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Mitochondria are dynamic organelles exhibiting diverse shapes. While the variation of shapes, ranging from spheres to elongated tubules, and the transition between them, are clearly seen in many cell types, the molecular mechanisms governing this morphological variability remain poorly understood. Here, we propose a novel shaping mechanism based on the interplay between the inner and outer mitochondrial membranes. Our biophysical model suggests that the difference in surface area, arising from the pulling of the inner membrane into cristae, correlates with mitochondrial elongation. Analysis of live cell super-resolution microscopy data supports this correlation, linking elongated shapes to the extent of cristae in the inner membrane. Knocking down cristae shaping proteins further confirms the impact on mitochondrial shape, demonstrating that defects in cristae formation correlate with mitochondrial sphericity. Our results suggest that the dynamics of the inner mitochondrial membrane are important not only for simply creating surface area required for respiratory capacity, but go beyond that to affect the whole organelle morphology. This work explores the biophysical foundations of individual mitochondrial shape, suggesting potential links between mitochondrial structure and function. This should be of profound significance, particularly in the context of disrupted cristae shaping proteins and their implications in mitochondrial diseases.
Dark matter could accumulate around neutron stars in sufficient amounts to affect their global properties. In this work, we study the effect of a specific model for dark matter -- a massive and self-interacting vector (spin-1) field -- on neutron stars. We describe the combined systems of neutron stars and vector dark matter using Einstein-Proca theory coupled to a nuclear-matter term, and find scaling relations between the field and metric components in the equations of motion. We construct equilibrium solutions of the combined systems, compute their masses and radii and also analyse their stability and higher modes. The combined systems admit dark matter (DM) core and cloud solutions. Core solutions compactify the neutron star component and tend to decrease the total mass of the combined system. Cloud solutions have the inverse effect. Electromagnetic observations of certain cloud-like configurations would appear to violate the Buchdahl limit. This could make Buchdahl-limit violating objects smoking gun signals for dark matter in neutron stars. The self-interaction strength is found to significantly affect both mass and radius. We also compare fermion Proca stars to objects where the dark matter is modelled using a complex scalar field. We find that fermion Proca stars tend to be more massive and geometrically larger than their scalar field counterparts for equal boson masses and self-interaction strengths. Both systems can produce degenerate masses and radii for different amounts of DM and DM particle masses.
Echolocating bats exhibit remarkable auditory behaviors, enabled by adaptations within and outside their auditory system. Yet, research in echolocating bats has focused mostly on brain areas that belong to the classic ascending auditory pathway. This study provides direct evidence linking the cerebellum, an evolutionarily ancient and non-classic auditory structure, to vocalization and hearing. We report that in the fruit-eating bat Carollia perspicillata, external sounds can evoke cerebellar responses with latencies below 20 ms. Such fast responses are indicative of early inputs to the bat cerebellum. In vocalizing bats, distinct spike train patterns allow the prediction with over 85% accuracy of the sound they are about to produce, or have just produced, i.e., communication calls or echolocation pulses. Taken together, our findings provide evidence of specializations for vocalization and hearing in the cerebellum of an auditory specialist.
Using limit linear series on chains of curves, we show that closures of certain Brill-Noether loci contain a product of pointed Brill-Noether loci of small codimension. As a result, we obtain new non-containments of Brill-Noether loci, in particular that dimensionally expected non-containments hold for expected maximal Brill-Noether loci. Using these degenerations, we also give a new proof that Brill-Noether loci with expected codimension −ρ≤⌈g/2⌉ have a component of the expected dimension. Additionally, we obtain new non-containments of Brill-Noether loci by considering the locus of the source curves of unramified double covers.
Antimatter is a research topic of fundamental interest. Sufficient matter-antimatter asymmetry in the early Universe created the matter-dominated world today. The origin of this asymmetry is not completely understood to date. High-energy nuclear collisions create conditions similar to the Universe microseconds after the Big Bang, with comparable amounts of matter and antimatter. Much of the antimatter created escapes the rapidly expanding fireball without annihilation, making such collisions an effective experimental tool to create heavy antimatter nuclear objects and study their properties. In this paper, we report the first observation of the antimatter hypernucleus 4Λ¯H¯¯¯¯, composed of an Λ¯, an antiproton and two antineutrons. The discovery was made through its two-body decay after production in ultrarelativistic heavy-ion collisions by the STAR experiment at the Relativistic Heavy Ion Collider. In total, 15.6 candidate 4Λ¯H¯¯¯¯ antimatter hypernuclei are obtained with an estimated background count of 6.4. Lifetimes of the antihypernuclei 3Λ¯H¯¯¯¯ and 4Λ¯H¯¯¯¯ are measured and compared with the lifetimes of their corresponding hypernuclei, testing the symmetry between matter and antimatter. Various production yield ratios among (anti)hypernuclei and (anti)nuclei are also measured and compared with theoretical model predictions, shedding light on their production mechanism.
With the STAR experiment at RHIC, we characterize √sNN = 200 GeV p+Au collisions by event activity (EA) measured within the pseudorapidity range η∈[−5,−3.4] in the Au-going direction and report correlations between this EA and hard- and soft-scale particle production at mid-rapidity (η∈[−1,1]). At the soft scale, charged particle production in low-EA p+Au collisions is comparable to that in \pp collisions and increases monotonically with increasing EA. At the hard scale, we report measurements of high transverse momentum (pT) jets in events of different EAs. In contrast to the soft particle production, high-pT particle production and EA are found to be inversely related. To investigate whether this is a signal of jet quenching in high-EA events, we also report ratios of pT imbalance and azimuthal separation of dijets in high- and low-EA events. Within our measurement precision, no significant differences are observed, disfavoring the presence of jet quenching in the highest 30% EA p+Au collisions at √sNN = 200 GeV.
Motivated by recently reported magnetic-field induced topological phases in ultracold atoms and correlated Moiré materials, we investigate topological phase transitions in a minimal model consisting of interacting spinless fermions described by the Hofstadter model on a square lattice. For interacting lattice Hamiltonians in the presence of a commensurate magnetic flux it has been demonstrated that the quantized Hall conductivity is constrained by a Lieb-Schultz-Mattis (LSM)-type theorem due to magnetic translation symmetry. In this work, we revisit the validity of the theorem for such models and establish that a topological phase transition from a topological to a trivial insulating phase can be realized but must be accompanied by spontaneous magnetic translation symmetry breaking caused by charge ordering of the spinless fermions. To support our findings, the topological phase diagram for varying interaction strength is mapped out numerically with exact diagonalization for different flux quantum ratios and band fillings using symmetry indicators. We discuss our results in the context of the LSM-type theorem.
We search for the di-photon decay of a light pseudoscalar axion-like particle, a, in radiative J/ψ decays, using 10 billion J/ψ events collected with the BESIII detector. We find no evidence of a signal and set upper limits at the 95% confidence level on the product branching fraction B(J/ψ→γa)×B(a→γγ) and the axion-like particle photon coupling constant gaγγ in the ranges of (3.7−48.5)×10−8 and (2.2−101.8)×10−4 GeV−1, respectively, for 0.18≤ma≤2.85 GeV/c2. These are the most stringent limits to date in this mass region.
Correlative dynamic imaging of cellular landmarks, such as nuclei and nucleoli, cell membranes, nuclear envelope and lipid droplets is critical for systems cell biology and drug discovery, but challenging to achieve with molecular labels. Virtual staining of label-free images with deep neural networks is an emerging solution for correlative dynamic imaging. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining leaves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Current approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. We report training protocols for virtual staining of nuclei and membranes robust to variations in imaging parameters, cell states, and cell types. We describe a flexible and scalable convolutional architecture, UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including human cell lines, neuromasts of zebrafish and stem cell (iPSC)-derived neurons, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and cell membranes. The models rescue missing labels, non-uniform expression of labels, and photobleaching. We share three pre-trained models (VSCyto3D, VSNeuromast, and VSCyto2D) and a PyTorch-based pipeline (VisCy) for training, inference, and deployment that leverages current community standards for image data and metadata.