a jerk has significantly higher amplitude in FJ compared to CM (respectively -0.14 ± 0.13 and +0.04 ± 0.09 (p < 0.001)). Adding ERD to the classical BP achieved an additional diagnostic gain of 53%. Furthermore, when combining ERD with quantified and classical BP, an additional diagnostic gain of 71% was achieved without loss of specificity. CONCLUSION: Based on the current findings we propose to the use of combined beta ERD assessment and quantitative BP analyses in patients with a clinical suspicion for all types of FJ with a negative classical BP

Growth in fossil and extant deer and implications for body size and life history evolution

© Kolb et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The attached file is the published version of the article

Natural and anthropogenic changes in atmospheric greenhouse gases over the past 2 millennia

Millennial changes in atmospheric trace gas composition are best determined from air enclosed in ice sheets. Air extracted from the open pores in firn and the bubbles in ice is measured to derive the past concentrations and isotopic ratios of the long lived trace gases. The significant increases observed in CO2, CH4 and N2O since about 1750 and the more recent appearance of synthetic gases such as the CFCs in the atmosphere are a key feature of the anthropocene. The millennia preceding the anthropocene, the Late Pre-Industrial Holocene (LPIH), show evidence of natural changes in trace gases that can be used to constrain models and improve their ability to predict future changes under scenarios of anthropogenic emissions and climate change. Precise measurements and ice core air samples that are accurately dated and highly resolved in time are required to record the small and rapid trace gas signals of this period. The atmospheric composition records produced by CSIRO and collaborators using the Law Dome, Antarctica ice cores are widely used in models of climate, atmospheric chemistry and the carbon cycle over the anthropocene and the LPIH. Results from these studies have been influential in informing global policies, including the Montreal and Kyoto Protocols. We will present the recently revised trace gas records from Law Dome and new measurements of tracers from these and other ice sites that reveal the causes of atmospheric changes over the anthropocene and the LPIH

Atmospheric CO2 and d13C-CO2 reconstruction of the little ice age from antarctic ice cores

The decrease of atmospheric CO2 concentration recorded in Antarctic ice around 1600 AD is one of the most significant atmospheric changes to have occurred during the last millennia, before the onset of the industrial period.Together with the temperature decrease, the CO2 drop has been used to derive the sensitivity of carbon stores to climate. However, the cause of it is still under debate because models are not yet able to reproduce either its magnitude, or its timing. Here we present new measurements of the CO2 concentration decrease recorded in an ice core from a medium accumulation rate site in Antarctica (DML). We show that the new record is compatible(differences <2 ppm) with the CO2 record from the high accumulation rate DSS site on Law Dome (East Antarctica), when the different age distributions are taken into account. We have also measured the d13C-CO2 change in DML ice, filling a gap around 1600 AD in the DSS d13C record. We use a double deconvolution of the CO2 and d13C records together to provide quantitative evidence that the CO2 decrease was caused by a change in the net flux to the terrestrial biosphere. Finally, we provide a new interpretation of a published record showing increasing atmospheric carbonyl sulphide during the CO2 decrease, suggesting that cooler LIA climate affected terrestrial biospheric fluxes. Altogether our findings support the hypothesis that reduced soil heterotrophic respiration is likely to have given the most significant contribution to the LIA CO2 decrease implying a positive CO2-climate feedback. © 2015, Authors

An Instruction on the In Vivo Shell-Less Chorioallantoic Membrane 3-Dimensional Tumor Spheroid Model

The traditional shell chicken chorioallantoic membrane (CAM) model has been used extensively in cancer research to study tumor growth and angiogenesis. Here we present a combined in vivo tumor spheroid and shell-less CAM three-dimensional model for use in quantitative and qualitative analysis. With this model, the angiogenic and tumorigenic environments can be generated locally without exogenous growth factors. This physiological model offers a stable, static and flat environment that features a large working area and wider field of view useful for imaging and biomedical engineering applications. The short experimental time frame allows for rapid data acquisition, screening and validation of biomedical devices. The method and application of this shell-less model are discussed in detail, providing a useful tool for biomedical engineering research

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Contrasting changes in the abundance and diversity of North American bird assemblages from 1971 to 2010

This article is based upon work from COST Action ES1101 "Harmonising Global Biodiversity Modelling" (Harmbio), supported by COST (European Cooperation in Science and Technology).Although it is generally recognized that global biodiversity is declining, few studies have examined long-term changes in multiple biodiversity dimensions simultaneously. In this study we quantified and compared temporal changes in the abundance, taxonomic diversity, functional diversity and phylogenetic diversity of bird assemblages, using roadside monitoring data of the North American Breeding Bird Survey from 1971 to 2010. We calculated 12 abundance and diversity metrics based on five year average abundances of 519 species for each of 768 monitoring routes. We did this for all bird species together as well as for four sub-groups based on breeding habitat affinity (grassland, woodland, wetland and shrubland breeders). The majority of the biodiversity metrics increased or remained constant over the study period, whereas the overall abundance of birds showed a pronounced decrease, primarily driven by declines of the most abundant species. These results highlight how stable or even increasing metrics of taxonomic, functional or phylogenetic diversity may occur in parallel with substantial losses of individuals. We further found that patterns of change differed among the species sub-groups, with both abundance and diversity increasing for woodland birds and decreasing for grassland breeders. The contrasting changes between abundance and diversity and among the breeding habitat groups underscore the relevance of a multi-faceted approach to measuring biodiversity change. Our findings further stress the importance of monitoring the overall abundance of individuals in addition to metrics of taxonomic, functional or phylogenetic diversity, thus confirming the importance of population abundance as an essential biodiversity variable.Publisher PDFPeer reviewe

Cell-scale degradation of peritumoural extracellular matrix fibre network and its role within tissue-scale cancer invasion

Local cancer invasion of tissue is a complex, multiscale process which plays an essential role in tumour progression. Occurring over many different temporal and spatial scales, the first stage of invasion is the secretion of matrix degrading enzymes (MDEs) by the cancer cells that consequently degrade the surrounding extracellular matrix (ECM). This process is vital for creating space in which the cancer cells can progress and it is driven by the activities of specific matrix metalloproteinases (MMPs). In this paper, we consider the key role of two MMPs by developing further the novel two-part multiscale model introduced in [33] to better relate at micro-scale the two micro-scale activities that were considered there, namely, the micro-dynamics concerning the continuous rearrangement of the naturally oriented ECM fibres within the bulk of the tumour and MDEs proteolytic micro-dynamics that take place in an appropriate cell-scale neighbourhood of the tumour boundary. Focussing primarily on the activities of the membrane-tethered MT1-MMP and the soluble MMP-2 with the fibrous ECM phase, in this work we investigate the MT1-MMP/MMP-2 cascade and its overall effect on tumour progression. To that end, we will propose a new multiscale modelling framework by considering the degradation of the ECM fibres not only to take place at macro-scale in the bulk of the tumour but also explicitly in the micro-scale neighbourhood of the tumour interface as a consequence of the interactions with molecular fluxes of MDEs that exercise their spatial dynamics at the invasive edge of the tumour

Development and external validation of a dynamic prognostic nomogram for primary extremity soft tissue sarcoma survivors.

Background:Prognostic nomograms for patients with extremity soft tissue sarcoma (eSTS) typically predict survival or the occurrence of local recurrence or distant metastasis at time of surgery. Our aim was to develop and externally validate a dynamic prognostic nomogram for overall survival in eSTS survivors for use during follow-up. Methods:All primary eSTS patients operated with curative intent between 1994 and 2013 at three European and one Canadian sarcoma centers formed the development cohort. Patients with Fédération Française des Centres de Lutte Contre le Cancer (FNCLCC) grade II and grade III eSTS operated between 2000 and 2016 at seven other European reference centers formed the external validation cohort. We used a landmark analysis approach and a multivariable Cox model to create a dynamic nomogram; the prediction window was fixed at five years. A backward procedure based on the Akaike Information Criterion was adopted for variable selection. We tested the nomogram performance in terms of calibration and discrimination. Findings:The development and validation cohorts included 3740 and 893 patients, respectively. The variables selected applying the backward procedure were patient's age, tumor size and its interaction with landmark time, tumor FNCLCC grade and its interaction with landmark time, histology, and both local recurrence and distant metastasis (as first event) indicator variables. The nomogram showed good calibration and discrimination. Harrell C indexes at different landmark times were between 0.776 (0.761-0.790) and 0.845 (0.823-0.862) in the development series and between 0.675 (0.643-0.704) and 0.810 (0.775-0.844) in the validation series. Interpretation:A new dynamic nomogram is available to predict 5-year overall survival at different times during the first three years of follow-up in patients operated for primary eSTS. This nomogram allows physicians to update the individual survival prediction during follow-up on the basis of baseline variables, time elapsed from surgery and first-event history

Multi-centre parallel arm randomised controlled trial to assess the effectiveness and cost-effectiveness of a group-based cognitive behavioural approach to managing fatigue in people with multiple sclerosis

Abstract (provisional) Background Fatigue is one of the most commonly reported and debilitating symptoms of multiple sclerosis (MS); approximately two-thirds of people with MS consider it to be one of their three most troubling symptoms. It may limit or prevent participation in everyday activities, work, leisure, and social pursuits, reduce psychological well-being and is one of the key precipitants of early retirement. Energy effectiveness approaches have been shown to be effective in reducing MS-fatigue, increasing self-efficacy and improving quality of life. Cognitive behavioural approaches have been found to be effective for managing fatigue in other conditions, such as chronic fatigue syndrome, and more recently, in MS. The aim of this pragmatic trial is to evaluate the clinical and cost-effectiveness of a recently developed group-based fatigue management intervention (that blends cognitive behavioural and energy effectiveness approaches) compared with current local practice. Methods This is a multi-centre parallel arm block-randomised controlled trial (RCT) of a six session group-based fatigue management intervention, delivered by health professionals, compared with current local practice. 180 consenting adults with a confirmed diagnosis of MS and significant fatigue levels, recruited via secondary/primary care or newsletters/websites, will be randomised to receive the fatigue management intervention or current local practice. An economic evaluation will be undertaken alongside the trial. Primary outcomes are fatigue severity, self-efficacy and disease-specific quality of life. Secondary outcomes include fatigue impact, general quality of life, mood, activity patterns, and cost-effectiveness. Outcomes in those receiving the fatigue management intervention will be measured 1 week prior to, and 1, 4, and 12 months after the intervention (and at equivalent times in those receiving current local practice). A qualitative component will examine what aspects of the fatigue management intervention participants found helpful/unhelpful and barriers to change. Discussion This trial is the fourth stage of a research programme that has followed the Medical Research Council guidance for developing and evaluating complex interventions. What makes the intervention unique is that it blends cognitive behavioural and energy effectiveness approaches. A potential strength of the intervention is that it could be integrated into existing service delivery models as it has been designed to be delivered by staff already working with people with MS. Service users will be involved throughout this research. Trial registration: Current Controlled Trials ISRCTN7651747