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Memory consolidation tends to be less robust in childhood than adulthood. However, little is known about the corresponding functional differences in the developing brain that may underlie age-related differences in retention of memories over time. This study examined system-level memory consolidation of object-scene associations after learning (immediate delay), one night of sleep (short delay), as well as two weeks (long delay) in 5-to-7-year-old children (n = 49) and in young adults (n = 39), as a reference group with mature consolidation systems. Particularly, we characterized how functional neural activation and reinstatement of neural patterns change over time, assessed by functional magnetic resonance imaging combined with representational similarity analysis (RSA). Our results showed that memory consolidation in children was less robust and strong (i.e., more forgetting) compared to young adults. Contrasting correctly retained remote versus recent memories across time delay, children showed less upregulation in posterior parahippocampal gyrus, lateral occipital cortex, and cerebellum than adults. In addition, both children and adults showed decrease in scene-specific neural reinstatement over time, indicating time-related decay of detailed differentiated memories. At the same time, we observed more generic gist-like neural reinstatement in medial-temporal and prefrontal brain regions uniquely in children, indicating qualitative difference in memory trace in children. Taken together, 5-to-7-year-old children, compared to young adults, show less robust memory consolidation, possibly due to difficulties in engaging in differentiated neural reinstatement in neocortical mnemonic regions during retrieval of remote memories, coupled with relying more on gist-like generic neural reinstatement.
From early to middle childhood, brain regions that underlie memory consolidation undergo profound maturational changes. However, there is little empirical investigation that directly relates age-related differences in brain structural measures to the memory consolidation processes. The present study examined system-level memory consolidations of intentionally studied object-location associations after one night of sleep (short delay) and after two weeks (long delay) in normally developing 5-to-7-year-old children (n = 50) and young adults (n = 39). Behavioural differences in memory consolidation were related to structural brain measures. Our results showed that children, in comparison to young adults, consolidate correctly learnt object-location associations less robustly over short and long delay. Moreover, using partial least squares correlation method, a unique multivariate profile comprised of specific neocortical (prefrontal, parietal, and occipital), cerebellar, and hippocampal subfield structures was found to be associated with variation in short-delay memory consolidation. A different multivariate profile comprised of a reduced set of brain structures, mainly consisting of neocortical (prefrontal, parietal, and occipital), and selective hippocampal subfield structures (CA1-2 and subiculum) was associated with variation in long-delay memory consolidation. Taken together, the results suggest that multivariate structural pattern of unique sets of brain regions are related to variations in short- and long-delay memory consolidation across children and young adults.
RESEARCH HIGHLIGHTS
* Short- and long-delay memory consolidation is less robust in children than in young adults
* Short-delay brain profile comprised of hippocampal, cerebellar, and neocortical brain regions
* Long-delay brain profile comprised of neocortical and selected hippocampal brain regions.
* Brain profiles differ between children and young adults.
From early to middle childhood, brain regions that underlie memory consolidation undergo profound maturational changes. However, there is little empirical investigation that directly relates age-related differences in brain structural measures to the memory consolidation processes. The present study examined system-level memory consolidations of intentionally studied object-location associations after one night of sleep (short delay) and after two weeks (long delay) in normally developing 5-to-7-year-old children (n = 50) and young adults (n = 39). Behavioural differences in memory consolidation were related to structural brain measures. Our results showed that children, in comparison to young adults, consolidate correctly learnt object-location associations less robustly over short and long delay. Moreover, using partial least squares correlation method, a unique multivariate profile comprised of specific neocortical (prefrontal, parietal, and occipital), cerebellar, and hippocampal subfield structures was found to be associated with variation in short-delay memory consolidation. A different multivariate profile comprised of a reduced set of brain structures, mainly consisting of neocortical (prefrontal, parietal, and occipital), and selective hippocampal subfield structures (CA1-2 and subiculum) was associated with variation in long-delay memory consolidation. Taken together, the results suggest that multivariate structural pattern of unique sets of brain regions are related to variations in short- and long-delay memory consolidation across children and young adults.
RESEARCH HIGHLIGHTS
Short- and long-delay memory consolidation is less robust in children than in young adults
* Short-delay brain profile comprised of hippocampal, cerebellar, and neocortical brain regions
* Long-delay brain profile comprised of neocortical and selected hippocampal brain regions.
* Brain profiles differ between children and young adults.
Selectivity remains a challenge for ATP-mimetic kinase inhibitors, an issue that may be overcome by targeting unique residues or binding pockets. However, to date only few strategies have been developed. Here we identify that bulky residues located N-terminal to the DFG motif (DFG-1) represent an opportunity for designing highly selective inhibitors with unexpected binding modes. We demonstrate that several diverse inhibitors exerted selective, non-canonical binding modes that exclusively target large hydrophobic DFG-1 residues present in many kinases including PIM, CK1, DAPK and CLK. Using the CLK family as a model, structural and biochemical data revealed that the DFG-1 valine controlled a non-canonical binding mode in CLK1, providing a rational for selectivity over the closely-related CLK3 which harbors a smaller DFG-1 alanine. Our data suggests that targeting the restricted back pocket in the small fraction of kinases that harbor bulky DFG-1 residues offers a versatile selectivity filter for inhibitor design.
MKK7 (MEK7) is a key regulator of the JNK stress signaling pathway and targeting MKK7 has been proposed as a chemotherapeutic strategy. Detailed understanding of the MKK7 structure and factors that impact its activity is therefore of critical importance. Here, we present a comprehensive set of MKK7 crystal structures revealing insights into catalytic domain plasticity and the role of the N-terminal regulatory helix, conserved in all MAP2Ks, mediating kinase activation. Crystal structures harboring this regulatory helix revealed typical structural features of active kinase, providing exclusively a first model of the MAP2K active state. A small molecule screening campaign yielded multiple scaffolds, including type-II irreversible inhibitors a binding mode that has not been reported previously. We also observed an unprecedented allosteric pocket located in the N-terminal lobe for the approved drug ibrutinib. Collectively, our structural and functional data expand and provide alternative targeting strategies for this important MAP2K kinase.
Recurrent cortical network dynamics plays a crucial role for sequential information processing in the brain. While the theoretical framework of reservoir computing provides a conceptual basis for the understanding of recurrent neural computation, it often requires manual adjustments of global network parameters, in particular of the spectral radius of the recurrent synaptic weight matrix. Being a mathematical and relatively complex quantity, the spectral radius is not readily accessible to biological neural networks, which generally adhere to the principle that information about the network state should either be encoded in local intrinsic dynamical quantities (e.g. membrane potentials), or transmitted via synaptic connectivity. We present two synaptic scaling rules for echo state networks that solely rely on locally accessible variables. Both rules work online, in the presence of a continuous stream of input signals. The first rule, termed flow control, is based on a local comparison between the mean squared recurrent membrane potential and the mean squared activity of the neuron itself. It is derived from a global scaling condition on the dynamic flow of neural activities and requires the separability of external and recurrent input currents. We gained further insight into the adaptation dynamics of flow control by using a mean field approximation on the variances of neural activities that allowed us to describe the interplay between network activity and adaptation as a two-dimensional dynamical system. The second rule that we considered, variance control, directly regulates the variance of neural activities by locally scaling the recurrent synaptic weights. The target set point of this homeostatic mechanism is dynamically determined as a function of the variance of the locally measured external input. This functional relation was derived from the same mean-field approach that was used to describe the approximate dynamics of flow control.
The effectiveness of the presented mechanisms was tested numerically using different external input protocols. The network performance after adaptation was evaluated by training the network to perform a time delayed XOR operation on binary sequences. As our main result, we found that flow control can reliably regulate the spectral radius under different input statistics, but precise tuning is negatively affected by interneural correlations. Furthermore, flow control showed a consistent task performance over a wide range of input strengths/variances. Variance control, on the other side, did not yield the desired spectral radii with the same precision. Moreover, task performance was less consistent across different input strengths.
Given the better performance and simpler mathematical form of flow control, we concluded that a local control of the spectral radius via an implicit adaptation scheme is a realistic alternative to approaches using classical “set point” homeostatic feedback controls of neural firing.
Author summary How can a neural network control its recurrent synaptic strengths such that network dynamics are optimal for sequential information processing? An important quantity in this respect, the spectral radius of the recurrent synaptic weight matrix, is a non-local quantity. Therefore, a direct calculation of the spectral radius is not feasible for biological networks. However, we show that there exist a local and biologically plausible adaptation mechanism, flow control, which allows to control the recurrent weight spectral radius while the network is operating under the influence of external inputs. Flow control is based on a theorem of random matrix theory, which is applicable if inter-synaptic correlations are weak. We apply the new adaption rule to echo-state networks having the task to perform a time-delayed XOR operation on random binary input sequences. We find that flow-controlled networks can adapt to a wide range of input strengths while retaining essentially constant task performance.
Recurrent cortical network dynamics plays a crucial role for sequential information processing in the brain. While the theoretical framework of reservoir computing provides a conceptual basis for the understanding of recurrent neural computation, it often requires manual adjustments of global network parameters, in particular of the spectral radius of the recurrent synaptic weight matrix. Being a mathematical and relatively complex quantity, the spectral radius is not readily accessible to biological neural networks, which generally adhere to the principle that information about the network state should either be encoded in local intrinsic dynamical quantities (e.g. membrane potentials), or transmitted via synaptic connectivity. We present two synaptic scaling rules for echo state networks that solely rely on locally accessible variables. Both rules work online, in the presence of a continuous stream of input signals. The first rule, termed flow control, is based on a local comparison between the mean squared recurrent membrane potential and the mean squared activity of the neuron itself. It is derived from a global scaling condition on the dynamic flow of neural activities and requires the separability of external and recurrent input currents. We gained further insight into the adaptation dynamics of flow control by using a mean field approximation on the variances of neural activities that allowed us to describe the interplay between network activity and adaptation as a two-dimensional dynamical system. The second rule that we considered, variance control, directly regulates the variance of neural activities by locally scaling the recurrent synaptic weights. The target set point of this homeostatic mechanism is dynamically determined as a function of the variance of the locally measured external input. This functional relation was derived from the same mean-field approach that was used to describe the approximate dynamics of flow control.
The effectiveness of the presented mechanisms was tested numerically using different external input protocols. The network performance after adaptation was evaluated by training the network to perform a time delayed XOR operation on binary sequences. As our main result, we found that flow control can reliably regulate the spectral radius under different input statistics, but precise tuning is negatively affected by interneural correlations. Furthermore, flow control showed a consistent task performance over a wide range of input strengths/variances. Variance control, on the other side, did not yield the desired spectral radii with the same precision. Moreover, task performance was less consistent across different input strengths.
Given the better performance and simpler mathematical form of flow control, we concluded that a local control of the spectral radius via an implicit adaptation scheme is a realistic alternative to approaches using classical “set point” homeostatic feedback controls of neural firing.
Author summary How can a neural network control its recurrent synaptic strengths such that network dynamics are optimal for sequential information processing? An important quantity in this respect, the spectral radius of the recurrent synaptic weight matrix, is a non-local quantity. Therefore, a direct calculation of the spectral radius is not feasible for biological networks. However, we show that there exist a local and biologically plausible adaptation mechanism, flow control, which allows to control the recurrent weight spectral radius while the network is operating under the influence of external inputs. Flow control is based on a theorem of random matrix theory, which is applicable if inter-synaptic correlations are weak. We apply the new adaption rule to echo-state networks having the task to perform a time-delayed XOR operation on random binary input sequences. We find that flow-controlled networks can adapt to a wide range of input strengths while retaining essentially constant task performance.
The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community’s massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field of drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made. In this paper, we present the COVID-19 PHARMACOME, a comprehensive drug-target-mechanism graph generated from a compilation of 10 separate disease maps and sources of experimental data focused on SARS-CoV-2 / COVID-19 pathophysiology. By applying our systematic approach, we were able to predict the synergistic effect of specific drug pairs, such as Remdesivir and Thioguanosine or Nelfinavir and Raloxifene, on SARS-CoV-2 infection. Experimental validation of our results demonstrate that our graph can be used to not only explore the involved mechanistic pathways, but also to identify novel combinations of drug repurposing candidates.
The multistep PROTAC (PROteolysis TArgeting Chimeras) degradation process poses challenges for their rational development, as rate limiting steps determining PROTAC efficiency remain largely unknown. Moreover, the slow throughput of currently used endpoint assays does not allow the comprehensive analysis of larger series of PROTACs. Here we developed cell-based assays using NanoLuciferase and HaloTags, that allow measuring PROTAC induced degradation and ternary complex formation kinetics and stability in cells. Using PROTACs developed for degradation of WDR5, the characterization of the mode of action of these PROTACs in the early degradation cascade revealed a key role of ternary complex formation and stability. Comparing a series of ternary complex crystal structures highlighted the importance of an efficient E3-target interface for ternary complex stability. The developed assays outline a strategy for the rational optimization of PROTACs using a series of live cell assays monitoring key steps of the early PROTAC induced degradation pathway.
Significance The multistep PROTAC induced degradation process of a POI poses a significant challenge for the rational design of these bifunctional small molecules as critical steps that limit PROTAC efficacy cannot be easily assayed at required throughput. In addition, the cellular location of the POI may pose additional challenges as some cellular compartments, such as the nucleus, may not be easily reached by PROTAC molecules and the targeted E3 ligases may not be present in this cellular compartment. We propose therefore a comprehensive assay panel for PROTACs evaluation in cellular environments using a sensor system that allows continuous monitoring of the protein levels of the endogenous POI. We developed a cell line expressing WDR5 from its endogenous locus in fusion with a small sequence tag (HiBIT) that can be reconstituted to functional NanoLuciferase (NLuc). This system allowed continuous monitoring of endogenous WDR5 levels in cells and together with HaloTag system also the continuous monitoring of ternary complex (E3, WDR5 and PROTAC) formation. As this assay can be run at high throughput, we used this versatile system monitoring three diverse chemical series of WDR5 PROTACs that markedly differ in their degradation properties. Monitoring cell penetration, binary complex formation (PROTAC-WDR5 and PROTAC-VHL) as well as ternary complex formation we found that PROTAC efficiency highly correlated with synergy of ternary complex formation in cells. This study represents a first data set on diverse PROTACs studying this property in cellulo and it outlines a strategy for the rational optimization of PROTACs. It also provided kinetic data on ternary complex assembly and dissociation that may serve as a benchmark for future studies utilizing also kinetic properties for PROTAC development. Comparative structural studies revealed larger PROTAC mediated interaction surfaces for PROTACs that efficiently formed ternary complexes highlighting the utility of structure based optimization of PROTAC induced ternary complexes in the development process.
Hydrogen is a promising fuel in a carbon-neutral economy, and many efforts are currently undertaken to produce hydrogen. One of the challenges is to store and transport the highly explosive gas in a safe and easy way. One option that is intensively analyzed by chemists and biologists is the conversion of hydrogen and CO2 to formic acid, the liquid organic hydrogen carrier. Here, we demonstrate for the first time that a bio-based system, using Acetobacterium woodii as the biocatalyst, allows multiple cycles of bi-directional hydrogenation of CO2 to formic acid in one bioreactor. The process was kept running over 2 weeks producing and oxidizing 330 mM formic acid in total. Unwanted side-product formation of acetic acid was prevented through metabolic engineering of the organism. The demonstrated process design can be considered as a future “bio-battery” for the reversible storage of electrons in the form of H2 in formic acid, a versatile compound.
We propose to measure azimuthal correlations of heavy-flavor hadrons to address the status of thermalization at the partonic stage of light quarks and gluons in high-energy nuclear collisions. In particular, we show that hadronic interactions at the late stage cannot significantly disturb the initial back-to-back azimuthal correlations of DDbar pairs. Thus, a decrease or the complete absence of these initial correlations does indicate frequent interactions of heavy-flavor quarks and also light partons in the partonic stage, which are essential for the early thermalization of light partons.
In this special issue of Matrix Biology centered on proteoglycan biology we have assembled a blend of articles focused on the state-of-the-art of proteoglycanology. The field has greatly expanded in the past three decades and now encompasses all the areas of biology. This special issue is divided into five chapters describing hyaluronan metabolism, biosynthetic and catabolic pathways of proteoglycans and their roles in inflammation, cancer, repair and development. We hope that the new original work and the reviews from recognized leaders will stimulate investigations in this exciting and fertile field of research.
Gasdermin-D (GSDMD) is the ultimate effector of pyroptosis, a form of programmed cell death associated with pathogen invasion and inflammation. After proteolytic cleavage by caspases activated by the inflammasome, the GSDMD N-terminal domain (GSDMDNT) assembles on the inner leaflet of the plasma membrane and induces the formation of large membrane pores. We use atomistic molecular dynamics simulations to study GSDMDNT monomers, oligomers, and rings in an asymmetric plasma membrane mimetic. We identify distinct interaction motifs of GSDMDNT with phosphatidylinositol-4,5-bisphosphate (PI(4,5)P2) and phosphatidylserine (PS) head-groups and describe differential lipid binding between the pore and prepore conformations. Oligomers are stabilized by shared lipid binding sites between neighboring monomers acting akin to double-sided tape. We show that already small GSDMDNT oligomers form stable, water-filled and ion-conducting membrane pores bounded by curled beta-sheets. In large-scale simulations, we resolve the process of pore formation by lipid detachment from GSDMDNT arcs and lipid efflux from partial rings. We find that that high-order GSDMDNT oligomers can crack under the line tension of 86 pN created by an open membrane edge to form the slit pores or closed GSDMDNT rings seen in experiment. Our simulations provide a detailed view of key steps in GSDMDNT-induced plasma membrane pore formation, including sublytic pores that explain nonselective ion flux during early pyroptosis.
During infection the SARS-CoV-2 virus fuses its viral envelope with cellular membranes of its human host. Initial contact with the host cell and membrane fusion are both mediated by the viral spike (S) protein. Proteolytic cleavage of S at the S2′ site exposes its 40 amino acid long fusion peptide (FP). Binding of the FP to the host membrane anchors the S2 domain of S in both the viral and the host membrane. The reorganization of S2 then pulls the two membranes together. Here we use molecular dynamics (MD) simulations to study the two core functions of the SARS-CoV-2 FP: to attach quickly to cellular membranes and to form an anchor strong enough to withstand the mechanical force during membrane fusion. In eight 10 μs-long MD simulations of FP in proximity to endosomal and plasma membranes, we find that FP binds spontaneously to the membranes and that binding proceeds predominantly by insertion of two short amphipathic helices into the membrane interface. Connected via a flexible linker, the two helices can bind the membrane independently, yet binding of one promotes the binding of the other by tethering it close to the target membrane. By simulating mechanical pulling forces acting on the C-terminus of the FP we then show that the bound FP can bear forces up to 250 pN before detaching from the membrane. This detachment force is more than ten-fold higher than an estimate of the force required to pull host and viral membranes together for fusion. We identify a fully conserved disulfide bridge in the FP as a major factor for the high mechanical stability of the FP membrane anchor. We conclude, first, that the sequential binding of two short amphipathic helices allows the SARS-CoV-2 FP to insert quickly into the target membrane, before the virion is swept away after shedding the S1 domain connecting it to the host cell receptor. Second, we conclude that the double attachment and the conserved disulfide bridge establish the strong anchoring required for subsequent membrane fusion. Multiple distinct membrane-anchoring elements ensure high avidity and high mechanical strength of FP-membrane binding.
Summary We introduce fsbrain, an R package for the visualization of neuroimaging data. The package can be used to visualize vertex-wise and region-wise morphometry data, parcellations, labels and statistical results on brain surfaces in three dimensions (3D). Voxel data can be displayed in lightbox mode. The fsbrain package offers various customization options and produces publication quality plots which can be displayed interactively, saved as bitmap images, or integrated into R notebooks.
Availability and Implementation The software, source code and documentation are available under the MIT license at https://github.com/dfsp-spirit/fsbrain. Releases can be installed directly from the Comprehensive R Archive Network (CRAN).
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population density and structure, and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 particles mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population size and structure and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
Treatments for amblyopia focus on vision therapy and patching of one eye. Predicting the success of these methods remains difficult, however. Recent research has used binocular rivalry to monitor visual cortical plasticity during occlusion therapy, leading to a successful prediction of the recovery rate of the amblyopic eye. The underlying mechanisms and their relation to neural homeostatic plasticity are not known. Here we propose a spiking neural network to explain the effect of short-term monocular deprivation on binocular rivalry. The model reproduces perceptual switches as observed experimentally. When one eye is occluded, inhibitory plasticity changes the balance between the eyes and leads to longer dominance periods for the eye that has been deprived. The model suggests that homeostatic inhibitory plasticity is a critical component of the observed effects and might play an important role in the recovery from amblyopia.
Introns of human transfer RNA precursors (pre-tRNAs) are excised by the tRNA splicing endonuclease TSEN in complex with the RNA kinase CLP1. Mutations in TSEN/CLP1 occur in patients with pontocerebellar hypoplasia (PCH), however, their role in the disease is unclear. Here, we show that intron excision is catalyzed by tetrameric TSEN assembled from inactive heterodimers independently of CLP1. Splice site recognition involves the mature domain and the anticodon-intron base pair of pre-tRNAs. The 2.1-Å resolution X-ray crystal structure of a TSEN15–34 heterodimer and differential scanning fluorimetry analyses show that PCH mutations cause thermal destabilization. While endonuclease activity in recombinant mutant TSEN is unaltered, we observe assembly defects and reduced pre-tRNA cleavage activity resulting in an imbalanced pre-tRNA pool in PCH patient-derived fibroblasts. Our work defines the molecular principles of intron excision in humans and provides evidence that modulation of TSEN stability may contribute to PCH phenotypes.
The heterotetrameric human transfer RNA (tRNA) splicing endonuclease (TSEN) catalyzes the excision of intronic sequences from precursor tRNAs (pre-tRNAs)1. Mutations in TSEN and its associated RNA kinase CLP1 are linked to the neurodegenerative disease pontocerebellar hypoplasia (PCH)2–8. The three-dimensional (3D) assembly of TSEN/CLP1, the mechanism of substrate recognition, and the molecular details of PCH-associated mutations are not fully understood. Here, we present cryo-electron microscopy structures of human TSEN with intron-containing pre-tRNATyrgta and pre-tRNAArgtct. TSEN exhibits broad structural homology to archaeal endonucleases9 but has evolved additional regulatory elements that are involved in handling and positioning substrate RNA. Essential catalytic residues of subunit TSEN34 are organized for the 3’ splice site which emerges from a bulge-helix configuration. The triple-nucleotide bulge at the intron/3’-exon boundary is stabilized by an arginine tweezer motif of TSEN2 and an interaction with the proximal minor groove of the helix. TSEN34 and TSEN54 define the 3’ splice site by holding the tRNA body in place. TSEN54 adapts a bipartite fold with a flexible central region required for CLP1 binding. PCH-associated mutations are located far from pre-tRNA binding interfaces explaining their negative impact on structural integrity of TSEN without abrogating its catalytic activity in vitro10. Our work defines the molecular framework of pre-tRNA recognition and cleavage by TSEN and provides a structural basis to better understand PCH in the future.
Experiment NA49 at the Cern SPS uses a large acceptance detector for a systematic study of particle yields and correlations in nucleus-nucleus, nucleon-nucleus and nucleon-nucleon collisions. Preliminary results for Pb+Pb collisions at 40, 80 and 158 A*GeV beam energy are shown and compared to measurements at lower and higher energies.
SARS-CoV-2 and stroke characteristics: a report from the Multinational COVID-19 Stroke Study Group
(2020)
Background: Stroke is reported as a consequence of SARS-CoV-2 infection. However, there is a lack of regarding comprehensive stroke phenotype and characteristics
Methods: We conducted a multinational observational study on features of consecutive acute ischemic stroke (AIS), intracranial hemorrhage (ICH), and cerebral venous or sinus thrombosis (CVST) among SARS-CoV-2 infected patients. We further investigated the association of demographics, clinical data, geographical regions, and countries’ health expenditure among AIS patients with the risk of large vessel occlusion (LVO), stroke severity as measured by National Institute of Health stroke scale (NIHSS), and stroke subtype as measured by the TOAST criteria. Additionally, we applied unsupervised machine learning algorithms to uncover possible similarities among stroke patients.
Results: Among the 136 tertiary centers of 32 countries who participated in this study, 71 centers from 17 countries had at least one eligible stroke patient. Out of 432 patients included, 323(74.8%) had AIS, 91(21.1%) ICH, and 18(4.2%) CVST. Among 23 patients with subarachnoid hemorrhage, 16(69.5%) had no evidence of aneurysm. A total of 183(42.4%) patients were women, 104(24.1%) patients were younger than 55 years, and 105(24.4%) patients had no identifiable vascular risk factors. Among 380 patients who had known interval onset of the SARS-CoV-2 and stroke, 144(37.8%) presented to the hospital with chief complaints of stroke-related symptoms, with asymptomatic or undiagnosed SARS-CoV-2 infection. Among AIS patients 44.5% had LVO; 10% had small artery occlusion according to the TOAST criteria. We observed a lower median NIHSS (8[3-17], versus 11 [5-17]; p=0.02) and higher rate of mechanical thrombectomy (12.4% versus 2%; p<0.001) in countries with middle to high-health expenditure when compared to countries with lower health expenditure. The unsupervised machine learning identified 4 subgroups, with a relatively large group with no or limited comorbidities.
Conclusions: We observed a relatively high number of young, and asymptomatic SARS-CoV-2 infections among stroke patients. Traditional vascular risk factors were absent among a relatively large cohort of patients. Among hospitalized patients, the stroke severity was lower and rate of mechanical thrombectomy was higher among countries with middle to high-health expenditure.
The new variant of concern (VOC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Omicron (B.1.1.529), is genetically very different from other VOCs. We compared Omicron with the preceding VOC Delta (B.1.617.2) and the wildtype strain (B.1) with respect to their interactions with the antiviral type I interferon (IFN-alpha/beta) response in infected cells. Our data indicate that Omicron has gained an elevated capability to suppress IFN-beta induction upon infection and to better withstand the antiviral state imposed by exogenously added IFN-alpha.
The basidiomycete smut fungi are predominantly plant parasitic, causing severe losses in some crops. Most species feature a saprotrophic haploid yeast stage, and several smut fungi are only known from this stage, with some isolated from habitats without suitable hosts, e.g. from Antarctica. Thus, these species are generally believed to be apathogenic, but recent findings that some of these might have a plant pathogenic sexual counterpart, casts doubts on the validity of this hypothesis. Here, four Pseudozyma genomes were re-annotated and compared to published smut pathogens and the well-characterised effector gene Pep1 from these species was checked for its ability to complement a Pep1 deletion strain of Ustilago maydis. It was found that 113 high-confidence putative effector proteins were conserved among smut and Pseudozyma genomes. Among these were several validated effector proteins, including Pep1. By genetic complementation we show that Pep1 homologs from the supposedly apathogenic yeasts restore virulence in Pep1-deficient mutants Ustilago maydis. Thus, it is concluded that Pseudozyma species have retained a suite of effectors. This hints at the possibility that Pseudozyma species have kept an unknown plant pathogenic stage for sexual recombination or that these effectors have positive effects when colonising plant surfaces.
The entire chemical modification repertoire of yeast ribosomal RNAs and the enzymes responsible for it have recently been identified. Nonetheless, in most cases the precise roles played by these chemical modifications in ribosome structure, function and regulation remain totally unclear. Previously, we demonstrated that yeast Rrp8 methylates m1A645 of 25S rRNA in yeast. Here, using mung bean nuclease protection assays in combination with quantitative RP-HPLC and primer extension, we report that 25S/28S rRNA of S. pombe, C. albicans and humans also contain a single m1A methylation in the helix 25.1. We characterized nucleomethylin (NML) as a human homolog of yeast Rrp8 and demonstrate that NML catalyzes the m1A1322 methylation of 28S rRNA in humans. Our in vivo structural probing of 25S rRNA, using both DMS and SHAPE, revealed that the loss of the Rrp8-catalyzed m1A modification alters the conformation of domain I of yeast 25S rRNA causing translation initiation defects detectable as halfmers formation, likely because of incompetent loading of 60S on the 43S-preinitiation complex. Quantitative proteomic analysis of the yeast Δrrp8 mutant strain using 2D-DIGE, revealed that loss of m1A645 impacts production of specific set of proteins involved in carbohydrate metabolism, translation and ribosome synthesis. In mouse, NML has been characterized as a metabolic disease-associated gene linked to obesity. Our findings in yeast also point to a role of Rrp8 in primary metabolism. In conclusion, the m1A modification is crucial for maintaining an optimal 60S conformation, which in turn is important for regulating the production of key metabolic enzymes.
While the liver, specifically hepatocytes, are widely accepted as the main source for hepatitis C virus (HCV) production, the role of the liver/hepatocytes in the clearance of circulating HCV remains largely unknown. Here we evaluated the function of the liver/hepatocytes in clearing virus from the circulation by investigating viral clearance during liver transplantation and from culture medium in vitro. Frequent HCV kinetic data during liver transplantation were recorded from 5 individuals throughout the anhepatic (AH) phase and for 4 hours after reperfusion (RP), along with recordings of fluid balances. Using mathematical modeling, the serum viral clearance rate, c, was estimated. Analogously, we monitored the clearance rate of HCV at 37°C from culture medium in vitro in the absence and presence of chronically infected Huh7 human hepatoma cells. During the AH phase, in 3 transplant cases viral levels remained at pre-AH levels, while in the other 2 cases HCV declined (half-life, t1/2~1h). Immediately post-RP, virus declined in a biphasic manner in Cases 1-4 consisting of an extremely rapid (median t1/2=5min) decline followed by a slower decline (HCV t1/2=67min). In Case 5, HCV remained at the same level post-RP as at the end of AH. Declines in virus level were not explained by adjusting for dilution from IV fluid and blood products. Consistent with what was observed in the majority of patients in the anhepatic phase, the t1/2 of HCV in cell culture was much longer in the absence of chronically HCV-infected Huh7 cells. Therefore, kinetic and modeling results from both in vivo liver transplantation cases and in vitro cell culture studies suggest that the liver plays a major role in clearing HCV from the circulation.
Pathophysiological models are urgently needed for personalized treatments of mental disorders. However, most potential neural markers for psychopathology are limited by low interpretability, prohibiting reverse inference from brain measures to clinical symptoms and traits. Neural signatures—i.e. multivariate brain-patterns trained to be both sensitive and specific to a construct of interest—might alleviate this problem, but are rarely applied to mental disorders. We tested whether previously developed neural signatures for negative affect and discrete emotions distinguish between healthy individuals and those with mental disorders characterized by emotion dysregulation, i.e. Borderline Personality Disorder (BPD) and complex Post-traumatic Stress Disorder (cPTSD). In three different fMRI studies, a total sample of 192 women (49 BPD, 62 cPTSD, 81 healthy controls) were shown pictures of scenes with negative or neutral content. Based on pathophysiological models, we hypothesized higher negative and lower positive reactivity of neural emotion signatures in participants with emotion dysregulation. The expression of neural signatures differed strongly between neutral and negative pictures (average Cohen’s d = 1.17). Nevertheless, a mega-analysis on individual participant data showed no differences in the reactivity of neural signatures between participants with and without emotion dysregulation. Confidence intervals ruled out even small effect sizes in the hypothesized direction and were further supported by Bayes factors. Overall, these results support the validity of neural signatures for emotional states during fMRI tasks, but raise important questions concerning their link to individual differences in emotion dysregulation.
Background Coronavirus disease 2019 (COVID-19) represents a significant challenge to health care systems around the world. A well-functioning primary care system is crucial in epidemic situations as it plays an important role in the development of a system-wide response.
Methods 2,187 Austrian and German GPs answered an internet suvey on preparedness, testing, staff protection, perception of risk, self-confidence, a decrease in the number of patient contacts, and efforts to control the spread of the virus in the practice during the early phase of the COVID-pandemic (3rd to 30th April).
Results The completion rate of the questionnaire was high (90.9%). GPs gave low ratings to their preparedness for a pandemic, testing of suspected cases and efforts to protect staff. The provision of information to GPs and the perception of risk were rated as moderate. On the other hand, the participants rated their self-confidence, a decrease in patient contacts and their efforts to control the spread of the disease highly.
Conclusion Primary care is an important resource for dealing with a pandemic like COVID-19. The workforce is confident and willing to take an active role, but needs to be provided with the appropriate surrounding conditions. This will require that certain conditions are met.
Registration Trial registration at the German Clinical Trials Register: DRKS00021231
EF-P and its paralog EfpL (YeiP) differentially control translation of proline containing sequences
(2024)
Polyproline sequences (XPPX) stall ribosomes, thus being deleterious for all living organisms. In bacteria, translation elongation factor P (EF-P) plays a crucial role in overcoming such arrests. 12% of eubacteria possess an EF-P paralog – YeiP (EfpL) of unknown function. Here, we functionally and structurally characterize EfpL from Escherichia coli and demonstrate its yet unrecognized role in the translational stress response. Through ribosome profiling, we analyzed the EfpL arrest motif spectrum and discovered additional stalls beyond the canonical XPPX motifs at single-proline sequences (XPX), that both EF-P and EfpL can resolve. Notably, the two factors can also induce pauses. We further report that, contrary to the housekeeping EF-P, EfpL can sense the metabolic state of the cell, via lysine acylation. Together, our work uncovers a new player in ribosome rescue at proline-containing sequences, and provides evidence that co-occurrence of EF-P and EfpL is an evolutionary driver for higher bacterial growth rates.
Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, relative duration and relative distance in time of two sequentially-organized events —standard S, with constant duration, and comparison C, varying trial-by-trial— are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer ISI helps counteracting such serial distortion effect only the constant S is in first position, but not if the unpredictable C is in first position. These results suggest the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanics generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones.
Living cells constantly remodel the shape of their lipid membranes. In the endo-plasmic reticulum (ER), the reticulon homology domain (RHD) of the reticulophagy regulator 1 (RETR1/FAM134B) forms dense autophagic puncta that are associated with membrane removal by ER-phagy. In molecular dynamics (MD) simulations, we find that FAM134B-RHD spontaneously forms clusters, driven in part by curvature-mediated attraction. At a critical size, the FAM134B-RHD clusters induce the formation of membrane buds. The kinetics of budding depends sensitively on protein concentration and bilayer asymmetry. Our MD simulations shed light on the role of FAM134B-RHD in ER-phagy and show that membrane asymmetry can be used to modulate the kinetics barrier for membrane remodeling.
TriMem: a parallelized hybrid Monte Carlo software for efficient simulations of lipid membranes
(2022)
Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane structures at atomic resolution are nearly impossible, due to their size, complexity, and the large times-scales required. Instead, elastic membrane models are used to simulate membrane topologies and transitions between them, and to infer their properties and functions. Unfortunately, efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate also large and highly curved sub-cellular structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. The software can tackle a range of membrane remodelling processes on sub-cellular and cellular scales. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.
The severity of the COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, calls for the urgent development of a vaccine. The primary immunological target is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface to mediate viral entry into the host cell. To identify possible antibody binding sites not shielded by glycans, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for vaccine development. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics in epitope mapping.
During animal development, it is crucial that cells can sense and adapt to mechanical forces from their environment. Ultimately, these forces are transduced through the actomyosin cortex. How the cortex can simultaneously respond to and create forces during cytokinesis is not well understood. Here we show that under mechanical stress, cortical actomyosin flow switches its polarization during cytokinesis in the C. elegans embryo. In unstressed embryos, longitudinal cortical flows contribute to contractile ring formation, while rotational cortical flow is additionally induced in uniaxially loaded embryos. Rotational cortical flow is required for the redistribution of the actomyosin cortex in loaded embryos. Rupture of longitudinally aligned cortical fibers during cortex rotation releases tension, initiates orthogonal longitudinal flow and thereby contributes to furrowing in loaded embryos. A targeted screen for factors required for rotational flow revealed that actomyosin regulators involved in RhoA regulation, cortical polarity and chirality are all required for rotational flow and become essential for cytokinesis under mechanical stress. In sum, our findings extend the current framework of mechanical stress response during cell division and show scaling of orthogonal cortical flows to the amount of mechanical stress.
A candidate gene cluster for the bioactive natural product gyrophoric acid in lichen-forming fungi
(2022)
Natural products of lichen-forming fungi are structurally diverse and have a variety of medicinal properties. Despite this, they a have limited implementation in industry, because the corresponding genes remain unknown for most of the natural products. Here we implement a long-read sequencing and bioinformatic approach to identify the biosynthetic gene cluster of the bioactive natural product gyrophoric acid (GA). Using 15 high-quality genomes representing nine GA-producing species of the lichen-forming fungal genus Umbilicaria, we identify the most likely GA cluster and investigate cluster gene organization and composition across the nine species. Our results show that GA clusters are promiscuous within Umbilicaria, with only three genes that are conserved across species, including the PKS gene. In addition, our results suggest that the same cluster codes for different but structurally similar NPs, i.e., GA, umbilicaric acid and hiascic acid, bringing new evidence that lichen metabolite diversity is also generated through regulatory mechanisms at the molecular level. Ours is the first study to identify the most likely GA cluster, and thus provides essential information to open new avenues for biotechnological approaches to producing and modifying GA and similar lichen-derived compounds. We show that bioinformatics approaches are useful in linking genes and potentially associated natural products. Genome analyses help unlocking the pharmaceutical potential of organisms such as lichens, which are biosynthetically diverse but slow growing, and difficult to cultivate due to their symbiotic nature.
Genome mining as a biotechnological tool for the discovery of novel biosynthetic genes in lichens
(2022)
The ever-increasing demand for novel drugs highlights the need for bioprospecting unexplored taxa for their biosynthetic potential. Lichen-forming fungi (LFF) are a rich source of natural products but their implementation in pharmaceutical industry is limited, mostly because the genes corresponding to a majority of their natural products is unknown. Furthermore, it is not known to what extent these genes encode structurally novel molecules. Advance in next-generation sequencing technologies has expanded the range of organisms that could be exploited for their biosynthetic potential. In this study, we mine the genomes of nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and categorize the BGCs as “associated product structurally known”, and “associated product putatively novel”. We found that about 25-30% of the biosynthetic genes are divergent when compared to the global database of BGCs comprising of 1,200,000 characterized biosynthetic genes from planta, bacteria and fungi. Out of 217 total BGCs, 43 were only distantly related to known BGCs, suggesting they encode structurally and functionally unknown natural products. Clusters encoding the putatively novel metabolic diversity comprise PKSs (30), NRPSs (12) and terpenes (1). Our study emphasizes the utility of genomic data in bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial application of unexplored taxa. We highlight the untapped structural metabolic diversity encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first investigation identifying genes coding for NPs with potentially novel therapeutic properties in LFF.
The cortical networks that underlie behavior exhibit an orderly functional organization at local and global scales, which is readily evident in the visual cortex of carnivores and primates1-6. Here, neighboring columns of neurons represent the full range of stimulus orientations and contribute to distributed networks spanning several millimeters2,7-11. However, the principles governing functional interactions that bridge this fine-scale functional architecture and distant network elements are unclear, and the emergence of these network interactions during development remains unexplored. Here, by using in vivo wide-field and 2-photon calcium imaging of spontaneous activity patterns in mature ferret visual cortex, we find widespread and specific modular correlation patterns that accurately predict the local structure of visually-evoked orientation columns from the spontaneous activity of neurons that lie several millimeters away. The large-scale networks revealed by correlated spontaneous activity show abrupt ‘fractures’ in continuity that are in tight register with evoked orientation pinwheels. Chronic in vivo imaging demonstrates that these large-scale modular correlation patterns and fractures are already present at early stages of cortical development and predictive of the mature network structure. Silencing feed-forward drive through either retinal or thalamic blockade does not affect network structure suggesting a cortical origin for this large-scale correlated activity, despite the immaturity of long-range horizontal network connections in the early cortex. Using a circuit model containing only local connections, we demonstrate that such a circuit is sufficient to generate large-scale correlated activity, while also producing correlated networks showing strong fractures, a reduced dimensionality, and an elongated local correlation structure, all in close agreement with our empirical data. These results demonstrate the precise local and global organization of cortical networks revealed through correlated spontaneous activity and suggest that local connections in early cortical circuits may generate structured long-range network correlations that underlie the subsequent formation of visually-evoked distributed functional networks.
RuO₂: a puzzle to be solved
(2023)
Altermagnetism is a topic that has lately been gaining attention and the RuO2 compound is among one of the most studied altermagnetic candidates. However, the survey of available literature on RuO2 properties suggests that there is no consensus about the magnetism of this material. By performing density functional theory calculations, we show that the electronic properties of stoichiometric RuO2 are described in terms of a smaller Hubbard U within DFT+U than the value required to have magnetism. We further argue that Ru vacancies can actually aid the formation of a magnetic state in RuO2. This in turn suggests that a characterization of the amount of Ru vacancies in experimental samples might help the resolution of the controversy between the different experimental results.
Invited talk at the 7th International Conference on Strangeness in Quark Matter, SQM 2003, Atlantic Beach, North Carolina, USA, 12-17 Mar, 2003. 11 pages, 12 figures. Journal-ref: J.Phys. G30 (2004) S139-S150. We review recent developments in the field of microscopic transport model calculations for ultrarelativistic heavy ion collisions. In particular, we focus on the strangeness production, for example, the phi-meson and its role as a messenger of the early phase of the system evolution. Moreover, we discuss the important e ects of the (soft) field properties on the multiparticle system. We outline some current problems of the models as well as possible solutions to them
Invited talk at the XXXIII International Symposium on Multiparticle Dynamics, Krakow, Poland, 5-11 Sept, 2003. 5 pages, 1 figure Journal-ref: Acta Phys.Polon. B35 (2004) 23-28. We review the recent developments on microscopic transport calculations for two-particle correlations at low relative momenta in ultrarelativistic heavy ion collisions at RHIC.
Invited talk at the International Workshop XXX on Gross Properties of Nuclei and Nuclear Excitations - Ultrarelativistic Heavy-Ion Collisions, Jan. 13-19, 2002, Hirschegg, Austria. Report-no: LBNL-49674. We discuss predictions for the pion and kaon interferometry measurements in relativistic heavy ion collisions at SPS and RHIC energies. In particular, we confront relativistic transport model calculations that include explicitly a first-order phase transition from a thermalized quark-gluon plasma to a hadron gas with recent data from the RHIC experiments. We critically examine the "HBT-puzzle" both from the theoretical as well as from the experimental point of view. Alternative scenarios are briefly explained.
The centrality dependence of (multi-)strange hadron abundances is studied for Pb(158 AGeV)Pb reactions and compared to p(158 GeV)Pb collisions. The microscopic transport model UrQMD is used for this analysis. The predicted Lambda/pi-, Xi-/pi- and Omega-/pi- ratios are enhanced due to rescattering in central Pb-Pb collisions as compared to peripheral Pb-Pb or p-Pb collisions. A reduction of the constituent quark masses to the current quark masses m_s \sim 230 MeV, m_q \sim 10 MeV, as motivated by chiral symmetry restoration, enhances the hyperon yields to the experimentally observed high values. Similar results are obtained by an ad hoc overall increase of the color electric field strength (effective string tension of kappa=3 GeV/fm). The enhancement depends strongly on the kinematical cuts. The maximum enhancement is predicted around midrapidity. For Lambda's, strangeness suppression is predicted at projectile/target rapidity. For Omega's, the predicted enhancement can be as large as one order of magnitude. Comparisons of Pb-Pb data to proton induced asymmetric (p-A) collisions are hampered due to the predicted strong asymmetry in the various rapidity distributions of the different (strange) particle species. In p-Pb collisions, strangeness is locally (in rapidity) not conserved. The present comparison to the data of the WA97 and NA49 collaborations clearly supports the suggestion that conventional (free) hadronic scenarios are unable to describe the observed high (anti-)hyperon yields in central collisions. The doubling of the strangeness to nonstrange suppression factor, gamma_s \approx 0.65, might be interpreted as a signal of a phase of nearly massless particles.
Directed and elliptic flow
(1999)
We compare microscopic transport model calculations to recent data on the directed and elliptic flow of various hadrons in 2 - 10 A GeV Au+Au and Pb (158 A GeV) Pb collisions. For the Au+Au excitation function a transition from the squeeze-out to an in-plane enhanced emission is consistently described with mean field potentials corresponding to one incompressibility. For the Pb (158 A GeV) Pb system the elliptic flow prefers in-plane emission both for protons and pions, the directed flow of protons is opposite to that of the pions, which exhibit anti-flow. Strong directed transverse flow is present for protons and Lambdas in Au (6 A GeV) Au collisions as well. Both for the SPS and the AGS energies the agreement between data and calculations is remarkable.
We calculate the Gaussian radius parameters of the pion-emitting source in high energy heavy ion collisions, assuming a first order phase transition from a thermalized Quark-Gluon-Plasma (QGP) to a gas of hadrons. Such a model leads to a very long-lived dissipative hadronic rescattering phase which dominates the properties of the two-pion correlation functions. The radii are found to depend only weakly on the thermalization time tau i, the critical temperature T c (and thus the latent heat), and the specific entropy of the QGP. The dissipative hadronic stage enforces large variations of the pion emission times around the mean. Therefore, the model calculations suggest a rapid increase of R out/R side as a function of K T if a thermalized QGP were formed.
We make predictions for the kaon interferometry measurements in Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC). A first order phase transition from a thermalized Quark-Gluon-Plasma (QGP) to a gas of hadrons is assumed for the transport calculations. The fraction of kaons that are directly emitted from the phase boundary is considerably enhanced at large transverse momenta K T ~ 1 GeV/c. In this kinematic region, the sensitivity of the R out/R side ratio to the QGP-properties is enlarged. Here, the results of the 1-dimensional correlation analysis are presented. The extracted interferometry radii, depending on K-Theta, are not unusually large and are strongly affected by momentum resolution effects.
We present calculations of two-pion and two-kaon correlation functions in relativistic heavy ion collisions from a relativistic transport model that includes explicitly a first-order phase transition from a thermalized quark-gluon plasma to a hadron gas. We compare the obtained correlation radii with recent data from RHIC. The predicted R_side radii agree with data while the R_out and R_long radii are overestimated. We also address the impact of in-medium modifications, for example, a broadening of the rho-meson, on the correlation radii. In particular, the longitudinal correlation radius R_long is reduced, improving the comparison to data.
The disappearance of flow
(1995)
We investigate the disappearance of collective flow in the reaction plane in heavy-ion collisions within a microscopic model (QMD). A systematic study of the impact parameter dependence is performed for the system Ca+Ca. The balance energy strongly increases with impact parameter. Momentum dependent interactions reduce the balance energies for intermediate impact parameters b ~ 4.5 fm. Dynamical negative flow is not visible in the laboratory frame but does exist in the contact frame for the heavy system Au+Au. For semi-peripheral collisions of Ca+Ca with b ~ 6.5 fm a new two-component flow is discussed. Azimuthal distributions exhibit strong collectiv flow signals, even at the balance energy.
We investigate the effects of strong color fields and of the associated enhanced intrinsic transverse momenta on the phi-meson production in ultrarelativistic heavy ion collisions at RHIC. The observed consequences include a change of the spectral slopes, varying particle ratios, and also modified mean transverse momenta. In particular, the composition of the production processes of phi-mesons, that is, direct production vs. coalescence-like production, depends strongly on the strength of the color fields and intrinsic transverse momenta and thus represents a sensitive probe for their measurement.
The yields of strange particles are calculated with the UrQMD model for p,Pb(158 AGeV)Pb collisions and compared to experimental data. The yields are enhanced in central collisions if compared to proton induced or peripheral Pb+Pb collisions. The enhancement is due to secondary interactions. Nevertheless, only a reduction of the quark masses or equivalently an increase of the string tension provides an adequate description of the large observed enhancement factors (WA97 and NA49). Furthermore, the yields of unstable strange resonances as the Lambda star(1520) resonance or the phi meson are considerably affected by hadronic rescattering of the decay products.
Age-related memory decline is associated with changes in neural functioning but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age, memory studies have shown that high similarity between activity patterns benefits memory performance for the respective stimuli. Here, we addressed this apparent conflict by investigating between-item representational similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) human adults (male and female) who studied scene-word associations using a mnemonic imagery strategy while electroencephalography was recorded. We compared the similarity of spatiotemporal frequency patterns elicited during encoding of items with different subsequent memory fate. Compared to younger adults, older adults’ memory representations were more similar to each other but items that elicited the most similar activity patterns early in the encoding trial were those that were best remembered by older adults. In contrast, young adults’ memory performance benefited from decreased similarity between earlier and later periods in the encoding trials, which might reflect their better success in forming unique memorable mental images of the joint picture–word pair. Our results advance the understanding of the representational properties that give rise to memory quality as well as how these properties change in the course of aging.
Consistent individual differences in behaviour (animal personality) are widespread throughout the Animal Kingdom. This includes variation in risk-taking versus risk-averse behavioural tendencies. Variation in several personality dimensions is associated with distinct fitness consequences and thus, may become a target of natural and/or sexual selection. However, the link between animal personality and mate choice—as a major component of sexual selection—remains understudied. We asked (1) whether females and males of the livebearing fish Poecilia mexicana prefer risk-taking mating partners (directional mating preference), (2) or if their preferences are dependent on the choosing individual’s own personality type (assortative mating). We characterized each test subject for its risk-taking behaviour, assessed as the time to emerge from shelter and enter an unknown area. In dichotomous association preference tests, we offered two potential mating partners that differed in risk-taking behaviour but were matched for other phenotypic traits (body size, shape, and colouration). Females, but not males, exhibited a strong directional preference for risk-taking over risk-averse mating partners. At the same time, the strength of females’ preferences correlated positively with their own risk-taking scores. Our study is the first to demonstrate that a strong overall preference for risk-taking mating partners does not preclude effects of choosing individuals’ own personality type on (subtle) individual variation in mating preferences. More generally, two different preferences functions appear to interact to determine the outcome of individual mate choice decisions.
The discovery of the 1144-phase, e.g. CaKFe4As4, creates opportunities to build novel intermetallics with alternative stacking of two parent compounds. Here we formalize the idea by defining a class of bulk crystalline solids with A-B stacking (including 1144-phases and beyond), which is a generalization of hetero-structures from few-layer or thin-film semi-conductors to bulk intermetallics. Theoretically, four families of phosphides \textit{AB}(TM)4P4 (TM=Fe, Ru, Co, Ni) are investigated by first-principles calculations, wherein configurational, vibrational and electronic degrees of freedom are considered. It predicts a variety of stable 1144-phases (especially Ru- and Fe-phosphides). Stability rules are found and structural/electronic properties are discussed. Experimentally, we synthesize high-purity CaKRu4P4 as a proof of principle example. The synthetic method is simple and easily applied. Moreover, it alludes to a strategy to explore complex multi-component compounds, facilitated by a phase diagram coordinated by collective descriptors.
The discovery of the 1144-phase, e.g. CaKFe4As4, creates opportunities to build novel intermetallics with alternative stacking of two parent compounds. Here we formalize the idea by defining a class of bulk crystalline solids with A-B stacking (including 1144-phases and beyond), which is a generalization of hetero-structures from few-layer or thin-film semi-conductors to bulk intermetallics. Theoretically, four families of phosphides \textit{AB}(TM)4P4 (TM=Fe, Ru, Co, Ni) are investigated by first-principles calculations, wherein configurational, vibrational and electronic degrees of freedom are considered. It predicts a variety of stable 1144-phases (especially Ru- and Fe-phosphides). Stability rules are found and structural/electronic properties are discussed. Experimentally, we synthesize high-purity CaKRu4P4 as a proof of principle example. The synthetic method is simple and easily applied. Moreover, it alludes to a strategy to explore complex multi-component compounds, facilitated by a phase diagram coordinated by collective descriptors.
The discovery of the 1144-phase, e.g. CaKFe4As4, creates opportunities to build novel intermetallics with alternative stacking of two parent compounds. Here we formalize the idea and introduce a concept, namely hetero-crystals (HC), to describe a unique class of bulk crystalline solids with such A-B stacking (including 1144-phases and beyond). HC generalizes hetero-structures from few-layer or thin-film semi-conductors to bulk intermetallics. We illustrate the HC concept with the example of 1144-phases. Theoretically, four families of phosphides \textit{AB}(TM)4P4 (TM=Fe, Ru, Co, Ni) are investigated by first-principles calculations, wherein configurational, vibrational and electronic degrees of freedom are considered. It predicts a variety of stable 1144-phases (especially Ru- and Fe-phosphides). Stability rules are found and structural/electronic properties are discussed. Experimentally, we synthesize high-purity CaKRu4P4 as a proof of principle example of such a HC. The synthetic method is simple and can be applied to other HC. Moreover, HC alludes to a new strategy to explore complex multi-component compounds, facilitated by a new phase diagram coordinated by collective descriptors.
BOLD signatures of sleep
(2019)
Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of non-rapid-eye-movement sleep are two major EEG events: slow waves and spindles. Here we sought to identify possible signatures of sleep in brain hemodynamic activity, using simultaneous fMRI-EEG. We found that, during the transition from wake to sleep, blood-oxygen-level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (~0.05Hz) oscillation prominent in light sleep and a high-frequency (~0.17Hz) oscillation in deep sleep. The two BOLD oscillations correlated with the occurrences of spindles and slow waves, respectively. They were detectable across the whole brain, cortically and subcortically, but had different regional distributions and opposite onset patterns. These spontaneous BOLD oscillations provide fMRI signatures of basic sleep processes, which may be employed to study human sleep at spatial resolution and brain coverage not achievable using EEG.
Although iron-based catalysts are regarded as a promising alternative to precious metal catalysts, their precise electronic structures during catalysis still pose challenges for computational descriptions. A particularly urgent question is the influence of the environment on the electronic structure, and how to describe this properly with computational methods. Here, we study an iron porphyrin chloride complex adsorbed on a graphene sheet using density functional theory calculations to detail how much the electronic structure is influenced by the presence of a graphene layer. Our results indicate that weak interactions due to van der Waals forces dominate between the porphyrin complex and graphene, and only a small amount of charge is transferred between the two entities. Furthermore, the interplay of the ligand field environment, strong p − d hybridization, and correlation effects within the complex are strongly involved in determining the spin state of the iron ion. By bridging molecular chemistry and solid state physics, this study provides first steps towards a joint analysis of the properties of iron-based catalysts from first principles.
Under temperature or pressure tuning, tetragonal EuPd2Si2 is known to undergo a valence transition from nearly divalent to nearly trivalent Eu accompanied by a volume reduction. Albeit intensive work, its microscopic origin is still being discussed. Here, we investigate the mechanism of the valence transition under volume compression by ab initio density functional theory (DFT) calculations. Our analysis of the electronic and magnetic properties of EuPd2Si2 when approaching the valence transition shows an enhanced c-f hybridization between localized Eu 4f states and itinerant conduction states (Eu 5d, Pd 4d, and Si 3p) where an electronic charge redistribution takes place. We observe that the change in the electronic structure is intimately related to the volume reduction where Eu-Pd(Si) bond lengths shorten and, for the transition to happen, we trace the delicate balance between electronic bandwidth, crystal field splitting, Coulomb repulsion, Hund's coupling and spin-orbit coupling. In a next step we compare and benchmark our DFT results to surface-sensitive photoemission data in which the mixed-valent properties of EuPd2Si2 are reflected in a simultaneous observation of divalent and trivalent signals from the Eu 4f shell. The study serves as well to explore the limits of density functional theory and the choice of exchange correlation functionals to describe such a phenomenon as a valence transition.
Under temperature or pressure tuning, tetragonal EuPd2Si2 is known to undergo a valence transition from nearly divalent to nearly trivalent Eu accompanied by a volume reduction. Albeit intensive work, its origin is not yet completely understood. Here, we investigate the mechanism of the valence transition under volume compression by density functional theory calculations (DFT). Our analysis suggests that the transition is a consequence of an enhanced c−f hybridization between localized Eu 4f states and itinerant conduction states (Eu 5d, Pd 4d, and Si 3p) where the interplay of the electronic bandwidth, crystal field environment, Coulomb repulsion, Hund's coupling and spin-orbit coupling plays a crucial role for the transition to happen. The change in the electronic structure is intimately related to the volume reduction where Eu-Pd(Si) bond lengths shorten. In a next step we compare our DFT results to surface-sensitive photoemission data in which the mixed-valent properties of EuPd2Si2 are reflected in a simultaneous observation of divalent and trivalent signals from the Eu 4f shell.
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
(2023)
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measure based on optimal transport theory called SpikeShip, which compares multi-neuron spiking patterns based on all the relative spike-timing relationships among neurons. SpikeShip computes the optimal transport cost to make all the relative spike timing relationships (across neurons) identical between two spiking patterns. We show that this transport cost can be decomposed into a temporal rigid translation term, which captures global latency shifts, and a vector of neuron-specific transport flows, which reflect inter-neuronal spike timing differences. SpikeShip can be effectively computed for high-dimensional neuronal ensembles, has a low (linear) computational cost that has the same order as the spike count, and is sensitive to higher-order correlations. Furthermore SpikeShip is binless, can handle any form of spike time distributions, is not affected by firing rate fluctuations, can detect patterns with a low signal-to-noise ratio, and can be effectively combined with a sliding window approach. We compare the advantages and differences between SpikeShip and other measures like SPIKE and Victor-P urpura distance. We applied SpikeShip to large-scale Neuropixel recordings during spontaneous activity and visual encoding. We show that high-dimensional spiking sequences detected via SpikeShip reliably distinguish between different natural images and different behavioral states. These spiking sequences carried complementary information to conventional firing rate codes. SpikeShip opens new avenues for studying neural coding and memory consolidation by rapid and unsupervised detection of temporal spiking patterns in high-dimensional neural ensembles.
The traditional view on coding in the cortex is that populations of neurons primarily convey stimulus information through the spike count. However, given the speed of sensory processing, it has been hypothesized that sensory encoding may rely on the spike-timing relationships among neurons. Here, we use a recently developed method based on Optimal Transport Theory called SpikeShip to study the encoding of natural movies by high-dimensional ensembles of neurons in visual cortex. SpikeShip is a generic measure of dissimilarity between spike train patterns based on the relative spike-timing relations among all neurons and with computational complexity similar to the spike count. We compared spike-count and spike-timing codes in up to N > 8000 neurons from six visual areas during natural video presentations. Using SpikeShip, we show that temporal spiking sequences convey substantially more information about natural movies than population spike-count vectors when the neural population size is larger than about 200 neurons. Remarkably, encoding through temporal sequences did not show representational drift both within and between blocks. By contrast, population firing rates showed better coding performance when there were few active neurons. Furthermore, the population firing rate showed memory across frames and formed a continuous trajectory across time. In contrast to temporal spiking sequences, population firing rates exhibited substantial drift across repetitions and between blocks. These findings suggest that spike counts and temporal sequences constitute two different coding schemes with distinct information about natural movies.
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.
Bleaching-independent, whole-cell, 3D and multi-color STED imaging with exchangeable fluorophores
(2018)
We demonstrate bleaching-independent STED microscopy using fluorogenic labels that reversibly bind to their target structure. A constant exchange of labels guarantees the removal of photobleached fluorophores and their replacement by intact fluorophores, thereby circumventing bleaching-related limitations of STED super-resolution imaging in fixed and living cells. Foremost, we achieve a constant labeling density and demonstrate a fluorescence signal for long and theoretically unlimited acquisition times. Using this concept, we demonstrate whole-cell, 3D, multi-color and live cell STED microscopy with up to 100 min acquisition time.
We want to draw the attention to the dynamics of a (finite) hadronizing quark matter drop. Strange and antistrange quarks do not hadronize at the same time for a baryon-rich system1. Both the hadronic and the quark matter phases enter the strange sector fs 6= 0 of the phase diagram almost immediately, which has up to now been neglected in almost all calculations of the time evolution of the system. Therefore it seems questionable, whether final particle yields reflect the actual thermodynamic properties of the system at a certain stage of the evolution. We put special interest on the possible formation of exotic states, namely strangelets (multistrange quark clusters). They may exist as (meta-)stable exotic isomers of nuclear matter 2. It was speculated that strange matter might exist also as metastable exotic multi-strange (baryonic) objects (MEMO s 3). The possible creation in heavy ion collisions of long-lived remnants of the quark-gluon-plasma, cooled and charged up with strangeness by the emission of pions and kaons, was proposed in 1,4,5. Strangelets can serve as signatures for the creation of a quark gluon plasma. Currently, both at the BNL-AGS and at the CERN-SPS experiments are carried out to search for MEMO s and strangelets, e. g. by the E864, E878 and the NA52 collaborations9,
In the framework of RQMD we investigate antiproton observables in massive heavy ion collisions at AGS energies and compare to preliminary results of the E878 collaboration. We focus here on the considerable influence of the real part of an antinucleon nucleus optical potential on the ¯p momentum spectra. Pacs-numbers: 14.20 Dh, 25.70.-z
We study the thermodynamic properties of infinite nuclear matter with the Ultrarelativistic Quantum Molecular Dynamics (URQMD), a semiclassical transport model, running in a box with periodic boundary conditions. It appears that the energy density rises faster than T4 at high temperatures of T approx. 200 - 300 MeV. This indicates an increase in the number of degrees of freedom. Moreover, We have calculated direct photon production in Pb+Pb collisions at 160 GeV/u within this model. The direct photon slope from the microscopic calculation equals that from a hydrodynamical calculation without a phase transition in the equation of state of the photon source.
A study of secondary Drell-Yan production in nuclear collisions is presented for SPS energies. In addition to the lepton pairs produced in the initial collisions of the projectile and target nucleons, we consider the potentially high dilepton yield from hard valence antiquarks in produced mesons and antibaryons. We calculate the secondary Drell-Yan contributions taking the collision spectrum of hadrons from the microscopic model URQMD. The con- tributions from meson-baryon interactions, small in hadron-nucleus interac- tions, are found to be substantial in nucleus-nucleus collisions at low dilepton masses. Preresonance collisions of partons may further increase the yields.
We calculate the evolution of quark-gluon-plasma droplets during the hadronization in a thermodynamical model. It is speculated that cooling as well as strangeness enrichment allow for the formation of strangelets even at very high initial entropy per baryon S/Ainit H 500 and low initial baryon numbers of Ainit B H 30. It is shown that the droplet with vanishing initial chemical potential of strange quarks and a very moderate chemical potential of up/down quarks immediately charges up with strangeness. Baryon densi- ties of H 2 0 and strange chemical potentials of µs > 350 MeV are reached if strangelets are stable. The importance of net baryon and net strangeness fluctuations for the possible strangelet formation at RHIC and LHC is em- phasized. Pacs-Classif.: 25.15.tr, 12.38.Mh, 24.85.tp
We present a RQMD calculation of antiproton yields and their momentum distribution in Ne + NaF collisions at 2 GeV/u. The antiprotons can be produced below threshold due to multi-step excitations for which meson-baryon interactions play a considerable role. In this system the annihilation probability for an initially produced antiproton is predicted to be about 65%.
Measured hadron yields from relativistic nuclear collisions can be equally well understood in two physically distinct models, namely a static thermal hadronic source vs. a time-dependent, nonequilibrium hadronization o a quark-gluon plasma droplet. Due to the time-dependent particle evapora- tion o the hadronic surface in the latter approach the hadron ratios change (by factors of <H 5) in time. Final particle yields reflect time averages over the actual thermodynamic properties of the system at a certain stage of the evolution. Calculated hadron, strangelet and (anti-)cluster yields as well as freeze-out times are presented for di erent systems. Due to strangeness distillation the system moves rapidly out of the T, µq plane into the µs-sector. Classif.: 25.75.Dw, 12.38.Mh, 24.85.+p
The deconfinement transition region between hadronic matter and quark-gluon plasma is studied for finite volumes. Assuming simple model equations of state and a first order phase transition, we find that fluctuations in finite volumes hinder a sharp separation between the two phases around the critical temperature, leading to a rounding of the phase transition. For reaction volumes expected in heavy ion experiments, the softening of the equation of state is reduced considerably. This is especially true when the requirement of exact color-singletness is included in the QGP equation of state.
We study J/psi suppression in AB collisions assuming that the charmonium states evolve from small, color transparent configurations. Their interaction with nucleons and nonequilibrated, secondary hadrons is simulated us- ing the microscopic model UrQMD. The Drell-Yan lepton pair yield and the J/psi /Drell-Yan ratio are calculated as a function of the neutral transverse en- ergy in Pb+Pb collisions at 160 GeV and found to be in reasonable agreement with existing data.
Dissociation rates of J / psi's with comoving mesons : thermal versus nonequilibrium scenario.
(1998)
We study J/psi dissociation processes in hadronic environments. The validity of a thermal meson gas ansatz is tested by confronting it with an alternative, nonequilibrium scenario. Heavy ion collisions are simulated in the frame- work of the microscopic transport model UrQMD, taking into account the production of charmonium states through hard parton-parton interactions and subsequent rescattering with hadrons. The thermal gas and microscopic transport scenarios are shown to be very dissimilar. Estimates of J/psi survival probabilities based on thermal models of comover interactions in heavy ion collisions are therefore not reliable.
Charmonium production and absorption in heavy ion collisions is studied with the Ultrarelativisitic Quantum Molecular Dynamics model. We compare the scenario of universal and time independent color-octet dissociation cross sections with one of distinct color-singlet J/psi, psi 2 and CHIc states, evolving from small, color transparent configurations to their asymptotic sizes. The measured J/psi production cross sections in pA and AB collisions at SPS energies are consistent with both purely hadronic scenarios. The predicted rapidity dependence of J/psi suppression can be used to discriminate between the two experimentally. The importance of interactions with secondary hadrons and the applicability of thermal reaction kinetics to J/psi absorption are in- vestigated. We discuss the e ect of nuclear stopping and the role of leading hadrons. The dependence of the 2/J/psi ratio on the model assumptions and the possible influence of refeeding processes is also studied.
Spatial attention increases both inter-areal synchronization and spike rates across the visual hierarchy. To investigate whether these attentional changes reflect distinct or common mechanisms, we performed simultaneous laminar recordings of identified cell classes in macaque V1 and V4. Enhanced V4 spike rates were expressed by both excitatory neurons and fast-spiking interneurons, and were most prominent and arose earliest in time in superficial layers, consistent with a feedback modulation. By contrast, V1-V4 gamma-synchronization reflected feedforward communication and surprisingly engaged only fast-spiking interneurons in the V4 input layer. In mouse visual cortex, we found a similar motif for optogenetically identified inhibitory-interneuron classes. Population decoding analyses further indicate that feedback-related increases in spikes rates encoded attention more reliably than feedforward-related increases in synchronization. These findings reveal distinct, cell-type-specific feedforward and feedback pathways for the attentional modulation of inter-areal synchronization and spike rates, respectively.
According to his own understanding, Jürgen Habermas’ Theory of Communicative Action offers a new account of the normative foundations of critical theory. 1 Habermas’ motivating insight is that neither a transcendental or metaphysical solution to the problem of normativity, nor a merely hermeneutic reconstruction of historically given norms, is sufficient to clarify the normative foundations of critical theory. In response to this insight, Habermas develops a novel account of normativity which locates the normative demands upon which critical theory draws within the socially instituted practice of communicative understanding. Although Habermas has claimed otherwise, this new foundation for critical theory constitutes a novel and innovative form of “immanent critique”. To argue for and to clarify this claim, I offer, in section 1, a formal account of immanent critique and distinguish between two different ways of carrying out such a critique. In section 2, I examine Habermas’ rejection of the first, hermeneutic option. Against this background, I then show, in section 3, that the Theory of Communicative Action attempts to formulate an immanent critique of contemporary societies according to a second, “practice-based” model. However, because Habermas, as I will argue in section 4, commits himself to an implausibly narrow view in regard to one central element of such a model – in regard to the social ontology of immanent normativity – his normative critique cannot develop its full potential (section 5).
Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ~10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, changes induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.
Path integration is a sensorimotor computation that can be used to infer latent dynamical states by integrating self-motion cues. We studied the influence of sensory observation (visual/vestibular) and latent control dynamics (velocity/acceleration) on human path integration using a novel motion-cueing algorithm. Sensory modality and control dynamics were both varied randomly across trials, as participants controlled a joystick to steer to a memorized target location in virtual reality. Visual and vestibular steering cues allowed comparable accuracies only when participants controlled their acceleration, suggesting that vestibular signals, on their own, fail to support accurate path integration in the absence of sustained acceleration. Nevertheless, performance in all conditions reflected a failure to fully adapt to changes in the underlying control dynamics, a result that was well explained by a bias in the dynamics estimation. This work demonstrates how an incorrect internal model of control dynamics affects navigation in volatile environments in spite of continuous sensory feedback.
Strangeness enhancement is discussed as a feature specific to relativistic nuclear collisions which create a fireball of strongly interacting matter at high energy density. At very high energy this is suggested to be partonic matter, but at lower energy it should consist of yet unknown hadronic degrees of freedom. The freeze-out of this high density state to a hadron gas can tell us about properties of fireball matter. The hadron gas at the instant of its formation captures conditions directly at the QCD phase boundary at top SPS and RHIC energy, chiefly the critical temperature and energy density.
A steep maximum occurs in the Wroblewski ratio between strange and non-strange quarks created in central nucleus-nucleus collisions, of about A=200, at the lower SPS energy square root s approximately equal to 7 GeV. By analyzing hadronic multiplicities within the grand canonical statistical hadronization model this maximum is shown to occur at a baryochemical potential of about 450 MeV. In comparison, recent QCD lattice calculations at finite baryochemical potential suggest a steep maximum of the light quark susceptibility, to occur at similar mu B, indicative of "critical fluctuation" expected to occur at or near the QCD critical endpoint. This endpoint hat not been firmly pinned down but should occur in the 300 MeV < mu c B < 700 MeV interval. It is argued that central collisions within the low SPS energy range should exhibit a turning point between compression/heating, and expansion/cooling at energy density, temperature and mu B close to the suspected critical point. Whereas from top SPS to RHIC energy the primordial dynamics create a turning point far above in epsilon and T, and far below in mu B. And at lower AGS energies the dynamical trajectory stays below the phase boundary. Thus, the observed sharp strangeness maximum might coincide with the critical square root s at which the dynamics settles at, or near the QCD endpoint.
A selection of recent data referring to Pb+Pb collisions at the SPS CERN energy of 158 GeV per nucleon is presented which might describe the state of highly excited strongly interacting matter both above and below the deconfinement to hadronization (phase) transition predicted by lattice QCD. A tentative picture emerges in which a partonic state is indeed formed in central Pb+Pb collisions which hadronizes at about T = 185 MeV, and expands its volume more than tenfold, cooling to about 120 MeV before hadronic collisions cease. We suggest further that all SPS collisions, from central S+S onward, reach that partonic phase, the maximum energy density increasing with more massive collision systems.
Hadronic yields and yield ratios observed in Pb+Pb collisions at the SPS energy of 158 GeV per nucleon are known to resemble a thermal equilibrium population at T=180 +/- 10 MeV, also observed in elementary e+ + e- to hadron data at LEP. We argue that this is the universal consequence of the QCD parton to hadron phase transition populating the maximum entropy state. This state is shown to survive the hadronic rescattering and expansion phase, freezing in right after hadronization due to the very rapid longitudinal and transverse expansion that is inferred from Bose-Einstein pion correlation analysis of central Pb+Pb collisions.
With new data available from the SPS, at 40 and 80 GeV/A, I review the systematics of bulk hadron multiplicities, with prime focus on strangeness production. The classical concept of strangeness enhancement in central AA collisions is reviewed, in view of the statistical hadronization model which suggests to understand strangeness enhancement to arise chiefly in the transition from the canonical to the grand canonical version of that model. I. e. enhancement results from the fading away of canonical suppression. The model also captures the striking strangeness maximum observed in the vicinity of sqrt s approx 8 GeV. A puzzle remains in the understanding of apparent grand canonical order at the lower SPS, and at AGS energies.
Relativistic nucleus-nucleus collisions create a "fireball" of strongly interacting matter at high energy density. At very high energy this is suggested to be partonic matter, but at lower energy it should consist of yet unknown hadronic, perhaps coherent degrees of freedom. The freeze-out of this high density state to a hadron gas can tell us about properties of fireball matter. Date (v1): Thu, 19 Dec 2002 12:52:34 GMT (146kb) Date (revised v2): Thu, 16 Jan 2003 15:11:47 GMT (146kb) Date (revised v3): Wed, 14 May 2003 12:49:35 GMT (146kb)
The ALICE experiment at the LHC investigates the properties of the hot and dense nuclear matter created in heavy-ion collisions. By comparing the particle production in pp and p-Pb collisions, possible nuclear initial state effects can be isolated. Measurements of the ω meson pT-spectra in pp and p-Pb collisions not only allow for a determination of the nuclear modification factor RpPb, but also provide insight into the fragmentation process and serve as vital input for decay background simulations for direct photons. In this contribution, measurements of the ω meson production in pp and p-Pb collisions at √sNN=5.02 TeV are presented. This includes the signal extraction and various corrections of the ω meson yields, leading to their production cross sections and the first measured nuclear modification factor RpPb of the ω meson at LHC energies.
Complexome profiling is an emerging ‘omics approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the “minimum information required for a complexome profiling experiment” (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.
In Arabidopsis thaliana, the stem cell niche (SCN) within the root apical meristem (RAM) is maintained by an intricate regulatory network that ensures optimal growth and high developmental plasticity. Yet, many aspects of this regulatory network of stem cell quiescence and replenishment are still not fully understood. Here, we investigate the interplay of the key transcription factors (TFs) BRASSINOSTEROID AT VASCULAR AND ORGANIZING CENTRE (BRAVO), PLETHORA 3 (PLT3) and WUSCHEL-RELATED HOMEOBOX 5 (WOX5) involved in SCN maintenance. Phenotypical analysis of mutants involving these TFs uncover their combinatorial regulation of cell fates and divisions in the SCN. Moreover, interaction studies employing fluorescence resonance energy transfer fluorescence lifetime imaging microscopy (FRET-FLIM) in combination with novel analysis methods, allowed us to quantify protein-protein interaction (PPI) affinities as well as higher-order complex formation of these TFs. We integrated our experimental results into a computational model, suggesting that cell type specific profiles of protein complexes and characteristic complex formation, that is also dependent on prion-like domains in PLT3, contribute to the intricate regulation of the SCN. We propose that these unique protein complex ‘signatures’ could serve as a read-out for cell specificity thereby adding another layer to the sophisticated regulatory network that balances stem cell maintenance and replenishment in the Arabidopsis root.
A critical discussion of the present status of the CERN experiments on charm dynamics and hadron collective flow is given. We emphasize the importance of the flow excitation function from 1 to 50 A·GeV: here the hydrodynamic model has predicted the collapse of the v1-flow and of the v2-flow at 10 A·GeV; at 40 A·GeV it has been recently observed by the NA49 collaboration. Since hadronic rescattering models predict much larger flow than observed at this energy we interpret this observation as potential evidence for a first order phase transition at high baryon density B. A detailed discussion of the collective flow as a barometer for the equation of state (EoS) of hot dense matter at RHIC follows. Here, hadronic rescattering models can explain < 30% of the observed elliptic flow, v2, for pT > 2 GeV/c. This is interpreted as evidence for the production of superdense matter at RHIC with initial pressure far above hadronic pressure, p > 1 GeV/fm3. We suggest that the fluctuations in the flow, v1 and v2, should be measured in future since ideal hydrodynamics predicts that they are larger than 50 % due to initial state fluctuations. Furthermore, the QGP coe cient of viscosity may be determined experimentally from the fluctuations observed. The connection of v2 to jet suppression is examined. It is proven experimentally that the collective flow is not faked by minijet fragmentation. Additionally, detailed transport studies show that the awayside jet suppression can only partially (< 50%) be due to hadronic rescattering. We, finally, propose upgrades and second generation experiments at RHIC which inspect the first order phase transition in the fragmentation region, i.e. at µB 400 MeV (y 4 5), where the collapse of the proton flow should be seen in analogy to the 40 A·GeV data. The study of Jet-Wake-riding potentials and Bow shocks caused by jets in the QGP formed at RHIC can give further information on the equation of state (EoS) and transport coe cients of the Quark Gluon Plasma (QGP).
Results from various theoretical approaches and ideas presented at this exciting meeting (summary talk at the 5th International Conference on Physics and Astrophysics of Quark Gluon Plasma (ICPAQGP - 2005)) are reviewed. I also point towards future directions, in particular hydrodynamic behaviour induced by jets traveling through the quark-gluon plasma, which might be worth looking at in more detail.
The experimental signatures of TeV-mass black hole (BH) formation in heavy ion collisions at the LHC is examined. We find that the black hole production results in a complete disappearance of all very high p_T (> 500 GeV) back-to-back correlated di-jets of total mass M > M_f ~ 1 TeV. We show that the subsequent Hawking-decay produces multiple hard mono-jets and discuss their detection. We study the possibility of cold black hole remnant (BHR) formation of mass ~ M_f and the experimental distinguishability of scenarios with BHRs and those with complete black hole decay. Due to the rather moderate luminosity in the first year of LHC running the least chance for the observation of BHs or BHRs at this early stage will be by ionizing tracks in the ALICE TPC. Finally we point out that stable BHRs would be interesting candidates for energy production by conversion of mass to Hawking radiation.
The production of Large Extra Dimension (LXD) Black Holes (BHs), with a new, fundamental mass scale of M_f = 1 TeV, has been predicted to occur at the Large Hadron Collider, LHC, with the formidable rate of 10^8 per year in p-p collisions at full energy, 14 TeV, and at full luminosity. We show that such LXD-BH formation will be experimentally observable at the LHC by the complete disappearance of all very high p_t (> 500 GeV) back-to-back correlated Di-Jets of total mass M > M_f = 1 TeV. We suggest to complement this clear cut-off signal at M > 2*500 GeV in the di-jet-correlation function by detecting the subsequent, Hawking-decay products of the LXD-BHs, namely either multiple high energy (> 100 GeV) SM Mono-Jets (i.e. away-side jet missing), sprayed off the evaporating BHs isentropically into all directions or the thermalization of the multiple overlapping Hawking-radiation in a eckler-Kapusta-Plasma. Microcanonical quantum statistical calculations of the Hawking evaporation process for these LXD-BHs show that cold black hole remnants (BHRs) of Mass sim M_f remain leftover as the ashes of these spectacular Di-Jet-suppressed events. Strong Di-Jet suppression is also expected with Heavy Ion beams at the LHC, due to Quark-Gluon-Plasma induced jet attenuation at medium to low jet energies, p_t < 200 GeV. The (Mono-)Jets in these events can be used to trigger for Tsunami-emission of secondary compressed QCD-matter at well defined Mach-angles, both at the trigger side and at the awayside (missing) jet. The Machshock-angles allow for a direct measurement of both the equation of state EoS and the speed of sound c_s via supersonic bang in the "big bang" matter. We discuss the importance of the underlying strong collective flow - the gluon storm - of the QCD- matter for the formation and evolution of these Machshock cones. We predict a significant deformation of Mach shocks from the gluon storm in central Au+Au collisions at RHIC and LHC energies, as compared to the case of weakly coupled jets propagating through a static medium. A possible complete stopping of pt > 50 GeV jets at the LHC in 2-3 fm yields nonlinear high density Mach shocks in he quark gluon plasma, which can be studied in the complex emission and disintegration pattern of the possibly supercooled matter. We report on first full 3-dimensional fluid dynamical studies of the strong effects of a first order phase transition on the evolution and the Tsunami-like Mach shock emission of the QCD matter.
To be published in J. Phys. G - Proceedings of SQM 2004 : We review the results from the various hydrodynamical and transport models on the collective flow observables from AGS to RHIC energies. A critical discussion of the present status of the CERN experiments on hadron collective flow is given. We emphasize the importance of the flow excitation function from 1 to 50 A.GeV: here the hydrodynamic model has predicted the collapse of the v2-flow ~ 10 A.GeV; at 40 A.GeV it has been recently observed by the NA49 collaboration. Since hadronic rescattering models predict much larger flow than observed at this energy we interpret this observation as evidence for a first order phase transition at high baryon density r b. Moreover, the connection of the elliptic flow v2 to jet suppression is examined. It is proven experimentally that the collective flow is not faked by minijet fragmentation. Additionally, detailed transport studies show that the away-side jet suppression can only partially (< 50%) be due to hadronic rescattering. Furthermore, the change in sign of v1, v2 closer to beam rapidity is related to the occurence of a high density first order phase transition in the RHIC data at 62.5, 130 and 200 A.GeV.
Dendrites display a striking variety of neuronal type-specific morphologies, but the mechanisms and principles underlying such diversity remain elusive. A major player in defining the morphology of dendrites is the neuronal cytoskeleton, including evolutionarily conserved actin-modulatory proteins (AMPs). Still, we lack a clear understanding of how AMPs might support developmental phenomena such as neuron-type specific dendrite dynamics. To address precisely this level of in vivo specificity, we concentrated on a defined neuronal type, the class III dendritic arborisation (c3da) neuron of Drosophila larvae, displaying actin-enriched short terminal branchlets (STBs). Computational modelling reveals that the main branches of c3da neurons follow a general growth model based on optimal wiring, but the STBs do not. Instead, model STBs are defined by a short reach and a high affinity to grow towards the main branches. We thus concentrated on c3da STBs and developed new methods to quantitatively describe dendrite morphology and dynamics based on in vivo time-lapse imaging of mutants lacking individual AMPs. In this way, we extrapolated the role of these AMPs in defining STB properties. We propose that dendrite diversity is supported by the combination of a common step, refined by a neuron type-specific second level. For c3da neurons, we present a molecular model of how the combined action of multiple AMPs in vivo define the properties of these second level specialisations, the STBs.
Cryo electron tomography (cryo-ET) combined with subtomogram averaging (StA) enables structural determination of macromolecules in their native context. A few structures were reported by StA at resolution higher than 4.5 Å, however all of these are from viral structural proteins or vesicle coats. Reaching high resolution for a broader range of samples is uncommon due to beam-induced sample drift, poor signal-to-noise ratio (SNR) of images, challenges in CTF correction, limited number of particles. Here we propose a strategy to address these issues, which consists of a tomographic data collection scheme and a processing workflow. Tilt series are collected with higher electron dose at zero-degree tilt in order to increase SNR. Next, after performing StA conventionally, we extract 2D projections of the particles of interest from the higher SNR images and use the single particle analysis tools to refine the particle alignment and generate a reconstruction. We benchmarked our proposed hybrid StA (hStA) workflow and improved the resolution for tobacco mosaic virus from 7.2 to 5.2 Å and the resolution for the ion channel RyR1 in crowded native membranes from 12.9 to 9.1 Å. We demonstrate that hStA can improve the resolution obtained by conventional StA and promises to be a useful tool for StA projects aiming at subnanometer resolution or higher.
Membrane receptors are central to cell-cell communication. Receptor clustering at the plasma membrane modulates physiological responses, and mesoscale receptor organization is critical for downstream signaling. Spatially restricted cluster formation of the neuropeptide Y2 hormone receptor (Y2R) was observed in vivo; however, the relevance of this confinement is not fully understood. Here, we controlled Y2R clustering in situ by a chelator nanotool. Due to the multivalent interaction, we observed a dynamic exchange in the microscale confined regions. Fast Y2R enrichment in clustered areas triggered a ligand-independent downstream signaling determined by an increase in cytosolic calcium, cell spreading, and migration. We revealed that the cell response to ligand-induced activation was amplified when cells were pre-clustered by the nanotool. Ligand-independent signaling by clustering differed from ligand-induced activation in the binding of arrestin-3 as downstream effector, which was recruited to the confined regions only in the presence of the ligand. This approach enables in situ clustering of membrane receptors and raises the possibility to explore different modalities of receptor activation.
Nuclear pore complexes (NPCs) constitute giant channels within the nuclear envelope that mediate nucleocytoplasmic exchange. NPC diameter is thought to be regulated by nuclear envelope tension, but how such diameter changes are physiologically linked to cell differentiation, where mechanical properties of nuclei are remodeled and nuclear mechanosensing occurs, remains unstudied. Here we used cryo-electron tomography to show that NPCs dilate during differentiation of mouse embryonic stem cells into neural progenitors. In Nup133-deficient cells, which are known to display impaired neural differentiation, NPCs however fail to dilate. By analyzing the architectures of individual NPCs with template matching, we revealed that the Nup133-deficient NPCs are structurally heterogeneous and frequently disintegrate, resulting in the formation of large nuclear envelope openings. We propose that the elasticity of the NPC scaffold mechanically safeguards the nuclear envelope. Our studies provide a molecular explanation for how genetic perturbation of scaffolding components of macromolecular complexes causes tissue-specific phenotypes.