Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

Multi-Vehicle Simulation in Urban Automated Driving: Technical Implementation and Added Benefit

This article investigates the simultaneous interaction between an automated vehicle (AV) and its passenger, and between the same AV and a human driver of another vehicle. For this purpose, we have implemented a multi-vehicle simulation consisting of two driving simulators, one for the AV and one for the manual vehicle. The considered scenario is a road bottleneck with a double-parked vehicle either on one side of the road or on both sides of the road where an AV and a simultaneously oncoming human driver negotiate the right of way. The AV communicates to its passenger via the internal automation human–machine interface (HMI) and it concurrently displays the right of way to the human driver via an external HMI. In addition to the regular encounters, this paper analyzes the effect of an automation failure, where the AV first communicates to yield the right of way and then changes its strategy and passes through the bottleneck first despite oncoming traffic. The research questions the study aims to answer are what methods should be used for the implementation of multi-vehicle simulations with one AV, and if there is an added benefit of this multi-vehicle simulation compared to single-driver simulator studies. The results show an acceptable synchronicity for using traffic lights as basic synchronization and a distance control as the detail synchronization method. The participants had similar passing times in the multi-vehicle simulation compared to a previously conducted single-driver simulation. Moreover, there was a lower crash rate in the multi-vehicle simulation during the automation failure. Concluding the results, the proposed method seems to be an appropriate solution to implement multi-vehicle simulation with one AV. Additionally, multi-vehicle simulation offers a benefit if more than one human affects the interaction within a scenario

From HMI to HMIs: Towards an HMI Framework for Automated Driving

During automated driving, there is a need for interaction between the automated vehicle (AV) and the passengers inside the vehicle and between the AV and the surrounding road users outside of the car. For this purpose, different types of human machine interfaces (HMIs) are implemented. This paper introduces an HMI framework and describes the different HMI types and the factors influencing their selection and content. The relationship between these HMI types and their influencing factors is also presented in the framework. Moreover, the interrelations of the HMI types are analyzed. Furthermore, we describe how the framework can be used in academia and industry to coordinate research and development activities. With the help of the HMI framework, we identify research gaps in the field of HMI for automated driving to be explored in the future

Importance of Defluviitalea raffinosedens for Hydrolytic Biomass Degradation in Co-Culture with Hungateiclostridium thermocellum

Rettenmaier R, Schneider M, Munk B, et al. Importance of Defluviitalea raffinosedens for Hydrolytic Biomass Degradation in Co-Culture with Hungateiclostridium thermocellum. Microorganisms. 2020;8(6): 915.Bacterial hydrolysis of polysaccharides is an important step for the production of sustainable energy, for example during the conversion of plant biomass to methane-rich biogas. Previously, Hungateiclostridium thermocellum was identified as cellulolytic key player in thermophilic biogas microbiomes with a great frequency as an accompanying organism. The aim of this study was to physiologically characterize a recently isolated co-culture of H. thermocellum and the saccharolytic bacterium Defluviitalea raffinosedens from a laboratory-scale biogas fermenter. The characterization focused on cellulose breakdown by applying the measurement of cellulose hydrolysis, production of metabolites, and the activity of secreted enzymes. Substrate degradation and the production of volatile metabolites was considerably enhanced when both organisms acted synergistically. The metabolic properties of H. thermocellum have been studied well in the past. To predict the role of D. raffinosedens in this bacterial duet, the genome of D. raffinosedens was sequenced for the first time. Concomitantly, to deduce the prevalence of D. raffinosedens in anaerobic digestion, taxonomic composition and transcriptional activity of different biogas microbiomes were analyzed in detail. Defluviitalea was abundant and metabolically active in reactor operating at highly efficient process conditions, supporting the importance of this organism for the hydrolysis of the raw substrate

Operando insights into correlating CO coverage and Cu–Au alloying with the selectivity of Au NP-decorated Cu2_2O nanocubes during the electrocatalytic C2_2 reduction

Electrochemical reduction of CO$_2$ (CO2RR) is an attractive technology to reintegrate the anthropogenic CO$_2$ back into the carbon cycle driven by a suitable catalyst. This study employs highly efficient multi-carbon (C$_{2+}$) producing Cu2O nanocubes (NCs) decorated with CO-selective Au nanoparticles (NPs) to investigate the correlation between a high CO surface concentration microenvironment and the catalytic performance. Structure, morphology and near-surface composition are studied via operando X-ray absorption spectroscopy and surface-enhanced Raman spectroscopy, operando high-energy X-ray diffraction as well as quasi in situ X-ray photoelectron spectroscopy. These operando studies show the continuous evolution of the local structure and chemical environment of our catalysts during reaction conditions. Along with its alloy formation, a CO-rich microenvironment as well as weakened average CO binding on the catalyst surface during CO$_2$RR is detected. Linking these findings to the catalytic function, a complex compositional interplay between Au and Cu is revealed in which higher Au loadings primarily facilitate CO formation. Nonetheless, the strongest improvement in C$_{2+}$ formation appears for the lowest Au loadings, suggesting a beneficial role of the Au–Cu atomic interaction for the catalytic function in CO$_2$RR. This study highlights the importance of site engineering and operando investigations to unveil the electrocatalyst's adaptations to the reaction conditions, which is a prerequisite to understand its catalytic behavior