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Measurements of the production cross sections of prompt D0, D+, D∗+, D+s, Λ+c, and Ξ+c charm hadrons at midrapidity in proton−proton collisions at s√=13 TeV with the ALICE detector are presented. The D-meson cross sections as a function of transverse momentum (pT) are provided with improved precision and granularity. The ratios of pT-differential meson production cross sections based on this publication and on measurements at different rapidity and collision energy provide a constraint on gluon parton distribution functions at low values of Bjorken-x (10−5−10−4). The measurements of Λ+c (Ξ+c) baryon production extend the measured pT intervals down to pT=0(3)~GeV/c. These measurements are used to determine the charm-quark fragmentation fractions and the cc¯¯ production cross section at midrapidity (|y|<0.5) based on the sum of the cross sections of the weakly-decaying ground-state charm hadrons D0, D+, D+s, Λ+c, Ξ0c and, for the first time, Ξ+c, and of the strongly-decaying J/psi mesons. The first measurements of Ξ+c and Σ0,++c fragmentation fractions at midrapidity are also reported. A significantly larger fraction of charm quarks hadronising to baryons is found compared to e+e− and ep collisions. The cc¯¯ production cross section at midrapidity is found to be at the upper bound of state-of-the-art perturbative QCD calculations.
The Chiral Magnetic Wave (CMW) phenomenon is essential to provide insights into the strong interaction in QCD, the properties of the quark-gluon plasma, and the topological characteristics of the early universe, offering a deeper understanding of fundamental physics in high-energy collisions. Measurements of the charge-dependent anisotropic flow coefficients are studied in Pb-Pb collisions at center-of-mass energy per nucleon-nucleon collision sNN−−−√= 5.02 TeV to probe the CMW. In particular, the slope of the normalized difference in elliptic (v2) and triangular (v3) flow coefficients of positively and negatively charged particles as a function of their event-wise normalized number difference, is reported for inclusive and identified particles. The slope rNorm3 is found to be larger than zero and to have a magnitude similar to rNorm2, thus pointing to a large background contribution for these measurements. Furthermore, rNorm2 can be described by a blast wave model calculation that incorporates local charge conservation. In addition, using the event shape engineering technique yields a fraction of CMW (fCMW) contribution to this measurement which is compatible with zero. This measurement provides the very first upper limit for fCMW, and in the 10-60% centrality interval it is found to be 26% (38%) at 95% (99.7%) confidence level.
Measurements of charged-particle production in pp, p−Pb, and Pb−Pb collisions in the toward, away, and transverse regions with the ALICE detector are discussed. These regions are defined event-by-event relative to the azimuthal direction of the charged trigger particle, which is the reconstructed particle with the largest transverse momentum (ptrigT) in the range 8<ptrigT<15 GeV/c. The toward and away regions contain the primary and recoil jets, respectively; both regions are accompanied by the underlying event (UE). In contrast, the transverse region perpendicular to the direction of the trigger particle is dominated by the so-called UE dynamics, and includes also contributions from initial- and final-state radiation. The relative transverse activity classifier, RT=NTch/⟨NTch⟩, is used to group events according to their UE activity, where NTch is the charged-particle multiplicity per event in the transverse region and ⟨NTch⟩ is the mean value over the whole analysed sample. The energy dependence of the RT distributions in pp collisions at s√=2.76, 5.02, 7, and 13 TeV is reported, exploring the Koba-Nielsen-Olesen (KNO) scaling properties of the multiplicity distributions. The first measurements of charged-particle pT spectra as a function of RT in the three azimuthal regions in pp, p−Pb, and Pb−Pb collisions at sNN−−−√=5.02 TeV are also reported. Data are compared with predictions obtained from the event generators PYTHIA 8 and EPOS LHC. This set of measurements is expected to contribute to the understanding of the origin of collective-like effects in small collision systems (pp and p−Pb).
The elliptic flow (v2) of D0 mesons from beauty-hadron decays (non-prompt D0) was measured in midcentral (30-50%) Pb-Pb collisions at a centre-of-mass energy per nucleon pair sNN−−−√ = 5.02 TeV with the ALICE detector at the LHC. The D0 mesons were reconstructed at midrapidity (|y|<0.8) from their hadronic decay D0→K−π+, in the transverse momentum interval 2<pT<12 GeV/c. The result indicates a positive v2 for non-prompt D0 mesons with a significance of 2.7σ. The non-prompt D0-meson v2 is lower than that of prompt non-strange D mesons with 3.2σ significance in 2<pT<8 GeV/c, and compatible with the v2 of beauty-decay electrons. Theoretical calculations of beauty-quark transport in a hydrodynamically expanding medium describe the measurement within uncertainties.
The ALICE Collaboration reports a differential measurement of inclusive jet suppression using pp and Pb−Pb collision data at a center-of-mass energy per nucleon-nucleon collision sNN−−−√=5.02 TeV. Charged-particle jets are reconstructed using the anti-kT algorithm with resolution parameters R= 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and R= 0.2, 0.4, 0.6 in central (0−10%), semi-central (30−50%), and peripheral (60−80%) Pb−Pb collisions. A novel approach based on machine learning is employed to mitigate the influence of jet background. This enables measurements of inclusive jet suppression in new regions of phase space, including down to the lowest jet pT≥40 GeV/c at R=0.6 in central Pb−Pb collisions. This is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, derived cross section, and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet-quenching models with varying levels of agreement.
The ubiquitin (Ub) code denotes the complex Ub architectures, including Ub chains of different length, linkage-type and linkage combinations, which enable ubiquitination to control a wide range of protein fates. Although many linkage-specific interactors have been described, how interactors are able to decode more complex architectures is not fully understood. We conducted a Ub interactor screen, in humans and yeast, using Ub chains of varying length, as well as, homotypic and heterotypic branched chains of the two most abundant linkage types – K48- and K63-linked Ub. We identified some of the first K48/K63 branch-specific Ub interactors, including histone ADP-ribosyltransferase PARP10/ARTD10, E3 ligase UBR4 and huntingtin-interacting protein HIP1. Furthermore, we revealed the importance of chain length by identifying interactors with a preference for Ub3 over Ub2 chains, including Ub-directed endoprotease DDI2, autophagy receptor CCDC50 and p97-adaptor FAF1. Crucially, we compared datasets collected using two common DUB inhibitors – Chloroacetamide and N-ethylmaleimide. This revealed inhibitor-dependent interactors, highlighting the importance of inhibitor consideration during pulldown studies. This dataset is a key resource for understanding how the Ub code is read.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton-proton collisions at a center-of-mass energy of s√=13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.
We prove that the projectivized strata of differentials are not contained in pointed Brill-Noether divisors, with only a few exceptions. For a generic element in a stratum of differentials, we show that many of the associated pointed Brill-Noether loci are of expected dimension. We use our results to study the Auel-Haburcak Conjecture: We obtain new non-containments between maximal Brill-Noether loci in Mg. Our results regarding quadratic differentials imply that the quadratic strata in genus 6 are uniruled.
For genus g=r(r+1)2+1, we prove that via the forgetful map, the universal Prym-Brill-Noether locus Rrg has a unique irreducible component dominating the moduli space Rg of Prym curves.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2024)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Isothermal titration calorimetry (ITC) is a widely used technique for the characterization of protein-protein and protein-ligand interactions. It provides information on the stoichiometry, affinity, and the thermodynamic driving forces of interactions. This chapter exemplifies the use of ITC to investigate interactions between human autophagy modifiers (LC3/GABARAP proteins) and their interaction partners, the LIR motif containing sequences. The purpose of this report is to present a detailed protocol for the production of LC3/GABARAP-interacting LIR peptides using E. coli expression systems. In addition, we outline the design of ITC experiments using the LC3/GABARAP:peptide interactions as an example. Comprehensive troubleshooting notes are provided to facilitate the adaptation of these protocols to different ligand-receptor systems. The methodology outlined for studying protein-ligand interactions will help to avoid common errors and misinterpretations of experimental results.
Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin clade from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have photosensory activity. A distinguishing feature of the clade is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a strongly blue-shifted intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified clade and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton–proton collisions at a center-of-mass energy of √s = 13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
Measurement of beauty-quark production in pp collisions at √s = 13 TeV via non-prompt D mesons
(2024)
The pT-differential production cross sections of non-prompt D0, D+, and D+s mesons originating from beauty-hadron decays are measured in proton−proton collisions at a centre-of-mass energy s√ of 13 TeV. The measurements are performed at midrapidity, |y|<0.5, with the data sample collected by ALICE from 2016 to 2018. The results are in agreement with predictions from several perturbative QCD calculations. The fragmentation fraction of beauty quarks to strange mesons divided by the one to non-strange mesons, fs/(fu+fd), is found to be 0.114±0.016 (stat.)±0.006 (syst.)±0.003 (BR)±0.003 (extrap.). This value is compatible with previous measurements at lower centre-of-mass energies and in different collision systems in agreement with the assumption of universality of fragmentation functions. In addition, the dependence of the non-prompt D meson production on the centre-of-mass energy is investigated by comparing the results obtained at s√=5.02 and 13 TeV, showing a hardening of the non-prompt D-meson pT-differential production cross section at higher s√. Finally, the bb¯¯¯ production cross section per unit of rapidity at midrapidity is calculated from the non-prompt D0, D+, D+s, and Λ+c hadron measurements, obtaining dσ/dy=75.2±3.2 (stat.)±5.2 (syst.)+12.3−3.2 (extrap.) μb.
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.
The intense photon fluxes from relativistic nuclei provide an opportunity to study photonuclear interactions in ultraperipheral collisions. The measurement of coherently photoproduced π+π−π+π− final states in ultraperipheral Pb-Pb collisions at sNN−−−√=5.02 TeV is presented for the first time. The cross section, dσ/dy, times the branching ratio (ρ→π+π+π−π−) is found to be 47.8±2.3 (stat.)±7.7 (syst.) mb in the rapidity interval |y|<0.5. The invariant mass distribution is not well described with a single Breit-Wigner resonance. The production of two interfering resonances, ρ(1450) and ρ(1700), provides a good description of the data. The values of the masses (m) and widths (Γ) of the resonances extracted from the fit are m1=1385±14 (stat.)±3 (syst.) MeV/c2, Γ1=431±36 (stat.)±82 (syst.) MeV/c2, m2=1663±13 (stat.)±22 (syst.) MeV/c2 and Γ2=357±31 (stat.)±49 (syst.) MeV/c2, respectively. The measured cross sections times the branching ratios are compared to recent theoretical predictions.
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 spike protein of SARS-CoV-2 is a highly flexible membrane receptor that triggers the translocation of the virus into cells by attaching to the human receptors. Like other type I membrane receptors, this protein has several extracellular domains connected by flexible hinges. The presence of these hinges results in high flexibility, which consequently results in challenges in defining the conformation of the protein. Here, We developed a new method to define the conformational space based on a few variables inspired by the robotic field’s methods to determine a robotic arm’s forward kinematics. Using newly performed atomistic molecular dynamics (MD) simulations and publicly available data, we found that the Denavit-Hartenberg (DH) parameters can reliably show the changes in the local conformation. Furthermore, the rotational and translational components of the homogenous transformation matrix constructed based on the DH parameters can identify the changes in the global conformation of the spike and also differentiate between the conformation with a similar position of the spike head, which other types of parameters, such as spherical coordinates, fail to distinguish between such conformations. Finally, the new method will be beneficial for looking at the conformational heterogeneity in all other type I membrane receptors.
Zinc finger (ZnF) domains appear in a pool of structural contexts and despite their small size achieve varying target specificities, covering single-stranded and double-stranded DNA and RNA as well as proteins. Combined with other RNA-binding domains, ZnFs enhance affinity and specificity of RNA-binding proteins (RBPs). The ZnF-containing immunoregulatory RBP Roquin initiates mRNA decay, thereby controlling the adaptive immune system. Its unique ROQ domain shape-specifically recognizes stem-looped cis-elements in mRNA 3’-untranslated regions (UTR). The N-terminus of Roquin contains a RING domain for protein-protein interactions and a ZnF, which was suggested to play an essential role in RNA decay by Roquin. The ZnF domain boundaries, its RNA motif preference and its interplay with the ROQ domain have remained elusive, also driven by the lack of high-resolution data of the challenging protein. We provide the solution structure of the Roquin-1 ZnF and use an RBNS-NMR pipeline to show that the ZnF recognizes AU-rich elements (ARE). We systematically refine the contributions of adenines in a poly(U)-background to specific complex formation. With the simultaneous binding of ROQ and ZnF to a natural target transcript of Roquin, our study for the first time suggests how Roquin integrates RNA shape and sequence specificity through the ROQ-ZnF tandem.
G protein-coupled receptors (GPCRs) play a crucial role in modulating physiological responses and serve as the main drug target. Specifically, salmeterol and salbutamol which are used for the treatment of pulmonary diseases, exert their effects by activating the GPCR β2-adrenergic receptor (β2AR). In our study, we employed coarse-grained molecular dynamics simulations with the Martini 3 force field to investigate the dynamics of drug molecules in membranes in presence and absence of β2AR. Our simulations reveal that in more than 50% of the flip-flop events the drug molecules use the β2AR surface to permeate the membrane. The pathway along the GPCR surface is significantly more energetically favorable for the drug molecules, which was revealed by umbrella sampling simulations along spontaneous flip-flop pathways. Furthermore, we assessed the behavior of drugs with intracellular targets, such as kinase inhibitors, whose therapeutic efficacy could benefit from this observation. In summary, our results show that β2AR surface interactions can significantly enhance membrane permeation of drugs, emphasizing their potential for consideration in future drug development strategies.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by lit, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1,000 short (3s) naturalistic video clips of visual events across ten human subjects. We use the videos’ extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.
From hunting and foraging to clearing land for agriculture, humans modify forest biodiversity, landscapes, and climate. Forests constantly undergo disturbance–recovery dynamics and understanding them is a major objective of ecologists and conservationists. Chronosequences are a useful tool for understanding global restoration efforts. They represent a space-for-time substitution approach suited for the quantification of the resistance of ecosystem properties to withstand disturbance and the resilience of these properties until reaching pre-disturbance levels. Here we introduce a newly established chronosequence with 62 plots (50 ⍰ 50 m) in active cacao plantations and pastures, early and late regeneration, and mature old-growth forests, across a 200 km2 area in the extremely wet Chocó rainforest. Our chronosequence covers by far the largest total area of plots compared to others in the Neotropics. Plots ranged from 159–615 masl in a forested landscape with 74 ± 2.8 % forest cover within a 1-km radius including substantial old-growth forest cover. Land-use legacy and regeneration time were not confounded by elevation. We tested how six forest structure variables (maximum tree height and DBH, basal area, number of stems, vertical vegetation heterogeneity, and light availability), aboveground biomass (AGB), and rarefied tree species richness change along our chronosequence. Forest structure variables, AGB, and tree species richness increased with regeneration time and are predicted to reach similar levels to those in old-growth forests after ca. 30–116, 202, and 108 yrs, respectively. Compared to previous work in the Neotropics, old-growth forests in Canandé accumulate high AGB that takes one of the largest time spans reported until total recovery. Our chronosequence comprises one of the largest tree species pools, covers the largest total area of regenerating and old-growth forests, and has higher forest cover than other Neotropical chronosequences. Hence, our chronosequence can be used to determine the time for recovery and stability (resistance and resilience) of different taxa and ecosystem functions, including species interaction networks. This integrative effort will ultimately help to understand how one of the most diverse forests on the planet recovers from large-scale disturbances.
Tree-related microhabitats (TreMs) describe the microhabitats that a tree can provide for a multitude of other taxonomic groups and have been proposed as an important indicator for forest biodiversity (Asbeck et al., 2021). So far, the focus of TreM studies has been on temperate forests, although many trees in the tropics harbour exceptionally high numbers of TreMs. In this study, TreMs in the lowland tropical forests of the Choco (Ecuador) and in the mountain tropical forests of Mount Kilimanjaro (Tanzania) were surveyed. Our results extend the existing typology of TreMs of Larrieu et al. (2018) to include tropical forests and enabled a comparison of the relative recordings and diversity of TreMs between tropical and temperate forests. A new TreM form, Root formations, and three new TreM groups, concavities build by fruits or leaves, dendrotelms, and root formations, were established. In total, 15 new TreM types in five different TreM groups were specified. The relative recordings of most TreMs were similar between tropical and temperate forests. However, ivy and lianas, and ferns were more common in the lowland rainforest than in temperate forests, and bark microsoil, limb breakage, and foliose and fruticose lichens in tropical montane forest than in lowland rainforest. Mountain tropical forests hosted the highest diversity for common and dominant TreM types, and lowland tropical forest the highest diversity for rare TreMs. Our extended typology of tree-related microhabitats can support studies of forest-dwelling biodiversity in tropical forests. Specifically, given the ongoing threat to tropical forests, TreMs can serve as an additional tool allowing rapid assessments of biodiversity in these hyperdiverse ecosystems.
Upon infection, human immunodeficiency virus (HIV-1) releases its cone-shaped capsid into the cytoplasm of infected T-cells and macrophages. As its largest known cargo, the capsid enters the nuclear pore complex (NPC), driven by interactions with numerous FG-repeat nucleoporins (FG-Nups). Whether NPCs structurally adapt to capsid passage and whether capsids are modified during passage remains unknown, however. Here, we combined super-resolution and correlative microscopy with cryo electron tomography and molecular simulations to study nuclear entry of HIV-1 capsids in primary human macrophages. We found that cytosolically bound cyclophilin A is stripped off capsids entering the NPC, and the capsid hexagonal lattice remains largely intact inside and beyond the central channel. Strikingly, the NPC scaffold rings frequently crack during capsid passage, consistent with computer simulations indicating the need for NPC widening. The unique cone shape of the HIV-1 capsid facilitates its entry into NPCs and helps to crack their rings.
Nuclear pore complexes (NPCs) constitute giant channels within the nuclear envelope that mediate nucleocytoplasmic exchange. NPC diameter is thought to be regulated by nuclear envelope tension, but how such diameter changes are physiologically linked to cell differentiation, where mechanical properties of nuclei are remodeled and nuclear mechanosensing occurs, remains unstudied. Here we used cryo-electron tomography to show that NPCs dilate during differentiation of mouse embryonic stem cells into neural progenitors. In Nup133-deficient cells, which are known to display impaired neural differentiation, NPCs however fail to dilate. By analyzing the architectures of individual NPCs with template matching, we revealed that the Nup133-deficient NPCs are structurally heterogeneous and frequently disintegrate, resulting in the formation of large nuclear envelope openings. We propose that the elasticity of the NPC scaffold mechanically safeguards the nuclear envelope. Our studies provide a molecular explanation for how genetic perturbation of scaffolding components of macromolecular complexes causes tissue-specific phenotypes.
Although iron-based catalysts are regarded as a promising alternative to precious metal catalysts, their precise electronic structures during catalysis still pose challenges for computational descriptions. A particularly urgent question is the influence of the environment on the electronic structure, and how to describe this properly with computational methods. Here, we study an iron porphyrin chloride complex adsorbed on a graphene sheet using density functional theory calculations to detail how much the electronic structure is influenced by the presence of a graphene layer. Our results indicate that weak interactions due to van der Waals forces dominate between the porphyrin complex and graphene, and only a small amount of charge is transferred between the two entities. Furthermore, the interplay of the ligand field environment, strong p − d hybridization, and correlation effects within the complex are strongly involved in determining the spin state of the iron ion. By bridging molecular chemistry and solid state physics, this study provides first steps towards a joint analysis of the properties of iron-based catalysts from first principles.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
Background: 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.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8′s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein′s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
In high light, the antenna system in oxygenic photosynthetic organisms switches to a photoprotective mode, dissipating excess energy in a process called non-photochemical quenching (NPQ). Diatoms exhibit very efficient NPQ, accompanied by a xanthophyll cycle in which diadinoxanthin is de-epoxidized into diatoxanthin. Diatoms accumulate pigments from this cycle in high light, and exhibit faster and more pronounced NPQ. The mechanisms underlying NPQ in diatoms remain unclear, but it can be mimicked by aggregation of their isolated light-harvesting complexes, FCP (fucoxanthin chlorophyll-a/c protein). We assess this model system by resonance Raman measurements of two peripheral FCPs, trimeric FCPa and nonameric FCPb, isolated from high- and low-light-adapted cells (LL, HL). Quenching is associated with a reorganisation of these proteins, affecting the conformation of their bound carotenoids, and in a manner which is highly dependent on the protein considered. FCPa from LL diatoms exhibits significant changes in diadinoxanthin structure, together with a smaller conformational change of at least one fucoxanthin. For these LL-FCPa, quenching is associated with consecutive events, displaying distinct spectral signatures, and its amplitude correlates with the planarity of the diadinoxanthin structure. HL-FCPa aggregation is associated with a change in planarity of a 515-nm-absorbing fucoxanthin, and, to a lesser extent, of diadinoxanthin. Finally, in FCPb, a blue-absorbing fucoxanthin is primarily affected. FCPs thus possess a plastic structure, undergoing several conformational changes upon aggregation, dependent upon their precise composition and structure. NPQ in diatoms may therefore arise from a combination of structural changes, dependent on the environment the cells are adapted to.
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.
EF-P and its paralog EfpL (YeiP) differentially control translation of proline containing sequences
(2024)
Polyproline sequences (XPPX) stall ribosomes, thus being deleterious for all living organisms. In bacteria, translation elongation factor P (EF-P) plays a crucial role in overcoming such arrests. 12% of eubacteria possess an EF-P paralog – YeiP (EfpL) of unknown function. Here, we functionally and structurally characterize EfpL from Escherichia coli and demonstrate its yet unrecognized role in the translational stress response. Through ribosome profiling, we analyzed the EfpL arrest motif spectrum and discovered additional stalls beyond the canonical XPPX motifs at single-proline sequences (XPX), that both EF-P and EfpL can resolve. Notably, the two factors can also induce pauses. We further report that, contrary to the housekeeping EF-P, EfpL can sense the metabolic state of the cell, via lysine acylation. Together, our work uncovers a new player in ribosome rescue at proline-containing sequences, and provides evidence that co-occurrence of EF-P and EfpL is an evolutionary driver for higher bacterial growth rates.
Upon infection of host cells, Legionella pneumophila releases a multitude of effector enzymes into the cells cytoplasm that hijack a plethora of cellular activities, including the hosts ubiquitination pathways. Effectors belonging to the SidE-family are involved in non-canonical serine phosphoribosyl ubiquitination of host substrate proteins contributing to the formation of a Legionella-containing vacuole that is crucial in the onset of Legionnaires’ disease. This dynamic process is reversed by effectors called Dups that hydrolyse the phosphodiester in the phosphoribosyl ubiquitinated protein. We installed reactive warheads on chemically prepared ribosylated ubiquitin to generate a set of probes targeting these Legionella enzymes. In vitro tests on recombinant DupA revealed that a vinyl sulfonate warhead was most efficient in covalent complex formation. Mutagenesis and x-ray crystallography approaches were used to identify the site of covalent crosslinking to be an allosteric cysteine residue. The subsequent application of this probe highlights the potential to selectively enrich the Dup enzymes from Legionella-infected cell lysates.
Highlights
• Family structure transitions decrease academic school track attendance among children of less educated parents.
• Children of highly educated fathers in single-mother families also have lower outcomes.
• Reduced income and increased exposure to poverty are relevant mediators.
• There is no cumulative disadvantage linked to a further transition to a stepfamily.
• Previous parental separation does not affect educational outcomes for children residing with a highly educated stepfather.
Abstract
Recent research has documented that the effect of parental separation on children’s educational outcomes depends on socioeconomic background. Yet, parental separation could lead to a stable single-parent family or to a further transition to a stepfamily. Little is known about how the effect of family structure transitions on educational outcomes depends on the education of parents and stepparents, and there has been limited empirical research into the mechanisms that explain heterogeneity in the effects of family transitions. Using longitudinal data from the German Socio-Economic Panel and models with entropy balancing and sibling fixed effects, I explore the heterogeneous effects of family transitions during early and middle childhood on academic secondary school track attendance, grades and aspirations. I find that family transitions only reduce the academic school track attendance among children of less educated parents living in stepfamilies or with a single mother after parental separation, and among children of highly educated fathers living in single-mother families. The mechanisms that partly explain these effects relate to reduced income and exposure to poverty after parental separation. The findings underscore the importance of considering the stepparent's educational level, indicating that the adverse consequences of parental separation on educational outcomes are mitigated when a highly educated stepfather becomes part of the family. Overall, these findings align more closely with the resource perspective than the family stability perspective.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI’s capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
One Sentence Summary: Bats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.
Alzheimer’s Disease (AD) is a progressive and irreversible neurodegenerative disorder, characterized by the accumulation of abeta-amyloid aggregates, which triggers tau hyperphosphorylation and neuronal loss. While the precise mechanisms underlying neurodegeneration in AD are not entirely understood, it is known that loss of proteostasis is implicated in this process. Maintaining neuronal proteostasis requires proper transfer RNA (tRNA) modifications, which are crucial for optimal translation. However, research into tRNA epitranscriptome in AD is limited, and it is not yet clear how alterations in tRNA modifying enzymes and tRNA modifications might contribute to disease progression. Here, we report that expression of the tRNA modifying enzyme ELP3 is reduced in the brain of AD patients and amyloid AD mouse models, suggesting ELP3 is implicated in proteostasis dysregulation observed in AD. To investigate the role of ELP3 specifically in neuronal proteostasis impairments in the context of amyloid pathology, we analyzed SH-SY5Y neuronal cells carrying the amyloidogenic Swedish familial AD mutation in the APP gene (SH-SWE) or the wild-type gene (SH-WT). Similarly to the amyloid mouse models, SH-SWE exhibited reduced levels of ELP3 which was associated with tRNA hypomodifications and reduced abundance, as well as proteostasis impairments. Furthermore, the knock-down of ELP3 in SH-WT recapitulated the proteostasis impairments observed in SH-SWE cells. Importantly, the correction of tRNA deficits due to ELP3 reduction rescued and reverted proteostasis impairments of SH-SWE and SH-WT knock-down for ELP3, respectively. Additionally, SH-WT exposed to the secretome of SH-SWE or synthetic amyloid aggregates recapitulate the SH-SWE phenotype, characterized by reduced ELP3 expression, tRNA hypomodification and increased protein aggregation. Taken together, our data suggest that amyloid pathology dysregulates neuronal proteostasis through the reduction of ELP3 and tRNA modifications. This study highlights the modulation of tRNA modifications as a potential therapeutic avenue to restore neuronal proteostasis in AD and preserve neuronal function.
Ribosomes catalyze protein synthesis by cycling through various functional states. These states have been extensively characterized in vitro, yet their distribution in actively translating human cells remains elusive. Here, we optimized a cryo-electron tomography-based approach and resolved ribosome structures inside human cells with a local resolution of up to 2.5 angstroms. These structures revealed the distribution of functional states of the elongation cycle, a Z tRNA binding site and the dynamics of ribosome expansion segments. In addition, we visualized structures of Homoharringtonine, a drug for chronic myeloid leukemia treatment, within the active site of the ribosome and found that its binding reshaped the landscape of translation. Overall, our work demonstrates that structural dynamics and drug effects can be assessed at near-atomic detail within human cells.
Transient receptor potential (TRP) ion channels are among the most well-studied classes of temperature-sensing molecules. Yet, the molecular mechanism and thermodynamic basis for the temperature sensitivity of TRP channels remains to this day poorly understood. One hypothesis is that the temperature-sensing mechanism can simply be described by a difference in heat capacity between the closed and open channel states. While such a two-state model may be simplistic it nonetheless has descriptive value, in the sense that it can be used to to compare overall temperature sensitivity between different channels and mutants. Here, we introduce a mathematical framework based on the two-state model to reliably extract temperature-dependent thermodynamic potentials and heat capacities from measurements of equilibrium constants at different temperatures. Our framework is implemented in an open-source data analysis package that provides a straightforward way to fit both linear and nonlinear van ‘t Hoff plots, thus avoiding some of the previous, potentially erroneous, assumptions when extracting thermodynamic variables from TRP channel electrophysiology data.
Background Vasoplegic syndrome is frequently observed during cardiac surgery and resembles a complication of high mortality and morbidity. There is a clinical need for therapy and prevention of vasoplegic syndrome during complex cardiac surgical procedures. Therefore, we investigated different strategies in a porcine model of vasoplegia.
Methods We evaluated new medical therapies and prophylaxis to avoid vasoplegic syndrome in a porcine model. After induction of anesthesia, cardiopulmonary bypass was established through median sternotomy and central cannulation. Prolonged aortic cross-clamping (120 min) simulated a complex surgical procedure. The influence of sevoflurane-guided anesthesia (sevoflurane group) and the administration of glibenclamide (glibenclamide group) were compared to a control group, which received standard anesthesia using propofol. Online hemodynamic assessment was performed using PiCCO® measurements. In addition, blood and tissue samples were taken to evaluate hemodynamic effects and the degree of inflammatory response.
Results Glibenclamide was able to break through early vasoplegic syndrome by raising the blood pressure and systemic vascular resistance as well as less need of norepinephrine doses. Sevoflurane reduced the occurrence of the vasoplegic syndrome in the mean of stable blood pressure and less need of norepinephrine doses.
Conclusion Glibenclamide could serve as a potent drug to reduce effects of vasoplegic syndrome. Sevoflurane anesthesia during cardiopulmonary bypass shows less occurrence of vasoplegic syndrome and therefore could be used to prevent it in high-risk patients.
Clinical Perspective; what is new?
* to our knowledge, this is the first randomized in vivo study evaluating the hemodynamic effects of glibenclamide after the onset of vasoplegic syndrome
* furthermore according to literature research, there is no study showing the effect of sevoflurane-guided anesthesia on the occurrence of a vasoplegic syndrome
Clinical Perspective; clinical implications?
to achieve better outcomes after complex cardiac surgery there is a need for optimized drug therapy and prevention of the vasoplegic syndrome
This research article examines the dual impact of protests on COVID-19 spread, a challenge for policymakers balancing public health and the right to assemble. Using a game theoretical model, it shows that protests can shift infection risks between counties, creating a dilemma for regulators. The empirical study analyzes two German protests in November 2020 using proprietary data from a bus-shuttle service, finding evidence to support the assumption that protests can shift infection risks. The article concludes by discussing the implications of these findings for policymakers, highlighting that regulators’ individually rational strategic decisions may lead to inefficient outcomes.
Deviance detection describes an increase of neural response strength caused by a stimulus with a low probability of occurrence. This ubiquitous phenomenon has been reported for multiple species, from subthalamic areas to auditory cortex. While cortical deviance detection has been well characterised by a range of studies covering neural activity at population level (mismatch negativity, MMN) as well as at cellular level (stimulus-specific adaptation, SSA), subcortical deviance detection has been studied mainly on cellular level in the form of SSA. Here, we aim to bridge this gap by using noninvasively recorded auditory brainstem responses (ABRs) to investigate deviance detection at population level in the lower stations of the auditory system of a hearing specialist: the bat Carollia perspicillata. Our present approach uses behaviourally relevant vocalisation stimuli that are closer to the animals' natural soundscape than artificial stimuli used in previous studies that focussed on subcortical areas. We show that deviance detection in ABRs is significantly stronger for echolocation pulses than for social communication calls or artificial sounds, indicating that subthalamic deviance detection depends on the behavioural meaning of a stimulus. Additionally, complex physical sound features like frequency- and amplitude-modulation affected the strength of deviance detection in the ABR. In summary, our results suggest that at population level, the bat brain can detect different types of deviants already in the brainstem. This shows that subthalamic brain structures exhibit more advanced forms of deviance detection than previously known.
Human language relies on hierarchically structured syntax to facilitate efficient and robust communication. The correct processing of syntactic information is essential for successful communication between speakers. As an abstract level of language, syntax has often been studied separately from the physical form of the speech signal, thus often masking the interactions that can promote better syntactic processing in the human brain. We analyzed a MEG dataset to investigate how acoustic cues, specifically prosody, interact with syntactic operations. We examined whether prosody enhances the cortical encoding of syntactic representations. We decoded left-sided dependencies directly from brain activity and evaluated possible modulations of the decoding by the presence of prosodic boundaries. Our findings demonstrate that prosodic boundary presence improves the representation of left-sided dependencies, indicating the facilitative role of prosodic cues in processing abstract linguistic features. This study gives neurobiological evidence for the boosting of syntactic processing via interaction with prosody.
Dual coding theories of knowledge suggest that meaning is represented in the brain by a double code, which comprises language-derived representations in the Anterior Temporal Lobe and sensory-derived representations in perceptual and motor regions. This approach predicts that concrete semantic features should activate both codes, whereas abstract features rely exclusively on the linguistic code. Using magnetoencephalography (MEG), we adopted a temporally resolved multiple regression approach to identify the contribution of abstract and concrete semantic predictors to the underlying brain signal. Results evidenced early involvement of anterior-temporal and inferior-frontal brain areas in both abstract and concrete semantic information encoding. At later stages, occipito-temporal regions showed greater responses to concrete compared to abstract features. The present findings shed new light on the temporal dynamics of abstract and concrete semantic representations in the brain and suggest that the concreteness of words processed first with a transmodal/linguistic code, housed in frontotemporal brain systems, and only after with an imagistic/sensorimotor code in perceptual and motor regions.
The traditional view on coding in the cortex is that populations of neurons primarily convey stimulus information through the spike count. However, given the speed of sensory processing, it has been hypothesized that sensory encoding may rely on the spike-timing relationships among neurons. Here, we use a recently developed method based on Optimal Transport Theory called SpikeShip to study the encoding of natural movies by high-dimensional ensembles of neurons in visual cortex. SpikeShip is a generic measure of dissimilarity between spike train patterns based on the relative spike-timing relations among all neurons and with computational complexity similar to the spike count. We compared spike-count and spike-timing codes in up to N > 8000 neurons from six visual areas during natural video presentations. Using SpikeShip, we show that temporal spiking sequences convey substantially more information about natural movies than population spike-count vectors when the neural population size is larger than about 200 neurons. Remarkably, encoding through temporal sequences did not show representational drift both within and between blocks. By contrast, population firing rates showed better coding performance when there were few active neurons. Furthermore, the population firing rate showed memory across frames and formed a continuous trajectory across time. In contrast to temporal spiking sequences, population firing rates exhibited substantial drift across repetitions and between blocks. These findings suggest that spike counts and temporal sequences constitute two different coding schemes with distinct information about natural movies.
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.
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.
To understand the neural mechanisms underlying brain function, neuroscientists aim to quantify causal interactions between neurons, for instance by perturbing the activity of neuron A and measuring the effect on neuron B. Recently, manipulating neuron activity using light-sensitive opsins, optogenetics, has increased the specificity of neural perturbation. However, using widefield optogenetic interventions, multiple neurons are usually perturbed, producing a confound -- any of the stimulated neurons can have affected the postsynaptic neuron making it challenging to discern which neurons produced the causal effect. Here, we show how such confounds produce large biases in interpretations. We explain how confounding can be reduced by combining instrumental variables (IV) and difference in differences (DiD) techniques from econometrics. Combined, these methods can estimate (causal) effective connectivity by exploiting the weak, approximately random signal resulting from the interaction between stimulation and the absolute refractory period of the neuron. In simulated neural networks, we find that estimates using ideas from IV and DiD outperform naive techniques suggesting that methods from causal inference can be useful to disentangle neural interactions in the brain.
Graph data is an omnipresent way to represent information in machine learning. Especially, in neuroscience research, data from Diffusion-Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI) is commonly represented as graphs. Exploiting the graph structure of these modalities using graph-specific machine learning applications is currently hampered by the lack of easy-to-use software. PHOTONAI Graph aims to close the gap between domain experts of machine learning, graph experts and neuroscientists. Leveraging the rapid machine learning model development features of the Python machine learning API PHOTONAI, PHOTONAI Graph enables the design, optimization, and evaluation of reliable graph machine learning models for practitioners. As such, it provides easy access to custom graph machine learning pipelines including, hyperparameter optimization and algorithm evaluation ensuring reproducibility and valid performance estimates. Integrating established algorithms such as graph neural networks, graph embeddings and graph kernels, it allows researchers without significant coding experience to build and optimize complex graph machine learning models within a few lines of code. We showcase the versatility of this toolbox by building pipelines for both resting–state fMRI and DTI data in the hope that it will increase the adoption of graph-specific machine learning algorithms in neuroscience research.
Macrophage infectivity potentiator (MIP) proteins are widespread in human pathogens including Legionella pneumophila, the causative agent of Legionnaires’ disease and protozoans such as Trypanosoma cruzi. All MIP proteins contain a FKBP (FK506 binding protein)-like prolyl-cis/trans- isomerase domain that hence presents an attractive drug target. Some MIPs such as the Legionella pneumophila protein (LpMIP) have additional appendage domains of mostly unknown function. In full- length, homodimeric LpMIP, the N-terminal dimerization domain is linked to the FKBP-like domain via a long, free-standing stalk helix. Combining X-ray crystallography, NMR and EPR spectroscopy and SAXS, we elucidated the importance of the stalk helix for protein dynamics and inhibitor binding to the FKBP-like domain and bidirectional crosstalk between the different protein regions. The first comparison of a microbial MIP and a human FKBP in complex with the same synthetic inhibitor was made possible by high-resolution structures of LpMIP with a [4.3.1]-aza-bicyclic sulfonamide and provides a basis for designing pathogen-selective inhibitors. Through stereospecific methylation, the affinity of inhibitors to L. pneumophila and T. cruzi MIP was greatly improved. The resulting X-ray inhibitor-complex structures of LpMIP and TcMIP at 1.49 and 1.34 Å, respectively, provide a starting point for developing potent inhibitors against MIPs from multiple pathogenic microorganisms.
Control of cell proliferation is critical for the lymphocyte life cycle. However, little is known on how stage-specific alterations in cell-cycle behavior drive proliferation dynamics during T-cell development. Here, we employed in vivo dual-nucleoside pulse labeling combined with determination of DNA replication over time as well as fluorescent ubiquitination-based cell-cycle indicator mice to establish a quantitative high-resolution map of cell-cycle kinetics of thymocytes. We developed an agent-based mathematical model of T-cell developmental dynamics. To generate the capacity for proliferative bursts, cell-cycle acceleration followed a 'stretch model', characterized by simultaneous and proportional contraction of both G1 and S phase. Analysis of cell-cycle phase dynamics during regeneration showed tailored adjustments of cell-cycle phase dynamics. Taken together, our results highlight intrathymic cell-cycle regulation as an adjustable system to maintain physiologic tissue homeostasis and foster our understanding of dysregulation of the T-cell developmental program.
Macrophage infectivity potentiator (MIP) proteins are widespread in human pathogens including Legionella pneumophila, the causative agent of Legionnaires’ disease and protozoans such as Trypanosoma cruzi. All MIP proteins contain a FKBP (FK506 binding protein)-like prolyl-cis/trans-isomerase domain that hence presents an attractive drug target. Some MIPs such as the Legionella protein (LpMIP) have additional appendage domains of mostly unknown function. In full-length, homodimeric LpMIP, the N-terminal dimerization domain is linked to the FKBP-like domain via a long, free-standing stalk helix. Combining X-ray crystallography, NMR and EPR spectroscopy and SAXS, we elucidated the importance of the stalk helix for protein dynamics and inhibitor binding to the FKBP-like domain and bidirectional crosstalk between the different protein regions. The first comparison of a microbial MIP and a human FKBP in complex with the same synthetic inhibitor was made possible by high-resolution structures of LpMIP with a [4.3.1]-aza-bicyclic sulfonamide and provides a basis for designing pathogen-selective inhibitors. Through stereospecific methylation, the affinity of inhibitors to to L. pneumophila and T. cruzi MIP was greatly improved. The resulting X-ray inhibitor-complex structures of LpMIP and TcMIP at 1.49 and 1.34 Å, respectively, provide a starting point for developing potent inhibitors against MIPs from multiple pathogenic microorganisms.
Knowledge is limited as to how prior SARS-CoV-2 infection influences cellular and humoral immunity after booster-vaccination with bivalent BA.4/5-adapted mRNA-vaccines, and whether vaccine-induced immunity correlates with subsequent infection. In this observational study, individuals with prior infection (n=64) showed higher vaccine-induced anti-spike IgG antibodies and neutralizing titers, but the relative increase was significantly higher in non-infected individuals (n=63). In general, both groups showed higher neutralizing activity towards the parental strain than towards Omicron subvariants BA.1, BA.2 and BA.5. In contrast, CD4 or CD8 T-cell levels towards spike from the parental strain and the Omicron subvariants, and cytokine expression profiles were similar irrespective of prior infection. Breakthrough infections occurred more frequently among previously non-infected individuals, who had significantly lower vaccine-induced spike-specific neutralizing activity and CD4 T-cell levels. Thus, the magnitude of vaccine-induced neutralizing activity and specific CD4 T-cells after bivalent vaccination may serve as a correlate for protection in previously non-infected individuals.
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modeled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.
Proton-powered c-ring rotation in mitochondrial ATP synthase is crucial to convert the transmembrane protonmotive force into torque to drive the synthesis of ATP. Capitalizing on recent cryo-EM structures, we aim at a structural and energetic understanding of how functional directional rotation is achieved. We performed multi-microsecond atomistic simulations to determine the free energy profiles along the c-ring rotation angle before and after the arrival of a new proton. Our results reveal that rotation proceeds by dynamic sliding of the ring over the a-subunit surface, during which interactions with conserved polar residues stabilize distinct intermediates. Ordered water chains line up for a Grotthuss-type proton transfer in one of these intermediates. After proton transfer, a high barrier prevents backward rotation and an overall drop in free energy favors forward rotation, ensuring the directionality of c-ring rotation required for the thermodynamically disfavored ATP synthesis. The essential arginine of the a-subunit stabilizes the rotated configuration through a salt-bridge with the c-ring. Overall, we describe a complete mechanism for the rotation step of the ATP synthase rotor, thereby illuminating a process critical to all life at atomic resolution.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. In other words, any two signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks, and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is unclear. We used computational modelling and EEG to test how context influences semantic object processing. Using representational similarity analysis, we established that EEG patterns dissociated between objects in congruent or incongruent scenes from around 300 ms. By modelling semantic processing of objects using independently normed properties, we confirm that the onset of semantic processing of both congruent and incongruent objects is similar (∼150 ms). Critically, after ∼275 ms, we discover a difference in the duration of semantic integration, lasting longer for incongruent compared to congruent objects. These results constrain our understanding of how contextual information supports access to semantic object information.
We explore the potential of optically-pumped magnetometers (OPMs) to infer the laminar origins of neural activity non-invasively. OPM sensors can be positioned closer to the scalp than conventional cryogenic MEG sensors, opening an avenue to higher spatial resolution when combined with high-precision forward modelling. By simulating the forward model projection of single dipole sources onto OPM sensor arrays with varying sensor densities and measurement axes, and employing sparse source reconstruction approaches, we find that laminar inference with OPM arrays is possible at relatively low sensor counts at moderate to high signal-to-noise ratios (SNR). We observe improvements in laminar inference with increasing spatial sampling densities and number of measurement axes. Surprisingly, moving sensors closer to the scalp is less advantageous than anticipated - and even detrimental at high SNRs. Biases towards both the superficial and deep surfaces at very low SNRs and a notable bias towards the deep surface when combining empirical Bayesian beamformer (EBB) source reconstruction with a whole-brain analysis pose further challenges. Adequate SNR through appropriate trial numbers and shielding, as well as precise co-registration, is crucial for reliable laminar inference with OPMs.
Sharp wave-ripples (SPW-Rs) are a hippocampal network phenomenon critical for memory consolidation and planning. SPW-Rs have been extensively studied in the adult brain, yet their developmental trajectory is poorly understood. While SPWs have been recorded in rodents shortly after birth, the time point and mechanisms of ripple emergence are still unclear. Here, we combine in vivo electrophysiology with optogenetics and chemogenetics in 4 to 12 days-old mice to address this knowledge gap. We show that ripples are robustly detected and induced by light stimulation of ChR2-transfected CA1 pyramidal neurons only from postnatal day (P) 10 onwards. Leveraging a spiking neural network model, we mechanistically link the maturation of inhibition and ripple emergence. We corroborate these findings by reducing ripple rate upon chemogenetic silencing of CA1 interneurons. Finally, we show that early SPW-Rs elicit a more robust prefrontal cortex response then SPWs lacking ripples. Thus, development of inhibition promotes ripples emergence.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. Here, we hypothesized that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Population analysis revealed that neuronal responses converged to a low dimensional subspace for natural but not for synthetic images. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the dominant low dimensional subspace, suggesting an alignment between the attentional and natural stimulus variance. The alignment was pronounced for late evoked responses but not for early transient responses of V1 neurons, supporting the notion that top-down feedback was required. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. brain signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded redundant and synergistic information during auditory prediction error processing. In both tasks, we observed multiple patterns of synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between auditory and frontal regions. Using a brain-constrained neural network, we simulated the spatio-temporal patterns of synergy and redundancy observed in the experimental results and further demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback and feedforward connections. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Anticipating future events is a key computational task for neuronal networks. Experimental evidence suggests that reliable temporal sequences in neural activity play a functional role in the association and anticipation of events in time. However, how neurons can differentiate and anticipate multiple spike sequences remains largely unknown. We implement a learning rule based on predictive processing, where neurons exclusively fire for the initial, unpredictable inputs in a spiking sequence, leading to an efficient representation with reduced post-synaptic firing. Combining this mechanism with inhibitory feedback leads to sparse firing in the network, enabling neurons to selectively anticipate different sequences in the input. We demonstrate that intermediate levels of inhibition are optimal to decorrelate neuronal activity and to enable the prediction of future inputs. Notably, each sequence is independently encoded in the sparse, anticipatory firing of the network. Overall, our results demonstrate that the interplay of self-supervised predictive learning rules and inhibitory feedback enables fast and efficient classification of different input sequences.
Proton-powered c-ring rotation in mitochondrial ATP synthase is crucial to convert the transmembrane protonmotive force into torque to drive the synthesis of ATP. Capitalizing on recent cryo-EM structures, we aim at a structural and energetic understanding of how functional directional rotation is achieved. We performed multi-microsecond atomistic simulations to determine the free energy profiles along the c-ring rotation angle before and after the arrival of a new proton. Our results reveal that rotation proceeds by dynamic sliding of the ring over the a-subunit surface, during which interactions with conserved polar residues stabilize distinct intermediates. Ordered water chains line up for a Grotthuss-type proton transfer in one of these intermediates. After proton transfer, a high barrier prevents backward rotation and an overall drop in free energy favors forward rotation, ensuring the directionality of c-ring rotation required for the thermodynamically disfavored ATP synthesis. The essential arginine of the a-subunit stabilizes the rotated configuration through a salt-bridge with the c-ring. Overall, we describe a complete mechanism for the rotation step of the ATP synthase rotor, thereby illuminating a process critical to all life at atomic resolution.
The MICOS complex subunit MIC13 is essential for mitochondrial cristae organization. Mutations in MIC13 cause severe mitochondrial hepato-encephalopathy displaying defective cristae morphology and loss of the MIC10-subcomplex. Here we identified SLP2 as a novel interacting partner of MIC13 and decipher a critical role of SLP2 for MICOS assembly at distinct steps. SLP2 provides a large interaction hub for MICOS subunits and loss of SLP2 imparted YME1L-mediated proteolysis of MIC26 and drastic alterations in cristae morphology. We further identified a MIC13-specific role in stabilizing the MIC10-subcomplex via a MIC13-YME1L axis. SLP2 together with the stabilized MIC10-subcomplex promotes efficient assembly of the MIC60-subcomplex forming the MICOS-MIB complex. Consistently, super-resolution nanoscopy showed a dispersed distribution of the MIC60 in cells lacking SLP2 and MIC13. Our study reveals converging and interdependent assembly pathways for the MIC10- and MIC60-subcomplexes which are controlled in two ways, the MIC13-YME1L and the SLP2-YME1L axes, revealing mechanistic insights of these factors in cristae morphogenesis. These results will be helpful in understanding the human pathophysiology linked to mutations in MIC13 or its interaction partners.
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.
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.
Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability
(2023)
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
Background: The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demanded the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties.
Main body: We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected in a consensus-based process by working groups of medical experts from the respective specialty to ensure that the contents are aligned with the research needs of the specialty. The selected data elements were mapped to international standardized vocabularies and data exchange specifications were created using HL7 FHIR profiles on the appropriate resources. All steps were performed in close interdisciplinary collaboration between medical domain experts, medical information scientists and FHIR developers. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process. In that way, we defined dataset specifications for a total number of 23 (immunization), 59 (pediatrics), and 50 (cardiology) data elements that augment the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module.
Conclusions: We here present extension modules for the GECCO core dataset that contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology. These extension modules were defined in an interdisciplinary, iterative, consensus-based approach that may serve as a blueprint for the development of further dataset definitions and GECCO extension modules. The here developed GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties.
Cryo-electron tomography (cryo-ET) is a powerful method to elucidate subcellular architecture and to structurally analyse biomolecules in situ by subtomogram averaging (STA). Specimen thickness is a key factor affecting cryo-ET data quality. Cells that are too thick for transmission imaging can be thinned by cryo-focused-ion-beam (cryo-FIB) milling. However, optimal specimen thickness for cryo-ET on lamellae has not been systematically investigated. Furthermore, the ions used to ablate material can cause damage in the lamellae, thereby reducing STA resolution. Here, we systematically benchmark the resolution depending on lamella thickness and the depth of the particles within the sample. Up to ca. 180 nm, lamella thickness does not negatively impact resolution. This shows that there is no need to generate very thin lamellae and thickness can be chosen such that it captures major cellular features. Furthermore, we show that gallium-ion-induced damage extends to depths of up to 30 nm from either lamella surface.
Representational Similarity Analysis (RSA) is an innovative approach used to compare neural representations across individuals, species and computational models. Despite its popularity within neuroscience, psychology and artificial intelligence, this approach has led to difficult-to-reconcile and contradictory findings, particularly when comparing primate visual representations with deep neural networks (DNNs). Here, we demonstrate how such contradictory findings could arise due to incorrect inferences about mechanism when comparing complex systems processing high-dimensional stimuli. In a series of studies comparing computational models, primate cortex and human cortex we find two problematic phenomena: 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, we provide recommendations to avoid these pitfalls and sketch a way forward to a more solid science of representation in cognitive systems.
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population density and structure, and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
Candida boidinii NAD+-dependent formate dehydrogenase (CbFDH) has gained significant attention for its potential applications in the production of biofuels and various industrial chemicals from inorganic carbon dioxide. The present study reports the atomic X-ray crystal structures of the wild-type CbFDH at cryogenic and ambient temperatures as well as Val120Thr mutant at cryogenic temperature determined at the Turkish Light Source "Turkish DeLight". The structures reveal new hydrogen bonds between Thr120 and water molecules in the mutant CbFDH's active site, suggesting increased stability of the active site and more efficient electron transfer during the reaction. Further experimental data is needed to test these hypotheses. Collectively, our findings provide invaluable insights into future protein engineering efforts that could potentially enhance the efficiency and effectiveness of CbFDH.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2023)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
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.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
The selective autophagy of mitochondria is linked to mitochondrial quality control and is critical to a healthy organism. Ubiquitylation is sometimes needed for marking damaged mitochondria for disposal but also for governing the expression and turnover of critical regulatory proteins. We have conducted a CRISPR/Cas9 screen of human E3 ubiquitin ligases for influence on mitophagy under both basal cell culture conditions and following acute mitochondrial depolarisation. We identify two Cullin RING ligases, VHL and FBXL4 as the most profound negative regulators of basal mitophagy. Here we show that these converge through control of the mitophagy adaptors BNIP3 and BNIP3L/NIX, but that this is achieved through different mechanisms. FBXL4 suppression of BNIP3 and NIX levels is mediated via direct interaction and protein destabilisation rather than suppression of HIF1α-mediated transcription. Depletion of NIX but not BNIP3 is sufficient to restore mitophagy levels. Our study enables a full understanding of the aetiology of early onset mitochondrial encephalomyopathy that is supported by analysis of a disease associated mutation. We further show that the compound MLN4924, which globally interferes with Cullin RING ligase activity, is a strong inducer of mitophagy which can provide a research tool in this context as well as a candidate therapeutic agent for conditions linked to mitochondrial quality control.
An excess of J/ψ yield at very low transverse momentum (pT<0.3 GeV/c), originating from coherent photoproduction, is observed in peripheral and semicentral hadronic Pb−Pb collisions at a center-of-mass energy per nucleon pair of sNN−−−√=5.02 TeV. The measurement is performed with the ALICE detector via the dimuon decay channel at forward rapidity (2.5<y<4). The nuclear modification factor at very low pT and the coherent photoproduction cross section are measured as a function of centrality down to the 10% most central collisions. These results extend the previous study at sNN−−−√=2.76 TeV, confirming the clear excess over hadronic production in the pT range 0−0.3 GeV/c and the centrality range 70−90%, and establishing an excess with a significance greater than 5σ also in the 50−70% and 30−50% centrality ranges. The results are compared with earlier measurements at sNN−−−√=2.76 TeV and with different theoretical predictions aiming at describing how coherent photoproduction occurs in hadronic interactions with nuclear overlap.
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.
Molecular mechanisms of inorganic-phosphate release from the core and barbed end of actin filaments
(2023)
The release of inorganic phosphate (Pi) from actin filaments constitutes a key step in their regulated turnover, which is fundamental to many cellular functions. However, the molecular mechanisms underlying Pi release from both the core and barbed end of actin filaments remain unclear. Here, we combine cryo-EM with molecular dynamics simulations and in vitro reconstitution to demonstrate how actin releases Pi through a ‘molecular backdoor’. While constantly open at the barbed end, the backdoor is predominantly closed in filament-core subunits and only opens transiently through concerted backbone movements and rotameric rearrangements of residues close to the nucleotide binding pocket. This mechanism explains why Pi escapes rapidly from the filament end and yet slowly from internal actin subunits. In an actin variant associated with nemaline myopathy, the backdoor is predominantly open in filament-core subunits, resulting in greatly accelerated Pi release after polymerization and filaments with drastically shortened ADP-Pi caps. This demonstrates that the Pi release rate from F-actin is controlled by steric hindrance through the backdoor rather than by the disruption of the ionic bond between Pi and Mg2+ at the nucleotide-binding site. Our results provide the molecular basis for Pi release from actin and exemplify how a single, disease-linked point mutation distorts the nucleotide state distribution and atomic structure of the actin filament.
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.
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
(2023)
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measure based on optimal transport theory called SpikeShip, which compares multi-neuron spiking patterns based on all the relative spike-timing relationships among neurons. SpikeShip computes the optimal transport cost to make all the relative spike timing relationships (across neurons) identical between two spiking patterns. We show that this transport cost can be decomposed into a temporal rigid translation term, which captures global latency shifts, and a vector of neuron-specific transport flows, which reflect inter-neuronal spike timing differences. SpikeShip can be effectively computed for high-dimensional neuronal ensembles, has a low (linear) computational cost that has the same order as the spike count, and is sensitive to higher-order correlations. Furthermore SpikeShip is binless, can handle any form of spike time distributions, is not affected by firing rate fluctuations, can detect patterns with a low signal-to-noise ratio, and can be effectively combined with a sliding window approach. We compare the advantages and differences between SpikeShip and other measures like SPIKE and Victor-P urpura distance. We applied SpikeShip to large-scale Neuropixel recordings during spontaneous activity and visual encoding. We show that high-dimensional spiking sequences detected via SpikeShip reliably distinguish between different natural images and different behavioral states. These spiking sequences carried complementary information to conventional firing rate codes. SpikeShip opens new avenues for studying neural coding and memory consolidation by rapid and unsupervised detection of temporal spiking patterns in high-dimensional neural ensembles.
The multistep PROTAC (PROteolysis TArgeting Chimeras) degradation process poses challenges for their rational development, as rate limiting steps determining PROTAC efficiency remain largely unknown. Moreover, the slow throughput of currently used endpoint assays does not allow the comprehensive analysis of larger series of PROTACs. Here we developed cell-based assays using NanoLuciferase and HaloTags, that allow measuring PROTAC induced degradation and ternary complex formation kinetics and stability in cells. Using PROTACs developed for degradation of WDR5, the characterization of the mode of action of these PROTACs in the early degradation cascade revealed a key role of ternary complex formation and stability. Comparing a series of ternary complex crystal structures highlighted the importance of an efficient E3-target interface for ternary complex stability. The developed assays outline a strategy for the rational optimization of PROTACs using a series of live cell assays monitoring key steps of the early PROTAC induced degradation pathway.
Significance The multistep PROTAC induced degradation process of a POI poses a significant challenge for the rational design of these bifunctional small molecules as critical steps that limit PROTAC efficacy cannot be easily assayed at required throughput. In addition, the cellular location of the POI may pose additional challenges as some cellular compartments, such as the nucleus, may not be easily reached by PROTAC molecules and the targeted E3 ligases may not be present in this cellular compartment. We propose therefore a comprehensive assay panel for PROTACs evaluation in cellular environments using a sensor system that allows continuous monitoring of the protein levels of the endogenous POI. We developed a cell line expressing WDR5 from its endogenous locus in fusion with a small sequence tag (HiBIT) that can be reconstituted to functional NanoLuciferase (NLuc). This system allowed continuous monitoring of endogenous WDR5 levels in cells and together with HaloTag system also the continuous monitoring of ternary complex (E3, WDR5 and PROTAC) formation. As this assay can be run at high throughput, we used this versatile system monitoring three diverse chemical series of WDR5 PROTACs that markedly differ in their degradation properties. Monitoring cell penetration, binary complex formation (PROTAC-WDR5 and PROTAC-VHL) as well as ternary complex formation we found that PROTAC efficiency highly correlated with synergy of ternary complex formation in cells. This study represents a first data set on diverse PROTACs studying this property in cellulo and it outlines a strategy for the rational optimization of PROTACs. It also provided kinetic data on ternary complex assembly and dissociation that may serve as a benchmark for future studies utilizing also kinetic properties for PROTAC development. Comparative structural studies revealed larger PROTAC mediated interaction surfaces for PROTACs that efficiently formed ternary complexes highlighting the utility of structure based optimization of PROTAC induced ternary complexes in the development process.
Autophagosome biogenesis requires a localized perturbation of lipid membrane dynamics and a unique protein-lipid conjugate. Autophagy-related (ATG) proteins catalyze this biogenesis on cellular membranes, but the underlying molecular mechanism remains unclear. Focusing on the final step of the protein-lipid conjugation reaction, ATG8/LC3 lipidation, we show how membrane association of the conjugation machinery is organized and fine-tuned at the atomistic level. Amphipathic α-helices in ATG3 proteins (AHATG3) are found to have low hydrophobicity and to be less bulky. Molecular dynamics simulations reveal that AHATG3 regulates the dynamics and accessibility of the thioester bond of the ATG3∼LC3 conjugate to lipids, allowing covalent lipidation of LC3. Live cell imaging shows that the transient membrane association of ATG3 with autophagic membranes is governed by the less bulky- hydrophobic feature of AHATG3. Collectively, the unique properties of AHATG3 facilitate protein- lipid bilayer association leading to the remodeling of the lipid bilayer required for the formation of autophagosomes.
Cyclic di-AMP is the only known essential second messenger in bacteria and archaea, regulating different proteins indispensable for numerous physiological processes. In particular, it controls various potassium and osmolyte transporters involved in osmoregulation. In Bacillus subtilis, the K+/H+ symporter KimA of the KUP family is inactivated by c-di-AMP. KimA sustains survival at potassium limitation at low external pH by mediating K+ ions uptake. However, at elevated intracellular K+ concentrations, further K+ accumulation would be toxic. In this study, we reveal the molecular basis of how c-di-AMP binding inhibits KimA. We report cryo-EM structures of KimA with bound c-di-AMP in detergent solution and reconstituted in amphipols. By combining structural data with functional assays and molecular dynamics simulations we reveal how c-di-AMP modulates transport. We show that an intracellular loop in the transmembrane domain interacts with c-di-AMP bound to the adjacent cytosolic domain. This reduces the mobility of transmembrane helices at the cytosolic side of the K+ binding site and therefore traps KimA in an inward-occluded conformation.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in three common awake marmosets and investigated to what extent event-related-potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesize that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we show that attention enhances the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Attentional enhancement of stimulus decodability from population responses occurs in low dimensional spaces, as revealed by principal component analysis, suggesting an alignment between the attentional and the natural stimulus variance. Moreover, natural scenes produce stimulus-specific oscillatory responses in V1, whose power undergoes a global shift from low to high frequencies with attention. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
Glioblastoma is a very aggressive tumor and represents the most common primary brain malignancy. Key characteristics include its high resistance against conventional treatments, such as radio- and chemotherapy and its diffuse tissue infiltration, preventing complete surgical resection. The analysis of migration and invasion processes in a physiological microenvironment allows for enhanced understanding of these processes and can lead to improved therapeutic approaches. Here, we combine two state-of-the-art techniques, adult organotypic brain tissue slice culture (OTC) and light sheet fluorescence microscopy (LSFM) of cleared tissues in a combined method termed OTCxLSFM. Using this methodology, we can show that glioblastoma tissue infiltration can be effectively blocked through treatment with arsenic trioxide, as well as genetic depletion of the tetraspanin, transmembrane receptor CD9. With our analysis-pipeline we gain single-cell level, three-dimensional information, as well as insights into the morphological appearance of the tumor cells.
VASP is a member of the Enabled/VASP protein family that is involved in cortical actin dynamics and may also contribute to the formation of gap junctions. In vessels, gap junctional coupling allows the transfer of signals along the vessel wall and coordinates vascular behavior. Moreover, VASP is reportedly a mediator of NO-induced inhibition of platelet aggregation. Therefore, we hypothesized that VASP exerts also important physiologic functions in arterioles. We examined the spread of vasodilations enabled by gap junctional coupling in endothelial cells as well as NO-induced arteriolar dilations in VASP-deficient mice by intravital microscopy of the microcirculation in a skeletal muscle in anesthetized mice. Conducted dilations were initiated by brief, locally confined stimulation of the arterioles with acetylcholine. The maximal diameters of the arterioles under study ranged from 30 to 40 μm. Brief stimulation with acetylcholine induced a short dilation at the local site that was also observed at remote, upstream sites without an attenuation of the amplitude up to a distance of 1.2 mm in control animals (wild-type). In contrast, remote dilations were reduced in VASP-deficient mice despite a similar local dilation indicating an impairment of conducted dilations. Superfusion of NOdonors induced a concentration-dependent dilation in wild-type mice. However, these dilations were slightly reduced in VASP-deficient animals. In contrast, dilations induced by the endothelial stimulator acetylcholine were fully preserved in VASP-deficient mice. In summary, this study suggests that VASP exerts critical functions in arteriolar diameter control. It is crucial for the conduction of dilator signals along the endothelial cell layer. The impairment possibly reflects a perturbed formation of gap junctions in the endothelial cell membrane. VASP also participates in the full dilatory potential of NOdonors although the effect of its deficiency is only subtle. In contrast, VASP is not required for dilations initiated by endothelial stimulation which are mediated in the murine microcirculation by an EDH-mechanism.
Rhythmic flicker stimulation has gained interest as a treatment for neurodegenerative diseases and a method for frequency tagging neural activity in human EEG/MEG recordings. Yet, little is known about the way in which flicker-induced synchronization propagates across cortical levels and impacts different cell types. Here, we used Neuropixels to simultaneously record from LGN, V1, and CA1 while presenting visual flicker stimuli at different frequencies. LGN neurons showed strong phase locking up to 40Hz, whereas phase locking was substantially weaker in V1 units and absent in CA1 units. Laminar analyses revealed an attenuation of phase locking at 40Hz for each processing stage, with substantially weaker phase locking in the superficial layers of V1. Gamma-rhythmic flicker predominantly entrained fast-spiking interneurons. Optotagging experiments showed that these neurons correspond to either PV+ or narrow-waveform Sst+ neurons. A computational model could explain the observed differences in phase locking based on the neurons’ capacitative low-pass filtering properties. In summary, the propagation of synchronized activity and its effect on distinct cell types strongly depend on its frequency.