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A remarkable part of children’ s development and education happens in educational institutions. Acoustic environments in these institutions are usually highly complex and noisy, hence it is demanding to identify relevant target speakers and to ignore irrelevant sounds. Previous research has analyzed auditory selective attention in adults, both in dichotic and binaural listening environments. Until now, there is little knowledge of auditory selective attention in children. In the present work, the original paradigm was adapted by using a task suited for children which included child-oriented elements. Further, the subject’s anthropometric sizes were considered for an aurally-accurate reproduction of the acoustic scene. Twenty-four adults and twenty-four children participated in an experiment on auditory selective attention. Noise and noise-free conditions and various target-distractor distributions in the room were analyzed among others. The result of this experiment revealed significant differences between adults and children, especially in the way auditory attention was influenced by noise.
Cannabis is the most commonly used illicit drug in the world. However, because of a changing legal landscape and rising interest in therapeutic utility, there is an increasing trend in (long-term) use and possibly cannabis impairment. Importantly, a growing body of evidence suggests that regular cannabis users develop tolerance to the impairing, as well as the rewarding, effects of the drug. However, the neuroadaptations that may underlie cannabis tolerance remain unclear. Therefore, this double-blind, randomized, placebo-controlled, cross-over study assessed the acute influence of cannabis on the brain and behavioral outcomes in two distinct cannabis user groups. Twelve occasional and 12 chronic cannabis users received acute doses of cannabis (300-μg/kg delta-9-tetrahydrocannabinol) and placebo and underwent ultrahigh field functional magnetic resonance imaging and magnetic resonance spectroscopy. In occasional users, cannabis induced significant neurometabolic alterations in reward circuitry, namely, decrements in functional connectivity and increments in striatal glutamate concentrations, which were associated with increases in subjective high and decreases in performance on a sustained attention task. Such changes were absent in chronic users. The finding that cannabis altered circuitry and distorted behavior in occasional, but not chronic users, suggests reduced responsiveness of the reward circuitry to cannabis intoxication in chronic users. Taken together, the results suggest a pharmacodynamic mechanism for the development of tolerance to cannabis impairment, of which is important to understand in the context of the long-term therapeutic use of cannabis-based medications, as well as in the context of public health and safety of cannabis use when performing day-to-day operations.
Cannabis is the most commonly used illicit drug in the world. However due to a changing legal landscape, and rising interest in therapeutic utility, there is an increasing trend in (long-term) use and possibly, cannabis impairment. Importantly, a growing body of evidence suggests regular cannabis users develop tolerance to the impairing, as well as the rewarding, effects of the drug. However, the neuroadaptations that may underlie cannabis tolerance remain unclear. Therefore, this double-blind, randomized, placebo controlled, cross-over study assessed the acute influence of cannabis on brain and behavioral outcomes in two distinct cannabis user groups. Twelve occasional (OUs) and 12 chronic (CUs) cannabis users received acute doses of cannabis (300 μg/kg THC) and placebo, and underwent ultra-high field functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS). In OUs, cannabis induced significant neurometabolic alterations in reward circuitry, namely decrements in functional connectivity and increments in striatal glutamate concentrations, which were associated with increases in subjective high and decreases in performance on a sustained attention task. Such changes were absent in CUs. The finding that cannabis altered circuitry and distorted behavior in OUs, but not CUs, suggests reduced responsiveness of the reward circuitry to cannabis intoxication in chronic users Taken together, the results suggest a pharmacodynamic mechanism for the development of tolerance to cannabis impairment.
Ecophysiological studies on Antarctic cryptophytes to assess whether climatic changes such as ocean acidification and enhanced stratification affect their growth in Antarctic coastal waters in the future are lacking so far. This is the first study that investigated the combined effects of increasing availability of pCO2 (400 and 1000 µatm) and irradiance (20, 200 and 500 μmol photons m−2 s −1) on growth, elemental composition and photophysiology of the Antarctic cryptophyte Geminigera cryophila. Under ambient pCO2, this species was characterized by a pronounced sensitivity to increasing irradiance with complete growth inhibition at the highest light intensity. Interestingly, when grown under high pCO2 this negative light effect vanished and it reached highest rates of growth and particulate organic carbon production at the highest irradiance compared to the other tested experimental conditions. Our results for G. cryophila reveal beneficial effects of ocean acidification in conjunction with enhanced irradiance on growth and photosynthesis. Hence, cryptophytes such as G. cryophila may be potential winners of climate change, potentially thriving better in more stratified and acidic coastal waters and contributing in higher abundance to future phytoplankton assemblages of coastal Antarctic waters.
Highlights
• The goal was to assess the intra- and inter-scanner reproducibility of qMRI data.
• Mean scan-rescan variations were not exceeding 2.14%.
• Mean inter-scanner model deviations were not exceeding 5.21%.
• Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low.
Abstract
Background: Quantitative MRI (qMRI) techniques allow assessing cerebral tissue properties. However, previous studies on the accuracy of quantitative T1 and T2 mapping reported a scanner model bias of up to 10% for T1 and up to 23% for T2. Such differences would render multi-centre qMRI studies difficult and raise fundamental questions about the general precision of qMRI. A problem in previous studies was that different methods were used for qMRI parameter mapping or for measuring the transmitted radio frequency field B1 which is critical for qMRI techniques requiring corrections for B1 non-uniformities.
Aims: The goal was to assess the intra- and inter-scanner reproducibility of qMRI data at 3 T, using two different scanner models from the same vendor with exactly the same multiparametric acquisition protocol.
Methods: Proton density (PD), T1, T2* and T2 mapping was performed on healthy subjects and on a phantom, performing each measurement twice for each of two scanner models. Although the scanners had different hardware and software versions, identical imaging sequences were used for PD, T1 and T2* mapping, adapting the codes of an existing protocol on the older system line by line to match the software version of the newer scanner. For T2-mapping, the respective manufacturer’s sequence was used which depended on the software version. However, system-dependent corrections were carried out in this case. Reproducibility was assessed by average values in regions of interest.
Results: Mean scan-rescan variations were not exceeding 2.14%, with average values of 1.23% and 1.56% for the new and old system, respectively. Inter-scanner model deviations were not exceeding 5.21% with average values of about 2.2–3.8% for PD, 2.5–3.0% for T2*, 1.6–3.1% for T1 and 3.3–5.2% for T2.
Conclusions: Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low. The level of systematic differences reported in this work may help to interpret multi-centre data.
Objective: Randomized trials have shown that concomitant methotrexate (MTX) augments the effectiveness of tumour necrosis factor (TNF) inhibitors in rheumatoid arthritis (RA), but its benefit in psoriatic arthritis (PsA) has not been demonstrated. The goal of this study was to examine whether the impact of concomitant MTX on therapeutic outcomes in patients with PsA was similar to its effects in RA.
Methods: We used data from highly comparable and concurrent observational studies of patients with PsA (N = 1424) or RA (N = 3148) who initiated adalimumab therapy during routine clinical care. The 28-joint Disease Activity Score (DAS28) and patient-reported pain scores were evaluated in patients who received 24 months of continuous treatment with adalimumab monotherapy or adalimumab + MTX and in patients who initiated or stopped concomitant MTX during ongoing adalimumab therapy.
Results: Twenty-four months of continuous treatment with adalimumab + MTX was superior to adalimumab monotherapy in RA patients, while no significant difference was observed in patients with PsA. RA patients who added MTX during the study showed significant individual improvements in DAS28 and pain scores at 6 months after the change in therapy, while those who removed MTX had slight increases in disease activity. In contrast, in patients with PsA, neither initiation nor removal of MTX during continuous adalimumab therapy had a significant effect on therapeutic outcomes.
Conclusion: Addition of MTX to adalimumab confers further therapeutic benefit in patients with RA, but not in those with PsA, suggesting differences in MTX effects in these two patient populations.
Clinicaltrials.gov NCT01078090, NCT01077258, NCT01111240
We investigate the role of the Pauli Exclusion Principle (PEP) for light nuclei, at the examples of 12C and 16O. We show that ignoring the PEP does lead not only to a too dense spectrum at low energy but also to a wrong grouping into bands. Using a geometrical mapping, a triangular structure for 12C and a tetrahedral structure in 16O in the ground state is obtained by using the indistinguishably of the α-particles.
Based on the positive results of the 0.63 m unmodulated 325 MHz Ladder-RFQ prototype from 2013 to 2016 [1, 2], a modulated 3.3m Ladder-RFQ (s. Fig. 1) has been designed and built for the acceleration of up to 100 mA protons from 95 keV to 3.0 MeV at the FAIR p-Linac [3, 4]. In this paper, we will show the results of manufacturing as well as low level RF measurements of the Ladder-RFQ including flatness and frequency tuning.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
In fungi, the mitochondrial respiratory chain complexes (complexes I–IV) are responsible for oxidative phosphorylation, as in higher eukaryotes. Cryo-EM was used to identify a 200 kDa membrane protein from Neurospora crassa in lipid nanodiscs as cytochrome c oxidase (complex IV) and its structure was determined at 5.5 Å resolution. The map closely resembles the cryo-EM structure of complex IV from Saccharomyces cerevisiae. Its ten subunits are conserved in S. cerevisiae and Bos taurus, but other transmembrane subunits are missing. The different structure of the Cox5a subunit is typical for fungal complex IV and may affect the interaction with complex III in a respiratory supercomplex. Additional density was found between the matrix domains of the Cox4 and Cox5a subunits that appears to be specific to N. crassa.
The small GTPases H, K, and NRAS are molecular switches that are indispensable for proper regulation of cellular proliferation and growth. Mutations in this family of proteins are associated with cancer and result in aberrant activation of signaling processes caused by a deregulated recruitment of downstream effector proteins. In this study, we engineered novel variants of the Ras-binding domain (RBD) of the kinase CRAF. These variants bound with high affinity to the effector binding site of active Ras. Structural characterization showed how the newly identified mutations cooperate to enhance affinity to the effector binding site compared to RBDwt. The engineered RBD variants closely mimic the interaction mode of naturally occurring Ras effectors and as dominant negative affinity reagent block their activation. Experiments with cancer cells showed that expression of these RBD variants inhibits Ras signaling leading to a reduced growth and inductions of apoptosis. Using the optimized RBD variants, we stratified patient-derived colorectal cancer organoids according to Ras dependency, which showed that the presence of Ras mutations was insufficient to predict sensitivity to Ras inhibition.
Attention-Deficit/Hyperactivity Disorder (ADHD) is frequently comorbid with other psychiatric disorders and also with somatic conditions, such as obesity. In addition to the clinical overlap, significant genetic correlations have been found between ADHD and obesity as well as body mass index (BMI). The biological mechanisms driving this association are largely unknown, but some candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the link between ADHD and obesity measures. Using the largest GWAS summary statistics currently available for ADHD (N=53,293), BMI (N=681,275), and obesity (N=98,697), we first tested the association of dopaminergic and circadian rhythm gene sets with each phenotype. This hypothesis-driven approach showed that the dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), while the circadian rhythm gene set was associated with BMI only (P=1.28×10−3). We then took a data-driven approach by conducting genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. This approach further supported the implication of dopaminergic signaling in the link between ADHD and obesity measures, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was significantly enriched in both the ADHD-BMI and ADHD-obesity gene-based meta-analysis results. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering the shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of preventive interventions and/or efficient treatment of these conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
Highlights
• This current review covers studies that have identified long non-coding RNAs in aortic aneurysm development and progression.
• We separately discuss transcripts and mechanisms of importance to thoracic as well as abdominal aortic aneurysms.
• Functional data on lncRNAs being identified are highlighted.
• Some have been studied in human as well as experimental models of the disease pathology.
Abstract
Aortic aneurysm (AA) is a complex and dangerous vascular disease, featuring progressive and irreversible vessel dilatation. AA is typically detected either by screening, or identified incidentally through imaging studies. To date, no effective pharmacological therapies have been identified for clinical AA management, and either endovascular repair or open surgery remains the only option capable of preventing aneurysm rupture. In recent years, multiple research groups have endeavored to both identify noncoding RNAs and to clarify their function in vascular diseases, including aneurysmal pathologies. Notably, the molecular roles of noncoding RNAs in AA development appear to vary significantly between thoracic aortic aneurysms (TAAs) and abdominal aortic aneurysms (AAAs). Some microRNAs (miRNA - a non-coding RNA subspecies) appear to contribute to AA pathophysiology, with some showing major potential for use as biomarkers or as therapeutic targets. Studies of long noncoding RNAs (lncRNAs) are more limited, and their specific contributions to disease development and progression largely remain unexplored. This review aims to summarize and discuss the most current data on lncRNAs and their mediation of AA pathophysiology.
Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this development.
This paper studies insurance demand for individuals with limited financial literacy. We propose uncertainty about insurance payouts, resulting from contract complexity, as a novel channel that affects decision-making of financially illiterate individuals. Then, a trade-off between second-order (risk aversion) and third-order (prudence) risk preferences drives insurance demand. Sufficiently prudent individuals raise insurance demand upon an increase in contract complexity, while the effect is reversed for less prudent individuals. We characterize competitive market equilibria that feature complex contracts since firms face costs to reduce complexity. Based on the equilibrium analysis, we propose a monetary measure for the welfare cost of financial illiteracy and show that it is mainly driven by individuals’ risk aversion. Finally, we discuss implications for regulation and consumer protection.
LICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing.
We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.
The Kinase Chemogenomic Set (KCGS): An open science resource for kinase vulnerability identification
(2019)
We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS) is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.