The Symptom Monitoring with Feedback Trial (SWIFT):protocol for a registry‑based cluster randomised controlled trial in haemodialysis

BACKGROUND: Kidney failure prevalence is increasing worldwide. Haemodialysis, peritoneal dialysis or kidney transplantation are undertaken to extend life with kidney failure. People receiving haemodialysis commonly experience fatigue, pain, nausea, cramping, itching, sleeping difficulties, anxiety and depression. This symptom burden contributes to poor health-related quality of life (QOL) and is a major reason for treatment withdrawal and death. The Symptom monitoring WIth Feedback Trial (SWIFT) will test the hypothesis that regular symptom monitoring with feedback to people receiving haemodialysis and their treating clinical team can improve QOL. METHODS: We are conducting an Australia and New Zealand Dialysis and Transplant (ANZDATA) registry-based cluster randomised controlled trial to determine the clinical- and cost-effectiveness at 12 months, of 3-monthly symptom monitoring using the Integrated Palliative Outcome Scale-Renal (IPOS-Renal) survey with clinician feedback, compared with usual care among adults treated with haemodialysis. Participants complete symptom scoring using a tablet, which are provided to participants and to clinicians. The trial aims to recruit 143 satellite haemodialysis centres, (up to 2400 participants). The primary outcome is change in health-related QOL, as measured by EuroQol 5-Dimension, 5-Level (EQ-5D-5L) instrument. Secondary outcomes include overall survival, symptom severity (including haemodialysis-associated fatigue), healthcare utilisation and cost-effectiveness. DISCUSSION: SWIFT is the first registry-based trial in the Australian haemodialysis population to investigate whether regular symptom monitoring with feedback to participants and clinicians improves QOL. SWIFT is embedded in the ANZDATA Registry facilitating pragmatic recruitment from public and private dialysis clinics, throughout Australia. SWIFT will inform future collection, storage and reporting of patient-reported outcome measures (PROMs) within a clinical quality registry. As the first trial to rigorously estimate the efficacy and cost-effectiveness of routine PROMs collection and reporting in haemodialysis units, SWIFT will provide invaluable information to health services, clinicians and researchers working to improve the lives of those with kidney failure. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12620001061921. Registered on 16 October 2020 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-022-06355-0

Substrate degradation kinetics, microbial diversity, and current efficiency of microbial fuel cells supplied with marine plankton

The decomposition of marine plankton in two-chamber, seawater-filled microbial fuel cells (MFCs) has been investigated and related to resulting chemical changes, electrode potentials, current efficiencies, and microbial diversity. Six experiments were run at various discharge potentials, and a seventh served as an open-circuit control. The plankton consisted of a mixture of freshly captured phytoplankton and zooplankton (0.21 to 1 mm) added at an initial batch concentration of 27.5 mmol liter¯¹ particulate organic carbon (OC). After 56.7 days, between 19.6 and 22.2% of the initial OC remained, sulfate reduction coupled to OC oxidation accounted for the majority of the OC that was degraded, and current efficiencies (of the active MFCs) were between 11.3 and 15.5%. In the open-circuit control cell, anaerobic plankton decomposition (as quantified by the decrease in total OC) could be modeled by three terms: two first-order reaction rate expressions (0.79 day¯¹ and 0.037 day¯¹, at 15°C) and one constant, no-reaction term (representing 10.6% of the initial OC). However, in each active MFC, decomposition rates increased during the third week, lagging just behind periods of peak electricity generation. We interpret these decomposition rate changes to have been due primarily to the metabolic activity of sulfur-reducing microorganisms at the anode, a finding consistent with the electrochemical oxidization of sulfide to elemental sulfur and the elimination of inhibitory effects of dissolved sulfide. Representative phylotypes, found to be associated with anodes, were allied with Delta-, Epsilon-, and Gammaproteobacteria as well as the Flavobacterium-Cytophaga-Bacteroides and Fusobacteria. Based upon these results, we posit that higher current efficiencies can be achieved by optimizing plankton-fed MFCs for direct electron transfer from organic matter to electrodes, including microbial precolonization of high-surface-area electrodes and pulsed flowthrough additions of biomass

The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklin’s exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context.The ExoMars Rosalind Franklin Mission is a partnership between ESA and NASA. The Rosalind Franklin Rover has eight instruments in its ‘Pasteur’ Payload, with Principal Investigators from seven countries all of whom we would like to thank for there support of this project. We would like to acknowledge the following funding bodies, people and institutions supporting the lead authors of this work. We thank the UK Space Agency (UK SA) for funding P. Fawdon, on grants; ST/W002736/1, ST/L00643X/1 and ST/R001413/1, MRB on grants; ST/T002913/1, ST/V001965/1, ST/R001383/1, ST/R001413/1, P. Grindrod on grants; ST/L006456/1, ST/R002355/1, ST/V002678/1 and J. Davis on grants ST/K502388/1, ST/R002355/1, ST/V002678/1 through the ongoing Aurora space exploration programme. C. Orgel was supported by the ESA Research Fellowship Program. Alessandro Frigeri: was funded by the Italian Space Agency (ASI) grant ASI-INAF number 2017-412-H.0 (ExoMars/Ma_MISS) and D. Loizeau was funded by the H2020-COMPET-2015 programme (grant 687302), C. Quantin-Nataf was supported by the French space agency CNES, I. Torres was supported by an ESA Young Graduate Traineeship, A. Nass was supported by Helmholtz Metadata Projects (#ZT-I-PF-3-008). We thank NASA and the HiRISE camera team for data collection support throughout the ExoMars landing site selection and charectorisation process. The USGS for the HiRISE DTM data and maintaining the ISIS and SOCET SET DEM workflows. The authors wish to thank the CaSSIS spacecraft and instrument engineering teams. CaSSIS is a project of the University of Bern and funded through the Swiss Space Office via ESA's PRODEX programme. The instrument hardware development was also supported by the Italian Space Agency (ASI) (ASI-INAF agreement no. I/2020-17-HH.0), INAF/Astronomical Observatory of Padova, and the Space Research Center (CBK) in Warsaw. Support from SGF (Budapest), the University of Arizona (Lunar and Planetary Lab.) and NASA are also gratefully acknowledged. Operations support from the UK Space Agency under grant ST/R003025/1 is also acknowledged. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) Technical support for setup of the Multi-Mission Geographic Information System for concurrent team mapping was provided by F. Calef (III) and T. Soliman at NASA JPL and S. de Witte at ESA-ESTEC.This work was supported by Agencia Estatal de Investigación [grant number ID2019-107442RB-C32, MDM-2017-0737]; Agenzia Spaziale Italiana [grant number 2017-412-H.0]; Bundesministerium für Wirtschaft und Technologie [grant number 50 QX 2002]; Centre National de la Recherche Scientifique; Centre National d’Etudes Spatiales; Euskal Herriko Unibertsitatea [grant number PES21/88]; Istituto Nazionale di Astrofisica [grant number I/ 060/10/0]; Ministerio de Economía y Competitividad [grant number PID2019-104205GB-C21]; Ministry of Science and Higher Education of the Russian Federation [grant number AAAA-A18-118012290370-6]; National Aeronautics and Space Administration [grant number NNX15AH46G]; Norges Forskningsråd [grant number 223272]; European Union's Horizon 2020 (H2020-COMPET-2015) [grant number 687302 (PTAL)]; Sofja Kovalevskaja Award of the Alexander von Humboldt Foundation; MINECO [grant number PID2019-107442RB-C32]; The Open University [grant number Space Strategic Research Area]; European Union's Horizon 2020 research and innovation programme [grant number 776276]; H2020-COMPET-2015 [grant number 687302]; The Research Council of Norway, Centres of Excellence funding scheme [grant number 223272]; Helmholtz Metadata Projects [grant number ZT-I-PF-3-008]; The Research Council of Norway [grant number 223272]; Swiss Space Office via ESA's PRODEX programme; Ines Torres was supported by an ESA Young Graduate Traineeship; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [grant number 200021_197293]; Science and Technology Facilities Council [grant number 1967420]; UK Space Agency [grant number ST/K502388/1, ST/R002355/1, ST/V002678/1]. The ExoMars Rosalind Franklin Mission is a partnership between ESA and NASA. The Rosalind Franklin Rover has eight instruments in its ‘Pasteur’ Payload, with Principal Investigators from seven countries all of whom we would like to thank for there support of this project. We would like to acknowledge the following funding bodies, people and institutions supporting the lead authors of this work. We thank the UK Space Agency (UK SA) for funding P. Fawdon, on grants; ST/W002736/1, ST/L00643X/1 and ST/R001413/1, MRB on grants; ST/T002913/1, ST/V001965/1, ST/R001383/1, ST/R001413/1, P. Grindrod on grants; ST/L006456/1, ST/R002355/1, ST/V002678/1 and J. Davis on grants ST/K502388/1, ST/R002355/1, ST/V002678/1 through the ongoing Aurora space exploration programme. C. Orgel was supported by the ESA Research Fellowship Program. Alessandro Frigeri: was funded by the Italian Space Agency (ASI) grant ASI-INAF number 2017-412-H.0 (ExoMars/Ma_MISS) and D. Loizeau was funded by the H2020-COMPET-2015 programme (grant 687302), C. Quantin-Nataf was supported by the French space agency CNES, I. Torres was supported by an ESA Young Graduate Traineeship, A. Nass was supported by Helmholtz Metadata Projects (#ZT-I-PF-3-008). We thank NASA and the HiRISE camera team for data collection support throughout the ExoMars landing site selection and charectorisation process. The USGS for the HiRISE DTM data and maintaining the ISIS and SOCET SET DEM workflows. The authors wish to thank the CaSSIS spacecraft and instrument engineering teams. CaSSIS is a project of the University of Bern and funded through the Swiss Space Office via ESA's PRODEX programme. The instrument hardware development was also supported by the Italian Space Agency (ASI) (ASI-INAF agreement no. I/2020-17-HH.0), INAF/Astronomical Observatory of Padova, and the Space Research Center (CBK) in Warsaw. Support from SGF (Budapest), the University of Arizona (Lunar and Planetary Lab.) and NASA are also gratefully acknowledged. Operations support from the UK Space Agency under grant ST/R003025/1 is also acknowledged. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) Technical support for setup of the Multi-Mission Geographic Information System for concurrent team mapping was provided by F. Calef (III) and T. Soliman at NASA JPL and S. de Witte at ESA-ESTEC.Peer reviewe

The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklin’s exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context

Kinetics of Reduction of Nitrobenzene and Carbon Tetrachloride at an Iron-Oxide Coated Gold Electrode

The rates of reduction of carbon tetrachloride (CT) and nitrobenzene (NB) by iron-oxide coated gold electrodes were studied to gain insight into the processes that control reduction of groundwater contaminants by zerovalent metal permeable reactive barriers. Fe(III)-oxide films were deposited on gold electrodes with a small fraction of the Fe(III) electrochemically reduced to Fe(II) to investigate the role of Fe(II) in the reduction of the CT and NB. Mass transport to the surface of the oxide film was controlled through use of a well-defined flow-through system similar to a wall-jet electrode. The factors affecting the overall reduction rate were investigated by varying the Fe(II) content in the iron-oxide, controlling mass transport of the electroactive species to the oxide surface, and varying the thickness of the oxide film. The rates of reduction of CT and NB were found to be independent of Fe(II) content in the iron-oxide and were only slightly dependent on the rate of transport to the surface of the oxide under a few sets of reaction conditions. Conversely, the rates of reduction were greatly dependent on the thickness of the oxide film, with the reduction rate decreasing as the oxide thickness increased. Evidence suggests that the location of the reduction reaction for CT and NB is at the gold surface and supports a barrier model for the system studied, in which the oxide film physically impedes direct contact of the electroactive species and the gold electrode, increases the diffusion path length, and creates adsorption sites

U(VI) Adsorption on Natural Iron-coated Sands: Comparison of Approaches for Modeling Adsorption on Heterogeneous Environmental Materials

Adsorption of U(VI) on 6 samples of natural Fe-rich sands from Oyster, VA was studied over a range of U(VI) concentrations (0.1–100 μM), pH values (3–7.6), and dithionite–citrate–bicarbonate (DCB) extractable amounts of Fe (3.1–12.3 μmol/g). Four modeling approaches were applied to represent the U(VI) adsorption data. Model I was a two-site, diffuse double layer, surface complexation model based on data for synthetic ferrihydrite [Geochim. Cosmochim. Acta 58 (1994) 5465–5478]. Considering the magnitude of approximations necessary for application of the laboratory-based model to natural sands, Model I was surprisingly accurate, as determined by the goodness of fit parameter, χ2/N of 53.1–22.2. Model II was based on the reactions and diffuse double layer treatment of Model I, but was calibrated to a portion of U(VI) adsorption data for each sand, and then used to predict adsorption data for the same sand under different experimental conditions. Model II did not increase the accuracy of the predictions made with Model I, χ2/N of 42.4–27.6. Models III and IV were four-site affinity spectrum models, without an explicit electric double layer model or explicit surface hydrolysis reactions. Model III was based on a discrete log K spectrum approach, and Model IV was obtained from adjusting all surface stability constants and site concentrations for all surface sites. Models III and IV represented the U(VI) adsorption data with the greatest accuracy, χ2/Nranged from 13.8 to 4.4. Model I provides evidence supporting the practice of using pure phase thermodynamic reaction constants for describing the adsorption characteristics of environmentally important sorbents in certain simple cases. Yet, affinity spectrum approaches (Models III and IV) become increasingly important as more accurate interpolation of adsorption data is necessary, the sorbent becomes increasingly complex, or the range of experimental conditions expands