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Fusion of mitochondrial outer membranes is crucial for proper organelle function and involves large GTPases called mitofusins. The discrete steps that allow mitochondria to attach to one another and merge their outer membranes are unknown. By combining an in vitro mitochondrial fusion assay with electron cryo-tomography (cryo-ET), we visualize the junction between attached mitochondria isolated from Saccharomyces cerevisiae and observe complexes that mediate this attachment. We find that cycles of GTP hydrolysis induce progressive formation of a docking ring structure around extended areas of contact. Further GTP hydrolysis triggers local outer membrane fusion at the periphery of the contact region. These findings unravel key features of mitofusin-dependent fusion of outer membranes and constitute an important advance in our understanding of how mitochondria connect and merge.
Epigenetic silencing of transgene expression represents a major obstacle for the efficient genetic modification of multipotent and pluripotent stem cells. We and others have demonstrated that a 1.5 kb methylation-free CpG island from the human HNRPA2B1-CBX3 housekeeping genes (A2UCOE) effectively prevents transgene silencing and variegation in cell lines, multipotent and pluripotent stem cells, and their differentiated progeny. However, the bidirectional promoter activity of this element may disturb expression of neighboring genes. Furthermore, the epigenetic basis underlying the anti-silencing effect of the UCOE on juxtaposed promoters has been only partially explored. In this study we removed the HNRPA2B1 moiety from the A2UCOE and demonstrate efficient anti-silencing properties also for a minimal 0.7 kb element containing merely the CBX3 promoter. This DNA element largely prevents silencing of viral and tissue-specific promoters in multipotent and pluripotent stem cells. The protective activity of CBX3 was associated with reduced promoter CpG-methylation, decreased levels of repressive and increased levels of active histone marks. Moreover, the anti-silencing effect of CBX3 was locally restricted and when linked to tissue-specific promoters did not activate transcription in off target cells. Thus, CBX3 is a highly attractive element for sustained, tissue-specific and copy-number dependent transgene expression in vitro and in vivo.
In this Letter we study the radiation measured by an accelerated detector, coupled to a scalar field, in the presence of a fundamental minimal length. The latter is implemented by means of a modified momentum space Green's function. After calibrating the detector, we find that the net flux of field quanta is negligible, and that there is no Planckian spectrum. We discuss possible interpretations of this result, and we comment on experimental implications in heavy ion collisions and atomic systems.
Explaining humans as rational creatures—capable of deductive reasoning—remains challenging for evolutionary naturalism. Schechter (Philosophical Perspectives, 24(1)437–464, 2011, 2013) proposes to link the evolution of this kind of reasoning with the ability to plan. His proposal, however, does neither include any elaborated theory on how logical abilities came into being within the hominin lineage nor is it sufficiently supported by empirical evidence. I present such a theory in broad outline and substantiate it with archeological findings. It is argued that the cognitive makeup of any animal is constituted by being embedded in a certain way of life. Changing ways of life thus foster appearances of new cognitive abilities. Finally, a new way of life of coordinated group behavior emerged within the hominins: anticipatory group planning involved in activities like making sophisticated spears for hunting. This gave rise to human logical cognition. It turned hominins into domain-general reasoner and adherents of intersubjective norms for reasoning. However, as I argue, it did not—and most likely could not—give rise to reason by deductive logic. More likely, deductive reasoning entered our world only a few thousand years ago: exclusively as a cultural artifact.
For experiments on fission-fragment induced desorption the detection of significant correlations between desorbed ions has been reported [1]. In this paper the method for the detection and quantitative description of these correlations will be described. The statistics of the desorption-process leads to equations for mass-line intensities of ion spectra. Using a time-to-amplitude-converter for flight-time measurements these intensities depend on interdependences of different ions desorbed by the same fission-fragment. The equations allow the computation of correlationcoefficients whose interdependence with desorption probabilities of the respective ions can be shown in Venn-diagrams. Results are given and an interpretation is suggested for fission-fragment desorbed thiamine molecular and fragment ions.
Background: Compound flaps offer the advantage of one stage defect reconstruction respecting all relevant tissues and early functional recovery by optimal vascularity of all components. Due to its specific vascular anatomy and the three-dimensional donor site, compound flaps with bone components may result in higher complication rates compared to soft tissue compound flaps. The meta-analysis summarizes the available evidence and evaluates whether bone components are a risk factor for periprocedural complications in upper extremity multidimensional defect reconstruction. Method: PubMed and Embase were searched for all publications addressing compound free flaps for upper extremity defect reconstruction with bone or soft tissue components published between January 1988 and May 2018. The methodological quality was assessed with the American Society of Plastic Surgeons Evidence Rating Scale for Therapeutic Studies. Flap loss, thrombosis rate, early infection, hematoma, seroma, as well as donor site complications were extracted and analyzed. Results: Twelve out of 1157 potentially eligible studies (evidence-III) comprising 159 patients were finally included with publication bias for all summarized complication rates. Complication rates for flaps with/ without bone components were: total flap loss 5%, 95% CI = 3%–10% (6%/5%); partial flap loss 8%, 95% CI = 5%–15%, (9%/8%); arterial/venous thrombosis 7%, 95% CI = 4%–12%, (8%/5%)/14%, 95% CI = 9%–21% (16%/6%, P < .05) with higher risk for flaps with bone components; infection 6%, 95% CI = 3%–12% (6%/6%); hematoma 6%, 95% CI = 3%–11% (6%/5%); seroma 5%, 95% CI = 3%–10% (5%/5%); dehiscence 10%, 95% CI = 6%–17% (11%/9%). Conclusion: Compound flaps for upper extremity defect reconstruction including bone components have a higher venous thrombosis rate compared to compound soft-tissue flaps.
Volatile organic compounds are secondary metabolites emitted by all organisms, especially by plants and microbes. Their role as aboveground signals has been established for decades. Recent evidence suggests that they might have a non-negligible role belowground and might be involved in root–root and root–microbial/pest interactions. Our aim here was to make a comprehensive review of belowground volatile diversity using a meta-analysis approach. At first we synthesized current literature knowledge on plant root volatiles and classified them in terms of chemical diversity. In a second step, relying on the mVOC database of microbial volatiles, we classified volatiles based on their emitters (bacteria vs. fungi) and their specific ecological niche (i.e., rhizosphere, soil). Our results highlight similarities and differences among root and microbial volatiles and also suggest that some might be niche specific. We further explored the possibility that volatiles might be involved in intra- and inter-specific root–root communication and discuss the ecological implications of such scenario. Overall this work synthesizes current knowledge on the belowground volatilome and the potential signaling role of its constituents. It also highlights that the total diversity of belowground volatiles might be orders of magnitude larger that the few hundreds of compounds described to date.
A message from the human placenta: structural and immunomodulatory defense against SARS-CoV-2
(2020)
The outbreak of the coronavirus disease 2019 (COVID-19) pandemic has caused a global public health crisis. Viral infections may predispose pregnant women to a higher rate of pregnancy complications, including preterm births, miscarriage and stillbirth. Despite reports of neonatal COVID-19, definitive proof of vertical transmission is still lacking. In this review, we summarize studies regarding the potential evidence for transplacental transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), characterize the expression of its receptors and proteases, describe the placental pathology and analyze virus-host interactions at the maternal-fetal interface. We focus on the syncytium, the barrier between mother and fetus, and describe in detail its physical andstructuraldefenseagainstviralinfections. Wefurtherdiscussthepotentialmolecularmechanisms, whereby the placenta serves as a defense front against pathogens by regulating the interferon type III signaling, microRNA-triggered autophagy and the nuclear factor-κB pathway. Based on these data, we conclude that vertical transmission may occur but rare, ascribed to the potent physical barrier, the fine-regulatedplacentalimmunedefenseandmodulationstrategies. Particularly,immunomodulatory mechanismsemployedbytheplacentamaymitigateviolentimmuneresponse,maybesoftencytokine storm tightly associated with severely ill COVID-19 patients, possibly minimizing cell and tissue damages, and potentially reducing SARS-CoV-2 transmission.
Background: Cognitive dysfunctions represent a core feature of schizophrenia and a predictor for clinical outcomes. One possible mechanism for cognitive impairments could involve an impairment in the experience-dependent modifications of cortical networks.
Methods: To address this issue, we employed magnetoencephalography (MEG) during a visual priming paradigm in a sample of chronic patients with schizophrenia (n = 14), and in a group of healthy controls (n = 14). We obtained MEG-recordings during the presentation of visual stimuli that were presented three times either consecutively or with intervening stimuli. MEG-data were analyzed for event-related fields as well as spectral power in the 1–200 Hz range to examine repetition suppression and repetition enhancement. We defined regions of interest in occipital and thalamic regions and obtained virtual-channel data.
Results: Behavioral priming did not differ between groups. However, patients with schizophrenia showed prominently reduced oscillatory response to novel stimuli in the gamma-frequency band as well as significantly reduced repetition suppression of gamma-band activity and reduced repetition enhancement of beta-band power in occipital cortex to both consecutive repetitions as well as repetitions with intervening stimuli. Moreover, schizophrenia patients were characterized by a significant deficit in suppression of the C1m component in occipital cortex and thalamus as well as of the late positive component (LPC) in occipital cortex.
Conclusions: These data provide novel evidence for impaired repetition suppression in cortical and subcortical circuits in schizophrenia. Although behavioral priming was preserved, patients with schizophrenia showed deficits in repetition suppression as well as repetition enhancement in thalamic and occipital regions, suggesting that experience-dependent modification of neural circuits is impaired in the disorder.
The development of epilepsy (epileptogenesis) involves a complex interplay of neuronal and immune processes. Here, we present a first-of-its-kind mathematical model to better understand the relationships among these processes. Our model describes the interaction between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model reproduces the available data from three animal models. The model successfully describes characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries or the existence of qualitatively different outcomes for varying injury intensity. In line with the concept of degeneracy, our simulations reveal multiple routes toward epilepsy with neuronal loss as a sufficient but non-necessary component. Finally, we show that our model allows for in silico predictions of therapeutic strategies, revealing injury-specific therapeutic targets and optimal time windows for intervention.
Selfish genetic elements that act as post-segregation distorters cause lethality in non-carrier individuals after fertilization. Two post-segregation distorters have been previously identified in Caenorhabditis elegans, the peel-1/zeel-1 and the sup-35/pha-1 elements. These elements seem to act as modification-rescue systems, also called toxin/antidote pairs. Here we show that the maternal-effect toxin/zygotic antidote pair sup-35/pha-1 is required for proper expression of apical junction (AJ) components in epithelia and that sup-35 toxicity increases when pathways that establish and maintain basal epithelial characteristics, die-1, elt-1, lin-26, and vab-10, are compromised. We demonstrate that pha-1(e2123) embryos, which lack the antidote, are defective in epidermal morphogenesis and frequently fail to elongate. Moreover, seam cells are frequently misshaped and mispositioned and cell bond tension is reduced in pha-1(e2123) embryos, suggesting altered tissue material properties in the epidermis. Several aspects of this phenotype can also be induced in wild-type embryos by exerting mechanical stress through uniaxial loading. Seam cell shape, tissue mechanics, and elongation can be restored in pha-1(e2123) embryos if expression of the AJ molecule DLG-1/Discs large is reduced. Thus, our experiments suggest that maternal-effect toxicity disrupts proper development of the epidermis which involves distinct transcriptional regulators and AJ components.
Background: Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine‐learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain.
Methods: Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine‐learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analysed by means of computational functional genomics in the Gene Ontology knowledgebase.
Results: Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signalling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research.
Conclusions: The present computational functional genomics‐based approach provided a computational systems‐biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine‐learned methods provide innovative approaches to knowledge discovery from previous evidence.
Significance: We show that knowledge discovery in genetic databases and contemporary machine‐learned techniques can identify relevant biological processes involved in Persitent pain.
A machine-learned analysis suggests non-redundant diagnostic information in olfactory subtests
(2019)
Background: The functional performance of the human sense of smell can be approached via assessment of the olfactory threshold, the ability to discriminate odors or the ability to identify odors. Contemporary clinical test batteries include all or a selection of these components, with some dissent about the required number and choice.
Methods: Olfactory thresholds, odor discrimination and odor identification scores were available from 10,714 subjects (3662 with anomia, 4299 with hyposmia, and 2752 with normal olfactory function). To assess, whether the olfactory subtests confer the same information or each subtest confers at least partly non-redundant information relevant to the olfactory diagnosis, we compared the diagnostic accuracy of supervised machine learning algorithms trained with the complete information from all three subtests with that obtained when performing the training with the information of only two or one subtests.
Results: The training of machine-learned algorithms with the full information about olfactory thresholds, odor discrimination and odor identification from 2/3 of the cases, resulted in a balanced olfactory diagnostic accuracy of 98% or better in the 1/3 remaining cases. The most pronounced decrease in the balanced accuracy, to approximately 85%, was observed when omitting olfactory thresholds from the training, whereas omitting odor discrimination or identification was associated with smaller decreases (balanced accuracies approximately 90%).
Conclusions: Results support partly non-redundant contributions of each olfactory subtest to the clinical olfactory diagnosis. Olfactory thresholds provided the largest amount of non-redundant information to the olfactory diagnosis.
Bacteria that are capable of organizing themselves as biofilms are an important public health issue. Knowledge discovery focusing on the ability to swarm and conquer the surroundings to form persistent colonies is therefore very important for microbiological research communities that focus on a clinical perspective. Here, we demonstrate how a machine learning workflow can be used to create useful models that are capable of discriminating distinct associated growth behaviors along distinct phenotypes. Based on basic gray-scale images, we provide a processing pipeline for binary image generation, making the workflow accessible for imaging data from a wide range of devices and conditions. The workflow includes a locally estimated regression model that easily applies to growth-related data and a shape analysis using identified principal components. Finally, we apply a density-based clustering application with noise (DBSCAN) to extract and analyze characteristic, general features explained by colony shapes and areas to discriminate distinct Bacillus subtilis phenotypes. Our results suggest that the differences regarding their ability to swarm and subsequently conquer the medium that surrounds them result in characteristic features. The differences along the time scales of the distinct latency for the colony formation give insights into the ability to invade the surroundings and therefore could serve as a useful monitoring tool.
The coordinate and momentum space configurations of the net baryon number in heavy ion collisions that undergo spinodal decomposition, due to a first-order phase transition, are investigated using state-of-the-art machine-learning methods. Coordinate space clumping, which appears in the spinodal decomposition, leaves strong characteristic imprints on the spatial net density distribution in nearly every event which can be detected by modern machine learning techniques. On the other hand, the corresponding features in the momentum distributions cannot clearly be detected, by the same machine learning methods, in individual events. Only a small subset of events can be systematically differ- entiated if only the momentum space information is available. This is due to the strong similarity of the two event classes, with and without spinodal decomposition. In such sce- narios, conventional event-averaged observables like the baryon number cumulants signal a spinodal non-equilibrium phase transition. Indeed the third-order cumulant, the skewness, does exhibit a peak at the beam energy (Elab = 3–4 A GeV), where the transient hot and dense system created in the heavy ion collision reaches the first-order phase transition.
Meat adulteration is a global problem which undermines market fairness and harms people with allergies or certain religious beliefs. In this study, a novel framework in which a one-dimensional convolutional neural network (1DCNN) serves as a backbone and a random forest regressor (RFR) serves as a regressor, named 1DCNN-RFR, is proposed for the quantitative detection of beef adulterated with pork using electronic nose (E-nose) data. The 1DCNN backbone extracted a sufficient number of features from a multichannel input matrix converted from the raw E-nose data. The RFR improved the regression performance due to its strong prediction ability. The effectiveness of the 1DCNN-RFR framework was verified by comparing it with four other models (support vector regression model (SVR), RFR, backpropagation neural network (BPNN), and 1DCNN). The proposed 1DCNN-RFR framework performed best in the quantitative detection of beef adulterated with pork. This study indicated that the proposed 1DCNN-RFR framework could be used as an effective tool for the quantitative detection of meat adulteration.
Recently, a 15-valent (PCV15) and a 20-valent pneumococcal conjugate vaccine (PCV20) have been licensed by the US Food and Drug Administration and are under evaluation by the European Medicines Agency. PCV15 contains all serotypes of the 13-valent conjugate vaccine (PCV13) plus serotype 22F and 33F and PCV20 includes PCV13 serotypes plus serotypes 8, 10A, 11A, 12F, 15B, 22F, 33F. We investigated pneumococcal serotype distribution, secular trends and proportion of pneumonia caused by serotypes included in PCV13, PCV15, PCV20, and the 23-valent pneumococcal polysaccharide vaccine (PPV23) among adult patients with all-cause community-acquired pneumonia (CAP) between 2013 and 2019. We applied logistic mixed regression modelling to assess annual trends. Urine samples from adult patients with CAP treated in the community or hospital in Germany and included in the CAPNETZ study, a prospective multi-centre cohort study, were analysed by two serotype-specific multiplex urinary antigen detection assays (UAD1/UAD2) at Pfizer’s Vaccines Research and Development Laboratory. UAD1 detects serotypes in PCV13, UAD2 detects additional serotypes in PCV20 plus serotypes 2, 9N, 17F and 20. Out of 1,831 patients screened, urine samples with a valid UAD test result were available for 1,343 patients (73.3%). Among those patients, 829 patients (61.7%) were male, 792 patients (59.0%) were aged ≥60 years, 1038 patients (77.3%) had at least one comorbidity and 1,204 patients (89.7%) were treated in the hospital. The overall proportion of vaccine-type pneumonia among all-cause CAP for PCV13, PCV15, PCV20 and PPV23 was 7.7% (n=103), 9.1% (n=122), 12.3% (n=165) and 13.3% (n=178). Over the entire observation period, we did not observe evidence for significant annual trends in pneumococcal vaccine serotype coverage against pneumonia in adults (PCV13: OR 0.94, 95% CI 0.83-1.05; PCV15: OR 0.93, 95% CI 0.84-1.03; PCV20: OR 0.95, 95% CI 0.86-1.04; PPV23: OR 0.99, 95% CI 0.90-1.08). In conclusion, our data show that i) the infant vaccination program of PCV13, which started in Germany 2010 did not result in a relevant and sustained decrease of PCV13 serotypes in pneumonia in adults and ii) that the gap in the coverage between PCV20 and PPV23 was small and did not increase over the entire observation time.
Recently, a 15-valent (PCV15) and a 20-valent pneumococcal conjugate vaccine (PCV20) have been licensed by the US Food and Drug Administration and are under evaluation by the European Medicines Agency. PCV15 contains all serotypes of the 13-valent conjugate vaccine (PCV13) plus serotype 22F and 33F and PCV20 includes PCV13 serotypes plus serotypes 8, 10A, 11A, 12F, 15B, 22F, 33F. We investigated pneumococcal serotype distribution, secular trends and proportion of pneumonia caused by serotypes included in PCV13, PCV15, PCV20, and the 23-valent pneumococcal polysaccharide vaccine (PPV23) among adult patients with all-cause community-acquired pneumonia (CAP) between 2013 and 2019. We applied logistic mixed regression modelling to assess annual trends. Urine samples from adult patients with CAP treated in the community or hospital in Germany and included in the CAPNETZ study, a prospective multi-centre cohort study, were analysed by two serotype-specific multiplex urinary antigen detection assays (UAD1/UAD2) at Pfizer’s Vaccines Research and Development Laboratory. UAD1 detects serotypes in PCV13, UAD2 detects additional serotypes in PCV20 plus serotypes 2, 9N, 17F and 20. Out of 1,831 patients screened, urine samples with a valid UAD test result were available for 1,343 patients (73.3%). Among those patients, 829 patients (61.7%) were male, 792 patients (59.0%) were aged ≥60 years, 1038 patients (77.3%) had at least one comorbidity and 1,204 patients (89.7%) were treated in the hospital. The overall proportion of vaccine-type pneumonia among all-cause CAP for PCV13, PCV15, PCV20 and PPV23 was 7.7% (n=103), 9.1% (n=122), 12.3% (n=165) and 13.3% (n=178). Over the entire observation period, we did not observe evidence for significant annual trends in pneumococcal vaccine serotype coverage against pneumonia in adults (PCV13: OR 0.94, 95% CI 0.83-1.05; PCV15: OR 0.93, 95% CI 0.84-1.03; PCV20: OR 0.95, 95% CI 0.86-1.04; PPV23: OR 0.99, 95% CI 0.90-1.08). In conclusion, our data show i) no decline of PCV13 serotypes in all-cause CAP between 2013-2019 mainly due to a persistently high proportion of serotype 3 suggesting no meaningful effect of childhood PCV13 vaccination on PCV13 coverage in pneumonia in adults during this time period and ii) that the gap in the coverage between PCV20 and PPV23 was small and did not increase over the entire observation time.
Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signaling pathways. Achieving a detailed understanding of intracellular GSH trafficking and regulation depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Herein, we present a new GSH sensing platform, TRaQ-G, for live-cell imaging. This small-molecule/protein hybrid sensor possesses a unique reactivity turn-on mechanism that ensures that the small molecule is only sensitive to GSH in the desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein of choice to give a ratiometric response. Using TRaQ-G-mGold, we demonstrated that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. We also used this sensor, in combination with roGFP, to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.
On average, "young" people underestimate whereas "old" people overestimate their chances to survive into the future. We adopt a Bayesian learning model of ambiguous survival beliefs which replicates these patterns. The model is embedded within a non-expected utility model of life-cycle consumption and saving. Our analysis shows that agents with ambiguous survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival probabilities. Our ambiguity-driven model therefore simultaneously accounts for three important empirical findings on household saving behavior.
Based on a cognitive notion of neo-additive capacities reflecting likelihood insensitivity with respect to survival chances, we construct a Choquet Bayesian learning model over the life-cycle that generates a motivational notion of neo-additive survival beliefs expressing ambiguity attitudes. We embed these neo-additive survival beliefs as decision weights in a Choquet expected utility life-cycle consumption model and calibrate it with data on subjective survival beliefs from the Health and Retirement Study. Our quantitative analysis shows that agents with calibrated neo-additive survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival chances. Our neo-additive life-cycle model can therefore simultaneously accommodate three important empirical findings on household saving behavior.
Tumor progression and pregnancy share many common features, such as immune tolerance and invasion. The invasion of trophoblasts in the placenta into the uterine wall is essential for fetal development, and is thus precisely regulated. Its deregulation has been implicated in preeclampsia, a leading cause for maternal and perinatal mortality and morbidity. Pathogenesis of preeclampsia remains to be defined. Microarray-based gene profiling has been widely used for identifying genes responsible for preeclampsia. In this review, we have summarized the recent data from the microarray studies with preeclamptic placentas. Despite the complex of gene signatures, suggestive of the heterogeneity of preeclampsia, these studies identified a number of differentially expressed genes associated with preeclampsia. Interestingly, most of them have been reported to be tightly involved in tumor progression. We have discussed these interesting genes and analyzed their potential molecular functions in preeclampsia, compared with their roles in malignancy development. Further investigations are warranted to explore the involvement in molecular network of each identified gene, which may provide not only novel strategies for prevention and therapy for preeclampsia but also a better understanding of cancer cells. The trophoblastic cells, with their capacity for proliferation and differentiation, apoptosis and survival, migration, angiogenesis and immune modulation by exploiting similar molecular pathways, make them a compelling model for cancer research.
The ability to respond appropriately to employees' work-related well-being requires leaders to pay attention to their employees' well-being in the first place. We propose that leaders' stress mindset, that is, the belief that stress is enhancing versus debilitating, may bias their perception of employees' well-being. We further propose that this judgment then influences leaders' intention to engage in or refrain from health-oriented leadership behavior, to express higher performance expectations, or to promote their employees. We expect this process to be stronger if leaders strongly identify with their team, increasing their perceived similarity with their employees. In three experiments (N1 = 198, N2 = 292, N3 = 250), we tested the effect of participants' stress mindset on their intention to show certain leadership behaviors, mediated by their perception of employee well-being (emotional exhaustion, somatic symptoms, work engagement) and moderated by their team identification. Our findings largely support the association between stress mindset and the perception of well-being. The results for the proposed mediation and the moderating function of identification were mixed. Overall, the results emphasize the critical role of leaders' stress mindset and may, thus, improve health promotion in organizations by helping leaders to adequately recognize employees' well-being and respond appropriately.
In the nineteenth century, two Neolithic axe-heads were reported from the Michelsberg enclosure system at Kapellenberg. The recent identification of an unusually large tumulus, from which the axe-heads were almost certainly once recovered, reveals that socio-political hierarchisation, linked to the emergence of high-ranking elites in Brittany and the Paris Basin during the fifth millennium cal BC, may have extended into Central Europe.
The human brain achieves visual object recognition through multiple stages of linear and nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
The human brain achieves visual object recognition through multiple stages of nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output M/EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
Spin waves in yttrium-iron garnet has been the subject of research for decades. Recently the report of Bose-Einstein condensation at room temperature has brought these experiments back into focus. Due to the small mass of quasiparticles compared to atoms for example, the condensation temperature can be much higher. With spin-wave quasiparticles, so-called magnons, even room temperature can be reached by externally injecting magnons. But also possible applications in information technologies are of interest. Using excitations as carriers for information instead of charges delivers a much more efficient way of processing data. Basic logical operations have already been realized. Finally the wavelength of spin waves which can be decreased to nanoscale, gives the opportunity to further miniaturize devices for receiving signals for example in smartphones.
For all of these purposes the magnon system is driven far out of equilibrium. In order to get a better fundamental understanding, we concentrate in the main part of this thesis on the nonequilibrium aspect of magnon experiments and investigate their thermalization process. In this context we develop formalisms which are of general interest and which can be adopted to many different kinds of systems.
A milestone in describing gases out of equilibrium was the Boltzmann equation discovered by Ludwig Boltzmann in 1872. In this thesis extensions to the Boltzmann equation with improved approximations are derived. For the application to yttrium-iron garnet we describe the thermalization process after magnons were excited by an external microwave field.
First we consider the Bose-Einstein condensation phenomena. A special property of thin films of yttrium-iron garnet is that the dispersion of magnons has its minimum at finite wave vectors which leads to an interesting behavior of the condensate. We investigate the spatial structure of the condensate using the Gross-Pitaevskii equation and find that the magnons can not condensate only at the energy minimum but that also higher Fourier modes have to be occupied macroscopically. In principle this can lead to a localization on a lattice in real space.
Next we use functional renormalization group methods to go beyond the perturbation theory expressions in the Boltzmann equation. It is a difficult task to find a suitable cutoff scheme which fits to the constraints of nonequilibrium, namely causality and the fluctuation-dissipation theorem when approaching equilibrium. Therefore the cutoff scheme we developed for bosons in the context of our considerations is of general interest for the functional renormalization group. In certain approximations we obtain a system of differential equations which have a similar transition rate structure to the Boltzmann equation. We consider a model of two kinds of free bosons of which one type of boson acts as a thermal bath to the other one. Taking a suitable initial state we can use our formalism to describe the dynamics of magnons such that an enhanced occupation of the ground state is achieved. Numerical results are in good agreement with experimental data.
Finally we extend our model to consider also the pumping process and the decrease of the magnon particle number till thermal equilibrium is reached again. Additional terms which explicitly break the U(1)-symmetry make it necessary to also extend the theory from which a kinetic equation can be deduced. These extensions are complicated and we therefore restrict ourselves to perturbation theory only. Because of the weak interactions in yttrium-iron garnet this provides already good results.
Background: The aim of this pilot study was to analyze postures during the work of neurologists with respect to their occupational activities.
Methods: A total data material of 64.8 h (3885.74 min) of nine (three m/six f) neurologists (assistant physicians) was collected. Kinematic data were collected using the CUELA system (electro-goniometry). In addition, the occupational tasks performed on-site were subject to a detailed objective activity analysis. All activities were assigned to the categories "Office activities" (I), "Measures on patients" (II) and "Other activities" (III). The angle values of each body region (evaluation parameters) were evaluated according to ergonomic ISO standards.
Results: Only 3.4% of the working hours were spent with (II), while 50.8% of time was spent with (I) and 45.8% with (III). All tasks of category (II) revealed an increased ergonomic risk to the head, neck, trunk and back areas. During category (I) especially neck and back movements in the sagittal plane showed higher ergonomic risk levels.
Conclusion: Despite frequently performed awkward body positions in (II), the ergonomic risk is considered as rather low, since the percentage time share totaled only 3.4%. As a result, "Office activities" have been detected as high predictor to cause stress load on the musculoskeletal system in the daily work of neurologists.
By running a temperature series of molecular dynamics (MD) simulations starting from the known low-temperature phase, the experimentally observed phase transition in a `jumping crystal' was captured, thereby providing a prediction of the unknown crystal structure of the high-temperature phase and clarifying the phase-transition mechanism. The phase transition is accompanied by a discontinuity in two of the unit-cell parameters. The structure of the high-temperature phase is very similar to that of the low-temperature phase. The anisotropic displacement parameters calculated from the MD simulations readily identified libration as the driving force behind the phase transition. Both the predicted crystal structure and the phase-transition mechanism were verified experimentally using TLS (translation, libration, screw) refinement against X-ray powder diffraction data.
Motivated by recent reports of a quantum-disordered ground state in the triangular lattice compound NaRuO2, we derive a jeff = 1/2 magnetic model for this system by means of first-principles calculations. The pseudospin Hamiltonian is dominated by bond-dependent off-diagonal Γ interactions, complemented by a ferromagnetic Heisenberg exchange and a notably antiferromagnetic Kitaev term. In addition to bilinear interactions, we find a sizable four-spin ring exchange contribution with a strongly anisotropic character, which has been so far overlooked when modeling Kitaev materials. The analysis of the magnetic model, based on the minimization of the classical energy and exact diagonalization of the quantum Hamiltonian, points toward the existence of a rather robust easy-plane ferromagnetic order, which cannot be easily destabilized by physically relevant perturbations.
Background: Novel microscopic techniques which bypass the resolution limit in light microscopy are becoming routinely established today. The higher spatial resolution of super-resolution microscopy techniques demands for precise correction of drift, spectral and spatial offset of images recorded at different axial planes.
Methods: We employ a hydrophilic gel matrix for super-resolution microscopy of cellular structures. The matrix allows distributing fiducial markers in 3D, and using these for drift correction and multi-channel registration. We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores at different axial planes. We calculate a correction matrix for each spectral channel, correct for drift, spectral and spatial offset in 3D.
Results and discussion: We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores in a hydrophilic gel matrix. We distribute multi-color fiducial markers in the gel matrix and correct for drift and register multiple imaging channels. We perform two-color super-resolution imaging of click-labeled DNA and histone H2B in different axial planes, and demonstrate the quality of drift correction and channel registration quantitatively. This approach delivers robust microscopic data which is a prerequisite for data interpretation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
Background & Aims: Elimination of chronic HBV/HDV infection remains a major global health challenge. Targeting excessive hepatitis B surface antigen (HBsAg) release may provide an interesting window of opportunity to break immune tolerance and to achieve a functional cure using additional antivirals.
Methods: We evaluated a HBsAg-specific human monoclonal antibody, as part of either a prophylactic or therapeutic strategy, against HBV/HDV infection in cell culture models and in human-liver chimeric mice. To assess prophylactic efficacy, mice were passively immunized prior to infection with HBV or HBV/HDV (coinfection and superinfection setting). Therapeutic efficacy was assessed in HBV and HBV/HDV-coinfected mice receiving 4 weeks of treatment. Viral parameters (HBV DNA, HDV RNA and HBsAg) were assessed in mouse plasma.
Results: The antibody could effectively prevent HBV/HDV infection in a dose-dependent manner with IC50 values of ∼3.5 ng/ml. Passive immunization showed complete protection of mice from both HBV and HBV/HDV coinfection. Moreover, HDV superinfection was either completely prevented or at least attenuated in HBV-infected mice. Finally, antibody treatment in mice with established HBV/HDV infection resulted in a significant decline in viremia and a concomitant drop in on-treatment HBsAg, with a moderate viral rebound following treatment cessation.
Conclusion: We present data on a valuable antibody candidate that could complement other antivirals in strategies aimed at achieving functional cure of chronic HBV and HDV infection.
Impact and implications: Patients chronically infected with HBV may eventually develop liver cancer and are at great risk of being superinfected with HDV, which worsens and accelerates disease progression. Unfortunately, current treatments can rarely eliminate both viruses from chronically infected patients. In this study, we present data on a novel antibody that is able to prevent chronic HBV/HDV infection in a mouse model with a humanized liver. Moreover, antibody treatment of HBV/HDV-infected mice strongly diminishes viral loads during therapy. This antibody is a valuable candidate for further clinical development.
We provide a Hopf boundary lemma for the regional fractional Laplacian (−Δ)sΩ, with Ω ⊂ RN a bounded open set. More precisely, given u a pointwise or weak super-solution of the equation (−Δ)s u = c(x)u in Ω, we show that the ratio u(x)∕(dist(x, 𝜕Ω))2s−1 is strictly Ω positive as x approaches the boundary 𝜕Ω of Ω. We also prove a strong maximum principle for distributional super-solutions.
Breast cancer is fast becoming the leading cause of oncologic morbidity and mortality among women worldwide. Demographic changes in Asia, Southeast Asia, and South America will further accelerate this trend. Different specialties are involved in the treatment of breast cancer patients: gynecology, surgery, pathology, hematology/oncology, radiology, radiation oncology, and nuclear medicine. Optimal results are seen in countries providing standardized breast cancer care in certified breast centers. The present article provides an overview of current state-of-the-art treatment strategies and explains the contributions of different specialties to optimal and individualized care for breast cancer patients. Breast cancer will be one of the most important health issues facing physicians involved with women’s health and a basic understanding of current treatment objectives will be essential medical knowledge for everyone taking care of female patients.
The geminal frustrated Lewis pair tBu2PCH2B(Fxyl)2 (1; Fxyl=3,5-(CF3)2C6H3) is accessible in 65 % yield from tBu2PCH2Li and (Fxyl)2BF. According to NMR spectroscopy and X-ray crystallography, 1 is monomeric both in solution and in the solid state. The intramolecular P⋅⋅⋅B distance of 2.900(5) Å and the full planarity of the borane site exclude any significant P/B interaction. Compound 1 readily activates a broad variety of substrates including H2, EtMe2SiH, CO2/CS2, Ph2CO, and H3CCN. Terminal alkynes react with heterolysis of the C−H bond. Haloboranes give cyclic adducts with strong P−BX3 and weak R3B−X bonds. Unprecedented transformations leading to zwitterionic XP/BCX3 adducts occur on treatment of 1 with CCl4 or CBr4 in Et2O. In less polar solvents (C6H6, n-pentane), XP/BCX3 adduct formation is accompanied by the generation of significant amounts of XP/BX adducts. FLP 1 catalyzes the hydrogenation of PhCH=NtBu and the hydrosilylation of Ph2CO with EtMe2SiH.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Low-caloric formula diets can improve hemodynamic parameters of patients with type 2 diabetes. We, therefore, hypothesized that persons with overweight or obesity can benefit from a high-protein, low-glycemic but moderate-caloric formula diet. This post-hoc analysis of the Almased Concept against Overweight and Obesity and Related Health Risk- (ACOORH) trial investigated the impact of a lifestyle intervention combined with a formula diet (INT, n = 308) compared to a control group with lifestyle intervention alone (CON, n = 155) on hemodynamic parameters (systolic and diastolic blood pressure (SBP, DBP), resting heart rate (HR), and pulse wave velocity (PWV)) in high-risk individuals with prehypertension or hypertension. INT replaced meals during the first 6 months (1 week: 3 meals/day; 2–4 weeks: 2 meals/day; 5–26 weeks: 1 meal/day). Study duration was 12 months. From the starting cohort, 304 (68.3%, INT: n = 216; CON: n = 101) participants had a complete dataset. Compared to CON, INT significantly reduced more SBP (−7.3 mmHg 95% CI [−9.2; −5.3] vs. −3.3 mmHg [−5.9; −0.8], p < 0.049) and DBP (−3.7 mmHg [−4.9; −2.5] vs. −1.4 mmHg [−3.1; 0.2], p < 0.028) after 12 months. Compared to CON, INT showed a pronounced reduction in resting HR and PWV after 6 months but both lost significance after 12 months. Changes in SBP, DBP, and PWV were significantly associated positively with changes in body weight and fat mass (all p < 0.05) and resting HR correlated positively with fasting insulin (p < 0.001) after 12 months. Combining a lifestyle intervention with a high-protein and low-glycemic formula diet improves hemodynamic parameters to a greater extent than lifestyle intervention alone in high-risk individuals with overweight and obesity.
We present a hierarchy of polynomial time lattice basis reduction algorithms that stretch from Lenstra, Lenstra, Lovász reduction to Korkine–Zolotareff reduction. Let λ(L) be the length of a shortest nonzero element of a lattice L. We present an algorithm which for k∈N finds a nonzero lattice vector b so that |b|2⩽(6k2)nkλ(L)2. This algorithm uses O(n2(kk+o(k))+n2)log B) arithmetic operations on O(n log B)-bit integers. This holds provided that the given basis vectors b1,…,bn∈Zn are integral and have the length bound B. This algorithm successively applies Korkine–Zolotareff reduction to blocks of length k of the lattice basis. We also improve Kannan's algorithm for Korkine-Zolotareff reduction.
Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to potential underlying mechanisms.
The transcription factor vitamin D receptor (VDR) is the high affinity nuclear target of the biologically active form of vitamin D3 (1,25(OH)2D3). In order to identify pure genomic transcriptional effects of 1,25(OH)2D3, we used VDR cistrome, transcriptome and open chromatin data, obtained from the human monocytic cell line THP-1, for a novel hierarchical analysis applying three bioinformatics approaches. We predicted 75.6% of all early 1,25(OH)2D3-responding (2.5 or 4 h) and 57.4% of the late differentially expressed genes (24 h) to be primary VDR target genes. VDR knockout led to a complete loss of 1,25(OH)2D3–induced genome-wide gene regulation. Thus, there was no indication of any VDR-independent non-genomic actions of 1,25(OH)2D3 modulating its transcriptional response. Among the predicted primary VDR target genes, 47 were coding for transcription factors and thus may mediate secondary 1,25(OH)2D3 responses. CEBPA and ETS1 ChIP-seq data and RNA-seq following CEBPA knockdown were used to validate the predicted regulation of secondary vitamin D target genes by both transcription factors. In conclusion, a directional network containing 47 partly novel primary VDR target transcription factors describes secondary responses in a highly complex vitamin D signaling cascade. The central transcription factor VDR is indispensable for all transcriptome-wide effects of the nuclear hormone.
Objectives: To compare efficacy and safety of ixekizumab (IXE) to adalimumab (ADA) in biological disease-modifying antirheumatic drug-naïve patients with both active psoriatic arthritis (PsA) and skin disease and inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARDs).
Methods: Patients with active PsA were randomised (1:1) to approved dosing of IXE or ADA in an open-label, head-to-head, blinded assessor clinical trial. The primary objective was to evaluate whether IXE was superior to ADA at week 24 for simultaneous achievement of a ≥50% improvement from baseline in the American College of Rheumatology criteria (ACR50) and a 100% improvement from baseline in the Psoriasis Area and Severity Index (PASI100). Major secondary objectives, also at week 24, were to evaluate whether IXE was: (1) non-inferior to ADA for achievement of ACR50 and (2) superior to ADA for PASI100 response. Additional PsA, skin, treat-to-target and quality-of-life outcome measures were assessed at week 24.
Results: The primary efficacy endpoint was met (IXE: 36%, ADA: 28%; p=0.036). IXE was non-inferior for ACR50 response (IXE: 51%, ADA: 47%; treatment difference: 3.9%) and superior for PASI100 response (IXE: 60%, ADA: 47%; p=0.001). IXE had greater response versus ADA in additional PsA, skin, nail, treat-to-target and quality-of-life outcomes. Serious adverse events were reported in 8.5% (ADA) and 3.5% (IXE) of patients.
Conclusions: IXE was superior to ADA in achievement of simultaneous improvement of joint and skin disease (ACR50 and PASI100) in patients with PsA and inadequate response to csDMARDs. Safety and tolerability for both biologicals were aligned with established safety profiles.
A handling study to assess use of the Respimat(®) Soft Mist™ inhaler in children under 5 years old
(2015)
Background: Respimat® Soft Mist™ Inhaler (SMI) is a hand-held device that generates an aerosol with a high, fine-particle fraction, enabling efficient lung deposition. The study objective was to assess inhalation success among children using Respimat SMI, and the requirement for assistance by the parent/caregiver and/or a valved holding chamber (VHC).
Methods: This open-label study enrolled patients aged <5 years with respiratory disease and history of coughing and/or recurrent wheezing. Patients inhaled from the Respimat SMI (air only; no aerosol) using a stepwise configuration: “1” (dose released by child); “2” (dose released by parent/caregiver), and “3” (Respimat SMI with VHC, facemask, and parent/caregiver help). Co-primary endpoints included the ability to perform successful inhalation as assessed by the investigators using a standardized handling questionnaire and evaluation of the reasons for success. Inhalation profile in the successful handling configuration was verified with a pneumotachograph. Patient satisfaction and preferences were investigated in a questionnaire.
Results: Of the children aged 4 to <5 years (n=27) and 3 to <4 years (n=30), 55.6% and 30.0%, respectively, achieved success without a VHC or help; with assistance, another 29.6% and 10.0%, respectively, achieved success, and the remaining children were successful with VHC. All children aged 2 to <3 years (n=20) achieved success with the Respimat SMI and VHC. Of those aged <2 years (n=22), 95.5% had successful handling of the Respimat SMI with VHC and parent/caregiver help. Inhalation flow profiles generally confirmed the outcome of the handling assessment by the investigators. Most parent/caregiver and/or child respondents were satisfied with operation, instructions for use, handling, and ease of holding the Respimat SMI with or without a VHC.
Conclusions: The Respimat SMI is suitable for children aged <5 years; however, children aged <5 years are advised to add a VHC to complement its use.
The haloarchaeon Haloferax volcanii contains nearly 2800 small non-coding RNAs (sRNAs). One intergenic sRNA, sRNA132, was chosen for a detailed characterization. A deletion mutant had a growth defect and thus underscored the importance of sRNA132. A microarray analysis identified the transcript of an operon for a phosphate-specific ABC transporter as a putative target of sRNA132. Both the sRNA132 and the operon transcript accumulated under low phosphate concentrations, indicating a positive regulatory role of sRNA132. A kinetic analysis revealed that sRNA132 is essential shortly after the onset of phosphate starvation, while other regulatory processes take over after several hours. Comparison of the transcriptomes of wild-type and the sRNA132 gene deletion mutant 30 min after the onset of phosphate starvation revealed that sRNA132 controls a regulon of about 40 genes. Remarkably, the regulon included a second operon for a phosphate-specific ABC transporter, which also depended on sRNA132 for rapid induction in the absence of phosphate. Competitive growth experiments of the wild-type and ABC transporter operon deletion mutants underscored the importance of both transporters for growth at low phosphate concentrations. Northern blot analyses of four additional members of the sRNA132 regulon verified that all four transcripts depended on sRNA132 for rapid regulation after the onset of phosphate starvation. Importantly, this is the first example for the transient importance of a sRNA for any archaeal and bacterial species. In addition, this study unraveled the first sRNA regulon for haloarchaea.
The caddisfly subfamily Drusinae BANKS comprises roughly 100 species inhabiting mountain ranges in Europe, Asia Minor and the Caucasus. A 3-gene phylogeny of the subfamily previously identified three major clades that were corroborated by larval morphology and feeding ecologies: scraping grazers, omnivorous shredders and filtering carnivores. Larvae of filtering carnivores exhibit unique head capsule complexities, unknown from other caddisfly larvae. Here we assess the species-level relationships within filtering carnivores, hypothesizing that head capsule complexity is derived from simple shapes observed in the other feeding groups. We summarize the current systematics and taxonomy of the group, clarify the systematic position of Cryptothrix nebulicola, and present a larval key to filtering carnivorous Drusinae. We infer relationships of all known filtering carnivorous Drusinae and 34 additional Drusinae species using Bayesian species tree analysis and concatenated Bayesian phylogenetic analysis of 3805bp of sequence data from six gene regions (mtCOI5-P, mtCOI3-P, 16S mrDNA, CADH, WG, 28S nrDNA), morphological cladistics from 308 characters, and a total evidence analysis. All analyses support monophyly of the three feeding ecology groups but fail to fully resolve internal relationships. Within filtering carnivores, variation in head setation and frontoclypeus structure may be associated with progressive niche adaptation, with less complex species recovered at a basal position. We propose that diversification of complex setation and frontoclypeus shape represents a recent evolutionary development, hypothetically enforcing speciation and niche specificity within filtering carnivorous Drusinae.
Autophagy is a highly conserved catabolic process cells use to maintain their homeostasis by degrading misfolded, damaged and excessive proteins, nonfunctional organelles, foreign pathogens and other cellular components. Hence, autophagy can be nonselective, where bulky portions of the cytoplasm are degraded upon stress, or a highly selective process, where preselected cellular components are degraded. To distinguish between different cellular components, autophagy employs selective autophagy receptors, which will link the cargo to the autophagy machinery, thereby sequestering it in the autophagosome for its subsequent degradation in the lysosome. Autophagy receptors undergo post-translational and structural modifications to fulfil their role in autophagy, or upon executing their role, for their own degradation. We highlight the four most prominent protein modifications – phosphorylation, ubiquitination, acetylation and oligomerisation – that are essential for autophagy receptor recruitment, function and turnover. Understanding the regulation of selective autophagy receptors will provide deeper insights into the pathway and open up potential therapeutic avenues.
Autophagy is a highly conserved catabolic process cells use to maintain their homeostasis by degrading misfolded, damaged and excessive proteins, nonfunctional organelles, foreign pathogens and other cellular components. Hence, autophagy can be nonselective, where bulky portions of the cytoplasm are degraded upon stress, or a highly selective process, where preselected cellular components are degraded. To distinguish between different cellular components, autophagy employs selective autophagy receptors, which will link the cargo to the autophagy machinery, thereby sequestering it in the autophagosome for its subsequent degradation in the lysosome. Autophagy receptors undergo post-translational and structural modifications to fulfil their role in autophagy, or upon executing their role, for their own degradation. We highlight the four most prominent protein modifications – phosphorylation, ubiquitination, acetylation and oligomerisation – that are essential for autophagy receptor recruitment, function and turnover. Understanding the regulation of selective autophagy receptors will provide deeper insights into the pathway and open up potential therapeutic avenues.
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information.
Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
Justification: In Mexico, the number of unidentified bodies has been steadily rising for years. By now, more than 50,000 bodies are considered unidentified. Forensic laboratories that could perform comparative molecular genetic investigation are often overburdened and examinations can take months. Therefore, pragmatic approaches that can help to identify more unknown bodies must be sought. The increased use of distinctive physical features might be one, and the high rate of tattooed people in Mexico points towards a great potential of tattoos as a tool for identification. The prerequisite for a comparison of antemortem (missing persons) and postmortem (unknown bodies) data is an objective description of the particularities, e.g., of the tattoos. The aim of this study was to establish an objective classification for tattoo motives, taking into consideration local preferences.
Methods: In the database of the medicolegal services of the Instituto Jaliscience de Ciencias Forenses (IJCF) in Guadalajara, postmortem data of 1000 tattooed bodies from 2019 were evaluated. According to sex and age, the tattooed body localization and the tattoo motives were categorized.
Results: The 1000 tattooed deceased showed tattoos on 2342 body localizations. The motives were grouped and linked to the following 11 keywords (with decreasing frequency): letters/numbers, human, symbol (other), plant, symbol (religious), animal, object, fantasy/demon/comic, tribal/ornament/geometry, other, unrecognizable.
Conclusion: Using the proposed classification, tattoo motives can be described objectively and classified in a practical way. If used for antemortem (missing persons) and postmortem (unknown bodies) documentation, motives can be searched and compared efficiently—helping to identify unknown bodies.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.
As part of the Next Generation EU (NGEU) program, the European Commission has pledged to issue up to EUR 250 billion of the NGEU bonds as green bonds, in order to confirm their commitment to sustainable finance and to support the transition towards a greener Europe. Thereby, the EU is not only entering the green bond market, but also set to become one of the biggest green bond issuers. Consequently, financial market participants are eager to know what to expect from the EU as a new green bond issuer and whether a negative green bond premium, a so-called Greenium, can be expected for the NGEU green bonds. This research paper formulates an expectation in regards to a potential Greenium for the NGEU green bonds, by conducting an interview with 15 sustainable finance experts and analyzing the public green bond market from September 2014 until June 2021, with respect to a potential green bond premium and its underlying drivers. The regression results confirm the existence of a significant Greenium (-0.7 bps) in the public green bond market and that the Greenium increases for supranational issuers with AAA rating, such as the EU. Moreover, the green bond premium is influenced by issuer sector and credit rating, but issue size and modified duration have no significant effect. Overall, the evaluated expert interviews and regression analysis lead to an expected Greenium for the NGEU green bonds of up to -4 bps, with the potential to further increase in the secondary market.
Ferroptosis is an iron-dependent form of cell death, which is triggered by disturbed membrane integrity due to an overproduction of lipid peroxides. Induction of ferroptosis comprises several alterations, i.e. altered iron metabolism, response to oxidative stress, or lipid peroxide production. At the physiological level transcription, translation, and microRNAs add to the appearance and/or activity of building blocks that negatively or positively balance ferroptosis. Ferroptosis contributes to tissue damage in the case of, e.g., brain and heart injury but may be desirable to overcome chemotherapy resistance. For a more complete picture, it is crucial to also consider the cellular microenvironment, which during inflammation and in the tumor context is dominated by hypoxia. This graphical review visualizes basic mechanisms of ferroptosis, categorizes general inducers and inhibitors of ferroptosis, and puts a focus on microRNAs, iron homeostasis, and hypoxia as regulatory components.
Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between multiple neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking the multivariate nature of interactions: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable because of the combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm uses interaction delays reconstructed for directed bivariate interactions to tag potentially spurious edges on the basis of their timing signatures in the context of the surrounding network. Such tagged interactions may then be pruned, which produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation in MATLAB to test the algorithm’s performance on simulated networks as well as networks derived from magnetoencephalographic data. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.
The membrane proximal external region (MPER) of the HIV-1 glycoprotein gp41 is targeted by the broadly neutralizing antibodies 2F5 and 4E10. To date, no immunization regimen in animals or humans has produced HIV-1 neutralizing MPER-specific antibodies. We immunized llamas with gp41-MPER proteoliposomes and selected a MPER-specific single chain antibody (VHH), 2H10, whose epitope overlaps with that of mAb 2F5. Bi-2H10, a bivalent form of 2H10, which displayed an approximately 20-fold increased affinity compared to the monovalent 2H10, neutralized various sensitive and resistant HIV-1 strains, as well as SHIV strains in TZM-bl cells. X-ray and NMR analyses combined with mutagenesis and modeling revealed that 2H10 recognizes its gp41 epitope in a helical conformation. Notably, tryptophan 100 at the tip of the long CDR3 is not required for gp41 interaction but essential for neutralization. Thus bi-2H10 is an anti-MPER antibody generated by immunization that requires hydrophobic CDR3 determinants in addition to epitope recognition for neutralization similar to the mode of neutralization employed by mAbs 2F5 and 4E10.
Wetlands such as bogs, swamps, or freshwater marshes are hotspots of biodiversity. For 5.1 million km2 of inland wetlands, the dynamics of area and water storage, which strongly impact biodiversity and ecosystem services, were simulated using the global hydrological model WaterGAP. For the first time, the impacts of both human water use and man‐made reservoirs (WUR) and future climate change (CC) on wetlands around the globe were quantified. WUR impacts are concentrated in arid/semiarid regions, where WUR decreased mean wetland water storage by more than 5% on 8.2% of the mean wetland area during 1986–2005 (Am), with highest decreases in groundwater depletion area. Using output of three climate models, CC impacts on wetlands were quantified, distinguishing unavoidable impacts [i.e., at 2 °C global warming (GW)] from avoidable impacts (difference between 3 °C and 2 °C impacts). Even unavoidable CC impacts are projected to be much larger than WUR impacts, also in arid/semiarid regions. On most wetland area with reliable estimates, avoidable CC impacts are more than twice as large as unavoidable impacts. In case of 2 °C GW, half of Am is estimated to be unaffected by mean storage changes of more than 5%, but only one third in case of 3 °C GW. Temporal variability of water storage will increase for most wetlands. Wetlands in dry regions will be affected the most, particularly by water storage decreases in the dry season. Different from wealthier countries, low‐income countries will dominantly suffer from a decrease in wetland water storage due to CC.
We examine how U.S. monetary policy affects the international activities of U.S. Banks. We access a rarely studied US bank‐level dataset to assess at a quarterly frequency how changes in the U.S. Federal funds rate (before the crisis) and quantitative easing (after the onset of the crisis) affects changes in cross‐border claims by U.S. banks across countries, maturities and sectors, and also affects changes in claims by their foreign affiliates. We find robust evidence consistent with the existence of a potent global bank lending channel. In response to changes in U.S. monetary conditions, U.S. banks strongly adjust their cross‐border claims in both the pre and post‐crisis period. However, we also find that U.S. bank affiliate claims respond mainly to host country monetary conditions.
Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global Historical Irrigation Dataset (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arc-minute resolution. We collected subnational irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 112 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining subnational irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to subnational irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land in the western United States as shown on historical maps. Mean aridity on irrigated land increased and river discharge decreased from 1900–1950 whereas aridity decreased from 1950–2005. The dataset and its documentation are made available in an open data repository at https://mygeohub.org/publications/8 (doi:10.13019/M2MW2G).
Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global historical irrigation data set (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arcmin resolution. We collected sub-national irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining sub-national irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to sub-national irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land as shown on historical maps for the western United States (around year 1900) and on a global map (around year 1960). Mean aridity on irrigated land increased and mean natural river discharge on irrigated land decreased from 1900 to 1950 whereas aridity decreased and river discharge remained approximately constant from 1950 to 2005. The data set and its documentation are made available in an open-data repository at https://mygeohub.org/publications/8 (doi:10.13019/M20599).
Global investment in biomedical research has grown significantly over the last decades, reaching approximately a quarter of a trillion US dollars in 2010. However, not all of this investment is distributed evenly by gender. It follows, arguably, that scarce research resources may not be optimally invested (by either not supporting the best science or by failing to investigate topics that benefit women and men equitably). Women across the world tend to be significantly underrepresented in research both as researchers and research participants, receive less research funding, and appear less frequently than men as authors on research publications. There is also some evidence that women are relatively disadvantaged as the beneficiaries of research, in terms of its health, societal and economic impacts. Historical gender biases may have created a path dependency that means that the research system and the impacts of research are biased towards male researchers and male beneficiaries, making it inherently difficult (though not impossible) to eliminate gender bias. In this commentary, we – a group of scholars and practitioners from Africa, America, Asia and Europe – argue that gender-sensitive research impact assessment could become a force for good in moving science policy and practice towards gender equity. Research impact assessment is the multidisciplinary field of scientific inquiry that examines the research process to maximise scientific, societal and economic returns on investment in research. It encompasses many theoretical and methodological approaches that can be used to investigate gender bias and recommend actions for change to maximise research impact. We offer a set of recommendations to research funders, research institutions and research evaluators who conduct impact assessment on how to include and strengthen analysis of gender equity in research impact assessment and issue a global call for action.
‘The whole is more than the sum of its parts.’ This idea has been brought forward by psychologists such as Max Wertheimer who formulated Gestalt laws that describe our perception. One law is that of collinearity: elements that correspond in their local orientation to their global axis of alignment form a collinear line, compared to a noncollinear line where local and global orientations are orthogonal. Psychophysical studies revealed a perceptual advantage for collinear over non-collinear stimulus context. It was suggested that this behavioral finding could be related to underlying neuronal mechanisms already in the primary visual cortex (V1). Studies have shown that neurons in V1 are linked according to a common fate: cells responding to collinearly aligned contours are predominantly interconnected by anisotropic long-range lateral connections. In the cat, the same holds true for visual interhemispheric connections. In the present study we aimed to test how the perceptual advantage of a collinear line is reflected in the anatomical properties within or between the two primary visual cortices. We applied two neurophysiological methods, electrode and optical recording, and reversibly deactivated the topographically corresponding contralateral region by cooling in eight anesthetized cats. In electrophysiology experiments our results revealed that influences by stimulus context significantly depend on a unit’s orientation preference. Vertical preferring units had on average a higher spike rate for collinear over non-collinear context. Horizontal preferring units showed the opposite result. Optical imaging experiments confirmed these findings for cortical areas assigned to vertical orientation preference. Further, when deactivating the contralateral region the spike rate for horizontal preferring units in the intact hemisphere significantly decreased in response to a collinear stimulus context. Most of the optical imaging experiments revealed a decrease in cortical activity in response to either stimulus context crossing the vertical midline. In conclusion, our results support the notion that modulating influences from stimulus context can be quite variable. We suggest that the kind of influence may depend on a cell’s orientation preference. The perceptual advantage of a collinear line as one of the Gestalt laws proposes is not uniformly represented in the activity of individual cells in V1. However, it is likely that the combined activity of many V1 neurons serves to activate neurons further up the processing stream which eventually leads to the perceptual phenomenon.
Recent phylogenomic studies have failed to conclusively resolve certain branches of the placental mammalian tree, despite the evolutionary analysis of genomic data from 32 species. Previous analyses of single genes and retroposon insertion data yielded support for different phylogenetic scenarios for the most basal divergences. The results indicated that some mammalian divergences were best interpreted not as a single bifurcating tree, but as an evolutionary network. In these studies the relationships among some orders of the super-clade Laurasiatheria were poorly supported, albeit not studied in detail. Therefore, 4775 protein-coding genes (6,196,263 nucleotides) were collected and aligned in order to analyze the evolution of this clade. Additionally, over 200,000 introns were screened in silico, resulting in 32 phylogenetically informative long interspersed nuclear elements (LINE) insertion events.
The present study shows that the genome evolution of Laurasiatheria may best be understood as an evolutionary network. Thus, contrary to the common expectation to resolve major evolutionary events as a bifurcating tree, genome analyses unveil complex speciation processes even in deep mammalian divergences. We exemplify this on a subset of 1159 suitable genes that have individual histories, most likely due to incomplete lineage sorting or introgression, processes that can make the genealogy of mammalian genomes complex.
These unexpected results have major implications for the understanding of evolution in general, because the evolution of even some higher level taxa such as mammalian orders may sometimes not be interpreted as a simple bifurcating pattern.
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.
BACKGROUND: Acetogenic bacteria are able to use CO2 as terminal electron acceptor of an anaerobic respiration, thereby producing acetate with electrons coming from H2. Due to this feature, acetogens came into focus as platforms to produce biocommodities from waste gases such as H2+CO2 and/or CO. A prerequisite for metabolic engineering is a detailed understanding of the mechanisms of ATP synthesis and electron-transfer reactions to ensure redox homeostasis. Acetogenesis involves the reduction of CO2 to acetate via soluble enzymes and is coupled to energy conservation by a chemiosmotic mechanism. The membrane-bound module, acting as an ion pump, was of special interest for decades and recently, an Rnf complex was shown to couple electron flow from reduced ferredoxin to NAD+ with the export of Na+ in Acetobacterium woodii. However, not all acetogens have rnf genes in their genome. In order to gain further insights into energy conservation of non-Rnf-containing, thermophilic acetogens, we sequenced the genome of Thermoanaerobacter kivui.
RESULTS: The genome of Thermoanaerobacter kivui comprises 2.9 Mbp with a G+C content of 35% and 2,378 protein encoding orfs. Neither autotrophic growth nor acetate formation from H2+CO2 was dependent on Na+ and acetate formation was inhibited by a protonophore, indicating that H+ is used as coupling ion for primary bioenergetics. This is consistent with the finding that the c subunit of the F1FO ATP synthase does not have the conserved Na+ binding motif. A search for potential H+-translocating, membrane-bound protein complexes revealed genes potentially encoding two different proton-reducing, energy-conserving hydrogenases (Ech).
CONCLUSIONS: The thermophilic acetogen T. kivui does not use Na+ but H+ for chemiosmotic ATP synthesis. It does not contain cytochromes and the electrochemical proton gradient is most likely established by an energy-conserving hydrogenase (Ech). Its thermophilic nature and the efficient conversion of H2+CO2 make T. kivui an interesting acetogen to be used for the production of biocommodities in industrial micobiology. Furthermore, our experimental data as well as the increasing number of sequenced genomes of acetogenic bacteria supported the new classification of acetogens into two groups: Rnf- and Ech-containing acetogens.
Background: To perform a comprehensive study on the relationship between vitamin D metabolism and the response to interferon-α-based therapy of chronic hepatitis C.
Methodology/Principal Findings: Associations between a functionally relevant polymorphism in the gene encoding the vitamin D 1α-hydroxylase (CYP27B1-1260 rs10877012) and the response to treatment with pegylated interferon-α (PEG-IFN-α) and ribavirin were determined in 701 patients with chronic hepatitis C. In addition, associations between serum concentrations of 25-hydroxyvitamin D3 (25[OH]D3) and treatment outcome were analysed. CYP27B1-1260 rs10877012 was found to be an independent predictor of sustained virologic response (SVR) in patients with poor-response IL28B genotypes (15% difference in SVR for rs10877012 genotype AA vs. CC, p = 0.02, OR = 1.52, 95% CI = 1.061–2.188), but not in patients with favourable IL28B genotype. Patients with chronic hepatitis C showed a high prevalence of vitamin D insufficiency (25[OH]D3<20 ng/mL) during all seasons, but 25(OH)D3 serum levels were not associated with treatment outcome.
Conclusions/Significance: Our study suggests a role of bioactive vitamin D (1,25[OH]2D3, calcitriol) in the response to treatment of chronic hepatitis C. However, serum concentration of the calcitriol precursor 25(OH)D3 is not a suitable predictor of treatment outcome.
Model frameworks, based on Floquet theory, have been shown to produce effective tools for accurately predicting phase-noise response of single (free-running) oscillator systems. This method of approach, referred to herein as macro-modeling, has been discussed in several highly influential papers and now constitutes an established branch of modern circuit theory. The increased application of, for example, injection-locked oscillators and oscillator arrays in modern communication systems has subsequently exposed the demand for similar rigorous analysis tools aimed at coupled oscillating systems. This paper presents a novel solution in terms of a macro-model characterizing the phase-response of synchronized coupled oscillator circuits and systems perturbed by weak noise sources. The framework is generalized and hence applicable to all circuit configurations and coupling topologies generating a synchronized steady-state. It advances and replaces the phenomenological descriptions currently found in the published literature pertaining to this topic and, as such, represents a significant breakthrough w.r.t. coupled oscillator noise modeling. The proposed model is readily implemented numerically using standard routines.
Using more than a million randomly generated equations of state that satisfy theoretical and observational constraints, we construct a novel, scale-independent description of the sound speed in neutron stars, where the latter is expressed in a unit cube spanning the normalized radius, r/R, and the mass normalized to the maximum one, M/MTOV. From this generic representation, a number of interesting and surprising results can be deduced. In particular, we find that light (heavy) stars have stiff (soft) cores and soft (stiff) outer layers, or that the maximum of the sound speed is located at the center of light stars but moves to the outer layers for stars with M/MTOV ≳ 0.7, reaching a constant value of cs = 1 2 2 as M → MTOV. We also show that the sound speed decreases below the conformal limit cs = 1 3 2 at the center of stars with M = MTOV. Finally, we construct an analytic expression that accurately describes the radial dependence of the sound speed as a function of the neutron-star mass, thus providing an estimate of the maximum sound speed expected in a neutron star.
Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental principle of dendritic constancy that has consequences for the overall computation in neural circuits.
LIN-2/7 (L27) domains are protein interaction modules that preferentially hetero-oligomerize, a property critical for their function in directing specific assembly of supramolecular signaling complexes at synapses and other polarized cell-cell junctions. We have solved the solution structure of the heterodimer composed of the L27 domains from LIN-2 and LIN-7. Comparison of this structure with other L27 domain structures has allowed us to formulate a general model for why most L27 domains form an obligate heterodimer complex. L27 domains can be divided in two types (A and B), with each heterodimer comprising an A/B pair. We have identified two keystone positions that play a central role in discrimination. The residues at these positions are energetically acceptable in the context of an A/B heterodimer, but would lead to packing defects or electrostatic repulsion in the context of A/A and B/B homodimers. As predicted by the model, mutations of keystone residues stabilize normally strongly disfavored homodimers. Thus, L27 domains are specifically optimized to avoid homodimeric interactions.
Introduction: Neuronal death and subsequent denervation of target areas are hallmarks of many neurological disorders. Denervated neurons lose part of their dendritic tree, and are considered "atrophic", i.e. pathologically altered and damaged. The functional consequences of this phenomenon are poorly understood.
Results: Using computational modelling of 3D-reconstructed granule cells we show that denervation-induced dendritic atrophy also subserves homeostatic functions: By shortening their dendritic tree, granule cells compensate for the loss of inputs by a precise adjustment of excitability. As a consequence, surviving afferents are able to activate the cells, thereby allowing information to flow again through the denervated area. In addition, action potentials backpropagating from the soma to the synapses are enhanced specifically in reorganized portions of the dendritic arbor, resulting in their increased synaptic plasticity. These two observations generalize to any given dendritic tree undergoing structural changes.
Conclusions: Structural homeostatic plasticity, i.e. homeostatic dendritic remodeling, is operating in long-term denervated neurons to achieve functional homeostasis.
Futures markets are a potentially valuable source of information about market expectations. Exploiting this information has proved difficult in practice, because the presence of a time-varying risk premium often renders the futures price a poor measure of the market expectation of the price of the underlying asset. Even though the expectation in principle may be recovered by adjusting the futures price by the estimated risk premium, a common problem in applied work is that there are as many measures of market expectations as there are estimates of the risk premium. We propose a general solution to this problem that allows us to uniquely pin down the best possible estimate of the market expectation for any set of risk premium estimates. We illustrate this approach by solving the long-standing problem of how to recover the market expectation of the price of crude oil. We provide a new measure of oil price expectations that is considerably more accurate than the alternatives and more economically plausible. We discuss implications of our analysis for the estimation of economic models of energy-intensive durables, for the debate on speculation in oil markets, and for oil price forecasting.
We consider versions of the FIND algorithm where the pivot element used is the median of a subset chosen uniformly at random from the data. For the median selection we assume that subsamples of size asymptotic to c⋅nα are chosen, where 0<α≤12, c>0 and n is the size of the data set to be split. We consider the complexity of FIND as a process in the rank to be selected and measured by the number of key comparisons required. After normalization we show weak convergence of the complexity to a centered Gaussian process as n→∞, which depends on α. The proof relies on a contraction argument for probability distributions on càdlàg functions. We also identify the covariance function of the Gaussian limit process and discuss path and tail properties.
This dissertation is devoted to the study of thermodynamics for quantum gauge theories.The poor convergence of quantum field theory at finite temperature has been the main obstacle in the practical applications of thermal QCD for decades. In this dissertation I apply hard-thermal-loop perturbation theory, which is a gauge-invariant reorganization of the conventional perturbative expansion for quantum gauge theories to the thermodynamics of QED and Yang-Mills theory to three-loop order. For the Abelian case, I present a calculation of the free energy of a hot gas of electrons and photons by expanding in a power series in mD/T, mf /T and e2, where mD and mf are the photon and electron thermal masses, respectively, and e is the coupling constant.I demonstrate that the hard-thermal-loop perturbation reorganization improves the convergence of the successive approximations to the QED free energy at large coupling, e ~ 2. For the non-Abelian case, I present a calculation of the free energy of a hot gas of gluons by expanding in a power series in mD/T and g2, where mD is the gluon thermal mass and g is the coupling constant. I show that at three-loop order hard-thermal-loop perturbation theory is compatible with lattice results for the pressure, energy density, and entropy down to temperatures T ~ 2 - 3 Tc. The results suggest that HTLpt provides a systematic framework that can be used to calculate static and dynamic quantities for temperatures relevant at LHC.
Yeast cells can be killed upon expression of pro-apoptotic mammalian proteins. We have established a functional yeast survival screen that was used to isolate novel human anti-apoptotic genes overexpressed in treatment-resistant tumors. The screening of three different cDNA libraries prepared from metastatic melanoma, glioblastomas and leukemic blasts allowed for the identification of many yeast cell death-repressing cDNAs, including 28% of genes that are already known to inhibit apoptosis, 35% of genes upregulated in at least one tumor entity and 16% of genes described as both anti-apoptotic in function and upregulated in tumors. These results confirm the great potential of this screening tool to identify novel anti-apoptotic and tumor-relevant molecules. Three of the isolated candidate genes were further analyzed regarding their anti-apoptotic function in cell culture and their potential as a therapeutic target for molecular therapy. PAICS, an enzyme required for de novo purine biosynthesis, the long non-coding RNA MALAT1 and the MAST2 kinase are overexpressed in certain tumor entities and capable of suppressing apoptosis in human cells. Using a subcutaneous xenograft mouse model, we also demonstrated that glioblastoma tumor growth requires MAST2 expression. An additional advantage of the yeast survival screen is its universal applicability. By using various inducible pro-apoptotic killer proteins and screening the appropriate cDNA library prepared from normal or pathologic tissue of interest, the survival screen can be used to identify apoptosis inhibitors in many different systems.
Species of the genus Blautia are typical inhabitants of the human gut and considered as beneficial gut microbes. However, their role in the gut microbiome and their metabolic features are poorly understood. Blautia schinkii was described as an acetogenic bacterium, characterized by a functional Wood–Ljungdahl pathway (WLP) of acetogenesis from H2 + CO2. Here we report that two relatives, Blautia luti and Blautia wexlerae do not grow on H2 + CO2. Inspection of the genome sequence revealed all genes of the WLP except genes encoding a formate dehydrogenase and an electron-bifurcating hydrogenase. Enzyme assays confirmed this prediction. Accordingly, resting cells neither converted H2 + CO2 nor H2 + HCOOH + CO2 to acetate. Carbon monoxide is an intermediate of the WLP and substrate for many acetogens. Blautia luti and B. wexlerae had an active CO dehydrogenase and resting cells performed acetogenesis from HCOOH + CO2 + CO, demonstrating a functional WLP. Bioinformatic analyses revealed that many Blautia strains as well as other gut acetogens lack formate dehydrogenases and hydrogenases. Thus, the use of formate instead of H2 + CO2 as an interspecies hydrogen and electron carrier seems to be more common in the gut microbiome.
Increased sympathetic noradrenergic signaling is crucially involved in fear and anxiety as defensive states. MicroRNAs regulate dynamic gene expression during synaptic plasticity and genetic variation of microRNAs modulating noradrenaline transporter gene (SLC6A2) expression may thus lead to altered central and peripheral processing of fear and anxiety. In silico prediction of microRNA regulation of SLC6A2 was confirmed by luciferase reporter assays and identified hsa-miR-579-3p as a regulating microRNA. The minor (T)-allele of rs2910931 (MAFcases = 0.431, MAFcontrols = 0.368) upstream of MIR579 was associated with panic disorder in patients (pallelic = 0.004, ncases = 506, ncontrols = 506) and with higher trait anxiety in healthy individuals (pASI = 0.029, pACQ = 0.047, n = 3112). Compared to the major (A)-allele, increased promoter activity was observed in luciferase reporter assays in vitro suggesting more effective MIR579 expression and SLC6A2 repression in vivo (p = 0.041). Healthy individuals carrying at least one (T)-allele showed a brain activation pattern suggesting increased defensive responding and sympathetic noradrenergic activation in midbrain and limbic areas during the extinction of conditioned fear. Panic disorder patients carrying two (T)-alleles showed elevated heart rates in an anxiety-provoking behavioral avoidance test (F(2, 270) = 5.47, p = 0.005). Fine-tuning of noradrenaline homeostasis by a MIR579 genetic variation modulated central and peripheral sympathetic noradrenergic activation during fear processing and anxiety. This study opens new perspectives on the role of microRNAs in the etiopathogenesis of anxiety disorders, particularly their cardiovascular symptoms and comorbidities.
The fungal interaction with plants is a 400 million years old phenomenon, which presumably assisted in the plants’ establishment on land. In a natural ecosystem, all plant-ranging from large trees to sea-grasses-are colonized by fungal endophytes, which can be detected inter- and intracellularly within the tissues of apparently healthy plants, without causing obvious negative effects on their host. These ubiquitous and diverse microorganisms are likely playing important roles in plant fitness and development. However, the knowledge on the ecological functions of fungal root endophytes is scarce. Among possible functions of endophytes, they are implicated in mutualisms with plants, which may increase plant resistance to biotic stressors like herbivores and pathogens, and/or to abiotic factors like soil salinity and drought. Also, endophytes are fascinating microorganisms in regard to their high potential to produce a great spectrum of secondary metabolites with expected ecological functions. However, evidences suggest that the interactions between host plants and endophytes are not static and endophytes express different symbiotic lifestyles ranging from mutualism to parasitism, which makes difficult to predict the ecological roles of these cryptic microorganisms. To reveal the ecological function of fungal root endophytes, this doctoral thesis aims at assessing fungal root endophytes interactions with different plants and their effects on plant fitness, based on their phylogeny, traits, and competition potential in settings encompassing different abiotic contexts. To understand the cryptic implication of nonmycorrhizal endophytes in ecosystem processes, we isolated a diverse spectrum of fungal endophytes from roots of several plant species growing in different natural contexts and tested their effects on different model plants under axenic laboratory conditions. Additionally,we aimed at investigating the effect of abiotic and biotic variables on the outcome of interactions between fungal root endophytes and plants.
In summary, the morphological and physiological traits of 128 fungal endophyte strains within ten fungal orders were studied and artificial experimental systems were used to reproduce their interactions with three plant species under laboratory conditions. Under defined axenic conditions, most endophytes behaved as weak parasites, but their performance varied across plant species and fungal taxa. The variation in the interactions was partly explained by convergent fungal traits that separate groups of endophytes with potentially different niche preferences. According to my findings, I predict that the functional complementarity of strains is essential in structuring natural root endophytic communities. Additionally, the responses of plant-endophyte interactions to different abiotic factors, namely nutrient availability, light intensity, and substrate’s pH, indicate that the outcome of plant-fungus relationships may be robust to changes in the abiotic environment. The assessment of the responses of plant endophyte interactions to biotic context, as combinations of selected dominant root fungal endophytes with different degrees of trait similarity and shared evolutionary history, indicates that frequently coexisting root-colonizing fungi may avoid competition in inter-specific interactions by occupying specific niches, and that their interactions likely define the structure of root-associated fungal communities and influence the microbiome impacts on plant fitness.
In conclusion, my findings suggest that dominant fungal lineages display different ecological preferences and complementary sets of functional traits, with different niche preferences within root tissues to avoid competition. Also, their diverse effects on plant fitness is likely host-isolate dependent and robust to changes in the abiotic environment when these encompass the tolerance range of either symbiont.
Background: The human ATP-binding cassette, subfamily B, member 11 (ABCB11) gene encodes the bile salt export pump, which is exclusively expressed at the canalicular membrane of hepatocytes. A frequent variant in the coding region, c.1331 T > C, leading to the amino acid exchange p.V444A, has been associated with altered serum bile salt levels in healthy individuals and predisposes homozygous carriers of the [C] allele for obstetric cholestasis. Recently, elevated bile salt levels were shown to be significantly associated with rates and risk of cirrhosis in patients with chronic hepatitis C virus (HCV) infection treated with pegylated interferon-alpha2 and ribavirin, suggesting a potential role for bile salt levels in HCV treatment outcomes and in the fibrogenic evolution of HCV-related liver disease. The aim of this study was to investigate a possible association of ABCB11 c.1331 T > C with hepatitis C virus (HCV) infection and fibrosis stages as assessed by non-invasive transient elastography in a German cohort of patients.
Methods: ABCB11 c.1331 T > C genotype was determined by allelic discrimination assay in 649 HCV infected cases and 413 controls. Overall, 444 cases were staged for fibrotic progression by measurement of liver stiffness.
Results: Homo- or heterozygous presence of the frequent [C] allele was associated with HCV positivity (OR = 1.41, CI = 1.02 - 1.95, p = 0.037). No association was detectable between the ABCB11 c.1331 T > C genotype and increased liver stiffness.
Conclusions: Our data confirm that homozygous presence of the major [C] allele of ABCB11 c.1331 T > C is a genetic susceptibility factor for HCV infection, but not for liver fibrosis.
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
A framework for the analysis and visualization of multielectrode spike trains / von Ovidiu F. Jurjut
(2009)
The brain is a highly distributed system of constantly interacting neurons. Understanding how it gives rise to our subjective experiences and perceptions depends largely on understanding the neuronal mechanisms of information processing. These mechanisms are still poorly understood and a matter of ongoing debate remains the timescale on which the coding process evolves. Recently, multielectrode recordings of neuronal activity have begun to contribute substantially to elucidating how information coding is implemented in brain circuits. Unfortunately, analysis and interpretation of multielectrode data is often difficult because of their complexity and large volume. Here we propose a framework that enables the efficient analysis and visualization of multielectrode spiking data. First, using self-organizing maps, we identified reoccurring multi-neuronal spike patterns that evolve on various timescales. Second, we developed a color-based visualization technique for these patterns. They were mapped onto a three-dimensional color space based on their reciprocal similarities, i.e., similar patterns were assigned similar colors. This innovative representation enables a quick and comprehensive inspection of spiking data and provides a qualitative description of pattern distribution across entire datasets. Third, we quantified the observed pattern expression motifs and we investigated their contribution to the encoding of stimulus-related information. An emphasis was on the timescale on which patterns evolve, covering the temporal scales from synchrony up to mean firing rate. Using our multi-neuronal analysis framework, we investigated data recorded from the primary visual cortex of anesthetized cats. We found that cortical responses to dynamic stimuli are best described as successions of multi-neuronal activation patterns, i.e., trajectories in a multidimensional pattern space. Patterns that encode stimulus-specific information are not confined to a single timescale but can span a broad range of timescales, which are tightly related to the temporal dynamics of the stimuli. Therefore, the strict separation between synchrony and mean firing rate is somewhat artificial as these two represent only extreme cases of a continuum of timescales that are expressed in cortical dynamics. Results also indicate that timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (~10-20 ms) appear to play a particularly salient role in coding, as patterns evolving on these timescales seem to be involved in the representation of stimuli with both slow and fast temporal dynamics.
We derive a shape derivative formula for the family of principal Dirichlet eigenvalues λs(Ω) of the fractional Laplacian (−Δ)s associated with bounded open sets Ω⊂RN of class C1,1. This extends, with a help of a new approach, a result in Dalibard and Gérard-Varet (Calc. Var. 19(4):976–1013, 2013) which was restricted to the case s=12. As an application, we consider the maximization problem for λs(Ω) among annular-shaped domains of fixed volume of the type B∖B¯¯¯¯′, where B is a fixed ball and B′ is ball whose position is varied within B. We prove that λs(B∖B¯¯¯¯′) is maximal when the two balls are concentric. Our approach also allows to derive similar results for the fractional torsional rigidity. More generally, we will characterize one-sided shape derivatives for best constants of a family of subcritical fractional Sobolev embeddings.
The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.
The extraordinary desiccation resistance of the opportunistic human pathogen Acinetobacter baumannii is a key to its survival and spread in medical care units. The accumulation of compatible solute such as glutamate, mannitol and trehalose contributes to the desiccation resistance. Here, we have used osmolarity as a tool to study the response of cells to low water activities and studied the role of a potential inorganic osmolyte, K+, in osmostress response. Growth of A. baumannii was K+-dependent and the K+-dependence increased with the osmolarity of the medium. After an osmotic upshock, cells accumulated K+ and K+ accumulation increased with the salinity of the medium. K+ uptake was reduced in the presence of glycine betaine. The intracellular pools of compatible solutes were dependent on the K+ concentration: mannitol and glutamate concentrations increased with increasing K+ concentrations whereas trehalose was highest at low K+. After osmotic upshock, cells first accumulated K+ followed by synthesis of glutamate; later, mannitol and trehalose synthesis started, accompanied with a decrease of intracellular K+ and glutamate. These experiments demonstrate K+ uptake as a first response to osmostress in A. baumannii and demonstrate a hierarchy in the time-dependent accumulation of K+ and different organic solutes.
The HADES experiment at GSI has recently provided data on the flow coefficients v1,..., v4 for protons in Au+Au reactions at Elab = 1.23 AGeV (or √sNN = 2.4 GeV). This data allows to estimate the shear viscosity over entropy density ratio, η/s at low energies via a coarse graining analysis of the UrQMD transport simulations of the flow harmonics in comparison to the experimental data. By this we can provide for the first time an estimate of η/s ≈ 0.65 ± 0.15 (or (8 ± 2)(4π)−1) at such low energies.
The paper proposes a variation of simulation for checking and proving contextual equivalence in a non-deterministic call-by-need lambda-calculus with constructors, case, seq, and a letrec with cyclic dependencies. It also proposes a novel method to prove its correctness. The calculus’ semantics is based on a small-step rewrite semantics and on may-convergence. The cyclic nature of letrec bindings, as well as nondeterminism, makes known approaches to prove that simulation implies contextual equivalence, such as Howe’s proof technique, inapplicable in this setting. The basic technique for the simulation as well as the correctness proof is called pre-evaluation, which computes a set of answers for every closed expression. If simulation succeeds in finite computation depth, then it is guaranteed to show contextual preorder of expressions.
Often adopting a feminist perspective, the sociological literature on migrant domestic services (MDS) does not make explicit which feminist paradigm it speaks from. This article situates this literature within ongoing debates in feminist theory, in particular the tension between materialist and poststructuralist approaches. Then, it discusses the empirical relevance of each of those two paradigms on the example of the results of original research into the personalization of employment relationships in MDS.
The contribution proposes a new way of making sense of the diversity of feminist theories, distinguishing between modern and postmodern approaches. Indeed, since the 1980s, feminist theory in the US and Western Europe has undergone a ‘postmodern turn’, which renders previous typologies much less up-to-speed with recent developments in the field. Then, the article examines which paradigms are implicit in the sociological literature on MDS. Initially, personalization in MDS was mainly seen in materialist terms, as a way to maximize the quantity and quality of labour (including emotional labour) extracted from domestic workers. The emergence of postmodern approaches in feminist theory set off a progressive shift in MDS literature. First, this literature showed that personalization also fulfils identity functions for employers and
workers, then it widened its focus to include the affective dimensions of domestic labour (not to be confused with emotional labour). The final section shows how modern and postmodern feminist approaches can be combined within a single research, on the example of original research on personalization in MDS in Belgium and Poland. In particular, the contribution shows that the distinction between material functions of personalization on the one hand, and its emotional/identity functions on the other is not empirically operative. Indeed, migrant domestic workers generally use emotional/identity categories to frame material questions, and vice versa. This final part shows that, rather than representing incompatible approaches, modern and postmodern feminisms complete each other, in this case showing a fuller image of personalization processes in MDS.
A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CBM experiment. For this study, UrQMD and the CBM detector simulation are used to generate Au+Au collision events at 10 AGeV which are then used to train and evaluate PointNet based architectures. The models can be trained on features like the hit position of particles in the CBM detector planes, tracks reconstructed from the hits or combinations thereof. The Deep Learning models reconstruct impact parameters from 2-14 fm with a mean error varying from -0.33 to 0.22 fm. For impact parameters in the range of 5-14 fm, a model which uses the combination of hit and track information of particles has a relative precision of 4-9% and a mean error of -0.33 to 0.13 fm. In the same range of impact parameters, a model with only track information has a relative precision of 4-10% and a mean error of -0.18 to 0.22 fm. This new method of event-classification is shown to be more accurate and less model dependent than conventional methods and can utilize the performance boost of modern GPU processor units.
Amide proton transfer-chemical exchange saturation transfer (APT-CEST) imaging provides important information for the diagnosis and monitoring of tumors. For such analysis, complete coverage of the brain is advantageous, especially when registration is performed with other magnetic resonance (MR) modalities, such as MR spectroscopy (MRS). However, the acquisition of Z-spectra across several slices via multislice imaging may be time-consuming. Therefore, in this paper, we present a new approach for fast multislice imaging, allowing us to acquire 16 slices per frequency offset within 8 s. The proposed fast CEST-EPI sequence employs a presaturation module, which drives the magnetization into the steady-state equilibrium for the first frequency offset. A second module, consisting of a single CEST pulse (for maintaining the steady-state) followed by an EPI acquisition, passes through a loop to acquire multiple slices and adjacent frequency offsets. Thus, the whole Z-spectrum can be recorded much faster than the conventional saturation scheme, which employs a presaturation for each single frequency offset. The validation of the CEST sequence parameters was performed by using the conventional saturation scheme. Subsequently, the proposed and a modified version of the conventional CEST sequence were compared in vitro on a phantom with different T1 times and in vivo on a brain tumor patient. No significant differences between both sequences could be found in vitro. The in vivo data yielded almost identical MTRasym contrasts for the white and gray matter as well as for tumor tissue. Our results show that the proposed fast CEST-EPI sequence allows for rapid data acquisition and provides similar CEST contrasts as the modified conventional scheme while reducing the scanning time by approximately 50%.