Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms

We push the boundaries of electronic structure-based ab-initio molecular dynamics (AIMD) beyond 100 million atoms. This scale is otherwise barely reachable with classical force-field methods or novel neural network and machine learning potentials. We achieve this breakthrough by combining innovations in linear-scaling AIMD, efficient and approximate sparse linear algebra, low and mixed-precision floating-point computation on GPUs, and a compensation scheme for the errors introduced by numerical approximations. The core of our work is the non-orthogonalized local submatrix method (NOLSM), which scales very favorably to massively parallel computing systems and translates large sparse matrix operations into highly parallel, dense matrix operations that are ideally suited to hardware accelerators. We demonstrate that the NOLSM method, which is at the center point of each AIMD step, is able to achieve a sustained performance of 324 PFLOP/s in mixed FP16/FP32 precision corresponding to an efficiency of 67.7% when running on 1536 NVIDIA A100 GPUs

Nitric oxide-independent vasodilator rescues heme-oxidized soluble guanylate cyclase from proteosomal degradation

Background: Nitric oxide (NO) is an essential vasodilator. In vascular diseases, oxidative stress attenuates NO signaling by both chemical scavenging of free NO and oxidation and down-regulation of its major intracellular receptor, the alpha/beta heterodimeric heme-containing soluble guanylate cyclase (sGC). Oxidation can also induce loss of sGC's heme and responsiveness to NO. Results: sGC activators such as BAY 58-2667 bind to oxidized/heme-free sGC and reactivate the enzyme to exert disease-specific vasodilation. Here we show that oxidation-induced down-regulation of sGC protein extends to isolated blood vessels. Mechanistically, degradation was triggered through sGC ubiquitination and proteasomal degradation. The heme-binding site ligand, BAY 58-2667, prevented sGC ubiquitination and stabilized both alpha and beta subunits. Conclusion: Collectively, our data establish oxidation-ubiquitination of sGC as a modulator of NO/cGMP signaling and point to a new mechanism of action for sGC activating vasodilators by stabilizing their receptor, oxidized/heme-free sGC

AgeWell.de – study protocol of a pragmatic multi-center cluster-randomized controlled prevention trial against cognitive decline in older primary care patients

Background: In the absence of treatment options, the WHO emphasizes the identification of effective prevention strategies as a key element to counteract the dementia epidemic. Regarding the complex nature of dementia, trials simultaneously targeting multiple risk factors should be particularly effective for prevention. So far, however, only few such multi-component trials have been launched, but yielding promising results. In Germany, comparable initiatives are lacking, and translation of these complex interventions into routine care was not yet done. Therefore, AgeWell.de will be conducted as the first multi-component prevention trial in Germany which is closely linked to the primary care setting. Methods: AgeWell.de will be designed as a multi-centric, cluster-randomized controlled multi-component prevention trial. Participants will be older community-dwelling general practitioner (GP) patients (60–77 years; n = 1,152) with increased dementia risk according to CAIDE (Cardiovascular Risk Factors, Aging, and Incidence of Dementia) Dementia Risk Score. Recruitment will take place at 5 study sites across Germany. GP practices will be randomized to either intervention A (advanced) or B (basic). GPs will be blinded to their respective group assignment, as will be the statistician conducting the randomization. The multi-component intervention (A) includes nutritional counseling, physical activity, cognitive training, optimization of medication, management of vascular risk factors, social activity, and, if necessary, further specific interventions targeting grief and depression. Intervention B includes general health advice on the intervention components and GP treatment as usual. We hypothesize that over the 2-year follow-up period the intervention group A will benefit significantly from the intervention program in terms of preserved cognitive function/delayed cognitive decline (primary outcome), and other relevant (secondary) outcomes (e.g. quality of life, social activities, depressive symptomatology, cost-effectiveness). Discussion: AgeWell.de will be the first multi-component trial targeting risk of cognitive decline in older adults in Germany. Compared to previous trials, AgeWell.de covers an even broader set of interventions suggested to be beneficial for the intended outcomes. The findings will add substantial knowledge on modifiable lifestyle factors to prevent or delay cognitive decline. Trial registration: German Clinical Trials Register (reference number: DRKS00013555)

Présentation du dossier « metal studies » : la naissance d'un champ

La rédaction de Volume ! voulait proposer, avec ce dossier de notes de lectures, un panorama de la recherche récente en metal studies, comme il est devenu commun d’appeler ce champ de recherches aujourd’hui au sein de la communauté internationale. Un domaine encore quasi-inexistant au début de ce siècle en sciences sociales (on n’employait d’ailleurs pas ce terme), mais qui se développe de manière exponentielle depuis 2008 au niveau mondial. Preuve en est le récent colloque « Heavy metal and ..

Mutations in KEOPS-Complex Genes Cause Nephrotic Syndrome with Primary Microcephaly

Galloway-Mowat syndrome (GAMOS) is an autosomal-recessive disease characterized by the combination of early-onset nephrotic syndrome (SRNS) and microcephaly with brain anomalies. Here we identified recessive mutations in OSGEP, TP53RK, TPRKB, and LAGE3, genes encoding the four subunits of the KEOPS complex, in 37 individuals from 32 families with GAMOS. CRISPR-Cas9 knockout in zebrafish and mice recapitulated the human phenotype of primary microcephaly and resulted in early lethality. Knockdown of OSGEP, TP53RK, or TPRKB inhibited cell proliferation, which human mutations did not rescue. Furthermore, knockdown of these genes impaired protein translation, caused endoplasmic reticulum stress, activated DNA-damage-response signaling, and ultimately induced apoptosis. Knockdown of OSGEP or TP53RK induced defects in the actin cytoskeleton and decreased the migration rate of human podocytes, an established intermediate phenotype of SRNS. We thus identified four new monogenic causes of GAMOS, describe a link between KEOPS function and human disease, and delineate potential pathogenic mechanisms

Condition Monitoring and Cloud-based Energy Analysis for Autonomous Mobile Manipulation - Smart Factory Concept with LUHbots

In this paper, a smart factory concept for autonomous mobile robots is presented. The main purpose is to increase productivity of the transport in machine-floor. It is based on advanced methods for failure handling and prevention, leading to increased robustness, less downtime and less effort in maintenance [1], [2]. Therefore, condition data and states of the robot are collected by Robot Operation System (ROS) and transferred to a factory hub (server). The collected data, e.g. voltages, currents, set points, velocities and accelerations are used to identify important system parameters, e.g. moving masses and friction parameters to enable the proposed smart factory concept. Further aim is to let the factory hub control a group of mobile robots using a self-organizing algorithm for different tasks. Due to the increasing customization of products causing smaller lot sizes [3], manufacturers of mobile robotic production systems have developed a diversity of flexible robots [4], [5], [6], [7], [8]. Mobile robots inside the production line allow for collecting and evaluation of system-inherent data e.g. handling and transportation time, wheel friction, workpieces mass, center of gravity and energy consumption during trajectory execution. In general, mobile robots are electrically driven. Hence, an estimation of the battery state is essential in order to automatically plan charging cycles and to organize and optimize the cooperation behavior of a group of mobile robots. In this proposed approach, mobile robots are equipped with a measurement system and connected via Bluetooth to a factory hub, providing monitoring, analyzing and planning tools. The battery states of all robots are considered in the process planning. The robots are based on the KUKA youBot, equipped with a soft gripper and a RealSense camera. A condition monitoring system measures the energy consumption of all components and transfers the information to the factory hub. The state of charge limits the number of executable operations. Therefore, in a first step the power consumption of all individual consumers is captured, e.g. EC-Maxxon base motors, PC, gripper, camera and five-axis arm. Experimental results show, that the youBot requires 46 W in standstill plus the drive power depending on the movement. Here, the results for mobile manipulation in industrial scenarios during preparation for the RoboCup@Work 2016 will be presented. The transfer of raw measurement data to the hub is shown, as well as the proposed algorithms allowing for range prediction and optimized set point generation. The concept provides excellent capability in data collection, analysis of existing production and production planning