Coronavirus Disease 2019-Related Alterations of Total and Anti-Spike IgG Glycosylation in Relation to Age and Anti-Spike IgG Titer

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been affecting the world since January 2020 and has caused millions of deaths. To gain a better insight into molecular changes underlying the COVID-19 disease, we investigated here the N-glycosylation of three immunoglobulin G (IgG) fractions isolated from plasma of 35 severe COVID-19 patients, namely total IgG(1), total IgG(2), and anti-Spike IgG, by means of MALDI-TOF-MS. All analyses were performed at the glycopeptide level to assure subclass- and site-specific information. For each COVID-19 patient, the analyses included three blood withdrawals at different time-points of hospitalization, which allowed profiling longitudinal alterations in IgG glycosylation. The COVID-19 patients presented altered IgG N-glycosylation profiles in all investigated IgG fractions. The most pronounced COVID-19-related changes were observed in the glycosylation profiles of antigen-specific anti-Spike IgG(1). Anti-Spike IgG(1) fucosylation and galactosylation showed the strongest variation during the disease course, with the difference in anti-Spike IgG(1) fucosylation being significantly correlated with patients' age. Decreases in anti-Spike IgG(1) galactosylation and sialylation in the course of the disease were found to be significantly correlated with the difference in anti-Spike IgG plasma concentration. The present findings suggest that patients' age and anti-S IgG abundance might influence IgG N-glycosylation alterations occurring in COVID-19

Elevated impulsivity and impaired decision-making cognition in heavy users of MDMA ("Ecstasy”)

Rationale: In animal studies, the common club drug 3,4-methylendioxymethamphetamine (MDMA, "Ecstasy”) consistently caused a prolonged loss of presynaptic serotonergic neurons, and evidence suggests that MDMA consumption may also affect the human serotonergic system. Serotonin (5-HT) has been implicated in the regulation of impulsivity and such executive functions as decision-making cognition. In fact, MDMA users have shown elevated impulsivity in two studies, but little is known about decision making in drug-free MDMA consumers. Objective: The aim of this study was to examine the cognitive neurotoxicity of MDMA with regard to behavioral impulsivity and decision-making cognition. Methods: Nineteen male, abstinent, heavy MDMA users; 19 male, abstinent cannabis users; and 19 male, drug-naïve controls were examined with the Matching Familiar Figures Test (MFFT) as well as with a Go/No-Go Task (GNG) for impulsivity and with a Gambling Task (GT) for executive functioning. Results: MDMA users showed significantly elevated impulsivity in the MFFT Impulsivity score (I-score), but not in commission errors of the GNG, compared with controls. Cannabis users did not yield altered impulsivity compared with controls. In the GT, MDMA users performed significantly worse than cannabis consumers and controls, whereas cannabis users exhibited the same decision-making capacity as controls. In addition, the I-score as well as the decision-making performance was correlated with measures of MDMA intake. The I-score and the decision-making performance were also correlated. Conclusion: These results suggest that heavy use of MDMA may elevate behavioral impulsivity and impair decision-making cognition possibly mediated by a selective impairment of the 5-HT syste

Report of the JRC’s Descriptor 2 workshop in support to the review of the Commission Decision 2010/477/EU concerning MSFD criteria for assessing Good Environmental Status for NIS

The MSFD workshop on non-indigenous species (NIS, MSFD D2), held in Ispra JRC (10th-11th of September 2015) aimed to provide clear proposals and conclusions on some of the outstanding issues identified in the D2 review manual (May 2015 consultation version: D2 review manual: https://circabc.europa.eu/sd/a/cd4bbd6a-454a-40db-b805-52fb195d4e56/COMDEC_Review_D2_V6.pdf) in the broader context of support to the review of Commission Decision 2010/477/EU. This report is complementing the Commission Decision 2010/477/EU review manual (JRC96884) and presents the result of the scientific and technical review concluding phase 1 of the review of the Commission Decision 2010/477/EU in relation to Descriptor 2. The review has been carried out by the EC JRC together with experts nominated by EU Member States, and has considered contributions from the GES Working Group in accordance with the roadmap set out in the MSFD implementation strategy (agreed on at the 11th CIS MSCG meeting). The main issues addressed and tackled in this workshop’s report are: - Proposed changes in D2 assessment criteria; - Indicators and methodological standards; - GES threshold values and reference points; - Way forward.JRC.H.1-Water Resource

The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing

Robotic manipulation is currently undergoing a profound paradigm shift due to the increasing needs for flexible manufacturing systems, and at the same time, because of the advances in enabling technologies such as sensing, learning, optimization, and hardware. This demands for robots that can observe and reason about their workspace, and that are skillfull enough to complete various assembly processes in weakly-structured settings. Moreover, it remains a great challenge to enable operators for teaching robots on-site, while managing the inherent complexity of perception, control, motion planning and reaction to unexpected situations. Motivated by real-world industrial applications, this paper demonstrates the potential of such a paradigm shift in robotics on the industrial case of an e-Bike motor assembly. The paper presents a concept for teaching and programming adaptive robots on-site and demonstrates their potential for the named applications. The framework includes: (i) a method to teach perception systems onsite in a self-supervised manner, (ii) a general representation of object-centric motion skills and force-sensitive assembly skills, both learned from demonstration, (iii) a sequencing approach that exploits a human-designed plan to perform complex tasks, and (iv) a system solution for adapting and optimizing skills online. The aforementioned components are interfaced through a four-layer software architecture that makes our framework a tangible industrial technology. To demonstrate the generality of the proposed framework, we provide, in addition to the motivating e-Bike motor assembly, a further case study on dense box packing for logistics automation

Elevated impulsivity and impaired decision-making cognition in heavy users of MDMA (“Ecstasy”)

Rationale: In animal studies, the common club drug 3,4-methylendioxymethamphetamine (MDMA, "Ecstasy”) consistently caused a prolonged loss of presynaptic serotonergic neurons, and evidence suggests that MDMA consumption may also affect the human serotonergic system. Serotonin (5-HT) has been implicated in the regulation of impulsivity and such executive functions as decision-making cognition. In fact, MDMA users have shown elevated impulsivity in two studies, but little is known about decision making in drug-free MDMA consumers. Objective: The aim of this study was to examine the cognitive neurotoxicity of MDMA with regard to behavioral impulsivity and decision-making cognition. Methods: Nineteen male, abstinent, heavy MDMA users; 19 male, abstinent cannabis users; and 19 male, drug-naïve controls were examined with the Matching Familiar Figures Test (MFFT) as well as with a Go/No-Go Task (GNG) for impulsivity and with a Gambling Task (GT) for executive functioning. Results: MDMA users showed significantly elevated impulsivity in the MFFT Impulsivity score (I-score), but not in commission errors of the GNG, compared with controls. Cannabis users did not yield altered impulsivity compared with controls. In the GT, MDMA users performed significantly worse than cannabis consumers and controls, whereas cannabis users exhibited the same decision-making capacity as controls. In addition, the I-score as well as the decision-making performance was correlated with measures of MDMA intake. The I-score and the decision-making performance were also correlated. Conclusion: These results suggest that heavy use of MDMA may elevate behavioral impulsivity and impair decision-making cognition possibly mediated by a selective impairment of the 5-HT syste

Report of the JRC’s Descriptor 2 workshop in support to the review of the Commission Decision 2010/477/EU concerning MSFD criteria for assessing Good Environmental Status for NIS

The MSFD workshop on non-indigenous species (NIS, MSFD D2), held in Ispra JRC (10th-11th of September 2015) aimed to provide clear proposals and conclusions on some of the outstanding issues identified in the D2 review manual (May 2015 consultation version: D2 review manual: https://circabc.europa.eu/sd/a/cd4bbd6a-454a-40db-b805-52fb195d4e56/COMDEC_Review_D2_V6.pdf) in the broader context of support to the review of Commission Decision 2010/477/EU. This report is complementing the Commission Decision 2010/477/EU review manual (JRC96884) and presents the result of the scientific and technical review concluding phase 1 of the review of the Commission Decision 2010/477/EU in relation to Descriptor 2. The review has been carried out by the EC JRC together with experts nominated by EU Member States, and has considered contributions from the GES Working Group in accordance with the roadmap set out in the MSFD implementation strategy (agreed on at the 11th CIS MSCG meeting). The main issues addressed and tackled in this workshop’s report are: - Proposed changes in D2 assessment criteria; - Indicators and methodological standards; - GES threshold values and reference points; - Way forwar

The Helmholtz Analytics Toolkit (Heat) and its role in the landscape of massively-parallel scientific Python

When it comes to enhancing exploitation of massive data, machine learning methods are at the forefront of researchers’ awareness. Much less so is the need for, and the complexity of, applying these techniques efficiently across large-scale, memory-distributed data volumes. In fact, these aspects typical for the handling of massive data sets pose major challenges to the vast majority of research communities, in particular to those without a background in high-performance computing. Often, the standard approach involves breaking up and analyzing data in smaller chunks; this can be inefficient and prone to errors, and sometimes it might be inappropriate at all because the context of the overall data set can get lost. The Helmholtz Analytics Toolkit (Heat) library offers a solution to this problem by providing memory-distributed and hardware-accelerated array manipulation, data analytics, and machine learning algorithms in Python. The main objective is to make memory-intensive data analysis possible across various fields of research ---in particular for domain scientists being non-experts in traditional high-performance computing who nevertheless need to tackle data analytics problems going beyond the capabilities of a single workstation. The development of this interdisciplinary, general-purpose, and open-source scientific Python library started in 2018 and is based on collaboration of three institutions (German Aerospace Center DLR, Forschungszentrum Jülich FZJ, Karlsruhe Institute of Technology KIT) of the Helmholtz Association. The pillars of its development are... - ...to enable memory distribution of n-dimensional arrays, - to adopt PyTorch as process-local compute engine (hence supporting GPU-acceleration), - to provide memory-distributed (i.e., multi-node, multi-GPU) array operations and algorithms, optimizing asynchronous MPI-communication (based on mpi4py) under the hood, and - to wrap functionalities in NumPy- or scikit-learn-like API to achieve porting of existing applications with minimal changes and to enable the usage by non-experts in HPC. In this talk we will give an illustrative overview on the current features and capabilities of our library. Moreover, we will discuss its role in the existing ecosystem of distributed computing in Python, and we will address technical and operational challenges in further development

Microbial Activities and Dissolved Organic Matter Dynamics in Oil-Contaminated Surface Seawater from the Deepwater Horizon Oil Spill Site

The Deepwater Horizon oil spill triggered a complex cascade of microbial responses that reshaped the dynamics of heterotrophic carbon degradation and the turnover of dissolved organic carbon (DOC) in oil contaminated waters. Our results from 21-day laboratory incubations in rotating glass bottles (roller bottles) demonstrate that microbial dynamics and carbon flux in oil-contaminated surface water sampled near the spill site two weeks after the onset of the blowout were greatly affected by activities of microbes associated with macroscopic oil aggregates. Roller bottles with oil-amended water showed rapid formation of oil aggregates that were similar in size and appearance compared to oil aggregates observed in surface waters near the spill site. Oil aggregates that formed in roller bottles were densely colonized by heterotrophic bacteria, exhibiting high rates of enzymatic activity (lipase hydrolysis) indicative of oil degradation. Ambient waters surrounding aggregates also showed enhanced microbial activities not directly associated with primary oil-degradation (β-glucosidase; peptidase), as well as a twofold increase in DOC. Concurrent changes in fluorescence properties of colored dissolved organic matter (CDOM) suggest an increase in oil-derived, aromatic hydrocarbons in the DOC pool. Thus our data indicate that oil aggregates mediate, by two distinct mechanisms, the transfer of hydrocarbons to the deep sea: a microbially-derived flux of oil-derived DOC from sinking oil aggregates into the ambient water column, and rapid sedimentation of the oil aggregates themselves, serving as vehicles for oily particulate matter as well as oil aggregate-associated microbial communities