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Institute
The phase diagram of the (1+1)-dimensional Gross-Neveu model is reanalyzed for (non-)zero chemical potential and (non-)zero temperature within the mean-field approximation. By investigating the momentum dependence of the bosonic two-point function, the well-known second-order phase transition from the Z2 symmetric phase to the so-called inhomogeneous phase is detected. In the latter phase the chiral condensate is periodically varying in space and translational invariance is broken. This work is a proof of concept study that confirms that it is possible to correctly localize second-order phase transition lines between phases without condensation and phases of spatially inhomogeneous condensation via a stability analysis of the homogeneous phase. To complement other works relying on this technique, the stability analysis is explained in detail and its limitations and successes are discussed in context of the Gross-Neveu model. Additionally, we present explicit results for the bosonic wave-function renormalization in the mean-field approximation, which is extracted analytically from the bosonic two-point function. We find regions -- a so-called moat regime -- where the wave function renormalization is negative accompanying the inhomogeneous phase as expected.
The phase diagram of the (1+1)-dimensional Gross-Neveu model is reanalyzed for (non-)zero chemical potential and (non-)zero temperature within the mean-field approximation. By investigating the momentum dependence of the bosonic two-point function, the well-known second-order phase transition from the Z2 symmetric phase to the so-called inhomogeneous phase is detected. In the latter phase the chiral condensate is periodically varying in space and translational invariance is broken. This work is a proof of concept study that confirms that it is possible to correctly localize second-order phase transition lines between phases without condensation and phases of spatially inhomogeneous condensation via a stability analysis of the homogeneous phase. To complement other works relying on this technique, the stability analysis is explained in detail and its limitations and successes are discussed in context of the Gross-Neveu model. Additionally, we present explicit results for the bosonic wave-function renormalization in the mean-field approximation, which is extracted analytically from the bosonic two-point function. We find regions -- a so-called moat regime -- where the wave function renormalization is negative accompanying the inhomogeneous phase as expected.
We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.
The most precise measurements to date of the 3ΛH lifetime τ and Λ separation energy BΛ are obtained using the data sample of Pb-Pb collisions at √sNN = 5.02 TeV collected by ALICE at the LHC. The 3ΛH is reconstructed via its charged two-body mesonic decay channel (3ΛH→ 3He + π− and the charge-conjugate process). The measured values τ=[253±11 (stat.)±6 (syst.)] ps and BΛ=[72±63 (stat.)±36 (syst.)] keV are compatible with predictions from effective field theories and conclusively confirm that the 3ΛH is a weakly-bound system.
The most precise measurements to date of the 3ΛH lifetime τ and Λ separation energy BΛ are obtained using the data sample of Pb-Pb collisions at √sNN = 5.02 TeV collected by ALICE at the LHC. The 3ΛH is reconstructed via its charged two-body mesonic decay channel (3ΛH→ 3He + π− and the charge-conjugate process). The measured values τ=[253±11 (stat.)±6 (syst.)] ps and BΛ=[72±63 (stat.)±35 (syst.)] keV are compatible with predictions from effective field theories and conclusively confirm that the 3ΛH is a weakly-bound system.
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.
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.
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.
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.