International patellofemoral osteoarthritis consortium: Consensus statement on the diagnosis, burden, outcome measures, prognosis, risk factors and treatment

Objective: To present the current status of knowledge in the field of patellofemoral (PF) osteoarthritis (OA) and formulate a research agenda in order to guide future research on this topic. Design: A 1-day meeting was organized with the aim to bring together international experts in the field to discuss the current state of knowledge on PF OA. Experts from multiple disciplines were invited based on their scientific publications in the field of PF OA and interest in the subject. Topics discussed include the diagnosis, impact, prognosis, and treatment of PF OA. Methods: Following context-setting presentations, an interactive discussion was held in order to achieve consensus on the PF OA topics of interest: (1) diagnosis and definition; (2) burden; (3) outcome measures; (4) prognosis; (5) risk factors, and (6) treatment. Groups of meeting attendees reviewed the literature on these topics and narratively summarized the current state of knowledge, and each group formulated research agenda items relevant to the specific topics of interest. Each consortium member consequently ranked the importance of all items on a 0–10 Numerical Rating Scale (NRS) (10 = extremely important, to 0 = not at all important). Results: After ranking all formulated items on importance, 6 of the 28 research agenda items formulated received an average of 7.5 points on the NRS. The most highly ranked items covered the fields of treatment, diagnosis, and definition of PF OA. Conclusions: We recommend to develop clear clinical criteria for PF OA and to reach consensus on the definition of PF OA by both radiographs and MRI. Additionally, more understanding is necessary to be able to distinguish PF symptoms from those arising from the tibiofemoral joint. More insight is needed on effective treatment strategies for PF OA; specifically, tailoring nonpharmacological treatments to individuals with PF OA, and determining whether isolated PF OA requires different treatment strategies than combined PF and tibiofemoral OA

Sudden Cardiac Death Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy: A Multinational Collaboration.

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. METHODS: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. RESULTS: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism. CONCLUSIONS: LTVA events in patients with ARVC can be predicted by a novel simple prediction model using only 4 clinical predictors. Prior sustained VA and the extent of functional heart disease are not associated with subsequent LTVA events

Growth Response of Drought-Stressed Pinus sylvestris Seedlings to Single- and Multi-Species Inoculation with Ectomycorrhizal Fungi

Many trees species form symbiotic associations with ectomycorrhizal (ECM) fungi, which improve nutrient and water acquisition of their host. Until now it is unclear whether the species richness of ECM fungi is beneficial for tree seedling performance, be it during moist conditions or drought. We performed a pot experiment using Pinus sylvestris seedlings inoculated with four selected ECM fungi (Cenococcum geophilum, Paxillus involutus, Rhizopogon roseolus and Suillus granulatus) to investigate (i) whether these four ECM fungi, in monoculture or in species mixtures, affect growth of P. sylvestris seedlings, and (ii) whether this effect can be attributed to species number per se or to species identity. Two different watering regimes (moist vs. dry) were applied to examine the context-dependency of the results. Additionally, we assessed the activity of eight extracellular enzymes in the root tips. Shoot growth was enhanced in the presence of S. granulatus, but not by any other ECM fungal species. The positive effect of S. granulatus on shoot growth was more pronounced under moist (threefold increase) than under dry conditions (twofold increase), indicating that the investigated ECM fungi did not provide additional support during drought stress. The activity of secreted extracellular enzymes was higher in S. granulatus than in any other species. In conclusion, our findings suggest that ECM fungal species composition may affect seedling performance in terms of aboveground biomass

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

Aims Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. Methods and results Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44–9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73–0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92–0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P < 0.001). Conclusion Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICD

Estimating time-to-onset of adverse drug reactions from spontaneous reporting databases.

International audienceBACKGROUND: Analyzing time-to-onset of adverse drug reactions from treatment exposure contributes to meeting pharmacovigilance objectives, i.e. identification and prevention. Post-marketing data are available from reporting systems. Times-to-onset from such databases are right-truncated because some patients who were exposed to the drug and who will eventually develop the adverse drug reaction may do it after the time of analysis and thus are not included in the data. Acknowledgment of the developments adapted to right-truncated data is not widespread and these methods have never been used in pharmacovigilance. We assess the use of appropriate methods as well as the consequences of not taking right truncation into account (naïve approach) on parametric maximum likelihood estimation of time-to-onset distribution. METHODS: Both approaches, naïve or taking right truncation into account, were compared with a simulation study. We used twelve scenarios for the exponential distribution and twenty-four for the Weibull and log-logistic distributions. These scenarios are defined by a set of parameters: the parameters of the time-to-onset distribution, the probability of this distribution falling within an observable values interval and the sample size. An application to reported lymphoma after anti TNF-¿ treatment from the French pharmacovigilance is presented. RESULTS: The simulation study shows that the bias and the mean squared error might in some instances be unacceptably large when right truncation is not considered while the truncation-based estimator shows always better and often satisfactory performances and the gap may be large. For the real dataset, the estimated expected time-to-onset leads to a minimum difference of 58 weeks between both approaches, which is not negligible. This difference is obtained for the Weibull model, under which the estimated probability of this distribution falling within an observable values interval is not far from 1. CONCLUSIONS: It is necessary to take right truncation into account for estimating time-to-onset of adverse drug reactions from spontaneous reporting databases

Ectomycorrhizal fungal diversity and community structure associated with cork oak in different landscapes

Cork oak (Quercus suber L.) forests play an important ecological and economic role. Ectomycorrhizal fungi (ECMF) are key components for the sustainability and functioning of these ecosystems. The community structure and composition of ECMF associated with Q. suber in different landscapes of distinct Mediterranean bioclimate regions have not previously been compared. In this work, soil samples from cork oak forests residing in different bioclimates (arid, semi-arid, sub-humid, and humid) were collected and surveyed for ectomycorrhizal (ECM) root tips. A global analysis performed on 3565 ECM root tips revealed that the ECMF community is highly enriched in Russula, Tomentella, and Cenoccocum, which correspond to the ECMF genera that mainly contribute to community differences. The ECMF communities from the rainiest and the driest cork oak forests were distinct, with soils from the rainiest climates being more heterogeneous than those from the driest climates. The analyses of several abiotic factors on the ECMF communities revealed that bioclimate, precipitation, soil texture, and forest management strongly influenced ECMF structure. Shifts in ECMF with different hyphal exploration types were also detected among forests, with precipitation, forest system, and soil texture being the main drivers controlling their composition. Understanding the effects of environmental factors on the structuring of ECM communities could be the first step for promoting the sustainability of this threatened ecosystem.This work was supported by Fundacao Ciencia e Tecnologia (FCT/MCTES/PIDDAC, Portugal), under the project (PEst-OE/BIA/UI4046/2014; UID/MULTI/04046/2013) and PhD grant to F.R. (SFRH/BD/86519/2012)

Responses of Auditory Nerve and Anteroventral Cochlear Nucleus Fibers to Broadband and Narrowband Noise: Implications for the Sensitivity to Interaural Delays

The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways

Contrasting Diversity Patterns of Crenarchaeal, Bacterial and Fungal Soil Communities in an Alpine Landscape

International audienceBackground: The advent of molecular techniques in microbial ecology has aroused interest in gaining an understanding about the spatial distribution of regional pools of soil microbes and the main drivers responsible of these spatial patterns. Here, we assessed the distribution of crenarcheal, bacterial and fungal communities in an alpine landscape displaying high turnover in plant species over short distances. Our aim is to determine the relative contribution of plant species composition, environmental conditions, and geographic isolation on microbial community distribution. Methodology/Principal Findings: Eleven types of habitats that best represent the landscape heterogeneity were investigated. Crenarchaeal, bacterial and fungal communities were described by means of Single Strand Conformation Polymorphism. Relationships between microbial beta diversity patterns were examined by using Bray-Curtis dissimilarities and Principal Coordinate Analyses. Distance-based redundancy analyses and variation partitioning were used to estimate the relative contributions of different drivers on microbial beta diversity. Microbial communities tended to be habitat- specific and did not display significant spatial autocorrelation. Microbial beta diversity correlated with soil pH. Fungal beta- diversity was mainly related to soil organic matter. Though the effect of plant species composition was significant for all microbial groups, it was much stronger for Fungi. In contrast, geographic distances did not have any effect on microbial beta diversity. Conclusions/Significance: Microbial communities exhibit non-random spatial patterns of diversity in alpine landscapes. Crenarcheal, bacterial and fungal community turnover is high and associated with plant species composition through different set of soil variables, but is not caused by geographical isolation

Spatial patterns of microbial diversity and activity in an aged creosote-contaminated site

Restoration of polluted sites via in situ bioremediation relies heavily on the indigenous microbes and their activities. Spatial heterogeneity of microbial populations, contaminants and soil chemical parameters on such sites is a major hurdle in optimizing and implementing an appropriate bioremediation regime. We performed a grid-based sampling of an aged creosote-contaminated site followed by geostatistical modelling to illustrate the spatial patterns of microbial diversity and activity and to relate these patterns to the distribution of pollutants. Spatial distribution of bacterial groups unveiled patterns of niche differentiation regulated by patchy distribution of pollutants and an east-to-west pH gradient at the studied site. Proteobacteria clearly dominated in the hot spots of creosote pollution, whereas the abundance of Actinobacteria, TM7 and Planctomycetes was considerably reduced from the hot spots. The pH preferences of proteobacterial groups dominating in pollution could be recognized by examining the order and family-level responses. Acidobacterial classes came across as generalists in hydrocarbon pollution whose spatial distribution seemed to be regulated solely by the pH gradient. Although the community evenness decreased in the heavily polluted zones, basal respiration and fluorescein diacetate hydrolysis rates were higher, indicating the adaptation of specific indigenous microbial populations to hydrocarbon pollution. Combining the information from the kriged maps of microbial and soil chemistry data provided a comprehensive understanding of the long-term impacts of creosote pollution on the subsurface microbial communities. This study also highlighted the prospect of interpreting taxa-specific spatial patterns and applying them as indicators or proxies for monitoring polluted sites