Infinite families of superintegrable systems separable in subgroup coordinates

A method is presented that makes it possible to embed a subgroup separable superintegrable system into an infinite family of systems that are integrable and exactly-solvable. It is shown that in two dimensional Euclidean or pseudo-Euclidean spaces the method also preserves superintegrability. Two infinite families of classical and quantum superintegrable systems are obtained in two-dimensional pseudo-Euclidean space whose classical trajectories and quantum eigenfunctions are investigated. In particular, the wave-functions are expressed in terms of Laguerre and generalized Bessel polynomials.Comment: 19 pages, 6 figure

Diversity of plant assemblages dampens the variability of the growing season phenology in wetland landscapes

Background: The functioning of ecosystems is highly variable through space and time. Climatic and edaphic factors are forcing ecological communities to converge, whereas the diversity of plant assemblages dampens these effects by allowing communities’ dynamics to diverge. This study evaluated whether the growing season phenology of wetland plant communities within landscapes is determined by the climatic/edaphic factors of contrasted regions, by the species richness of plant communities, or by the diversity of plant assemblages. From 2013 to 2016, we monitored the phenology and floristic composition of 118 wetland plant communities across five landscapes distributed along a gradient of edaphic and climatic conditions in the Province of Québec, Canada. Results: The growing season phenology of wetlands was driven by differences among plant assemblage within landscapes, and not by the species richness of each individual community (< 1% of the explained variation). Variation in the growing season length of wetlands reflected the destabilizing effect of climatic and edaphic factors on green-up dates, which is opposed to the dampening effect of plant assemblage diversity on green-down dates. Conclusions: The latter dampening effect may be particularly important in the context of increasing anthropogenic activities, which are predicted to impair the ability of wetlands to adapt to fluctuating environmental conditions. Our findings suggest that stakeholders should not necessarily consider local species-poor plant communities of lower conservation value to the global functioning of wetland ecosystems

Photons as a 21st century reagent

A pharmaceutical industry viewpoint on how the fundamental laws of photochemistry are used to identify the parameters required to implement photochemistry from lab to scale. Parameters such as photon stoichiometry and light intensity are highlighted within to inform future publications

Penalized G-estimation for effect modifier selection in a structural nested mean model for repeated outcomes

Effect modification occurs when the impact of the treatment on an outcome varies based on the levels of other covariates known as effect modifiers. Modeling of these effect differences is important for etiological goals and for purposes of optimizing treatment. Structural nested mean models (SNMMs) are useful causal models for estimating the potentially heterogeneous effect of a time-varying exposure on the mean of an outcome in the presence of time-varying confounding. A data-driven approach for selecting the effect modifiers of an exposure may be necessary if these effect modifiers are a priori unknown and need to be identified. Although variable selection techniques are available in the context of estimating conditional average treatment effects using marginal structural models, or in the context of estimating optimal dynamic treatment regimens, all of these methods consider an outcome measured at a single point in time. In the context of an SNMM for repeated outcomes, we propose a doubly robust penalized G-estimator for the causal effect of a time-varying exposure with a simultaneous selection of effect modifiers and use this estimator to analyze the effect modification in a study of hemodiafiltration. We prove the oracle property of our estimator, and conduct a simulation study for evaluation of its performance in finite samples and for verification of its double-robustness property. Our work is motivated by and applied to the study of hemodiafiltration for treating patients with end-stage renal disease at the Centre Hospitalier de l'Universit\'e de Montr\'eal. We apply the proposed method to investigate the effect heterogeneity of dialysis facility on the repeated session-specific hemodiafiltration outcomes

Nxt1 Is Necessary for the Terminal Step of Crm1-Mediated Nuclear Export

Soluble factors are required to mediate nuclear export of protein and RNA through the nuclear pore complex (NPC). These soluble factors include receptors that bind directly to the transport substrate and regulators that determine the assembly state of receptor–substrate complexes. We recently reported the identification of NXT1, an NTF2-related export factor that stimulates nuclear protein export in permeabilized cells and undergoes nucleocytoplasmic shuttling in vivo (Black, B.E., L. Lévesque, J.M. Holaska, T.C. Wood, and B.M. Paschal. 1999. Mol. Cell. Biol. 19:8616–8624). Here, we describe the molecular characterization of NXT1 in the context of the Crm1-dependent export pathway. We find that NXT1 binds directly to Crm1, and that the interaction is sensitive to the presence of Ran-GTP. Moreover, mutations in NXT1 that reduce binding to Crm1 inhibit the activity of NXT1 in nuclear export assays. We show that recombinant Crm1 and Ran are sufficient to reconstitute nuclear translocation of a Rev reporter protein from the nucleolus to an antibody accessible site on the cytoplasmic side of the NPC. Further progress on the export pathway, including the terminal step of Crm1 and Rev reporter protein release, requires NXT1. We propose that NXT1 engages with the export complex in the nucleoplasm, and that it facilitates delivery of the export complex to a site on the cytoplasmic side of NPC where the receptor and substrate are released into the cytoplasm

Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study

INTRODUCTION: The holistic management of hearing loss (HL) requires an understanding of factors that predict hearing aid (HA) use and benefit beyond the acoustics of listening environments. Although several predictors have been identified, no study has explored the role of audiological, cognitive, behavioural and physiological data nor has any study collected real-time HA data. This study will collect ‘big data’, including retrospective HA logging data, prospective clinical data and real-time data via smart HAs, a mobile application and biosensors. The main objective is to enable the validation of the EVOTION platform as a public health policy-making tool for HL. METHODS AND ANALYSIS: This will be a big data international multicentre study consisting of retrospective and prospective data collection. Existing data from approximately 35 000 HA users will be extracted from clinical repositories in the UK and Denmark. For the prospective data collection, 1260 HA candidates will be recruited across four clinics in the UK and Greece. Participants will complete a battery of audiological and other assessments (measures of patient-reported HA benefit, mood, cognition, quality of life). Patients will be offered smart HAs and a mobile phone application and a subset will also be given wearable biosensors, to enable the collection of dynamic real-life HA usage data. Big data analytics will be used to detect correlations between contextualised HA usage and effectiveness, and different factors and comorbidities affecting HL, with a view to informing public health decision-making. ETHICS AND DISSEMINATION: Ethical approval was received from the London South East Research Ethics Committee (17/LO/0789), the Hippokrateion Hospital Ethics Committee (1847) and the Athens Medical Center’s Ethics Committee (KM140670). Results will be disseminated through national and international events in Greece and the UK, scientific journals, newsletters, magazines and social media. Target audiences include HA users, clinicians, policy-makers and the general public. TRIAL REGISTRATION NUMBER: NCT03316287; Pre-results