Inducible forebrain-specific ablation of the transcription factor Creb during adulthood induces anxiety but no spatial/contextual learning deficits

The cyclic AMP (cAMP)-response element binding protein (CREB) is an activity-dependent transcription factor playing a role in synaptic plasticity, learning and memory, and emotional behavior. However, the impact of Creb ablation on rodent behavior is vague as e.g. memory performance of different Creb mutant mice depends on the specific type of mutation per se but additionally on the background and learning protocol differences. Here we present the first targeted ablation of CREB induced during adulthood selectively in principal forebrain neurons in a pure background strain of C57BL/6 mice. All hippocampal principal neurons exhibited lack of CREB expression. Mutant mice showed a severe anxiety phenotype in the openfield and novel object exploration test as well as in the Dark-Light Box Test, but unaltered hippocampus-dependent long-term memory in the Morris water maze and in context dependent fear conditioning. On the molecular level, CREB ablation led to CREM up regulation in the hippocampus and frontal cortex which may at least in part compensate for the loss of CREB. BDNF, a postulated CREB target gene, was down regulated in the frontal lobe but not in the hippocampus; neurogenesis remained unaltered. Our data indicate that in the adult mouse forebrain the late onset of CREB ablation can, in case of memory functionality, be compensated for and is not essential for memory consolidation and retrieval during adulthood. In contrast, the presence of CREB protein during adulthood seems to be pivotal for the regulation of emotional behavior

Automated experience-based learning for plug and produce assembly systems

YesThis paper presents a self-learning technique for adapting modular automated assembly systems. The technique consists of automatically analysing sensor data and acquiring experience on the changes made on an assembly system to cope with new production requirements or to recover from disruptions. Experience is generalised into operational knowledge that is used to aid engineers in future adaptations by guiding them throughout the process. At each step, applicable changes are presented and ranked based on: (1) similarity between the current context and those in the experience base; (2) estimate of the impact on system performance. The experience model and the self-learning technique reflect the modular structure of the assembly machine and are particularly suitable for plug and produce systems, which are designed to offer high levels of self-organisation and adaptability. Adaptations can be performed and evaluated at different levels: from the smallest pluggable unit to the whole assembly system. Knowledge on individual modules can be reused when modules are plugged into other systems. An experimental evaluation has been conducted on an industrial case study and the results show that, with experience-based learning, adaptations of plug and produce systems can be performed in a shorter time.European Union [grant number 314762]

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

Evaluation of the ‘jumping to conclusions’ bias in different subgroups of the at-risk mental state: from cognitive basic symptoms to UHR criteria

Background. Patients with psychosis display the so-called 'Jumping to Conclusions' bias (JTC) - a tendency for hasty decision-making in probabilistic reasoning tasks. So far, only a few studies have evaluated the JTC bias in 'at-risk mental state' (ARMS) patients, specifically in ARMS samples fulfilling 'ultra-high risk' (UHR) criteria, thus not allowing for comparisons between different ARMS subgroups. Method. In the framework of the PREVENT (secondary prevention of schizophrenia) study, a JTC task was applied to 188 patients either fulfilling UHR criteria or presenting with cognitive basic symptoms (BS). Similar data were available for 30 healthy control participants matched for age, gender, education and premorbid verbal intelligence. ARMS patients were identified by the Structured Interview for Prodromal Symptoms (SIPS) and the Schizophrenia Proneness Instrument - Adult Version (SPI-A). Results. The mean number of draws to decision (DTD) significantly differed between ARM - subgroups: UHR patients made significantly less draws to make a decision than ARMS patients with only cognitive BS. Furthermore, UHR patients tended to fulfil behavioural criteria for JTC more often than BS patients. In a secondary analysis, ARMS patients were much hastier in their decision-making than controls. In patients, DTD was moderately associated with positive and negative symptoms as well as disorganization and excitement. Conclusions. Our data indicate an enhanced JTC bias in the UHR group compared to ARMS patients with only cognitive BS. This underscores the importance of reasoning deficits within cognitive theories of the developing psychosis. Interactions with the liability to psychotic transitions and therapeutic interventions should be unravelled in longitudinal studies

Heparanase: a target for drug discovery in cancer and inflammation

The remodelling of the extracellular matrix (ECM) has been shown to be highly upregulated in cancer and inflammation and is critically linked to the processes of invasion and metastasis. One of the key enzymes involved in specifically degrading the heparan sulphate (HS) component of the ECM is the endo-β-glucuronidase enzyme heparanase. Processing of HS by heparanase releases both a host of bioactive growth factors anchored within the mesh of the ECM as well as defined fragments of HS capable of promoting cellular proliferation. The finding that heparanase is elevated in a wide variety of tumor types and is subsequently linked to the development of pathological processes has led to an explosion of therapeutic strategies to inhibit its enzyme activity. So far only one compound, the sulphated oligosaccharide PI88, which both inhibits heparanase activity and has effects on growth factor binding has reached clinical trials where it has shown to have promising efficacy. The scene has clearly been set however for a new generation of compounds, either specific to the enzyme or with dual roles, to emerge from the lab and enter the clinic. The aim of this review is to describe the current drug discovery status of small molecule, sugar and neutralising antibody inhibitors of heparanase enzyme activity. Potential strategies will also be discussed on the selection of suitable biomarker strategies for specific monitoring of in vivo heparanase inhibition which will be crucial for both animal model and clinical trial testing