Eco-evolutionary dynamics on deformable fitness landscapes

Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem. We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner. We observe that this model can exhibit either of the two behavioural modes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change. We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution

A novel formulation of inhaled sodium cromoglicate (PA101) in idiopathic pulmonary fibrosis and chronic cough: a randomised, double-blind, proof-of-concept, phase 2 trial

Background Cough can be a debilitating symptom of idiopathic pulmonary fibrosis (IPF) and is difficult to treat. PA101 is a novel formulation of sodium cromoglicate delivered via a high-efficiency eFlow nebuliser that achieves significantly higher drug deposition in the lung compared with the existing formulations. We aimed to test the efficacy and safety of inhaled PA101 in patients with IPF and chronic cough and, to explore the antitussive mechanism of PA101, patients with chronic idiopathic cough (CIC) were also studied. Methods This pilot, proof-of-concept study consisted of a randomised, double-blind, placebo-controlled trial in patients with IPF and chronic cough and a parallel study of similar design in patients with CIC. Participants with IPF and chronic cough recruited from seven centres in the UK and the Netherlands were randomly assigned (1:1, using a computer-generated randomisation schedule) by site staff to receive PA101 (40 mg) or matching placebo three times a day via oral inhalation for 2 weeks, followed by a 2 week washout, and then crossed over to the other arm. Study participants, investigators, study staff, and the sponsor were masked to group assignment until all participants had completed the study. The primary efficacy endpoint was change from baseline in objective daytime cough frequency (from 24 h acoustic recording, Leicester Cough Monitor). The primary efficacy analysis included all participants who received at least one dose of study drug and had at least one post-baseline efficacy measurement. Safety analysis included all those who took at least one dose of study drug. In the second cohort, participants with CIC were randomly assigned in a study across four centres with similar design and endpoints. The study was registered with ClinicalTrials.gov (NCT02412020) and the EU Clinical Trials Register (EudraCT Number 2014-004025-40) and both cohorts are closed to new participants. Findings Between Feb 13, 2015, and Feb 2, 2016, 24 participants with IPF were randomly assigned to treatment groups. 28 participants with CIC were enrolled during the same period and 27 received study treatment. In patients with IPF, PA101 reduced daytime cough frequency by 31·1% at day 14 compared with placebo; daytime cough frequency decreased from a mean 55 (SD 55) coughs per h at baseline to 39 (29) coughs per h at day 14 following treatment with PA101, versus 51 (37) coughs per h at baseline to 52 (40) cough per h following placebo treatment (ratio of least-squares [LS] means 0·67, 95% CI 0·48–0·94, p=0·0241). By contrast, no treatment benefit for PA101 was observed in the CIC cohort; mean reduction of daytime cough frequency at day 14 for PA101 adjusted for placebo was 6·2% (ratio of LS means 1·27, 0·78–2·06, p=0·31). PA101 was well tolerated in both cohorts. The incidence of adverse events was similar between PA101 and placebo treatments, most adverse events were mild in severity, and no severe adverse events or serious adverse events were reported. Interpretation This study suggests that the mechanism of cough in IPF might be disease specific. Inhaled PA101 could be a treatment option for chronic cough in patients with IPF and warrants further investigation

Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study

Background The impact of COVID-19 on physical and mental health and employment after hospitalisation with acute disease is not well understood. The aim of this study was to determine the effects of COVID-19-related hospitalisation on health and employment, to identify factors associated with recovery, and to describe recovery phenotypes. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a multicentre, long-term follow-up study of adults (aged ≥18 years) discharged from hospital in the UK with a clinical diagnosis of COVID-19, involving an assessment between 2 and 7 months after discharge, including detailed recording of symptoms, and physiological and biochemical testing. Multivariable logistic regression was done for the primary outcome of patient-perceived recovery, with age, sex, ethnicity, body-mass index, comorbidities, and severity of acute illness as covariates. A post-hoc cluster analysis of outcomes for breathlessness, fatigue, mental health, cognitive impairment, and physical performance was done using the clustering large applications k-medoids approach. The study is registered on the ISRCTN Registry (ISRCTN10980107). Findings We report findings for 1077 patients discharged from hospital between March 5 and Nov 30, 2020, who underwent assessment at a median of 5·9 months (IQR 4·9–6·5) after discharge. Participants had a mean age of 58 years (SD 13); 384 (36%) were female, 710 (69%) were of white ethnicity, 288 (27%) had received mechanical ventilation, and 540 (50%) had at least two comorbidities. At follow-up, only 239 (29%) of 830 participants felt fully recovered, 158 (20%) of 806 had a new disability (assessed by the Washington Group Short Set on Functioning), and 124 (19%) of 641 experienced a health-related change in occupation. Factors associated with not recovering were female sex, middle age (40–59 years), two or more comorbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial but only weakly associated with the severity of acute illness. Four clusters were identified with different severities of mental and physical health impairment (n=767): very severe (131 patients, 17%), severe (159, 21%), moderate along with cognitive impairment (127, 17%), and mild (350, 46%). Of the outcomes used in the cluster analysis, all were closely related except for cognitive impairment. Three (3%) of 113 patients in the very severe cluster, nine (7%) of 129 in the severe cluster, 36 (36%) of 99 in the moderate cluster, and 114 (43%) of 267 in the mild cluster reported feeling fully recovered. Persistently elevated serum C-reactive protein was positively associated with cluster severity. Interpretation We identified factors related to not recovering after hospital admission with COVID-19 at 6 months after discharge (eg, female sex, middle age, two or more comorbidities, and more acute severe illness), and four different recovery phenotypes. The severity of physical and mental health impairments were closely related, whereas cognitive health impairments were independent. In clinical care, a proactive approach is needed across the acute severity spectrum, with interdisciplinary working, wide access to COVID-19 holistic clinical services, and the potential to stratify care. Funding UK Research and Innovation and National Institute for Health Research

Maternal Embryonic Leucine Zipper Kinase: Key Kinase for Stem Cell Phenotype in Glioma and Other Cancers

Maternal embryonic leucine zipper kinase (MELK) is a member of the snf1/AMPK family of protein Serine/Threonine kinases that has recently gained significant attention in the stem cell and cancer biology field. Recent studies suggest that activation of this kinase is tightly associated with extended survival and accelerated proliferation of cancer stem cells (CSCs) in various organs. Overexpression of MELK has been noted in various cancers, including colon, breast, ovaries, pancreas, prostate, and brain, making the inhibition of MELK an attractive therapeutic strategy for a variety of cancers. In the experimental cancer models, depletion of MELK by RNA interference or small molecule inhibitors induces apoptotic cell death of cancer stem cells derived from glioblastoma and breast cancer, both in vitro and in vivo. Mechanism of action of MELK includes, yet may not be restricted to, direct binding and activation of the oncogenic transcription factors c-JUN and FOXM1 in cancer cells but not in the normal counterparts. Following these pre-clinical studies, the Phase I clinical trial for advanced cancers with OTS167 started in 2013, as the first-in-class MELK inhibitor. This review summarizes the current molecular understanding of MELK and the recent pre-clinical studies about MELK as a cancer therapeutic target

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Tiand nehave been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks

Runaway electron beam control

Post-disruption runaway electron (RE) beams in tokamaks with large current can cause deep melting of the vessel and are one of the major concerns for ITER operations. Consequently, a considerable effort is provided by the scientific community in order to test RE mitigation strategies. We present an overview of the results obtained at FTU and TCV controlling the current and position of RE beams to improve safety and repeatability of mitigation studies such as massive gas (MGI) and shattered pellet injections (SPI). We show that the proposed RE beam controller (REB-C) implemented at FTU and TCV is effective and that current reduction of the beam can be performed via the central solenoid reducing the energy of REs, providing an alternative/parallel mitigation strategy to MGI/SPI. Experimental results show that, meanwhile deuterium pellets injected on a fully formed RE beam are ablated but do not improve RE energy dissipation rate, heavy metals injected by a laser blow off system on low-density flat-top discharges with a high level of RE seeding seem to induce disruptions expelling REs. Instabilities during the RE beam plateau phase have shown to enhance losses of REs, expelled from the beam core. Then, with the aim of triggering instabilities to increase RE losses, an oscillating loop voltage has been tested on RE beam plateau phase at TCV revealing, for the first time, what seems to be a full conversion from runaway to ohmic current. We finally report progresses in the design of control strategies at JET in view of the incoming SPI mitigation experiments

Comparison of runaway electron generation parameters in small, medium-sized and large tokamaks - A survey of experiments in COMPASS, TCV, ASDEX-Upgrade and JET

This paper presents a survey of the experiments on runaway electrons (RE) carried out recently in frames of EUROFusion Consortium in different tokamaks: COMPASS, ASDEX-Upgrade, TCV and JET. Massive gas injection (MGI) has been used in different scenarios for RE generation in small and medium-sized tokamaks to elaborate the most efficient and reliable ones for future RE experiments. New data on RE generated at disruptions in COMPASS and ASDEX-Upgrade was collected and added to the JET database. Different accessible parameters of disruptions, such as current quench rate, conversion rate of plasma current into runaways, etc have been analysed for each tokamak and compared to JET data. It was shown, that tokamaks with larger geometrical sizes provide the wider limits for spatial and temporal variation of plasma parameters during disruptions, thus extending the parameter space for RE generation. The second part of experiments was dedicated to study of RE generation in stationary discharges in COMPASS, TCV and JET. Injection of Ne/Ar have been used to mock-up the JET MGI runaway suppression experiments. Secondary RE avalanching was identified and quantified for the first time in the TCV tokamak in RE generating discharges after massive Ne injection. Simulations of the primary RE generation and secondary avalanching dynamics in stationary discharges has demonstrated that RE current fraction created via avalanching could achieve up to 70-75% of the total plasma current in TCV. Relaxations which are reminiscent the phenomena associated to the kinetic instability driven by RE have been detected in RE discharges in TCV. Macroscopic parameters of RE dominating discharges in TCV before and after onset of the instability fit well to the empirical instability criterion, which was established in the early tokamaks and examined by results of recent numerical simulations