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Beside its involvement in somatic dysfunctions, altered insulin signalling constitutes a risk factor for the development of mental disorders like Alzheimer’s disease and obsessive-compulsive disorder. While insulin-related somatic and mental disorders are often comorbid, the fundamental mechanisms underlying this association are still elusive. Studies conducted in rodent models appear well suited to help decipher these mechanisms. Specifically, these models are apt to prospective studies in which causative mechanisms can be manipulated via multiple tools (e.g., genetically engineered models and environmental interventions), and experimentally dissociated to control for potential confounding factors. Here, we provide a narrative synthesis of preclinical studies investigating the association between hyperglycaemia – as a proxy of insulin-related metabolic dysfunctions – and impairments in working and spatial memory, and attention. Ultimately, this review will advance our knowledge on the role of glucose metabolism in the comorbidity between somatic and mental illnesses.
Demographic change is supposed to be the most important indirect driver for changing biodiversity. In this article, a systematic review of 148 studies was conducted to examine the scientific evidence for this relationship and to identify potential gaps in research. We explored the spatial distribution of studies, the categories addressed with respect to biodiversity and demographic change, and the ways in which their relationships were conceptualised (spatially and temporally) and valued. The majority of studies were carried out in Africa, Europe and North America. Our analysis confirms the trend that demographic phenomena were mostly found to negatively influence biodiversity. However, a considerable number of studies also point towards impacts that were context dependent, either positive or negative under certain circumstances. In addition to that we identified significant gaps in research. In particular, there is a lack of addressing (1) other demographic aspects such as population decline, age structure or gender differences, (2) spatial variability of, e.g. human population growth, (3) long-term effects of demographic processes, and (4) the context dependency (e.g. regulations/law enforcement, type of human activities, and choice of scale or proxy). We conclude there is evidence that the relationship between biodiversity and demographic change is much more complex than expected and so far represented in research. Thus, we call for a social–ecological biodiversity research that particularly focusses on the functional relation between biodiversity and human activities, namely the different types, context, and interdependent dynamics (spatial and temporal) of this complex relation.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
In a year marked by challenging market dynamics, the importance of ESG investments remains unwavering. But the wave of ESG regulations and requests generates a demand for more scalable ways to collect and analyze ESG data. The rise of AI could mark a turning point in an industry heavily burdened by reporting requirements, and unlock the true potential of ESG for businesses and investors alike.
In this survey paper, we present a multiscale post-processing method in exploration. Based on a physically relevant mollifier technique involving the elasto-oscillatory Cauchy–Navier equation, we mathematically describe the extractable information within 3D geological models obtained by migration as is commonly used for geophysical exploration purposes. More explicitly, the developed multiscale approach extracts and visualizes structural features inherently available in signature bands of certain geological formations such as aquifers, salt domes etc. by specifying suitable wavelet bands.
It is widely believed that chiral symmetry is spontaneously broken at zero temperature in the strong coupling limit of staggered fermions, for any number of colors and flavors. Using Monte Carlo simulations, we show that this conventional wisdom, based on a mean-field analysis, is wrong. For sufficiently many fundamental flavors, chiral symmetry is restored via a bulk, first-order transition. This chirally symmetric phase appears to be analytically connected with the expected conformal window of manyflavor continuum QCD. We perform simulations in the chirally symmetric phase at zero quark mass for various system sizes L, and measure the torelon mass and the Dirac spectrum. We find that all observables scale with L, which is hence the only infrared length scale. Thus, the strong-coupling chirally restored phase appears as a convenient laboratory to study IR-conformality. Finally, we present a conjecture for the phase diagram of lattice QCD as a function of the bare coupling and the number of quark flavors.
Many cellular processes are regulated via pH, and maintaining the pH of different organelles is crucial for cell survival. A pH-sensitive GFP variant, the so-called pHluorin, has proven to be a valuable tool to study the pH of the cytosol, mitochondria and other organelles in vivo. We found that the fluorescence intensity of Endoplasmic Reticulum (ER)-targeted pHluorin in the yeast Saccharomyces cerevisiae was very low and barely showed pH sensitivity, probably due to misfolding in the oxidative environment of the ER. We therefore developed a superfolder variant of pHluorin which enabled us to monitor pH changes in the ER and the cytosol of S. cerevisiae in vivo. The superfolder pHluorin variant is likely to be functional in cells of different organisms as well as in additional compartments that originate from the secretory pathway like the Golgi apparatus and pre-vacuolar compartments, and therefore has a broad range of possible future applications.
Recently the Universal Linear Accelerator (UNILAC) serves as a powerful high duty factor (25%) heavy ion beam accelerator for the ambitious experiment program at GSI. Beam time availability for SHE (Super Heavy Element)-research will be decreased due to the limitation of the UNILAC providing Uranium beams with an extremely high peak current for FAIR simultaneously. To keep the GSI-SHE program competitive on a high level and even beyond, a standalone superconducting continuous wave (100% duty factor) LINAC in combination with the upgraded GSI High Charge State injector is envisaged. In preparation for this, the first LINAC section (financed by HIM and GSI) will be tested with beam in 2017, demonstrating the future experimental capabilities. Further on the construction of an extended cryo module comprising two shorter Crossbar-H cavities is foreseen to test until end of 2017. As a final R&D step towards an entire LINAC three advanced cryo modules, each comprising two CH cavities, should be built until 2019, serving for first user experiments at the Coulomb barrier.
A study on the impact of mobile telecommunication on the welfare of sub saharan african countries
(2010)
Africa: A continent is waking up. Not through aid or wealth from the exploitation of natural resources, but through a technological revolution. The access to affordable mobile telecommunication. Inspired by deregulation and pioneered by local champions who have taken a lead in what is today's fastest growing mobile market in the world. There is money to be made in these markets, attracting more and more operators from the northern hemisphere.
However positive the short term impact of this revolution may be, governments should try hard to assure a market of continued competition among network operators, as this competition is the source of a self propelled creation of welfare and new opportunities, motivated from within Africa.
Chapter 1 of this thesis highlights the positive impact of mobile telecommunication on the social and economic life in Sub Saharan Africa. Chapter 2 builds on the static as well as the dynamic version of the Network Pricing Game, a model developed by Dr. Carolyn Gideon, to stress the immanent threat of network markets turning into a monopoly. This theses ends in Chapter 3 with an brief outlook on further drivers of economic growth and opportunities awaiting Sub Saharan Africa in the coming decade.
We investigate the well-known vector state ψ(4040) in the frame-work of a quantum field theoretical model. In particular, we study its spectral function and search for the pole(s) in the complex plane. Quite interestingly, the spectral function has a non-standard shape and two poles are present. The role of the meson-meson quantum loops (in particular DD* ones) is crucial and could also explain the not yet conformed “state” Y(4008).
This paper explores the many interesting implications for oscillator design, with optimized phase-noise performance, deriving from a newly proposed model based on the concept of oscillator conjugacy. For the case of 2-D (planar) oscillators, the model prominently predicts that only circuits producing a perfectly symmetric steady-state can have zero amplitude-to-phase (AM-PM) noise conversion, a so-called zero-state. Simulations on standard industry oscillator circuits verify all model predictions and, however, also show that these circuit classes cannot attain zero-states except in special limit-cases which are not practically relevant. Guided by the newly acquired design rules, we describe the synthesis of a novel 2-D reduced-order LC oscillator circuit which achieves several zero-states while operating at realistic output power levels. The potential future application of this developed theoretical framework for implementation of numerical algorithms aimed at optimizing oscillator phase-noise performance is briefly discussed.
Did the Federal Reserves’ Quantitative Easing (QE) in the aftermath of the financial crisis have macroeconomic effects? To answer this question, the authors estimate a large-scale DSGE model over the sample from 1998 to 2020, including data of the Fed’s balance sheet. The authors allow for QE to affect the economy via multiple channels that arise from several financial frictions. Their nonlinear Bayesian likelihood approach fully accounts for the zero lower bound on nominal interest rates. They find that between 2009 to 2015, QE increased output by about 1.2 percent. This reflects a net increase in investment of nearly 9 percent, that was accompanied by a 0.7 percent drop in aggregate consumption. Both, government bond and capital asset purchases were effective in improving financing conditions. Especially capital asset purchases significantly facilitated new investment and increased the production capacity. Against the backdrop of a fall in consumption, supply side effects dominated which led to a mild disinflationary effect of about 0.25 percent annually.
Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is an indolent lymphoma, but can transform into diffuse large B cell lymphoma (DLBCL), showing a more aggressive clinical behavior. Little is known about these cases on the molecular level. Therefore, the aim of the present study was to characterize DLBCL transformed from NLPHL (LP-DLBCL) by gene expression profiling (GEP). GEP revealed an inflammatory signature pinpointing to a specific host response. In a coculture model resembling this host response, DEV tumor cells showed an impaired growth behavior. Mechanisms involved in the reduced tumor cell proliferation included a downregulation of MYC and its target genes. Lack of MYC expression was also confirmed in 12/16 LP-DLBCL by immunohistochemistry. Furthermore, CD274/PD-L1 was upregulated in DEV tumor cells after coculture with T cells or monocytes and its expression was validated in 12/19 cases of LP-DLBCL. Thereby, our data provide new insights into the pathogenesis of LP-DLBCL and an explanation for the relatively low tumor cell content. Moreover, the findings suggest that treatment of these patients with immune checkpoint inhibitors may enhance an already ongoing host response in these patients.
Therapy evasion – and subsequent disease progression – is a major challenge in current oncology. An important role in this context seems to be played by various forms of cancer cell dormancy. For example, therapy-induced dormancy, over short timescales, can create serious obstacles to aggressive treatment approaches such as chemotherapy, and long-term dormancy may lead to relapses and metastases even many years after an initially successful treatment. The underlying dormancy-related mechanisms are complex and highly diverse, so that the analysis even of basic patterns of the population-level consequences of dormancy requires abstraction and idealization, as well as the identification of the relevant specific scenarios.
In this paper, we focus on a situation in which individual cancer cells may switch into and out of a dormant state both spontaneously as well as in response to treatment, and over relatively short time-spans. We introduce a mathematical ‘toy model’, based on stochastic agent-based interactions, for the dynamics of cancer cell populations involving individual short-term dormancy, and allow for a range of (multi-drug) therapy protocols. Our analysis shows that in our idealized model, even a small initial population of dormant cells can lead to therapy failure under classical (and in the absence of dormancy successful) single-drug treatments. We further investigate the effectiveness of several multidrug regimes (manipulating dormant cancer cells in specific ways) and provide some basic rules for the design of (multi-)drug treatment protocols depending on the types and parameters of dormancy mechanisms present in the population.
A stochastic model for the joint evaluation of burstiness and regularity in oscillatory spike trains
(2013)
The thesis provides a stochastic model to quantify and classify neuronal firing patterns of oscillatory spike trains. A spike train is a finite sequence of time points at which a neuron has an electric discharge (spike) which is recorded over a finite time interval. In this work, these spike times are analyzed regarding special firing patterns like the presence or absence of oscillatory activity and clusters (so called bursts). These bursts do not have a clear and unique definition in the literature. They are often fired in response to behaviorally relevant stimuli, e.g., an unexpected reward or a novel stimulus, but may also appear spontaneously. Oscillatory activity has been found to be related to complex information processing such as feature binding or figure ground segregation in the visual cortex. Thus, in the context of neurophysiology, it is important to quantify and classify these firing patterns and their change under certain experimental conditions like pharmacological treatment or genetical manipulation. In neuroscientific practice, the classification is often done by visual inspection criteria without giving reproducible results. Furthermore, descriptive methods are used for the quantification of spike trains without relating the extracted measures to properties of the underlying processes.
For that reason, a doubly stochastic point process model is proposed and termed 'Gaussian Locking to a free Oscillator' - GLO. The model has been developed on the basis of empirical observations in dopaminergic neurons and in cooperation with neurophysiologists. The GLO model uses as a first stage an unobservable oscillatory background rhythm which is represented by a stationary random walk whose increments are normally distributed. Two different model types are used to describe single spike firing or clusters of spikes. For both model types, the distribution of the random number of spikes per beat has different probability distributions (Bernoulli in the single spike case or Poisson in the cluster case). In the second stage, the random spike times are placed around their birth beat according to a normal distribution. These spike times represent the observed point process which has five easily interpretable parameters to describe the regularity and the burstiness of the firing patterns.
It turns out that the point process is stationary, simple and ergodic. It can be characterized as a cluster process and for the bursty firing mode as a Cox process. Furthermore, the distribution of the waiting times between spikes can be derived for some parameter combination. The conditional intensity function of the point process is derived which is also called autocorrelation function (ACF) in the neuroscience literature. This function arises by conditioning on a spike at time zero and measures the intensity of spikes x time units later. The autocorrelation histogram (ACH) is an estimate for the ACF. The parameters of the GLO are estimated by fitting the ACF to the ACH with a nonlinear least squares algorithm. This is a common procedure in neuroscientific practice and has the advantage that the GLO ACF can be computed for all parameter combinations and that its properties are closely related to the burstiness and regularity of the process. The precision of estimation is investigated for different scenarios using Monte-Carlo simulations and bootstrap methods.
The GLO provides the neuroscientist with objective and reproducible classification rules for the firing patterns on the basis of the model ACF. These rules are inspired by visual inspection criteria often used in neuroscientific practice and thus support and complement usual analysis of empirical spike trains. When applied to a sample data set, the model is able to detect significant changes in the regularity and burst behavior of the cells and provides confidence intervals for the parameter estimates.
A stochastic forward-looking model to assess the profitability and solvency of european insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
A stochastic forward-looking model to assess the profitability and solvency of European insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
Non-coding variations located within regulatory elements may alter gene expression by modifying Transcription Factor (TF) binding sites and thereby lead to functional consequences like various traits or diseases. To understand these molecular mechanisms, different TF models are being used to assess the effect of DNA sequence variations, such as Single Nucleotide Polymorphisms (SNPs). However, few statistical approaches exist to compute statistical significance of results but they often are slow for large sets of SNPs, such as data obtained from a genome-wide association study (GWAS) or allele-specific analysis of chromatin data.
Results We investigate the distribution of maximal differential TF binding scores for general computational models that assess TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo data sets showed that our new approach improves on an existing method in terms of performance and speed. In applications on large sets of eQTL and GWAS SNPs we could illustrate the usefulness of the novel statistic to highlight cell type specific regulators and TF target genes.
Conclusions Our approach allows the evaluation of DNA changes that induce differential TF binding in a fast and accurate manner, permitting computations on large mutation data sets. An implementation of the novel approach is freely available at https://github.com/SchulzLab/SNEEP.
Highlights
• Single nucleotide variants (SNVs) may affect transcription factor (TF) binding
• Fast statistical approach to assess significance of differential TF binding for SNVs
• Validate new approach on in vitro and in vivo TF binding assays
• Applications on GWAS SNVs and large eQTL studies illustrate utility
Summary
Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.
Highlights
• Gender cues are defined differently across languages.
• We propose a new refined and standardized definition of gender transparency.
• Gender transparency is quantifiable with values that match theoretical expectations.
• We present the first quantitative method to measure the gender transparency of languages.
Abstract
Languages can express grammatical gender through different ortho-phonological regularities present in nouns (e.g., the cues “-o” and “-a” for the masculine and the feminine respectively in Italian, Portuguese, or Spanish). The term “gender transparency” was coined to describe these regularities (Bates et al., 1995). In gendered languages, we can hence distinguish between transparent nouns, i.e., those displaying form regularities; opaque nouns, i.e., those with ambiguous endings; and irregular nouns, i.e., those that display the typical form regularities but are associated with the opposite gender. Following a descriptive analysis of such regularities, languages have been recently classified according to their degree of gender transparency, which seems relevant in regard to gender acquisition and processing. Yet, there are certain inconsistencies in determining which languages are overall transparent and which are opaque. In particular, it is not clear whether some other complex regularities such as derivational suffixes are also “transparent” cues for gender, what really constitutes an “opaque” noun, or which role orthography and morphology have in transparency. Given the existing inconsistencies in classifying languages as transparent or opaque, this work introduces a proposal to assess gender transparency systematically. Our methodology adapts the standardized factors proposed by Audring (2019) to analyse the relative complexity of gender systems. Such factors are adapted to gender transparency on the basis of the literature on gender acquisition and processing. To support the feasibility of such a proposal, the concepts have been instantiated in a quantitative model to obtain for the first time an objective measure of gender transparency using European Portuguese and Dutch as instances of target languages. Our results coincide with the theoretically expected outcome: European Portuguese obtains a high value of gender transparency while Dutch obtains a moderately low one. Future adaptations of this model to the gender systems of other languages could allow the continuum of gender transparency to sustain robust predictions in studies on gender processing and acquisition.
The analysis of postmortem protein degradation has become of large interest for the estimation of the postmortem interval (PMI). Although several techniques have been published in recent years, protein degradation-based techniques still largely did not exceed basic research stages. Reasons include impractical and complex sampling procedures, as well as highly variable protocols in the literature, making it difficult to compare results. Following a three-step procedure, this study aimed to establish an easily replicable standardized procedure for sampling and processing, and further investigated the reliability and limitations for routine application. Initially, sampling and processing were optimized using a rat animal model. In a second step, the possible influences of sample handling and storage on postmortem protein degradation dynamics were assessed on a specifically developed human extracorporeal degradation model. Finally, the practical application was simulated by the collection of tissue in three European forensic institutes and an international transfer to our forensic laboratory, where the samples were processed and analyzed according to the established protocol.
Emerging evidence suggests a complex relationship between sphingosine 1-phosphate (S1P) signaling and stroke. Here, we show the kinetics of S1P in the acute phase of ischemic stroke and highlight accompanying changes in immune cells and S1P receptors (S1PR). Using a C57BL/6 mouse model of middle cerebral artery occlusion (MCAO), we assessed S1P concentrations in the brain, plasma, and spleen. We found a steep S1P gradient from the spleen towards the brain. Results obtained by qPCR suggested that cells expressing the S1PR type 1 (S1P1+) were the predominant population deserting the spleen. Here, we report the cerebral recruitment of T helper (TH) and regulatory T (TREG) cells to the ipsilateral hemisphere, which was associated with differential regulation of cerebral S1PR expression patterns in the brain after MCAO. This study provides insight that the S1P-S1PR axis facilitates splenic T cell egress and is linked to the cerebral recruitment of S1PR+ TH and TREG cells. Further insights by which means the S1P-S1PR-axis orchestrates neuronal positioning may offer new therapeutic perspectives after ischemic stroke.
After a short introduction into traditional image transform coding, multirate systems and multiscale signal coding the paper focuses on the subject of image encoding by a neural network. Taking also noise into account a network model is proposed which not only learns the optimal localized basis functions for the transform but also learns to implement a whitening filter by multi-resolution encoding. A simulation showing the multi-resolution capabilitys concludes the contribution.
CD4+CD25+ regulatory T cells (Tregs) represent a specialized subpopulation of T cells, which are essential for maintaining peripheral tolerance and preventing autoimmunity. The immunomodulatory effects of Tregs depend on their activation status. Here we show that, in contrast to conventional anti-CD4 monoclonal antibodies (mAbs), the humanized CD4-specific monoclonal antibody tregalizumab (BT-061) is able to selectively activate the suppressive properties of Tregs in vitro. BT-061 activates Tregs by binding to CD4 and activation of signaling downstream pathways. The specific functionality of BT-061 may be explained by the recognition of a unique, conformational epitope on domain 2 of the CD4 molecule that is not recognized by other anti-CD4 mAbs. We found that, due to this special epitope binding, BT-061 induces a unique phosphorylation of T-cell receptor complex-associated signaling molecules. This is sufficient to activate the function of Tregs without activating effector T cells. Furthermore, BT-061 does not induce the release of pro-inflammatory cytokines. These results demonstrate that BT-061 stimulation via the CD4 receptor is able to induce T-cell receptor-independent activation of Tregs. Selective activation of Tregs via CD4 is a promising approach for the treatment of autoimmune diseases where insufficient Treg activity has been described. Clinical investigation of this new approach is currently ongoing.
Taking blood via venipuncture is part of the necessary surveillance before and after liver transplantation. The spectrum of response from children and their parents is variable, ranging from a short and limited aversion to paralyzing phobia. The aim of this retrospective, cross-sectional study was to determine the level of anxiety amongst children during venipuncture, to compare the anxiety reported by children and parents, and to identify the factors affecting the children’s and parents’ anxiety in order to develop therapeutic strategies. In total, 147 children (aged 0–17 years, 78 female) and their parents completed questionnaires. Statistical analysis was performed using qualitative and quantitative methods. Results showed that the majority of children reported anxiety and pain during venipuncture. Younger children had more anxiety (self-reported or assessed by parents). Children and parental reports of anxiety were highly correlated. However, the child’s anxiety was often reported as higher by parents than by the children themselves. The child’s general anxiety as well as the parents’ perceived stress from surgical interventions (but not the number of surgical interventions) prompted parental report of child anxiety. For children, the main stressors that correlated with anxiety and pain were factors during the blood collection itself (e.g., feeling the puncture, seeing the syringe). Parental anxiety was mainly related to circumstances before the blood collection (e.g., approaching the clinic, sitting in the waiting room). The main stressors mentioned by parents were the child’s discomfort and their inability to calm the child. Results indicate that the children’s fear of factors during the blood collection, along with the parents’ perceived stress and helplessness as well as their anticipatory anxiety are important starting points for facilitating the drawing of blood from children before and after liver transplantation, thereby supporting a better disease course in the future.
The dependence of the Escherichia coli Na+H+ antiporter A (EcNhaA) pH sensor mutant E241C on H+ and Na+ concentrations was tested using a solid supported membrane (SSM) based electrophysiological approach. Proteoliposome preparations with right side out (RSO) oriented carriers were used to investigate the passive downhill uptake mode (physiologically the reverse transport mode) at zero membrane potential. Na+ concentration gradients established with a rapid solution exchange acted as the driving force. When a Na+ concentration gradient was established at symmetrical pH, the transport activity of the E241C EcNhaA variant was similar to that of the wildtype EcNhaA, with no shift of the bell-shaped pH dependence, an increase of the KmNa at acidic pH and a decrease of the KmNa at alkaline pH, supporting the model of a competitive binding of Na+ and H+ to a common binding site.
Small RNAs have been implicated in numerous cellular processes, including effects on chromatin structure and the repression of transposons. We describe the generation of a small RNA response at DNA ends in Drosophila that is analogous to the recently reported double-strand break (DSB)-induced RNAs or Dicer- and Drosha-dependent small RNAs in Arabidopsis and vertebrates. Active transcription in the vicinity of the break amplifies this small RNA response, demonstrating that the normal messenger RNA contributes to the endogenous small interfering RNAs precursor. The double-stranded RNA precursor forms with an antisense transcript that initiates at the DNA break. Breaks are thus sites of transcription initiation, a novel aspect of the cellular DSB response. This response is specific to a double-strand break since nicked DNA structures do not trigger small RNA production. The small RNAs are generated independently of the exact end structure (blunt, 3′- or 5′-overhang), can repress homologous sequences in trans and may therefore—in addition to putative roles in repair—exert a quality control function by clearing potentially truncated messages from genes in the vicinity of the break.
Background: The oral administration of the gum resin extracts of Indian frankincense (Boswellia serrata Roxb. ex Colebr) results in very low plasma concentrations of boswellic acids (BAs), being far below the pharmacologically active concentrations required in vitro for anti-inflammatory activity. For that reason the use of Indian frankincense in clinical practice and pharmaceutical development has substantially lagged behind. Recently the application of new formulation technologies resulted in a formulation of frankincense extract with lecithin, which revealed improved absorption and tissue penetration of BAs in a rodent study, leading for the first time to plasma concentrations of BAs in the range of their anti-inflammatory activity.
Purpose: In order to verify these encouraging results in humans, the absorption of a standardized Boswellia serrata extract (BE) and its lecithin formulation (CSP) was comparatively investigated in healthy volunteers.
Study design: According to a randomized cross-over design with two treatments, two sequences and two periods, 12 volunteers alternatively received the lecithin-formulated Boswellia extract (CSP) or the non-formulated Boswellia extract (BE) at a dosage of 2 × 250 mg capsules.
Methods: The plasma concentrations of the six major BAs (KBA, AKBA, βBA, αBA, AβBA, AαBA) were determined using LC/MS.
Results: With the exception of KBA, a significantly higher (both in terms of weight-to-weight and molar comparison) and quicker absorption of BAs from the lecithin formulation was observed, leading to Cmax in the range required for the interaction with their molecular targets.
Conclusion: These findings pave the way to further studies evaluating the clinical potential of BAs, and verify the beneficial effect of lecithin formulation to improve the absorption of poorly soluble phytochemicals.
Site-specific recombinases (SSR) are utilized as important genome engineering tools to precisely modify the genome of mice and other model organisms. Reporter mice that mark cells that at any given time had expressed the enzyme are frequently used for lineage tracing and to characterize newly generated mice expressing a recombinase from a chosen promoter. With increasing sophistication of genome alteration strategies, the demand for novel SSR systems that efficiently and specifically recombine their targets is rising and several SSR-systems are now used in combination to address complex biological questions in vivo. Generation of reporter mice for each one of these recombinases is cumbersome and increases the number of mouse lines that need to be maintained in animal facilities. Here we present a multi-reporter mouse line for loci-of-recombination (X) (MuX) that streamlines the characterization of mice expressing prominent recombinases. MuX mice constitutively express nuclear green fluorescent protein after recombination by either Cre, Flp, Dre or Vika recombinase, rationalizing the number of animal lines that need to be maintained. We also pioneer the use of the Vika/vox system in mice, illustrating its high efficacy and specificity, thereby facilitating future designs of sophisticated recombinase-based in vivo genome engineering strategies.
The entire chemical modification repertoire of yeast ribosomal RNAs and the enzymes responsible for it have recently been identified. Nonetheless, in most cases the precise roles played by these chemical modifications in ribosome structure, function and regulation remain totally unclear. Previously, we demonstrated that yeast Rrp8 methylates m1A645 of 25S rRNA in yeast. Here, using mung bean nuclease protection assays in combination with quantitative RP-HPLC and primer extension, we report that 25S/28S rRNA of S. pombe, C. albicans and humans also contain a single m1A methylation in the helix 25.1. We characterized nucleomethylin (NML) as a human homolog of yeast Rrp8 and demonstrate that NML catalyzes the m1A1322 methylation of 28S rRNA in humans. Our in vivo structural probing of 25S rRNA, using both DMS and SHAPE, revealed that the loss of the Rrp8-catalyzed m1A modification alters the conformation of domain I of yeast 25S rRNA causing translation initiation defects detectable as halfmers formation, likely because of incompetent loading of 60S on the 43S-preinitiation complex. Quantitative proteomic analysis of the yeast Δrrp8 mutant strain using 2D-DIGE, revealed that loss of m1A645 impacts production of specific set of proteins involved in carbohydrate metabolism, translation and ribosome synthesis. In mouse, NML has been characterized as a metabolic disease-associated gene linked to obesity. Our findings in yeast also point to a role of Rrp8 in primary metabolism. In conclusion, the m1A modification is crucial for maintaining an optimal 60S conformation, which in turn is important for regulating the production of key metabolic enzymes.
The entire chemical modification repertoire of yeast ribosomal RNAs and the enzymes responsible for it have recently been identified. Nonetheless, in most cases the precise roles played by these chemical modifications in ribosome structure, function and regulation remain totally unclear. Previously, we demonstrated that yeast Rrp8 methylates m1A645 of 25S rRNA in yeast. Here, using mung bean nuclease protection assays in combination with quantitative RP-HPLC and primer extension, we report that 25S/28S rRNA of S. pombe, C. albicans and humans also contain a single m1A methylation in the helix 25.1. We characterized nucleomethylin (NML) as a human homolog of yeast Rrp8 and demonstrate that NML catalyzes the m1A1322 methylation of 28S rRNA in humans. Our in vivo structural probing of 25S rRNA, using both DMS and SHAPE, revealed that the loss of the Rrp8-catalyzed m1A modification alters the conformation of domain I of yeast 25S rRNA causing translation initiation defects detectable as halfmers formation, likely because of incompetent loading of 60S on the 43S-preinitiation complex. Quantitative proteomic analysis of the yeast Δrrp8 mutant strain using 2D-DIGE, revealed that loss of m1A645 impacts production of specific set of proteins involved in carbohydrate metabolism, translation and ribosome synthesis. In mouse, NML has been characterized as a metabolic disease-associated gene linked to obesity. Our findings in yeast also point to a role of Rrp8 in primary metabolism. In conclusion, the m1A modification is crucial for maintaining an optimal 60S conformation, which in turn is important for regulating the production of key metabolic enzymes.
Background: Prospective memory is the ability to recall intended actions or events at the right time or in the right context. While cannabis is known to impair prospective memory, the acute effect of cocaine is unknown. In addition, it is not clear whether changes in prospective memory represent specific alterations in memory processing or result from more general effects on cognition that spread across multiple domains such as arousal and attention.
Aims: The main objective of the study was, therefore, to determine whether drug-induced changes in prospective memory are memory specific or associated with more general drug-induced changes in attention and arousal.
Methods: A placebo-controlled, three-way, cross-over study including 15 regular poly-drug users was set up to test the influence of oral cocaine (300 mg) and vaporised cannabis (300+150 ‘booster’ µg/kg bodyweight) on an event-based prospective memory task. Attentional performance was assessed using a divided attention task and subjective arousal was assessed with the Profile of Mood States questionnaire.
Results: Results showed that cocaine enhanced prospective memory, attention and arousal. Mean performance of prospective memory and attention, as well as levels of arousal were lowest during treatment with cannabis as compared with placebo and cocaine as evinced by a significantly increased trend across treatment conditions. Prospective memory performance was only weakly positively associated to measures of attention and arousal.
Conclusion: Together, these results indicate that cocaine enhancement of prospective memory performance cannot be fully explained by parallel changes in arousal and attention levels, and is likely to represent a direct change in the neural network underlying prospective memory.
Orientation hypercolumns in the visual cortex are delimited by the repeating pinwheel patterns of orientation selective neurons. We design a generative model for visual cortex maps that reproduces such orientation hypercolumns as well as ocular dominance maps while preserving retinotopy. The model uses a neural placement method based on t–distributed stochastic neighbour embedding (t–SNE) to create maps that order common features in the connectivity matrix of the circuit. We find that, in our model, hypercolumns generally appear with fixed cell numbers independently of the overall network size. These results would suggest that existing differences in absolute pinwheel densities are a consequence of variations in neuronal density. Indeed, available measurements in the visual cortex indicate that pinwheels consist of a constant number of ∼30, 000 neurons. Our model is able to reproduce a large number of characteristic properties known for visual cortex maps. We provide the corresponding software in our MAPStoolbox for Matlab.
Introduction: Aim of this study was to reduce blood loss caused by diagnostic blood sampling and to minimize the development of anemia in a high-risk group of mechanically ventilated medical intensive care patients. We therefore implemented a “blood-saving bundle” (BSB) combining a closed-loop arterial blood sampling system, smaller sampling tubes, reduced frequency of blood drawings, and reduced sample numbers.
Methods: The study included all patients from our medical ICU who were ventilated for more than 72 hours. Exclusion criteria were: acute or chronic anemia on admission, bleeding episode(s) during the ICU stay, or end-of-life therapy. The BSB was introduced in 2009 with training and educational support. Patients treated in 2008, before the introduction of the BSB, served as a control group (n = 41, 617 observation days), and were compared with patients treated in 2010 after the introduction of the BSB (BSB group, n = 50, 559 observation days). Primary endpoints were blood loss per day, and development of anemia. Secondary endpoints were numbers of blood transfusions, number of days on mechanical ventilation, and length of the ICU stay.
Results: Mean blood loss per ICU day was decreased from 43.3 ml (95% CI: 41.2 to 45.3 ml) in the controls to 15.0 ml (14.3 to 15.7 ml) in the BSB group (P < 0.001). The introduction of a closed-loop arterial blood sampling system was the major contributor to this effect. Mean hemoglobin concentrations showed no significant differences in both groups during the ICU stay. Hemoglobin values <9 g/dl, however, were recorded in 21.2% of observation days in the controls versus 15.4% in the BSB group (P = 0.01). Units of transfused red blood cells per 100 observation days decreased from 7 to 2.3 (P < 0.001). The mean number of ventilation days was 7.1 days (6.1 to 8.3 days) in the controls and 7.5 days (6.6 to 8.5 days) in the BSB group (P = NS). In total, patients in the BSB group stayed in ICU for a mean of 9.9 days (8.6 to 11.3 days), compared to a mean ICU stay of 13.0 days (10.9 to 15.4 days) in the control group (P = 0.014). Due to the longitudinal study design, however, we cannot exclude uncontrolled confounders affecting the transfusion frequency and mean ICU stay.
Conclusion: Our BSB could be easily implemented and was able to reduce diagnostic blood loss.
Specifying accurate informative prior distributions is a question of carefully selecting studies that comprise the body of comparable background knowledge. Psychological research, however, consists of studies that are being conducted under different circumstances, with different samples and varying instruments. Thus, results of previous studies are heterogeneous, and not all available results can and should contribute equally to an informative prior distribution. This implies a necessary weighting of background information based on the similarity of the previous studies to the focal study at hand. Current approaches to account for heterogeneity by weighting informative prior distributions, such as the power prior and the meta-analytic predictive prior are either not easily accessible or incomplete. To complicate matters further, in the context of Bayesian multiple regression models there are no methods available for quantifying the similarity of a given body of background knowledge to the focal study at hand. Consequently, the purpose of this study is threefold. We first present a novel method to combine the aforementioned sources of heterogeneity in the similarity measure ω. This method is based on a combination of a propensity-score approach to assess the similarity of samples with random- and mixed-effects meta-analytic models to quantify the heterogeneity in outcomes and study characteristics. Second, we show how to use the similarity measure ω as a weight for informative prior distributions for the substantial parameters (regression coefficients) in Bayesian multiple regression models. Third, we investigate the performance and the behavior of the similarity-weighted informative prior distribution in a comprehensive simulation study, where it is compared to the normalized power prior and the meta-analytic predictive prior. The similarity measure ω and the similarity-weighted informative prior distribution as the primary results of this study provide applied researchers with means to specify accurate informative prior distributions.
We present an immersed boundary method for the solution of elliptic interface problems with discontinuous coefficients which provides a second-order approximation of the solution. The proposed method can be categorised as an extended or enriched finite element method. In contrast to other extended FEM approaches, the new shape functions get projected in order to satisfy the Kronecker-delta property with respect to the interface. The resulting combination of projection and restriction was already derived in Höllbacher and Wittum (TBA, 2019a) for application to particulate flows. The crucial benefits are the preservation of the symmetry and positive definiteness of the continuous bilinear operator. Besides, no additional stabilisation terms are necessary. Furthermore, since our enrichment can be interpreted as adaptive mesh refinement, the standard integration schemes can be applied on the cut elements. Finally, small cut elements do not impair the condition of the scheme and we propose a simple procedure to ensure good conditioning independent of the location of the interface. The stability and convergence of the solution will be proven and the numerical tests demonstrate optimal order of convergence.
We study simulated animats in terms of wheeled robots with the most simple neural controller possible – a single neuron per actuator. The system is fully self-organized in the sense that the controlling neuron receives uniquely the actual angle of the wheel as an input. Non-trivial locomotion results in structured environments, with the robot determining autonomously the direction of movement (time-reversal symmetry is spontaneously broken). Our controller, which mimics the mechanism used to transmit power in steam locomotives, abstracts from the body plan of the animat, working without problems also in the presence of noise and for chains of individual two-wheeled cars. Being fully compliant our controller may be also used, in the spirit of morphological computation, as a basic unit for higher-level evolutionary algorithms.
Autophagy is a cytosolic quality control process that recognizes substrates through receptor‐mediated mechanisms. Procollagens, the most abundant gene products in Metazoa, are synthesized in the endoplasmic reticulum (ER), and a fraction that fails to attain the native structure is cleared by autophagy. However, how autophagy selectively recognizes misfolded procollagens in the ER lumen is still unknown. We performed siRNA interference, CRISPR‐Cas9 or knockout‐mediated gene deletion of candidate autophagy and ER proteins in collagen producing cells. We found that the ER‐resident lectin chaperone Calnexin (CANX) and the ER‐phagy receptor FAM134B are required for autophagy‐mediated quality control of endogenous procollagens. Mechanistically, CANX acts as co‐receptor that recognizes ER luminal misfolded procollagens and interacts with the ER‐phagy receptor FAM134B. In turn, FAM134B binds the autophagosome membrane‐associated protein LC3 and delivers a portion of ER containing both CANX and procollagen to the lysosome for degradation. Thus, a crosstalk between the ER quality control machinery and the autophagy pathway selectively disposes of proteasome‐resistant misfolded clients from the ER.
A second Yalta
(2014)
We explore the parameter space of the two-flavor thermal quark–meson model and its Polyakov loop-extended version under the influence of a constant external magnetic field B. We investigate the behavior of the pseudo critical temperature for chiral symmetry breaking taking into account the likely dependence of two parameters on the magnetic field: the Yukawa quark–meson coupling and the parameter T0 of the Polyakov loop potential. Under the constraints that magnetic catalysis is realized at zero temperature and the chiral transition at B=0 is a crossover, we find that the quark–meson model leads to thermal magnetic catalysis for the whole allowed parameter space, in contrast to the present picture stemming from lattice QCD.
Small interfering RNAs (siRNAs) are now established as the preferred tool to inhibit gene function in mammalian cells yet trigger unintended gene silencing due to their inherent miRNA-like behavior. Such off-target effects are primarily mediated by the sequence-specific interaction between the siRNA seed regions (position 2–8 of either siRNA strand counting from the 5'-end) and complementary sequences in the 3'UTR of (off-) targets. It was previously shown that chemical modification of siRNAs can reduce off-targeting but only very few modifications have been tested leaving more to be identified. Here we developed a luciferase reporter-based assay suitable to monitor siRNA off-targeting in a high throughput manner using stable cell lines. We investigated the impact of chemically modifying single nucleotide positions within the siRNA seed on siRNA function and off-targeting using 10 different types of chemical modifications, three different target sequences and three siRNA concentrations. We found several differently modified siRNAs to exercise reduced off-targeting yet incorporation of the strongly destabilizing unlocked nucleic acid (UNA) modification into position 7 of the siRNA most potently reduced off-targeting for all tested sequences. Notably, such position-specific destabilization of siRNA–target interactions did not significantly reduce siRNA potency and is therefore well suited for future siRNA designs especially for applications in vivo where siRNA concentrations, expectedly, will be low.
The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences.
This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible channel (0.45–1 μm) of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005) and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards) were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present) was applied that combines the Standard Normal Homogeneity Test (SNHT) and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN) and about 50 stations of the Global Energy Balance Archive (GEBA) over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of any segment between two break points to the last segment (2006–present). Corrections are applied to the most significant breaks that can be related to satellite changes. This study focuses on the European region, but the methods can be generalized to other regions. To account for seasonal dependence of the mean-shifts the correction was performed independently for each calendar month. In comparison to the ground-based reference the homogenised data record shows an improvement over the original data record in terms of anomaly correlation and bias. In general the method can also be applied for the adjustment of satellite datasets addressing other variables to bridge the gap between CDRs and near-real-time data.
A safe core mandate
(2023)
Central banks have vastly expanded their footprint on capital markets. At a time of extraordinary pressure by many sides, a simple benchmark for the scale and scope of their core mandate of price and financial stability may be useful.
We make a case for a narrow mandate to maintain and safeguard the border between safe and quasi safe assets. This ex-ante definition minimizes ambiguity and discourages risk creation and limit panic runs, primarily by separating market demand for reliable liquidity from risk-intolerant, price-insensitive demand for a safe store of value. The central bank may be occasionally forced to intervene beyond the safe core but should not be bound by any such ex-ante mandate, unless directed to specific goals set by legislation with explicit fiscal support.
We review distinct features of liquidity and safety demand, seeking a definition of the safety border, and discuss LOLR support for borderline safe assets such as MMF or uninsured deposits.
A safe core formulation is close to the historical focus on regulated entities, collateralized lending and attention to the public debt market, but its specific framing offers some context on controversial issues such as the extent of LOLR responsibilities. It also justifies a persistently large scale for central bank liabilities (Greenwood, Hansom and Stein 2016), as safety demand is related to financial wealth rather than GDP. Finally, it is consistent with an active central bank role in supporting liquidity in government debt markets trading and clearing (Duffie 2020, 2021).
Background: In general, the prevalence of work-related musculoskeletal disorders (WMSD) in dentistry is high, and dental assistants (DA) are even more affected than dentists (D). Furthermore, differentiations between the fields of dental specialization (e.g., general dentistry, endodontology, oral and maxillofacial surgery, or orthodontics) are rare. Therefore, this study aims to investigate the ergonomic risk of the aforementioned four fields of dental specialization for D and DA on the one hand, and to compare the ergonomic risk of D and DA within each individual field of dental specialization. Methods: In total, 60 dentists (33 male/27 female) and 60 dental assistants (11 male/49 female) volunteered in this study. The sample was composed of 15 dentists and 15 dental assistants from each of the dental field, in order to represent the fields of dental specialization. In a laboratory setting, all tasks were recorded using an inertial motion capture system. The kinematic data were applied to an automated version of the Rapid Upper Limb Assessment (RULA). Results: The results revealed significantly reduced ergonomic risks in endodontology and orthodontics compared to oral and maxillofacial surgery and general dentistry in DAs, while orthodontics showed a significantly reduced ergonomic risk compared to general dentistry in Ds. Further differences between the fields of dental specialization were found in the right wrist, right lower arm, and left lower arm in DAs and in the neck, right wrist, right lower arm, and left wrist in Ds. The differences between Ds and DAs within a specialist discipline were rather small. Discussion: Independent of whether one works as a D or DA, the percentage of time spent working in higher risk scores is reduced in endodontologists, and especially in orthodontics, compared to general dentists or oral and maxillofacial surgeons. In order to counteract the development of WMSD, early intervention should be made. Consequently, ergonomic training or strength training is recommended.