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We use the quantum null energy condition in strongly coupled two-dimensional field theories (QNEC2) as diagnostic tool to study a variety of phase structures, including crossover, second and first order phase transitions. We find a universal QNEC2 constraint for first order phase transitions with kinked entanglement entropy and discuss in general the relation between the QNEC2-inequality and monotonicity of the Casini-Huerta c-function. We then focus on a specific example, the holographic dual of which is modelled by three-dimensional Einstein gravity plus a massive scalar field with one free parameter in the self-interaction potential. We study translation invariant stationary states dual to domain walls and black branes. Depending on the value of the free parameter we find crossover, second and first order phase transitions between such states, and the c-function either flows to zero or to a finite value in the infrared. We present evidence that evaluating QNEC2 for ground state solutions allows to predict the existence of phase transitions at finite temperature.
Holography has provided valuable insights into the time evolution of strongly coupled gauge theories in a fixed spacetime. However, this framework is insufficient if this spacetime is dynamical. We present a scheme to evolve a four-dimensional, strongly interacting gauge theory coupled to four-dimensional dynamical gravity in the semiclassical regime. As in previous work, we use holography to evolve the quantum gauge theory stress tensor, whereas the four-dimensional metric evolves according to Einstein’s equations coupled to the expectation value of the stress tensor. The novelty of our approach is that both the boundary and the bulk spacetimes are constructed dynamically, one time step at a time. We focus on Friedmann-Lemaître-Robertson-Walker geometries and evolve far-from-equilibrium initial states that lead to asymptotically expanding, flat or collapsing Universes.
According to the inflationary theory of cosmology, most elementary particles in the current Universe were created during a period of reheating after inflation. In this Letter, we self-consistently couple the Einstein-inflaton equations to a strongly coupled quantum field theory as described by holography. We show that this leads to an inflating universe, a reheating phase, and finally a universe dominated by the quantum field theory in thermal equilibrium.
Using full 3+1 dimensional general-relativistic hydrodynamic simulations of equal- and unequal-mass neutron-star binaries with properties that are consistent with those inferred from the inspiral of GW170817, we perform a detailed study of the quark-formation processes that could take place after merger. We use three equations of state consistent with current pulsar observations derived from a novel finite-temperature framework based on V-QCD, a non-perturbative gauge/gravity model for Quantum Chromodynamics. In this way, we identify three different post-merger stages at which mixed baryonic and quark matter, as well as pure quark matter, are generated. A phase transition triggered collapse already ≲ 10 ms after the merger reveals that the softest version of our equations of state is actually inconsistent with the expected second-long post-merger lifetime of GW170817. Our results underline the impact that gravitational wave observations of binary neutron-star mergers can have in constraining the equation of state of nuclear matter, especially in its most extreme regimes.
We present a novel framework for the equation of state of dense and hot quantum chromodynamics (QCD), which focuses on the region of the phase diagram relevant for neutron star mergers and core-collapse supernovae. The model combines predictions from the gauge/gravity duality with input from lattice field theory, QCD perturbation theory, chiral effective theory, and statistical modeling. It is therefore, by construction, in good agreement with theoretical constraints both at low and high densities and temperatures. The main ingredients of our setup are the nonperturbative V-QCD model based on the gauge/gravity duality, a van der Waals model for nucleon liquid, and the DD2 version of the Hempel-Schaffner-Bielich statistical model of nuclear matter. By consistently combining these models, we also obtain a description for the nuclear to quark matter phase transition and its critical end point. The parameter dependence of the model is represented by three (soft, intermediate, and stiff) variants of the equation of state, all of which agree with observational constraints from neutron stars and their mergers. We discuss resulting constraints for the equation of state, predictions for neutron stars, and the location of the critical point.
Biological as well as advanced artificial intelligences (AIs) need to decide which goals to pursue. We review nature's solution to the time allocation problem, which is based on a continuously readjusted categorical weighting mechanism we experience introspectively as emotions. One observes phylogenetically that the available number of emotional states increases hand in hand with the cognitive capabilities of animals and that raising levels of intelligence entail ever larger sets of behavioral options. Our ability to experience a multitude of potentially conflicting feelings is in this view not a leftover of a more primitive heritage, but a generic mechanism for attributing values to behavioral options that can not be specified at birth. In this view, emotions are essential for understanding the mind. For concreteness, we propose and discuss a framework which mimics emotions on a functional level. Based on time allocation via emotional stationarity (TAES), emotions are implemented as abstract criteria, such as satisfaction, challenge and boredom, which serve to evaluate activities that have been carried out. The resulting timeline of experienced emotions is compared with the “character” of the agent, which is defined in terms of a preferred distribution of emotional states. The long-term goal of the agent, to align experience with character, is achieved by optimizing the frequency for selecting individual tasks. Upon optimization, the statistics of emotion experience becomes stationary.
We analyzed a eukaryotically encoded rubredoxin from the cryptomonad Guillardia theta and identified additional domains at the N- and C-termini in comparison to known prokaryotic paralogous molecules. The cryptophytic N-terminal extension was shown to be a transit peptide for intracellular targeting of the protein to the plastid, whereas a C-terminal domain represents a membrane anchor. Rubredoxin was identified in all tested phototrophic eukaryotes. Presumably facilitated by its C-terminal extension, nucleomorph-encoded rubredoxin (nmRub) is associated with the thylakoid membrane. Association with photosystem II (PSII) was demonstrated by co-localization of nmRub and PSII membrane particles and PSII core complexes and confirmed by comparative electron paramagnetic resonance measurements. The midpoint potential of nmRub was determined as +125 mV, which is the highest redox potential of all known rubredoxins. Therefore, nmRub provides a striking example of the ability of the protein environment to tune the redox potentials of metal sites, allowing for evolutionary adaption in specific electron transport systems, as for example that coupled to the PSII pathway.
IHMCIF: an extension of the PDBx/mmCIF data standard for integrative structure determination methods
(2024)
IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.
Highlights
• Sampling the large conformational space of disordered proteins requires extensive molecular dynamics (MD) simulations.
• Fragment assembly complements MD simulations to produce extensive ensembles of disordered proteins with atomic detail.
• Hierarchical chain growth (HCG) ensembles capture key experimental descriptors “out of the box”.
• HCG has revealed local structural characteristics associated with protein dysfunction in neurodegeneration.
Abstract
Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.
Substantial progress in the field of neuroscience has been made from anaesthetized preparations. Ketamine is one of the most used drugs in electrophysiology studies, but how ketamine affects neuronal responses is poorly understood. Here, we used in vivo electrophysiology and computational modelling to study how the auditory cortex of bats responds to vocalisations under anaesthesia and in wakefulness. In wakefulness, acoustic context increases neuronal discrimination of natural sounds. Neuron models predicted that ketamine affects the contextual discrimination of sounds regardless of the type of context heard by the animals (echolocation or communication sounds). However, empirical evidence showed that the predicted effect of ketamine occurs only if the acoustic context consists of low-pitched sounds (e.g., communication calls in bats). Using the empirical data, we updated the naïve models to show that differential effects of ketamine on cortical responses can be mediated by unbalanced changes in the firing rate of feedforward inputs to cortex, and changes in the depression of thalamo-cortical synaptic receptors. Combined, our findings obtained in vivo and in silico reveal the effects and mechanisms by which ketamine affects cortical responses to vocalisations.