How different experimental models of secondary hyperalgesia change the nociceptive flexion reflex

In this neurophysiological study in healthy humans, we assessed how central sensitization induced by either high-frequency stimulation (HFS) or topical capsaicin application modulates features of the RIII reflex response. The ability of these stimuli to engage the endogenous pain modulatory system was also tested. In 26 healthy participants we elicited an RIII reflex using suprathreshold stimulation of the sural nerve. Subsequently HFS or capsaicin were applied to the foot and the RIII reflex repeated after 15 minutes. Contact heating of the volar forearm served as the heterotopic test stimulus to probe activation of the endogenous pain modulatory system. HFS significantly reduced the pain threshold by 29% and the RIII reflex threshold by 20%. Capsaicin significantly reduced the pain threshold by 17% and the RIII reflex threshold by 18%. Both HFS and capsaicin left RIII reflex size unaffected. Numerical Rating Scale (NRS) pain scores elicited by the heterotopic noxious heat stimulus were unaffected by capsaicin and slightly increased by HFS. HFS and capsaicin similarly modulated the pain threshold and RIII reflex threshold, without a concomitant inhibitory effect of the endogenous pain modulatory system. Our neurophysiological study supports the use of the RIII reflex in investigating central sensitization in humans

Predicting gene function using hierarchical multi-label decision tree ensembles

<p>Abstract</p> <p>Background</p> <p><it>S. cerevisiae</it>, <it>A. thaliana </it>and <it>M. musculus </it>are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability.</p> <p>Results</p> <p>We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO). We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use.</p> <p>Conclusions</p> <p>Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.</p

Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information

A miniature world in decline: European Red List of Mosses, Liverworts and Hornworts

AimThis Red List is a summary of the conservation status of the European species of mosses, liverworts and hornworts, collectively known as bryophytes, evaluated according to IUCN’s Guidelines for Application of IUCN Red List Criteria at Regional Level. It provides the first comprehensive, region-wide assessment of bryophytes and it identifies those species that are threatened with extinction at a European level, so that appropriate policy measures and conservation actions, based on the best available evidence, can be taken to improve their status.ScopeAll bryophytes native to or naturalised in Europe (a total of 1,817 species), have been included in this Red List. In Europe, 1,796 species were assessed, with the remaining 21 species considered Not Applicable (NA). For the EU 28, 1,728 species were assessed, with a remaining 20 species considered NA and 69 species considered Not Evaluated (NE). The geographical scope is continentwide, extending from Iceland in the west to the Urals in the east, and from Franz Josef Land in the north to theCanary Islands in the south. The Caucasus region is not included. Red List assessments were made at two regional levels: for geographical Europe and for the 28 Member States of the European Union.ResultsOverall, 22.5% of European bryophyte species assessed in this study are considered threatened in Europe, with two species classified as Extinct and six assessed as Regionally Extinct (RE). A further 9.6% (173 species) are considered Near Threatened and 63.5% (1,140 species) are assessed as Least Concern. For 93 species (5.3%), there was insufficient information available to be able to evaluate their risk of extinction and thus they were classified as Data Deficient (DD). The main threats identified were natural system modifications (i.e., dam construction, increases in fire frequency/intensity, and water management/use), climate change (mainly increasing frequency of droughts and temperature extremes), agriculture (including pollution from agricultural effluents) and aquaculture.RecommendationsPolicy measures• Use the European Red List as the scientific basis to inform regional/national lists of rare and threatened species and to identify priorities for conservation action in addition to the requirements of the Habitats Directive, thereby highlighting the conservation status of bryophytes at the regional/local level.• Use the European Red List to support the integration of conservation policy with the Common Agricultural Policy (CAP) and other national and international policies. For example, CAP Strategic Plans should include biodiversity recovery commitments that could anticipate, among others, the creation of Important Bryophyte Areas. An increased involvement of national environmental agencies in the preparation of these strategic plans, and more broadly in ongoing discussions on the Future CAP Green Architecture, would likely also ensure the design of conservation measures better tailored to conserve bryophytes in agricultural landscapes.• Update the European Red List every decade to ensure that the data remains current and relevant.• Develop Key Biodiversity Areas for bryophytes in Europe with a view to ensuring adequate site-based protection for bryophytes.Research and monitoring• Use the European Red List as a basis for future targeted fieldwork on possibly extinct and understudied species.• Establish a monitoring programme for targeted species (for example, threatened species and/or arable bryophytes).• Use the European Red List to obtain funding for research into the biology and ecology of key targeted species.Action on the ground• Use the European Red List as evidence to support multi-scale conservation initiatives, including designation of protected areas, reform of agricultural practices and land management, habitat restoration and rewilding, and pollution reduction measures.• Use the European Red List as a tool to target species that would benefit the most from the widespread implementation of the solutions offered by the 1991 Nitrates Directive (Council Directive 91/676/EEC), including the application of correct amounts of nutrients for each crop, only in periods of crop growth under suitable climatic conditions and never during periods of heavy rainfall or on frozen ground, and the creation of buffer zones to protect waters from run-off from the application of fertilizers.Ex situ conservation• Undertake ex situ conservation of species of conservation concern in botanic gardens and spore and gene banks, with a view to reintroduction where appropriate.</p