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In this work, inhomogeneous chiral phases are studied in a variety of Four-Fermion and Yukawa models in 2+1 dimensions at zero and non-zero temperature and chemical potentials. Employing the mean-field approximation, we do not find indications for an inhomogeneous phase in any of the studied models. We show that the homogeneous phases are stable against inhomogeneous perturbations. At zero temperature, full analytic results are presented.
Gasdermin-D (GSDMD) is the ultimate effector of pyroptosis, a form of programmed cell death associated with pathogen invasion and inflammation. After proteolytic cleavage by caspases activated by the inflammasome, the GSDMD N-terminal domain (GSDMDNT) assembles on the inner leaflet of the plasma membrane and induces the formation of large membrane pores. We use atomistic molecular dynamics simulations to study GSDMDNT monomers, oligomers, and rings in an asymmetric plasma membrane mimetic. We identify distinct interaction motifs of GSDMDNT with phosphatidylinositol-4,5-bisphosphate (PI(4,5)P2) and phosphatidylserine (PS) head-groups and describe differential lipid binding between the pore and prepore conformations. Oligomers are stabilized by shared lipid binding sites between neighboring monomers acting akin to double-sided tape. We show that already small GSDMDNT oligomers form stable, water-filled and ion-conducting membrane pores bounded by curled beta-sheets. In large-scale simulations, we resolve the process of pore formation by lipid detachment from GSDMDNT arcs and lipid efflux from partial rings. We find that that high-order GSDMDNT oligomers can crack under the line tension of 86 pN created by an open membrane edge to form the slit pores or closed GSDMDNT rings seen in experiment. Our simulations provide a detailed view of key steps in GSDMDNT-induced plasma membrane pore formation, including sublytic pores that explain nonselective ion flux during early pyroptosis.
Intrinsically disordered regions (IDRs) are essential for membrane receptor regulation but often remain unresolved in structural studies. TRPV4, a member of the TRP vanilloid channel family involved in thermo- and osmosensation, has a large N-terminal IDR of approximately 150 amino acids. With an integrated structural biology approach, we analyze the structural ensemble of the TRPV4 IDR and identify a network of regulatory elements that modulate channel activity in a hierarchical lipid-dependent manner through transient long-range interactions. A highly conserved autoinhibitory patch acts as a master regulator by competing with PIP2 binding to attenuate channel activity. Molecular dynamics simulations show that loss of the interaction between the PIP2-binding site and the membrane reduces the force exerted by the IDR on the structured core of TRPV4. This work demonstrates that IDR structural dynamics are coupled to TRPV4 activity and highlights the importance of IDRs for TRP channel function and regulation.
The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown. Here, we generated large stochastic populations of biophysically realistic hippocampal granule cell models comparing those with all 15 ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were more frequent and more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve target excitability.
We report about the properties of the underlying event measured with ALICE at the LHC in pp and p−Pb collisions at sNN−−−√=5.02 TeV. The event activity, quantified by charged-particle number and summed-pT densities, is measured as a function of the leading-particle transverse momentum (ptrigT). These quantities are studied in three azimuthal-angle regions relative to the leading particle in the event: toward, away, and transverse. Results are presented for three different pT thresholds (0.15, 0.5, and 1 GeV/c) at mid-pseudorapidity (|η|<0.8). The event activity in the transverse region, which is the most sensitive to the underlying event, exhibits similar behaviour in both pp and p−Pb collisions, namely, a steep increase with ptrigT for low ptrigT, followed by a saturation at ptrigT≈5 GeV/c. The results from pp collisions are compared with existing measurements at other centre-of-mass energies. The quantities in the toward and away regions are also analyzed after the subtraction of the contribution measured in the transverse region. The remaining jet-like particle densities are consistent in pp and p−Pb collisions for ptrigT>10 GeV/c, whereas for lower ptrigT values the event activity is slightly higher in p−Pb than in pp collisions. The measurements are compared with predictions from the PYTHIA 8 and EPOS LHC Monte Carlo event generators.
We demonstrate ultra-sharp (≲10 nm) lateral p-n junctions in graphene using electronic transport, scanning tunneling microscopy, and first principles calculations. The p-n junction lies at the boundary between differentially-doped regions of a graphene sheet, where one side is intrinsic and the other is charge-doped by proximity to a flake of α-RuCl3 across a thin insulating barrier. We extract the p-n junction contribution to the device resistance to place bounds on the junction width. We achieve an ultra-sharp junction when the boundary between the intrinsic and doped regions is defined by a cleaved crystalline edge of α-RuCl3 located 2 nm from the graphene. Scanning tunneling spectroscopy in heterostructures of graphene, hexagonal boron nitride, and α-RuCl3 shows potential variations on a sub-10 nm length scale. First principles calculations reveal the charge-doping of graphene decays sharply over just nanometers from the edge of the α-RuCl3 flake.
Effective spectral functions of the ρ meson are reconstructed by considering the lifetimes inside different media using the hadronic transport SMASH (Simulating Many Accelerated Strongly-interacting Hadrons). Due to inelastic scatterings, resonance lifetimes are dynamically shortened (collisional broadening), even though the employed approach assumes vacuum resonance properties. Analyzing the ρ meson lifetimes allows to quantify an effective broadening of the decay width and spectral function, which is important in order to distinguish dynamical effects from additional genuine medium modifications to the spectral functions, indicating e.g. an onset of chiral symmetry restoration. The broadening of the spectral function in a thermalized system is shown to be consistent with other theoretical calculations. The effective ρ meson spectral function is also presented for the dynamical evolution of heavy-ion collisions, finding a clear correlation of the broadening to system size, which is explained by an observed dependence of the width on the local hadron density. Furthermore, the difference in the results between the thermal system and full collision dynamics is explored, which may point to non-equilibrium effects.
The exploration of hot and dense nuclear matter: Introduction to relativistic heavy-ion physics
(2022)
This article summarizes our present knowledge about nuclear matter at the highest energy densities and its formation in relativistic heavy ion collisions. We review what is known about the structure and properties of the quark-gluon plasma and survey the observables that are used to glean information about it from experimental data.
More than 75% of surface and secreted proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, influencing protein dynamics and interactions with other molecules. Glycan conformational freedom impairs complete structural elucidation of glycoproteins. Computer simulations may be used to model glycan structure and dynamics. However, such simulations typically require thousands of computing hours on specialized supercomputers, thus limiting routine use. Here, we describe a reductionist method that can be implemented on personal computers to graft ensembles of realistic glycan conformers onto static protein structures in a matter of minutes. Using this open-source pipeline, we reconstructed the full glycan cover of SARS-CoV-2 Spike protein (S-protein) and a human GABAA receptor. Focusing on S-protein, we show that GlycoSHIELD recapitulates key features of extended simulations of the glycosylated protein, including epitope masking, and provides new mechanistic insights on N-glycan impact on protein structural dynamics.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.