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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.
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.
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%.
The firing pattern of ventral midbrain dopamine neurons is controlled by afferent and intrinsic activity to generate prediction error signals that are essential for reward-based learning. Given the absence of intracellular in vivo recordings in the last three decades, the subthreshold membrane potential events that cause changes in dopamine neuron firing patterns remain unknown. By establishing stable in vivo whole-cell recordings of >100 spontaneously active midbrain dopamine neurons in anaesthetized mice, we identified the repertoire of subthreshold membrane potential signatures associated with distinct in vivo firing patterns. We demonstrate that dopamine neuron in vivo activity deviates from a single spike pacemaker pattern by eliciting transient increases in firing rate generated by at least two diametrically opposing biophysical mechanisms: a transient depolarization resulting in high frequency plateau bursts associated with a reactive, depolarizing shift in action potential threshold; and a prolonged hyperpolarization preceding slower rebound bursts characterized by a predictive, hyperpolarizing shift in action potential threshold. Our findings therefore illustrate a framework for the biophysical implementation of prediction error and sensory cue coding in dopamine neurons by tuning action potential threshold dynamics.
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 discovery of superconductivity in layered vanadium-based kagome metals AV3Sb5 (A: K, Rb, Cs) has added a new family of materials to the growing class of possible unconventional superconductors. However, the nature of the superconducting pairing in these materials remains elusive. We present a microscopic theoretical study of the leading superconducting instabilities on the kagome lattice based on spin- and charge-fluctuation mediated Cooper pairing. The applied methodology includes effects of both on-site and nearest-neighbor repulsive Coulomb interactions. Near the upper van Hove filling -- relevant for the AV3Sb5 materials -- we find a rich phase diagram with several pairing symmetries being nearly degenerate. In particular, while a substantial fraction of the phase diagram is occupied by a spin-singlet order parameter transforming as a two-dimensional irreducible representation of the point group, several nodal spin-triplet pairing states remain competitive. We compute the band and interaction parameter-dependence of the hierarchy of the leading superconducting instabilities, and determine the detailed momentum dependence of the resulting preferred gap structures. Crucially, for moderate values of the interaction parameters, the individual pairing states depend strongly on momentum and exhibit multiple nodes on the Fermi surface. We discuss the properties of these superconducting gap structures in light of recent experimental developments of the AV3Sb5 materials.
We reexamine the scenario of homogeneous nucleation of the quark-gluon plasma produced in ultra-relativistic heavy ion collisions. A generalization of the standard nucleation theory to rapidly expanding system is proposed. The nucleation rate is derived via the new scaling parameter Z. It is shown that the size distribution of hadronic clusters plays an important role in the dynamics of the phase transition. The longitudinally expanding system is supercooled to about 3 6%, then it is reheated, and the hadronization is completed within 6 10 fm/c, i.e. 5 10 times faster than it was estimated earlier, in a strongly nonequilibrium way. PACS: 12.38.Mh; 12.39.Ba; 25.75.-q; 64.60.Qb
Communication sounds are ubiquitous in the animal kingdom, where they play a role in advertising physiological states and/or socio-contextual scenarios. Distress sounds, for example, are typically uttered in distressful scenarios such as agonistic interactions. Here, we report on the occurrence of superfast temporal periodicities in distress calls emitted by bats (species Carollia perspicillata). Distress vocalizations uttered by this bat species are temporally modulated at frequencies close to 1.7 kHz, that is, ∼17 times faster than modulation rates observed in human screams. Fast temporal periodicities are represented in the bats’ brain by means of frequency following responses, and temporally periodic sounds are more effective in boosting the heart rate of awake bats than their demodulated versions. Altogether, our data suggest that bats, an animal group classically regarded as ultrasonic, can exploit the low frequency portion of the soundscape during distress calling to create spectro-temporally complex, arousing sounds.
Effective knowledge communication presupposes common ground (Clark & Brennan, 1991) that needs to be established and maintained. This is particularly difficult in remote communication as well as in non-interactive settings, because the speaker cannot use gestures or mimic and has to tailor his utterances to the addressee without receiving feedback. In these situations, the speaker may achieve mutual understanding for example by adopting the addressee’s perspective. We present a study conducted to test the impact of instructions that support and hinder individual problem solving and knowledge communication. We used a picture-sorting task requiring individual cognitive processes of feature search (Treisman & Gelade, 1980) in addition to referential communication. As our study focused on the design of utterances, all participants assumed the role of speaker. Participants were told that their descriptions would be recorded and then listened to later on by a participant in the role of addressee. Eight sets of pictures were used, which varied on two dimensions: the individual cognitive demands of detecting the relevant features (varied as between-subject factor) and the communicative demands (varied as within-subject factor). A further between-subject factor was the type of instructions: The participants received either a collaboration script as supporting instructions, or time pressure was applied to induce stress, or else they were given no additional instructions (control group). We used the speakers’ verbal utterances to examine the quality of the speakers’ descriptions. For both dimensions of difficulty, we found the expected effects. In the conditions with a collaboration script, there were fewer irrelevant features mentioned and fewer features were described with delay. In the conditions with time pressure, there were fewer irrelevant features described, but the number of correctly described pictures was impaired through the fact that relevant features were also neglected. Under time pressure, speakers tended to provide ambiguous descriptions regarding the frame of reference.
We propose a framework of individual problem-solving and communicative demands (IproCo) that bridges the gap between models from cognitive psychology and communication pragmatics. Furthermore, we present two experiments conducted to identify factors influencing the demands and to test possibilities for support. The experiments employed a remote collaborative picture-sorting task with concrete and abstract pictures and applied non-interactive conditions compared to interactive conditions. In a first experiment, the influence of the postulated demands on collaboration process and outcome was analysed, and the impact of shared applications was tested. In a second experiment, we evaluated instructional support measures consisting of model collaboration and a collaboration script. The collaboration process showed benefits of the support but the outcome did not. However, the support measures fostered the collaboration process even in the particularly difficult conditions with non-interactive communication. We discuss the impact of the IproCo framework and apply it to other tasks.
We address the production of black holes at LHC in space times with compactified space-like large extra dimensions (LXD). Final state black hole production leads to suppression of high-PT jets, i.e. a sharp cut-o in (pp!jet+X). This signal is compared to the jet plus missing energy signature due to graviton production in the final state as proposed by the ATLAS collaboration. Time evolution and lifetimes of the newly created black holes are calculated based on the micro- canonical formalism. It is demonstrated that previous lifetime estimates of micro black holes have been dramatically underestimated. The creation of a large number of quasi-stable black holes is predicted with life times of hundred fm/c at LHC. Medium modifications of the black holes evaporation rate due to the quark gluon plasma in relativistic heavy ion collisions as well as provided by the cosmic fluid in the early universe are studied
A model for the production of quarkonium states in the midrapidity region at RHIC and LHC energy range is presented which explores well understood properties of QCD only. An increase of the quarkonium hadronisation time with the initial energy leads to a gradual change of the most important phenomena from fixed target- to collider-energies. We evaluate nuclear e ects in the quarkonium production due to medium modification of the momentum distribution of the heavy quarks produced in the hard interactions, i.e. due to the broadening of the transverse momentum distribution. Other nuclear effects, i.e. nuclear shadowing and parton energy loss, are also evaluated.
The production yield of the Λ(1520) baryon resonance is measured at mid-rapidity in Pb-Pb collisions at sNN−−−√ = 2.76 TeV with the ALICE detector at the LHC. The measurement is performed in the Λ(1520)→pK− (and charge conjugate) hadronic decay channel as a function of the transverse momentum (pT) and collision centrality. The pT-integrated production rate of Λ(1520) relative to Λ in central collisions is suppressed by about a factor of 2 with respect to peripheral collisions. This is the first observation of the suppression of a baryonic resonance at LHC and the first evidence of Λ(1520) suppression in heavy-ion collisions. The measured Λ(1520)/Λ ratio in central collisions is smaller than the value predicted by the statistical hadronisation model calculations. The shape of the measured pT distribution and the centrality dependence of the suppression are reproduced by the EPOS3 Monte Carlo event generator. The measurement adds further support to the formation of a dense hadronic phase in the final stages of the evolution of the fireball created in heavy-ion collisions, lasting long enough to cause a significant reduction in the observable yield of short-lived resonances.
The production yield of the Λ(1520) baryon resonance is measured at mid-rapidity in Pb-Pb collisions at sNN−−−√ = 2.76 TeV with the ALICE detector at the LHC. The measurement is performed in the Λ(1520)→pK− (and charge conjugate) hadronic decay channel as a function of the transverse momentum (pT) and collision centrality. The pT-integrated production rate of Λ(1520) relative to Λ in central collisions is suppressed by about a factor of 2 with respect to peripheral collisions. This is the first observation of the suppression of a baryonic resonance at the LHC and the first 3σ evidence of Λ(1520) suppression within a single collision system. The measured Λ(1520)/Λ ratio in central collisions is smaller than the value predicted by the statistical hadronisation model calculations. The shape of the measured pT distribution and the centrality dependence of the suppression are reproduced by the EPOS3 Monte Carlo event generator. The measurement adds further support to the formation of a dense hadronic phase in the final stages of the evolution of the fireball created in heavy-ion collisions, lasting long enough to cause a significant reduction in the observable yield of short-lived resonances.
Abstract
Seed harvesting from wild plant populations is key for ecological restoration, but may threaten the persistence of source populations. Consequently, several countries have set guidelines limiting the proportions of harvestable seeds. However, these guidelines are so far inconsistent, and they lack a solid empirical basis. Here, we use high-resolution data from 298 plant species to model the demographic consequences of seed harvesting. We find that the current guidelines do not protect populations of annuals and short-lived perennials, while they are overly restrictive for long-lived plants. We show that the maximum possible fraction of seed production – what can be harvested without compromising the long-term persistence of populations – is strongly related to the generation time of the target species. When harvesting every year, this safe seed fraction ranges from 80% in long-lived species to 2% in most annuals. Less frequent seed harvesting substantially increases the safe seed fraction: In the most vulnerable annual species, it is safe to harvest 5%, 10% or 30% of population seed production when harvesting every two, five or ten years, respectively. Our results provide a quantitative basis for seed harvesting legislations worldwide, based on species’ generation time and harvesting regime.
Significance The UN Decade on Ecosystem Restoration, 2021-2030, foresees upscaling restoration, and the demand for native seed is skyrocketing. Seeds for restoring native vegetation are often harvested in wild, but too intensive harvest can threaten the donor populations. Existing guidelines that set limits to wild seed harvest are mostly based on expert opinions, yet they commonly lack empirical basis and vary among regions in one order of magnitude. We show that the current guidelines urgently need to be reformulated, because they are overly restrictive in long-lived species, while they do not protect annual plants from extinction. Using matrix population models of nearly 300 plant species, we provide a quantitative basis for a new seed harvesting legislation world-wide.
Seed harvesting from wild plant populations is key for ecological restoration, but may threaten the persistence of source populations. Consequently, several countries have set guidelines limiting the proportions of harvestable seeds. Here, we use high-resolution data from 298 plant species to model the demographic consequences of seed harvesting. We find that the current guidelines only protect some species, but are insufficient or overly restrictive for others. We show that the maximum possible fraction of seed harvesting is strongly associated with harvesting frequency and generation time of the target species, ranging from 100% in long-lived species to <1% in the most annuals. Our results provide quantitative basis to guide seed harvesting legislation based on species’ generation time and harvesting regime.
Antimicrobial resistance is a major threat to global health and food security today. Scheduling cycling therapies by targeting phenotypic states associated to specific mutations can help us to eradicate pathogenic variants in chronic infections. In this paper, we introduce a logistic switching model in order to abstract mutation networks of collateral resistance. We found particular conditions for which unstable zero-equilibrium of the logistic maps can be stabilized through a switching signal. That is, persistent populations can be eradicated through tailored switching regimens.
Starting from an optimal-control formulation, the switching policies show their potential in the stabilization of the zero-equilibrium for dynamics governed by logistic maps. However, employing such switching strategies, deserve a specific characterization in terms of limit behaviour. Ultimately, we use evolutionary and control algorithms to find either optimal and sub-optimal switching policies. Simulations results show the applicability of Parrondo’s Paradox to design cycling therapies against drug resistance.
We use the topological heavy fermion (THF) model and its Kondo Lattice (KL) formulation to study the symmetric Kondo state in twisted bilayer graphene. Via a large-N approximation, we find a symmetric Kondo (SK) state in KL mode at fillings ν=0,±1,±2. In the SK state, all symmetries are preserved and the local moments are Kondo screened by the conduction electrons. At the mean-field level of the THF model at ν=0,±1,±2,±3, we also find a similar symmetric state. We study the stability of the symmetric state by comparing its energy with the ordered states and find the ordered states to have lower energy. However, moving away from integer fillings by doping holes to the light bands, we find the energy difference is reduced, which suggests the loss of ordering and a tendency towards Kondo screening. In order to include many-body effects beyond the mean-field approximation, we perform dynamical mean-field theory (DMFT) calculations on the THF model. We find the spin susceptibility follows a Curie behavior at ν=0,±1,±2 down to ∼2K where the onset of screening of the local moment becomes visible. This hints to very low Kondo temperatures at these fillings, in agreement with the outcome of our mean-field calculations. At non-integer filling ν=±0.5,±0.8,±1.2 DMFT shows deviations from a 1/T-susceptibility at much higher temperatures, suggesting a more effective screening of local moments with doping. Finally, we study the effect of a C3z-rotational-symmetry-breaking strain via mean-field approaches and find that a symmetric phase (that only breaks C3z symmetry) can be stabilized at sufficiently large strain at ν=0,±1,±2. Our results suggest that a symmetric Kondo phase is strongly suppressed at integer fillings, but could be stabilized either at non-integer fillings or by applying strain.
Symmetrie
(1997)
A newly developed observable for correlations between symmetry planes, which characterize the direction of the anisotropic emission of produced particles, is measured in Pb-Pb collisions at sNN−−−√=2.76 TeV with ALICE. This so-called Gaussian Estimator allows for the first time the study of these quantities without the influence of correlations between different flow amplitudes. The centrality dependence of various correlations between two, three and four symmetry planes is presented. The ordering of magnitude between these symmetry plane correlations is discussed and the results of the Gaussian Estimator are compared with measurements of previously used estimators. The results utilizing the new estimator lead to significantly smaller correlations than reported by studies using the Scalar Product method. Furthermore, the obtained symmetry plane correlations are compared to state-of-the-art hydrodynamic model calculations for the evolution of heavy-ion collisions. While the model predictions provide a qualitative description of the data, quantitative agreement is not always observed, particularly for correlators with significant non-linear response of the medium to initial state anisotropies of the collision system. As these results provide unique and independent information, their usage in future Bayesian analysis can further constrain our knowledge on the properties of the QCD matter produced in ultrarelativistic heavy-ion collisions.
A newly developed observable for correlations between symmetry planes, which characterize the direction of the anisotropic emission of produced particles, is measured in Pb-Pb collisions at sNN−−−√=2.76 TeV with ALICE. This so-called Gaussian Estimator allows for the first time the study of these quantities without the influence of correlations between different flow amplitudes. The centrality dependence of various correlations between two, three and four symmetry planes is presented. The ordering of magnitude between these symmetry plane correlations is discussed and the results of the Gaussian Estimator are compared with measurements of previously used estimators. The results utilizing the new estimator lead to significantly smaller correlations than reported by studies using the Scalar Product method. Furthermore, the obtained symmetry plane correlations are compared to state-of-the-art hydrodynamic model calculations for the evolution of heavy-ion collisions. While the model predictions provide a qualitative description of the data, quantitative agreement is not always observed, particularly for correlators with significant non-linear response of the medium to initial state anisotropies of the collision system. As these results provide unique and independent information, their usage in future Bayesian analysis can further constrain our knowledge on the properties of the QCD matter produced in ultrarelativistic heavy-ion collisions.
Release of neuropeptides from dense core vesicles (DCVs) is essential for neuromodulation. Compared to the release of small neurotransmitters, much less is known about the mechanisms and proteins contributing to neuropeptide release. By optogenetics, behavioral analysis, electrophysiology, electron microscopy, and live imaging, we show that synapsin SNN-1 is required for cAMP-dependent neuropeptide release in Caenorhabditis elegans hermaphrodite cholinergic motor neurons. In synapsin mutants, behaviors induced by the photoactivated adenylyl cyclase bPAC, which we previously showed to depend on acetylcholine and neuropeptides (Steuer Costa et al., 2017), are altered like in animals with reduced cAMP. Synapsin mutants have slight alterations in synaptic vesicle (SV) distribution, however, a defect in SV mobilization was apparent after channelrhodopsin-based photostimulation. DCVs were largely affected in snn-1 mutants: DCVs were ∼30% reduced in synaptic terminals, and not released following bPAC stimulation. Imaging axonal DCV trafficking, also in genome-engineered mutants in the serine-9 protein kinase A phosphorylation site, showed that synapsin captures DCVs at synapses, making them available for release. SNN-1 co-localized with immobile, captured DCVs. In synapsin deletion mutants, DCVs were more mobile and less likely to be caught at release sites, and in non-phosphorylatable SNN-1B(S9A) mutants, DCVs traffic less and accumulate, likely by enhanced SNN-1 dependent tethering. Our work establishes synapsin as a key mediator of neuropeptide release.
Omicron BA.1 variant isolates were previously shown to replicate less effectively in interferon-competent cells and to be more sensitive to interferon treatment than a Delta isolate. Here, an Omicron BA.2 isolate displayed intermediate replication patterns in interferon-competent Caco-2-F03 cells when compared to BA.1 and Delta isolates. Moreover, BA.2 was less sensitive than BA.1 and similarly sensitive as Delta to betaferon treatment. Delta and BA.1 displayed similar sensitivity to the approved anti-SARS-CoV-2 drugs remdesivir, nirmatrelvir, EIDD-1931 (the active metabolite of molnupiravir) and the protease inhibitor aprotinin, whereas BA.2 was less sensitive than Delta and BA.1 to EIDD-1931, nirmatrelvir and aprotinin. Nirmatrelvir, EIDD-1931, and aprotinin (but not remdesivir) exerted synergistic antiviral activity in combination with betaferon, with some differences in the extent of synergism detected between the different SARS-CoV-2 variants. In conclusion, even closely related SARS-CoV-2 (sub)variants can differ in their biology and in their response to antiviral treatments. Betaferon combinations with nirmatrelvir and, in particular, with EIDD-1931 and aprotinin displayed high levels of synergism, which makes them strong candidates for clinical testing. Notably, effective antiviral combination therapies are desirable, as a higher efficacy is expected to reduce resistance formation.
Non-ribosomal peptide synthetases (NRPSs) are the origin of a wide range of natural products, including many clinically used drugs. Engineering of these often giant biosynthetic machineries to produce novel non-ribosomal peptides (NRPs) at high titre is an ongoing challenge. Here we describe a strategy to functionally combine NRPS fragments of Gram-negative and -positive origin, synthesising novel peptides at titres up to 290 mg l-1. Extending from the recently introduced definition of eXchange Units (XUs), we inserted synthetic zippers (SZs) to split single protein NRPSs into up to three independently expressed and translated polypeptide chains. These synthetic type of NRPS (type S) enables easier access to engineering, overcomes cloning limitations, and provides a simple and rapid approach to building peptide libraries via the combination of different NRPS subunits.
System size and centrality dependence of the balance function in A + A collisions at √sNN = 17.2 GeV
(2004)
Electric charge correlations were studied for p+p, C+C, Si+Si and centrality selected Pb+Pb collisions at sqrt s_NN = 17.2$ GeV with the NA49 large acceptance detector at the CERN-SPS. In particular, long range pseudo-rapidity correlations of oppositely charged particles were measured using the Balance Function method. The width of the Balance Function decreases with increasing system size and centrality of the reactions. This decrease could be related to an increasing delay of hadronization in central Pb+Pb collisions.
The first measurements of K∗(892)0 resonance production as a function of charged-particle multiplicity in Xe−Xe collisions at sNN−−−√= 5.44 TeV and pp collisions at s√= 5.02 TeV using the ALICE detector are presented. The resonance is reconstructed at midrapidity (|y|<0.5) using the hadronic decay channel K∗0→K±π∓. Measurements of transverse-momentum integrated yield, mean transverse-momentum, nuclear modification factor of K∗0, and yield ratios of resonance to stable hadron (K∗0/K) are compared across different collision systems (pp, p−Pb, Xe−Xe, and Pb−Pb) at similar collision energies to investigate how the production of K∗0 resonances depends on the size of the system formed in these collisions. The hadronic rescattering effect is found to be independent of the size of colliding systems and mainly driven by the produced charged-particle multiplicity, which is a proxy of the volume of produced matter at the chemical freeze-out. In addition, the production yields of K∗0 in Xe−Xe collisions are utilized to constrain the dependence of the kinetic freeze-out temperature on the system size using HRG-PCE model.
Strange particle production in A+A interactions at 158 AGeV is studied by the CERN experiment NA49 as a function of system size and collision geometry. Yields of charged kaons, phi and Lambda are measured and compared to those of pions in central C+C, Si+Si and centrality-selected Pb+Pb reactions. An overall increase of relative strangeness production with the size of the system is observed which does not scale with the number of participants. Arguing that rescattering of secondaries plays a minor role in small systems the observed strangeness enhancement can be related to the space-time density of the primary nucleon-nucleon collisions.
We argue that the shape of the system-size dependence of strangeness production in nucleus-nucleus collisions can be understood in a picture that is based on the formation of clusters of overlapping strings. A string percolation model combined with a statistical description of the hadronization yields a quantitative agreement with the data at sqrt s_NN = 17.3 GeV. The model is also applied to RHIC energies.
System-size dependence of strangeness production in nucleus-nucleus collisions at √sNN = 17.3 GeV
(2005)
Emission of pi, K, phi and Lambda was measured in near-central C+C and Si+Si collisions at 158 AGeV beam energy. Together with earlier data for p+p, S+S and Pb+Pb, the system-size dependence of relative strangeness production in nucleus-nucleus collisions is obtained. Its fast rise and the saturation observed at about 60 participating nucleons can be understood as onset of the formation of coherent partonic subsystems of increasing size. PACS numbers: 25.75.-q
We present the first systematic comparison of the charged-particle pseudorapidity densities for three widely different collision systems, pp, p-Pb, and Pb-Pb, at the top energy of the Large Hadron Collider (sNN−−−√=5.02 TeV) measured over a wide pseudorapidity range (−3.5<η<5), the widest possible among the four experiments at that facility. The systematic uncertainties are minimised since the measurements are recorded by the same experimental apparatus (ALICE). The distributions for p-Pb and Pb-Pb collisions are determined as a function of the centrality of the collisions, while results from pp collisions are reported for inelastic events with at least one charged particle at midrapidity. The charged-particle pseudorapidity densities are, under simple and robust assumptions, transformed to charged-particle rapidity densities. This allows for the calculation and the presentation of the evolution of the width of the rapidity distributions and of a lower bound on the Bjorken energy density, as a function of the number of participants in all three collision systems. We find a decreasing width of the particle production, and roughly a smooth ten fold increase in the energy density, as the system size grows, which is consistent with a gradually higher dense phase of matter.
We present the first systematic comparison of the charged-particle pseudorapidity densities for three widely different collision systems, pp, p-Pb, and Pb-Pb, at the top energy of the Large Hadron Collider (sNN−−−√=5.02 TeV) measured over a wide pseudorapidity range (−3.5<η<5), the widest possible among the four experiments at that facility. The systematic uncertainties are minimised since the measurements are recorded by the same experimental apparatus (ALICE). The distributions for p-Pb and Pb-Pb collisions are determined as a function of the centrality of the collisions, while results from pp collisions are reported for inelastic events with at least one charged particle at midrapidity. The charged-particle pseudorapidity densities are, under simple and robust assumptions, transformed to charged-particle rapidity densities. This allows for the calculation and the presentation of the evolution of the width of the rapidity distributions and of a lower bound on the Bjorken energy density, as a function of the number of participants in all three collision systems. We find a decreasing width of the particle production, and roughly a smooth ten fold increase in the energy density, as the system size grows, which is consistent with a gradually higher dense phase of matter.
The correlations between event-by-event fluctuations of anisotropic flow harmonic amplitudes have been measured in Pb-Pb collisions at sNN−−−√ = 2.76 TeV with the ALICE detector at the LHC. The results are reported in terms of multiparticle correlation observables dubbed Symmetric Cumulants. These observables are robust against biases originating from nonflow effects. The centrality dependence of correlations between the higher order harmonics (the quadrangular v4 and pentagonal v5 flow) and the lower order harmonics (the elliptic v2 and triangular v3 flow) is presented. The transverse momentum dependence of correlations between v3 and v2 and between v4 and v2 is also reported. The results are compared to calculations from viscous hydrodynamics and A Multi-Phase Transport ({AMPT}) model calculations. The comparisons to viscous hydrodynamic models demonstrate that the different order harmonic correlations respond differently to the initial conditions and the temperature dependence of the ratio of shear viscosity to entropy density (η/s). A small average value of η/s is favored independent of the specific choice of initial conditions in the models. The calculations with the AMPT initial conditions yield results closest to the measurements. Correlations between the magnitudes of v2, v3 and v4 show moderate pT dependence in mid-central collisions. Together with existing measurements of individual flow harmonics, the presented results provide further constraints on the initial conditions and the transport properties of the system produced in heavy-ion collisions.
The correlations between event-by-event fluctuations of anisotropic flow harmonic amplitudes have been measured in Pb-Pb collisions at sNN−−−√ = 2.76 TeV with the ALICE detector at the Large Hadron Collider. The results are reported in terms of multiparticle correlation observables dubbed Symmetric Cumulants. These observables are robust against biases originating from nonflow effects. The centrality dependence of correlations between the higher order harmonics (the quadrangular v4 and pentagonal v5 flow) and the lower order harmonics (the elliptic v2 and triangular v3 flow) is presented. The transverse momentum dependences of correlations between v3 and v2 and between v4 and v2 are also reported. The results are compared to calculations from viscous hydrodynamics and A Multi-Phase Transport ({AMPT}) model calculations. The comparisons to viscous hydrodynamic models demonstrate that the different order harmonic correlations respond differently to the initial conditions and the temperature dependence of the ratio of shear viscosity to entropy density (η/s). A small average value of η/s is favored independent of the specific choice of initial conditions in the models. The calculations with the AMPT initial conditions yield results closest to the measurements. Correlations between the magnitudes of v2, v3 and v4 show moderate pT dependence in mid-central collisions. This might be an indication of possible viscous corrections to the equilibrium distribution at hadronic freeze-out, which might help to understand the possible contribution of bulk viscosity in the hadronic phase of the system. Together with existing measurements of individual flow harmonics, the presented results provide further constraints on the initial conditions and the transport properties of the system produced in heavy-ion collisions.
Measurements of the pT-dependent flow vector fluctuations in Pb-Pb collisions at sNN−−−√=5.02 TeV using azimuthal correlations with the ALICE experiment at the LHC are presented. A four-particle correlation approach [1] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the pT-dependent flow vector fluctuations at sNN−−−√=5.02 TeV with two-particle correlations. Significant pT-dependent fluctuations of the V⃗ 2 flow vector in Pb-Pb collisions are found across different centrality ranges, with the largest fluctuations of up to ∼15% being present in the 5% most central collisions. In parallel, no evidence of significant pT-dependent fluctuations of V⃗ 3 or V⃗ 4 is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than 5σ significance in central collisions. These observations in Pb-Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high pT, which might be biased by pT-dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be re-examined to improve our understanding of initial conditions, quark--gluon plasma (QGP) properties, and the dynamic evolution of the created system.
Neural computations emerge from recurrent neural circuits that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, it is challenging to predict which spiking network connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We established a mapping between the stabilized supralinear network (SSN) and spiking activity which allowed us to pinpoint the location in parameter space where these activity regimes occur. Notably, we found that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we showed that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.
It becomes more and more obvious that deregulation of host metabolism play an important role in SARS-CoV-2 pathogenesis with implication for increased risk of severe course of COVID-19. Furthermore, it is expected that COVID-19 patients recovered from severe disease may experience long-term metabolic disorders. Thereby understanding the consequences of SARS-CoV-2 infection on host metabolism can facilitate efforts for effective treatment option. We have previously shown that SARS-CoV-2-infected cells undergo a shift towards glycolysis and that 2-deoxy-D-glucose (2DG) inhibits SARS-CoV-2 replication. Here, we show that also pentose phosphate pathway (PPP) is remarkably deregulated. Since PPP supplies ribonucleotides for SARS-CoV-2 replication, this could represent an attractive target for an intervention. On that account, we employed the transketolase inhibitor benfooxythiamine and showed dose-dependent inhibition of SARS-CoV-2 in non-toxic concentrations. Importantly, the antiviral efficacy of benfooxythiamine was further increased in combination with 2DG.
Autophagy is a highly conserved catabolic process through which defective or otherwise harmful cellular components are targeted for degradation via the lysosomal route. Regulatory pathways, involving post-translational modifications such as phosphorylation, play a critical role in controlling this tightly orchestrated process. Here, we demonstrate that TBK1 regulates autophagy by phosphorylating autophagy modifiers LC3C and GABARAP-L2 on surface-exposed serine residues (LC3C S93 and S96; GABARAP-L2 S87 and S88). This phosphorylation event impedes their binding to the processing enzyme ATG4 by destabilizing the complex. Phosphorylated LC3C/GABARAP-L2 cannot be removed from liposomes by ATG4 and are thus protected from ATG4-mediated premature removal from nascent autoph-agosomes. This ensures a steady coat of lipidated LC3C/GABARAP-L2 throughout the early steps in autophagosome formation and aids in maintaining a unidirectional flow of the autophagosome to the lysosome. Taken together, we present a new regulatory mechanism of autophagy, which influences the conjugation and de-conjugation of LC3C and GABARAP-L2 to autophagosomes by TBK1-mediated phosphorylation.
In a Quark-Gluon Plasma (QGP), the fundamental building blocks of matter, quarks and gluons, are under extreme conditions of temperature and density. A QGP could exist in the early stages of the Universe, and in various objects and events in the cosmos. The thermodynamic and hydrodynamic properties of the QGP are described by Quantum Chromodynamics (QCD) and can be studied in heavy-ion collisions. Despite being a key thermodynamic parameter, the QGP temperature is still poorly known. Thermal lepton pairs (e+e− and μ+μ−) are ideal penetrating probes of the true temperature of the emitting source, since their invariant-mass spectra suffer neither from strong final-state interactions nor from blue-shift effects due to rapid expansion. Here we measure the QGP temperature using thermal e+e− production at the Relativistic Heavy Ion Collider (RHIC). The average temperature from the low-mass region (in-medium ρ0 vector-meson dominant) is (1.99±0.24)×1012 K, consistent with the chemical freeze-out temperature from statistical models and the phase transition temperature from LQCD. The average temperature from the intermediate mass region (above the ρ0 mass, QGP dominant) is significantly higher at (3.40±0.55)×1012 K. This work provides essential experimental thermodynamic measurements to map out the QCD phase diagram and understand the properties of matter under extreme conditions.
The rapid spread and evolution of various strains of SARS-CoV-2, the virus responsible for COVID-19, continues to challenge the disease controlling measures globally. Alarming concern is, the number of second wave infections surpassed the first wave and the onset of severe symptoms manifesting rapidly. In this scenario, testing of maximum population in less time and minimum cost with existing diagnostic amenities is the only possible way to control the spread of the virus. The previously described RNA extraction-free methods using dry swab have been shown to be advantageous in these critical times by different studies. In this work, we show the temporal stability and performance of the dry swab viral detection method at two different temperatures. Contrived dry swabs holding serially diluted SARS-CoV-2 strains A2a and A3i at 25°C (room temperature; RT) and 4°C were subjected to direct RT-PCR and compared with standard VTM-RNA based method. The results clearly indicate that dry swab method of RNA detection is as efficient as VTM-RNA-based method in both strains, when checked for up to 72 hours. The lesser CT values of dry swab samples in comparison to that of the VTM-RNA samples suggest better sensitivity of the method within 48 hours of time. The results collectively suggest that dry swab samples are stable at RT for 24 hours and the detection of SARS-CoV-2 RNA by RT-PCR do not show variance from VTM-RNA. This extraction free, direct RT-PCR method holds phenomenal standing in the present life-threatening circumstances due to SARS-CoV-2.
The quantum entangled J/ψ→Σ+Σ¯− pairs from (1.0087±0.0044)×1010 J/ψ events taken by the BESIII detector are used to study the non-leptonic two-body weak decays Σ+→nπ+ and Σ¯−→n¯π−. The CP-odd weak decay parameters of the decays Σ+→nπ+ (α+) and Σ¯−→n¯π− (α¯−) are determined to be −0.0565±0.0047stat±0.0022syst and 0.0481±0.0031stat±0.0019syst, respectively. The decay parameter α¯− is measured for the first time, and the accuracy of α+ is improved by a factor of four compared to the previous results. The simultaneously determined decay parameters allow the first precision CP symmetry test for any hyperon decay with a neutron in the final state with the measurement of ACP=(α++α¯−)/(α+−α¯−) = −0.080±0.052stat±0.028syst. Assuming CP conservation, the average decay parameter is determined as ⟨α+⟩=(α+−α¯−)/2 = −0.0506±0.0026stat±0.0019syst, while the ratios α+/α0 and α¯−/α¯0 are −0.0490±0.0032stat±0.0021syst and −0.0571±0.0053stat±0.0032syst, where α0 and α¯0 are the decay parameters of the decays Σ+→pπ0 and Σ¯−→p¯π0, respectively.
Airborne transmission of SARS-CoV-2 through virus-containing aerosol particles has been established as an important pathway for Covid-19 infection. Suitable measures to prevent such infections are imperative, especially in situations when a high number of persons convene in closed rooms. Here we tested the efficiency and practicability of operating four air purifiers equipped with HEPA filters in a high school classroom while regular classes were taking place. We monitored the aerosol number concentration for particles > 3 nm at two locations in the room, the aerosol size distribution in the range from 10 nm to 10 µm, PM10 and CO2 concentration. For comparison, we performed similar measurements in a neighboring classroom without purifiers. In times when classes were conducted with windows and door closed, the aerosol concentration was reduced by more than 90 % within less than 30 minutes when running the purifiers (air exchange rate 5.5 h-1). The reduction was homogeneous throughout the room and for all particle sizes. The measurements are supplemented by a calculation estimating the maximum concentration levels of virus-containing aerosol from a highly contagious person speaking in a closed room with and without air purifiers. Measurements and calculation demonstrate that air purifiers potentially represent a well-suited measure to reduce the risks of airborne transmission of SARS-CoV-2 substantially. Staying for two hours in a closed room with a highly infective person, we estimate that the inhaled dose is reduced by a factor of six when using air purifiers with a total air exchange rate of 5.7 h-1.
The survivin suppressant YM155 is a drug candidate for neuroblastoma. Here, we tested YM155 in 101 neuroblastoma cell lines (19 parental cell lines, 82 drug-adapted sublines). 77 cell lines displayed YM155 IC50s in the range of clinical YM155 concentrations. ABCB1 was an important determinant of YM155 resistance. The activity of the ABCB1 inhibitor zosuquidar ranged from being similar to that of the structurally different ABCB1 inhibitor verapamil to being 65-fold higher. ABCB1 sequence variations may be responsible for this, suggesting that the design of variant-specific ABCB1 inhibitors may be possible. Further, we showed that ABCC1 confers YM155 resistance. Previously, p53 depletion had resulted in decreased YM155 sensitivity. However, TP53-mutant cells were not generally less sensitive to YM155 than TP53 wild-type cells in this study. Finally, YM155 cross-resistance profiles differed between cells adapted to drugs as similar as cisplatin and carboplatin. In conclusion, the large cell line panel was necessary to reveal an unanticipated complexity of the YM155 response in neuroblastoma cell lines with acquired drug resistance. Novel findings include that ABCC1 mediates YM155 resistance and that YM155 cross-resistance profiles differ between cell lines adapted to drugs as similar as cisplatin and carboplatin.
Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Background Eukaryotic gene expression is controlled by cis-regulatory elements (CREs) including promoters and enhancers which are bound by transcription factors (TFs). Differential expression of TFs and their putative binding sites on CREs cause tissue and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and thus gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined ChIP-seq and RNA-seq data exist, they do not offer good usability, have limited support for large-scale data processing, and provide only minimal functionality for visual result interpretation.
Results We developed TF-Prioritizer, an automated java pipeline to prioritize condition-specific TFs derived from multi-modal data. TF-Prioritizer creates an interactive, feature-rich, and user-friendly web report of its results. To showcase the potential of TF-Prioritizer, we identified known active TFs (e.g., Stat5, Elf5, Nfib, Esr1), their target genes (e.g., milk proteins and cell-cycle genes), and newly classified lactating mammary gland TFs (e.g., Creb1, Arnt).
Conclusion TF-Prioritizer accepts ChIP-seq and RNA-seq data, as input and suggests TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanims, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of one type is larger than the other. The higher reproductive success may stem from either more frequent reproduction, or from larger numbers of offspring, and is encoded in a measure Λ for each of the two types. Our approach consists of constructing a Λ-asymmetric Moran model in which individuals of the two populations compete, rather than considering a Moran model for each population. Under certain conditions, that we call the "partial order of adaptation", we can couple these measures. This allows us to construct the central object of this paper, the Λ−asymmetric ancestral selection graph, leading to a pathwise duality of the forward in time Λ-asymmetric Moran model with its ancestral process. Interestingly, the construction also provides a connection to the theory of optimal transport. We apply the ancestral selection graph in order to obtain scaling limits of the forward and backward processes, and note that the frequency process converges to the solution of an SDE with discontinous paths. Finally, we derive a Griffiths representation for the generator of the SDE and use it to find a semi-explicit formula for the probability of fixation of the less beneficial of the two types.
Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanims, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of one type is larger than the other. The higher reproductive success may stem from either more frequent reproduction, or from larger numbers of offspring, and is encoded in a measure Λ for each of the two types. Our approach consists of constructing a Λ-asymmetric Moran model in which individuals of the two populations compete, rather than considering a Moran model for each population. Under certain conditions, that we call the ``partial order of adaptation'', we can couple these measures. This allows us to construct the central object of this paper, the Λ−asymmetric ancestral selection graph, leading to a pathwise duality of the forward in time Λ-asymmetric Moran model with its ancestral process. Interestingly, the construction also provides a connection to the theory of optimal transport. We apply the ancestral selection graph in order to obtain scaling limits of the forward and backward processes, and note that the frequency process converges to the solution of an SDE with discontinous paths. Finally, we derive a Griffiths representation for the generator of the SDE and use it to find a semi-explicit formula for the probability of fixation of the less beneficial of the two types.
The brains of black 6 mice (Mus musculus) and Seba’s short-tailed bats (Carollia perspicillata) weigh roughly the same and share the mammalian neocortical laminar architecture. Bats have highly developed sonar calls and social communication and are an excellent neuroethological animal model for auditory research. Mice are olfactory and somatosensory specialists and are used frequently in auditory neuroscience, particularly for their advantage of standardization and genetic tools. Investigating their potentially different general auditory processing principles would advance our understanding of how the ecological needs of a species shape the development and function of the mammalian nervous system. We compared two existing datasets, recorded with linear multichannel electrodes down the depth of the primary auditory cortex (A1) while awake, across both species while presenting repetitive stimulus trains with different frequencies (∼5 and ∼40 Hz). We found that while there are similarities between cortical response profiles in bats and mice, there was a better signal to noise ratio in bats under these conditions, which allowed for a clearer following response to stimuli trains. This was most evident at higher frequency trains, where bats had stronger response amplitude suppression to consecutive stimuli. Phase coherence was far stronger in bats during stimulus response, indicating less phase variability in bats across individual trials. These results show that although both species share cortical laminar organization, there are structural differences in relative depth of layers. Better signal to noise ratio in bats could represent specialization for faster temporal processing shaped by their individual ecological niches.
Based on Eysenck’s pioneering work, CNS arousal has long been considered an encouraging biological candidate that may explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. Notably, the vast majority of published results have been derived from small samples, and EEG alpha power has usually served as exclusive indicator for CNS arousal. In this study, we selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and CNS arousal by using the low-resolution electromagnetic tomography-based analysis tool VIGALL. Our analyses revealed that subjects who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of CNS arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained strongest evidence for neuroticism facet ‘impulsivity’ and reduced CNS arousal. We regard these findings as well in line with the postulations of Eysenck and Zuckerman and consistent with the assumptions of the ‘arousal regulation model’. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large studies with at least several hundreds of subjects.
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.
The Calderón problem with finitely many unknowns is equivalent to convex semidefinite optimization
(2023)
We consider the inverse boundary value problem of determining a coefficient function in an elliptic partial differential equation from knowledge of the associated Neumann-Dirichlet-operator. The unknown coefficient function is assumed to be piecewise constant with respect to a given pixel partition, and upper and lower bounds are assumed to be known a-priori.
We will show that this Calderón problem with finitely many unknowns can be equivalently formulated as a minimization problem for a linear cost functional with a convex non-linear semidefinite constraint. We also prove error estimates for noisy data, and extend the result to the practically relevant case of finitely many measurements, where the coefficient is to be reconstructed from a finite-dimensional Galerkin projection of the Neumann-Dirichlet-operator.
Our result is based on previous works on Loewner monotonicity and convexity of the Neumann-Dirichlet-operator, and the technique of localized potentials. It connects the emerging fields of inverse coefficient problems and semidefinite optimization.
The clinical and economic value of a successful shutdown during the SARS-CoV-2 pandemic in Germany
(2020)
Background and aim A shutdown of businesses enacted during the SARS-CoV-2 pandemic can serve different goals, e.g., preventing the intensive care unit (ICU) capacity from being overwhelmed (‘flattening the curve’) or keeping the reproduction number substantially below one (‘squashing the curve’). The aim of this study was to determine the clinical and economic value of a shutdown that is successful in ‘flattening’ or ‘squashing the curve’ in Germany.
Methods In the base case, the study compared a successful shutdown to a worst-case scenario with no ICU capacity left to treat COVID-19 patients. To this end, a decision model was developed using, e.g., information on age-specific fatality rates, ICU outcomes, and the herd protection threshold. The value of an additional life year was borrowed from new, innovative oncological drugs, as cancer reflects a condition with a similar morbidity and mortality burden in the general population in the short term as COVID-19.
Results A shutdown that is successful in ‘flattening the curve’ is projected to yield an average health gain between 0.02 and 0.08 life years (0.2 to 0.9 months) per capita in the German population. The corresponding economic value ranges between €1543 and €8027 per capita or, extrapolated to the total population, 4% to 19% of the gross domestic product (GDP) in 2019. A shutdown that is successful in ‘squashing the curve’ is expected to yield a minimum health gain of 0.10 life years (1.2 months) per capita, corresponding to 24% of the GDP in 2019. Results are particularly sensitive to mortality data and the prevalence of undetected cases.
Conclusion A successful shutdown is forecasted to yield a considerable gain in life years in the German population. Nevertheless, questions around the affordability and underfunding of other parts of the healthcare system emerge.
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 development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereogramms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.
We investigate the excitation function of quark-gluon plasma formation and of directed in-plane flow of nucleons in the energy range of the BNLAGS and for the Ekin Lab = 40A GeV Pb+Pb collisions performed recently at the CERN-SPS. We employ the three-fluid model with dynamical unification of kinetically equilibrated fluid elements. Within our model with first-order phase transition at high density, droplets of QGP coexisting with hadronic matter are produced already at BNL-AGS energies, Ekin Lab C 10A GeV. A substantial decrease of the isentropic velocity of sound, however, requires higher energies, Ekin Lab C 40A GeV. We show the e ect on the flow of nucleons in the reaction plane. According to our model calculations, kinematic requirements and EoS effects work hand-in-hand at Ekin Lab = 40A GeV to allow the observation of the dropping velocity of sound via an increase of the directed flow around midrapidity as compared to top BNL-AGS energy.
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.
There is increasing evidence that rapid phenotypic adaptation of quantitative traits is not uncommon in nature. However, the circumstances under which rapid adaptation of polygenic traits occurs are not yet understood. Building on previous concepts of soft selection, i.e. frequency and density dependent selection, I developed and tested the hypothesis that adaptation speed of a polygenic trait depends on the number of offspring per breeding pair in a randomly mating diploid population.
Using individual based modelling on a range of offspring per parent (2–200) in populations of various size (100–10000 individuals), I could show that the by far largest proportion of variance (42%) was explained by the offspring number, regardless of genetic trait architecture (10–50 loci, different locus contribution distributions). In addition, it was possible to identify the majority of the responsible loci and account for even more of the observed phenotypic change with a moderate population size.
The simulation results suggest that offspring numbers may a crucial factor for the adaptation speed of quantitative loci. Moreover, as large offspring numbers translates to a large phenotypic variance in the offspring of each parental pair, this genetic bet hedging strategy increases the chance to contribute to the next generation in unpredictable environments.
Background: Trauma-related guilt and shame are crucial for the development and maintenance of PTSD (posttraumatic stress disorder). We developed an intervention combining cognitive techniques with loving-kindness meditations (C-METTA) that specifically target these emotions. C-METTA is an intervention of six weekly individual treatment sessions followed by a four-week practice phase.
Objective: This study examined C-METTA in a proof-of-concept study within a randomized wait-list controlled trial.
Method: We randomly assigned 32 trauma-exposed patients with a DSM-5 diagnosis to C-METTA or a wait-list condition (WL). Primary outcomes were clinician-rated PTSD symptoms (CAPS-5) and trauma-related guilt and shame. Secondary outcomes included psychopathology, self-criticism, well-being, and self-compassion. Outcomes were assessed before the intervention phase and after the practice phase.
Results: Mixed-design analyses showed greater reductions in C-METTA versus WL in clinician-rated PTSD symptoms (d = −1.09), guilt (d = −2.85), shame (d = −2.14), psychopathology and self-criticism.
Conclusion: Our findings support positive outcomes of C-METTA and might contribute to improved care for patients with stress-related disorders. The study was registered in the German Clinical Trials Register (DRKS00023470).
HIGHLIGHTS
C-METTA is an intervention that addresses trauma-related guilt and shame and combines cognitive interventions with loving-kindness meditations.
A proof-of-concept study was conducted examining C-METTA in a wait-list randomized controlled trial
C-METTA led to reductions in trauma-related guilt and shame and PTSD symptoms.
Long non-coding RNAs (lncRNAs) can act as regulatory RNAs which, by altering the expression of target genes, impact on the cellular phenotype and cardiovascular disease development. Endothelial lncRNAs and their vascular functions are largely undefined. Deep RNA-Seq and FANTOM5 CAGE analysis revealed the lncRNA LINC00607 to be highly enriched in human endothelial cells. LINC00607 was induced in response to hypoxia, arteriosclerosis regression in non-human primates and also in response to propranolol used to induce regression of human arteriovenous malformations. siRNA knockdown or CRISPR/Cas9 knockout of LINC00607 attenuated VEGF-A-induced angiogenic sprouting. LINC00607 knockout in endothelial cells also integrated less into newly formed vascular networks in an in vivo assay in SCID mice. Overexpression of LINC00607 in CRISPR knockout cells restored normal endothelial function. RNA- and ATAC-Seq after LINC00607 knockout revealed changes in the transcription of endothelial gene sets linked to the endothelial phenotype and in chromatin accessibility around ERG-binding sites. Mechanistically, LINC00607 interacted with the SWI/SNF chromatin remodeling protein BRG1. CRISPR/Cas9-mediated knockout of BRG1 in HUVEC followed by CUT&RUN revealed that BRG1 is required to secure a stable chromatin state, mainly on ERG-binding sites. In conclusion, LINC00607 is an endothelial-enriched lncRNA that maintains ERG target gene transcription by interacting with the chromatin remodeler BRG1.
Mechanisms by which specific histone modifications regulate distinct gene regulatory networks remain little understood. We investigated how H3K79me2, a modification catalyzed by DOT1L and previously considered a general transcriptional activation mark, regulates gene expression in mammalian cardiogenesis. Early embryonic cardiomyocyte ablation of Dot1l revealed that H3K79me2 does not act as a general transcriptional activator, but rather regulates highly specific gene regulatory networks at two critical cardiogenic junctures: left ventricle patterning and postnatal cardiomyocyte cell cycle withdrawal. Mechanistic analyses revealed that H3K79me2 in two distinct domains, gene bodies and regulatory elements, synergized to promote expression of genes activated by DOT1L. Surprisingly, these analyses also revealed that H3K79me2 in specific regulatory elements contributed to silencing genes usually not expressed in cardiomyocytes. As DOT1L mutants had increased numbers of postnatal mononuclear cardiomyocytes and prolonged cardiomyocyte cell cycle activity, controlled inhibition of DOT1L might be a strategy to promote cardiac regeneration post-injury.
Bears are iconic mammals with a complex evolutionary history. Natural bear hybrids and studies of few nuclear genes indicate that gene flow among bears may be more common than expected and not limited to the closely related polar and brown bears. Here we present a genome analysis of the bear family with representatives of all living species. Phylogenomic analyses of 869 mega base pairs divided into 18,621 genome fragments yielded a well-resolved coalescent species tree despite signals for extensive gene flow across species. However, genome analyses using three different statistical methods show that gene flow is not limited to closely related species pairs. Strong ancestral gene flow between the Asiatic black bear and the ancestor to polar, brown and American black bear explains numerous uncertainties in reconstructing the bear phylogeny. Gene flow across the bear clade may be mediated by intermediate species such as the geographically wide-spread brown bears leading to massive amounts of phylogenetic conflict. Genome-scale analyses lead to a more complete understanding of complex evolutionary processes. The increasing evidence for extensive inter-specific gene flow, found also in other animal species, necessitates shifting the attention from speciation processes achieving genome-wide reproductive isolation to the selective processes that maintain species divergence in the face of gene flow.
Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. Orthologous genes that are detected across the full diversity of contemporary life allow reconstructing the gene set of LUCA, the last universal common ancestor. These genes presumably represent the functional repertoire common to – and necessary for – all living organisms. Design of artificial life has the potential to test this. Recently, a minimal gene (MG) set for a self-replicating cell was determined experimentally, and a surprisingly high number of genes have unknown functions and are not represented in LUCA. However, as similarity between orthologs decays with time, it becomes insufficient to infer common ancestry, leaving ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the evolutionary traceability, together with the software protTrace, that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. We show that the LUCA set comprises only high-traceable proteins most of which have catalytic functions. We further show that proteins in the MG set lacking orthologs outside bacteria mostly have low traceability, leaving open whether their eukaryotic orthologs have just been overlooked. On the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and non-detection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks.
The exploration of hot and dense nuclear matter: Introduction to relativistic heavy-ion physics
(2022)
This article summarizes our present knowledge about nuclear matter at the highest energy densities and its formation in relativistic heavy ion collisions. We review what is known about the structure and properties of the quark-gluon plasma and survey the observables that are used to glean information about it from experimental data.
The Miocene is a key time in the evolution of African mammals and their ecosystems witnessing the origin of the African apes and the isolation of eastern coastal forests through an expanding biogeographic arid corridor. Until recently, however, Miocene sites from the southeastern regions of the continent were unknown. Here we report discovery of the first Miocene fossil teeth from the shoulders of the Urema Rift in Gorongosa National Park, Mozambique, at the southern East African Rift System. We provide the first 1) radiometric age determinations of the fossiliferous Mazamba Formation, 2) reconstructions of past vegetation in the region based on pedogenic carbonates and fossil wood, and 3) description of fossil teeth from the southern rift. Gorongosa is unique in the East African Rift System in combining marine invertebrates, marine vertebrates, terrestrial mammals, and fossil woods in coastal paleoenvironments. The Gorongosa fossil sites offer the first evidence of persistent woodlands and forests on the coastal margins of southeastern Africa during the Miocene, and an exceptional assemblage of fossil vertebrates including new species. Further work will allow the testing of hypotheses positing the formation of a northeast-southwest arid corridor isolating species on the eastern coastal forests from those elsewhere in Africa.
Brief The Miocene is a key time in the evolution of African mammals and their ecosystems encompassing hominine origins and the establishment of an arid corridor that isolated eastern Africa’s coastal forests. Until now, however, Miocene sites from southeastern Africa have been unknown. We report the discovery of the first Miocene fossil sites from Gorongosa National Park, Mozambique, and show that these sites formed in coastal settings. We provide radiometric ages for the fossiliferous sediments, reconstructions of past vegetation based on stable isotopes and fossil wood, and a description of the first fossil teeth from the region. Gorongosa is the only paleontological site in the East African Rift that combines fossil woods, marine invertebrates, marine vertebrates, and terrestrial mammals. Gorongosa offers the first evidence of persistent woodlands and forests on the coastal margins of southeastern Africa during the Miocene.
The gradual heterogeneity of climatic factors pose varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift, and adaptation to non-clinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool-Seq data, and population genetic modelling. Common-garden experiments revealed a positive correlation of population growth rates corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an FST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in other studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.
Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the “German Corona Consensus Dataset” (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data.
Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.
Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.
Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.
The high E(T) drop of J / psi to Drell-Yan ratio from the statistical c anti-c coalescence model
(2002)
The dependence of the J/psi yield on the transverse energy ET in heavy ion collisions is considered within the statistical c¯c coalescence model. The model fits the NA50 data for Pb+Pb collisions at the CERN SPS even in the high-ET region (ET >< 100 GeV). Here ET -fluctuations and ET -losses in the dimuon event sample naturally create the celebrated drop in the J/psi to Drell-Yan ratio.
The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020 [37]. In view of most recent information on testing activity [32], we present here an update of our initial work [4]. In this work, mathematical models have been developed to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended here to account for undetected infections, as well as for stages of infections and age groups. The models are calibrated on data until April 5, data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases and reduced contact to risk groups.
Modular polyketide synthases (PKSs) produce complex, bioactive secondary metabolites in assembly line-like multistep reactions. Longstanding efforts to produce novel, biologically active compounds by recombining intact modules to new modular PKSs have mostly resulted in poorly active chimeras and decreased product yields. Recent findings demonstrate that the low efficiencies of modular chimeric PKSs also result from rate limitations in the transfer of the growing polyketide chain across the non-cognate module:module interface and further processing of the non-native polyketide substrate by the ketosynthase (KS) domain. In this study, we aim at disclosing and understanding the low efficiency of chimeric modular PKSs and at establishing guidelines for modular PKSs engineering. To do so, we work with a bimodular PKS testbed and systematically vary substrate specificity, substrate identity, and domain:domain interfaces of the KS involved reactions. We observe that KS domains employed in our chimeric bimodular PKSs are bottlenecks with regards to both substrate specificity as well as interaction with the ACP. Overall, our systematic study can explain in quantitative terms why early oversimplified engineering strategies based on the plain shuffling of modules mostly failed and why more recent approaches show improved success rates. We moreover identify two mutations of the KS domain that significantly increased turnover rates in chimeric systems and interpret this finding in mechanistic detail.
Ribosomes translate the genetic code into proteins. Recent technical advances have facilitated in situ structural analyses of ribosome functional states inside eukaryotic cells and the minimal bacterium Mycoplasma. However, such analyses of Gram-negative bacteria are lacking, despite their ribosomes being major antimicrobial drug targets. Here we compare two E. coli strains, a lab E. coli K-12 and human gut isolate E. coli ED1a, for which tetracycline exhibits bacteriostatic and bactericidal action, respectively. The in situ ribosome structures upon tetracycline treatment show a virtually identical drug binding-site in both strains, yet the distribution of ribosomal complexes clearly differs. While K-12 retains ribosomes in a translation competent state, tRNAs are lost in the vast majority of ED1a ribosomes. A differential response is also reflected in proteome-wide abundance and thermal stability assessment. Our study underlines the need to include molecular analyses and to consider gut bacteria when addressing antibiotic mode of action.
The Kinase Chemogenomic Set (KCGS): An open science resource for kinase vulnerability identification
(2019)
We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS) is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.
To characterize the left-ventral occipito-temporal cortex (lvOT) role during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filter out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging. Empirically, using functional magnetic resonance imaging, we demonstrate that quantitative LCM simulations predict lvOT activation across three studies better than alternative models. Besides, we found that word-likeness, which is assumed as input to LCM, is represented posterior to lvOT. In contrast, a dichotomous word/non-word contrast, which is assumed as the LCM’s output, could be localized to upstream frontal brain regions. Finally, we found that training lexical categorization results in more efficient reading. Thus, we propose a ventral-visual-stream processing framework for reading involving word-likeness extraction followed by lexical categorization, before meaning extraction.
After myocardial infarction in the adult heart the remaining, non-infarcted tissue adapts to compensate the loss of functional tissue. This adaptation requires changes in gene expression networks, which are mostly controlled by transcription regulating proteins. Long non-coding transcripts (lncRNAs) are now recognized for taking part in fine-tuning such gene programs. We identified and characterized the cardiomyocyte specific lncRNA Sweetheart RNA (Swhtr), an approximately 10 kb long transcript divergently expressed from the cardiac core transcription factor coding gene Nkx2-5. We show that Swhtr is dispensable for normal heart development and function, but becomes essential for the tissue adaptation process after myocardial infarction. Re-expressing Swhtr from an exogenous locus rescues the Swhtr null phenotype. Genes depending on Swhtr after cardiac stress are significantly occupied, and therefore most likely regulated by NKX2-5. Our results indicate a synergistic role for Swhtr and the developmentally essential transcription factor NKX2-5 in tissue adaptation after myocardial injury.
Vertebrate life depends on renal function to filter excess fluid and remove low-molecular-weight waste products. An essential component of the kidney filtration barrier is the slit diaphragm (SD), a specialized cell-cell junction between podocytes. Although the constituents of the SD are largely known, its molecular organization remains elusive. Here, we use super-resolution correlative light and electron microscopy to quantify a linear rate of reduction in albumin concentration across the filtration barrier under no-flow conditions. Next, we use cryo-electron tomography of vitreous lamellae from high-pressure frozen native glomeruli to analyze the molecular architecture of the SD. The resulting densities resemble a fishnet pattern. Fitting of Nephrin and Neph1, the main constituents of the SD, results in a complex interaction pattern with multiple contact sites between the molecules. Using molecular dynamics simulations, we construct a blueprint of the SD that explains its molecular architecture. Our architectural understanding of the SD reconciles previous findings and provides a mechanistic framework for the development of novel therapies to treat kidney dysfunction.
Vertebrate life depends on renal function to filter excess fluid and remove low-molecular-weight waste products. An essential component of the kidney filtration barrier is the slit diaphragm (SD), a specialized cell-cell junction between podocytes. Although the constituents of the SD are largely known, its molecular organization remains elusive. Here, we use super-resolution correlative light and electron microscopy to quantify a linear rate of reduction in albumin concentration across the filtration barrier. Next, we use cryo-electron tomography of vitreous lamellae from high-pressure frozen native glomeruli to analyze the molecular architecture of the SD. The resulting densities resemble a fishnet pattern. Fitting of Nephrin and Neph1, the main constituents of the SD, results in a complex interaction pattern with multiple contact sites between the molecules. Using molecular dynamics flexible fitting, we construct a blueprint of the SD, where we describe all interactions. Our architectural understanding of the SD reconciles previous findings and provides a mechanistic framework for the development of novel therapies to treat kidney dysfunction.
A key event in cellular physiology is the decision between membrane biogenesis and fat storage. Phosphatidic acid (PA) is an important lipid intermediate and signaling lipid at the branch point of these pathways and constantly monitored by the transcriptional repressor Opi1 to orchestrate lipid metabolism. Here, we report on the mechanism of membrane recognition by Opi1 and identify an amphipathic helix (AH) for the selective binding to membranes containing PA over phosphatidylserine (PS). The insertion of the AH into the hydrophobic core of the membrane renders Opi1 sensitive to the lipid acyl chain composition as an important factor contributing to the regulation of membrane biogenesis. Based on these findings, we rationally designed the membrane binding properties of Opi1 to control its responsiveness in the physiological context. Using extensive molecular dynamics (MD) simulations, we identified two PA-selective three-finger grips that tightly bind the phosphate headgroup, while interacting less intimately and more transiently with PS. This work establishes lipid headgroup selectivity as a new feature in the family of AH-containing membrane property sensors.
The fundamental structure of cortical networks arises early in development prior to the onset of sensory experience. However, how endogenously generated networks respond to the onset of sensory experience, and how they form mature sensory representations with experience remains unclear. Here we examine this "nature-nurture transform" using in vivo calcium imaging in ferret visual cortex. At eye-opening, visual stimulation evokes robust patterns of cortical activity that are highly variable within and across trials, severely limiting stimulus discriminability. Initial evoked responses are distinct from spontaneous activity of the endogenous network. Visual experience drives the development of low-dimensional, reliable representations aligned with spontaneous activity. A computational model shows that alignment of novel visual inputs and recurrent cortical networks can account for the emergence of reliable visual representations.
Evading imminent predator threat is critical for survival. Effective defensive strategies can vary, even between closely related species. However, the neural basis of such species-specific behaviours is still poorly understood. Here we find that two sister species of deer mice (genus Peromyscus) show different responses to the same looming stimulus: P. maniculatus, which occupy densely vegetated habitats, predominantly dart to escape, while the open field specialist, P. polionotus, pause their movement. This difference arises from species-specific escape thresholds, is largely context-independent, and can be triggered by both visual and auditory threat stimuli. Using immunohistochemistry and electrophysiological recordings, we find that although visual threat activates the superior colliculus in both species, the role of the dorsal periaqueductal gray (dPAG) in driving behaviour differs. While dPAG activity scales with running speed and involves both excitatory and inhibitory neurons in P. maniculatus, the dPAG is largely silent in P. polionotus, even when darting is triggered. Moreover, optogenetic activation of excitatory dPAG neurons reliably elicits darting behaviour in P. maniculatus but not P. polionotus. Together, we trace the evolution of species-specific escape thresholds to a central circuit node, downstream of peripheral sensory neurons, localizing an ecologically relevant behavioural difference to a specific region of the complex mammalian brain.
The family of cubic noncentrosymmetric 3-4-3 compounds has become a fertile ground for the discovery of novel correlated metallic and insulating phases. Here, we report the synthesis of a new heavy fermion compound, Ce3Bi4Ni3. It is an isoelectronic analog of the prototypical Kondo insulator Ce3Bi4Pt3 and of the recently discovered Weyl-Kondo semimetal Ce3Bi4Pd3. In contrast to the volume-preserving Pt-Pd substitution, structural and chemical analyses reveal a positive chemical pressure effect in Ce3Bi4Ni3 relative to its heavier counterparts. Based on the results of electrical resistivity, Hall effect, magnetic susceptibility, and specific heat measurements, we identify an energy gap of 65-70 meV, about 8 times larger than that in Ce3Bi4Pt3 and about 45 times larger than that of the Kondo-insulating background hosting the Weyl nodes in Ce3Bi4Pd3. We show that this gap as well as other physical properties do not evolve monotonically with increasing atomic number, i.e., in the sequence Ce3Bi4Ni3-Ce3Bi4Pd3-Ce3Bi4Pt3, but instead with increasing partial electronic density of states of the d orbitals at the Fermi energy. To understand under which condition topological states form in these materials is a topic for future studies.
The C-type lectin-like receptor NKG2D contributes to the immunosurveillance of virally infected and malignant cells by cytotoxic lymphocytes. A peculiar and puzzling feature of the NKG2D-based immunorecognition system is the high number of ligands for this single immunoreceptor. In humans, there are a total of eight NKG2D ligands (NKG2DL) comprising two members of the MIC (MICA, MICB) and six members of the ULBP family of glycoproteins (ULBP1 to ULBP6). While MICA has been extensively studied with regard to its biochemistry, cellular expression and function, very little is known about the NKG2DL ULBP4. This is, at least in part, due to its rather restricted expression by very few cell lines and tissues. Recently, constitutive ULBP4 expression by human monocytes was reported, questioning the view of tissue-restricted ULBP4 expression. Here, we scrutinized ULBP4 expression by human peripheral blood mononuclear cells and monocytes by analyzing ULBP4 transcripts and ULBP4 surface expression. In contrast to MICA, there was no ULBP4 expression detectable, neither by freshly isolated monocytes nor by PAMP-activated monocytes. However, a commercial antibody erroneously indicated surface ULBP4 on monocytes due to a non-ULBP4-specific binding activity, emphasizing the critical importance of validated reagents for life sciences. Collectively, our data show that ULBP4 is not expressed by monocytes, and likely also not by other peripheral blood immune cells, and therefore exhibits an expression pattern rather distinct from other human NKG2DL.
Each lifecycle of the Hepatitis C virus (HCV) produces structural and non-structural (NS) proteins in equimolar. Structural proteins were either assembled or degraded by host proteolysis systems, while NS proteins remain inside the host cells and don’t accumulate. Therefore, they must be degraded. Here, NS3 and NS5A half-lives were quantified in the presence of autolysosome and proteasome different modulators. Inhibitors of both systems increased the half-life, while inducers decreased the half-life. Furthermore, polyubiquitination of NS3 and NS5A was observed. Additionally, their intracellular co-localization with autolysosome (LAMP2) and proteasome (PSMB5) was observed, and inhibitors of both systems increased the degree of co-localization. A better understanding of NS protein degradation might help to improve medical interventions during HCV infections in the future.
Each lifecycle of the Hepatitis C virus (HCV) produces structural and non-structural (NS) proteins in equimolar. Structural proteins were either assembled or degraded by host proteolysis systems, while NS proteins remain inside the host cells and don’t accumulate. Therefore, they must be degraded. Here, NS3 and NS5A half-lives were quantified in the presence of autolysosome and proteasome different modulators. Inhibitors of both systems increased the half-life, while inducers decreased the half-life. Furthermore, polyubiquitination of NS3 and NS5A was observed. Additionally, their intracellular co-localization with autolysosome (LAMP2) and proteasome (PSMB5) was observed, and inhibitors of both systems increased the degree of co-localization. A better understanding of NS protein degradation might help to improve medical interventions during HCV infections in the future.
The properties of the outer crust of non-accreting cold neutron stars are studied by using modern nuclear data and theoretical mass tables updating in particular the classic work of Baym, Pethick and Sutherland. Experimental data from the atomic mass table from Audi, Wapstra, and Thibault of 2003 is used and a thorough comparison of many modern theoretical nuclear models, relativistic and non-relativistic ones, is performed for the first time. In addition, the influences of pairing and deformation are investigated. State-of-the-art theoretical nuclear mass tables are compared in order to check their differences concerning the neutron dripline, magic neutron numbers, the equation of state, and the sequence of neutron-rich nuclei up to the dripline in the outer crust of non-accreting cold neutron stars.
The ACL 2008 Workshop on Parsing German features a shared task on parsing German. The goal of the shared task was to find reasons for the radically different behavior of parsers on the different treebanks and between constituent and dependency representations. In this paper, we describe the task and the data sets. In addition, we provide an overview of the test results and a first analysis.
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.
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.
The dynamics of many systems are described by ordinary differential equations (ODE). Solving ODEs with standard methods (i.e. numerical integration) needs a high amount of computing time but only a small amount of storage memory. For some applications, e.g. short time weather forecast or real time robot control, long computation times are prohibitive. Is there a method which uses less computing time (but has drawbacks in other aspects, e.g. memory), so that the computation of ODEs gets faster? We will try to discuss this question for the assumption that the alternative computation method is a neural network which was trained on ODE dynamics and compare both methods using the same approximation error. This comparison is done with two different errors. First, we use the standard error that measures the difference between the approximation and the solution of the ODE which is hard to characterize. But in many cases, as for physics engines used in computer games, the shape of the approximation curve is important and not the exact values of the approximation. Therefore, we introduce a subjective error based on the Total Least Square Error (TLSE) which gives more consistent results. For the final performance comparison, we calculate the optimal resource usage for the neural network and evaluate it depending on the resolution of the interpolation points and the inter-point distance. Our conclusion gives a method to evaluate where neural nets are advantageous over numerical ODE integration and where this is not the case. Index Terms—ODE, neural nets, Euler method, approximation complexity, storage optimization.
We study the phase diagram of dense, locally neutral three-flavor quark matter within the framework of the Nambu--Jona-Lasinio model. In the analysis, dynamically generated quark masses are taken into account self-consistently. The phase diagram in the plane of temperature and quark chemical potential is presented. The results for two qualitatively different regimes, intermediate and strong diquark coupling strength, are presented. It is shown that the role of gapless phases diminishes with increasing diquark coupling strength.
We study the effect of neutrino trapping on the phase diagram of dense, locally neutral three-flavor quark matter within the framework of a Nambu--Jona-Lasinio model. In the analysis, dynamically generated quark masses are taken into account self-consistently. The phase diagrams in the plane of temperature and quark chemical potential, as well as in the plane of temperature and lepton-number chemical potential are presented. We show that neutrino trapping favors two-flavor color superconductivity and disfavors the color-flavor-locked phase at intermediate densities of matter. At the same time, the location of the critical line separating the two-flavor color-superconducting phase and the normal phase of quark matter is little affected by the presence of neutrinos. The implications of these results for the evolution of protoneutron stars are briefly discussed. PACS numbers: 12.39.-x 12.38.Aw 26.60.+c
The pitfalls of measuring representational similarity using representational similarity analysis
(2022)
A core challenge in neuroscience is to assess whether diverse systems represent the world similarly. Representational Similarity Analysis (RSA) is an innovative approach to address this problem and has become increasingly popular across disciplines from machine learning to computational neuroscience. Despite these successes, RSA regularly uncovers difficult-to-reconcile and contradictory findings. Here we demonstrate the pitfalls of using RSA to infer representational similarity and explain how contradictory findings arise and support false inferences when left unchecked. By comparing neural representations in primate, human and computational models, we reveal two problematic phenomena that are ubiquitous in current research: a “mimic” effect, where confounds in stimuli can lead to high RSA scores between provably dissimilar systems, and a “modulation effect”, where RSA-scores become dependent on stimuli used for testing. Since our results bear on existing findings and inferences, we provide recommendations to avoid these pitfalls and sketch a way forward.
The pitfalls of measuring representational similarity using representational similarity analysis
(2022)
A core challenge in cognitive and brain sciences is to assess whether different biological systems represent the world in a similar manner. Representational Similarity Analysis (RSA) is an innovative approach to address this problem and has become increasingly popular across disciplines ranging from artificial intelligence to computational neuroscience. Despite these successes, RSA regularly uncovers difficult-to-reconcile and contradictory findings. Here, we demonstrate the pitfalls of using RSA and explain how contradictory findings arise due to false inferences about representational similarity based on RSA-scores. In a series of studies that capture increasingly plausible training and testing scenarios, we compare neural representations in computational models, primate cortex and human cortex. These studies reveal two problematic phenomena that are ubiquitous in current research: a “mimic” effect, where confounds in stimuli can lead to high RSA-scores between provably dissimilar systems, and a “modulation effect”, where RSA-scores become dependent on stimuli used for testing. Since our results bear on a number of influential findings and the inferences drawn by current practitioners in a wide range of disciplines, we provide recommendations to avoid these pitfalls and sketch a way forward to a more solid science of representation in cognitive systems.
Age-related diseases pose great challenges to health care systems worldwide. During aging, endothelial senescence increases the risk for cardiovascular disease. Recently, it was described that Phosphatase 1 Nuclear Targeting Subunit (PNUTS) has a central role in cardiomyocyte aging and homeostasis. Here, we determined the role of PNUTS in endothelial cell aging. We confirmed that PNUTS is repressed in senescent endothelial cells (ECs). Moreover, PNUTS silencing elicits several of the hallmarks of endothelial aging: senescence, reduced angiogenesis and loss of barrier function. To validate our findings in vivo, we generated an endothelial-specific inducible PNUTS-deficient mouse line (Cdh5-CreERT2;PNUTSfl/fl), termed PNUTSEC-KO. Two weeks after PNUTS deletion, PNUTSEC-KO mice presented severe multiorgan failure and vascular leakage. We showed that the PNUTS binding motif for protein phosphatase 1 (PP1) is essential to maintain endothelial barrier function. Transcriptomic analysis of PNUTS-silenced HUVECs and lungs of PNUTSEC-KO mice revealed that the PNUTS-PP1 axis tightly regulates the expression of semaphorin 3B (SEMA3B). Indeed, silencing of SEMA3B completely restored barrier function after PNUTS loss-of-function. These results reveal a pivotal role for PNUTS in endothelial homeostasis through a PP1-SEMA3B downstream pathway that provides a potential target against the effects of aging in ECs.
Within the last year, expressions of second-hand embarrassment on Twitter significantly increased. We show how this relates to the current situation in U.S. politics under Trump and provide two explanations for why people feel this way in response to his actions. First, compared to former politicians, Trump’s norm violations seem intentional. Second, intentional norm violations specifically threaten the social integrity of in-group members—in this case, U.S citizens. We theorize that these strong, frequent and widespread feelings of second-hand embarrassment motivate political actions to prevent further harm to individuals’ self-concept and protect their social integrity.
The causative/anticausative alternation has been the topic of much typological and theoretical discussion in the linguistic literature. This alternation is characterized by verbs with transitive and intransitive uses, such that the transitive use of a verb V means roughly "cause to Vintransitive" (see Levin 1993). The discussion revolves around two issues: the first one concerns the similarities and differences between the anticausative and the passive, and the second one concerns the derivational relationship, if any, between the transitive and intransitive variant. With respect to the second issue, a number of approaches have been developed. Judging the approach conceptually unsatisfactory, according to which each variant is assigned an independent lexical entry, it was concluded that the two variants have to be derivationally related. The question then is which one of the two is basic and where this derivation takes place in the grammar. Our contribution to this discussion is to argue against derivational approaches to the causative / anticausative alternation. We focus on the distribution of PPs related to external arguments (agent, causer, instrument, causing event) in passives and anticausatives of English, German and Greek and the set of verbs undergoing the causative/anticausative alternation in these languages. We argue that the crosslinguistic differences in these two domains provide evidence against both causativization and detransitivization analyses of the causative / anticausative alternation. We offer an approach to this alternation which builds on a syntactic decomposition of change of state verbs into a Voice and a CAUS component. Crosslinguistic variation in passives and anticausatives depends on properties of Voice and its combinations with CAUS and various types of roots.
We developed a three-center phenomenological model,able to explain qualitatively the recently obtained experimental results concerning the quasimolecular stage of a light-particle accompanied fission process. It was derived from the liquid drop model under the assumption that the aligned configuration, with the emitted particle between the light and heavy fragment, is reached by increasing continuously the separation distance, while the radii of the heavy fragment and of the light particle are kept constant. In such a way,a new minimum of a short-lived molecular state appears in the deformation energy at a separation distance very close to the touching point. This minimum allows the existence of a short-lived quasi-molecular state, decaying into the three final fragments.The influence of the shell effects is discussed. The half-lives of some quasimolecular states which could be formed in the $^{10}$Be and $^{12}$C accompanied fission of $^{252}$Cf are roughly estimated to be the order of 1 ns, and 1 ms, respectively.