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Strain-free GaAs/AlGaAs semiconductor quantum dots (QDs) grown by droplet etching and nanohole infilling (DENI) are highly promising candidates for the on-demand generation of indistinguishable and entangled photon sources. The spectroscopic fingerprint and quantum optical properties of QDs are significantly influenced by their morphology. The effects of nanohole geometry and infilled material on the exciton binding energies and fine structure splitting are well-understood. However, a comprehensive understanding of GaAs/AlGaAs QD morphology remains elusive. To address this, we employ high-resolution scanning transmission electron microscopy (STEM) and reverse engineering through selective chemical etching and atomic force microscopy (AFM). Cross-sectional STEM of uncapped QDs reveals an inverted conical nanohole with Al-rich sidewalls and defect-free interfaces. Subsequent selective chemical etching and AFM measurements further reveal asymmetries in element distribution. This study enhances the understanding of DENI QD morphology and provides a fundamental three-dimensional structural model for simulating and optimizing their optoelectronic properties.

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model that does not reproduce the true dynamical behavior of the underlying molecule. Here, we present Bartender, a quantum mechanics (QM)/MD-based parametrization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing numerically stable and physically realistic CG models.

Sepsis-associated encephalopathy (SAE) is a frequent complication of severe systemic infection resulting in delirium, premature death, and long-term cognitive impairment. We closely mimicked SAE in a murine peritoneal contamination and infection (PCI) model. We found long-lasting synaptic pathology in the hippocampus including defective long-term synaptic plasticity, reduction of mature neuronal dendritic spines, and severely affected excitatory neurotransmission. Genes related to synaptic signaling, including the gene for activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) and members of the transcription-regulatory EGR gene family, were downregulated. At the protein level, ARC expression and mitogen-activated protein kinase signaling in the brain were affected. For targeted rescue we used adeno-associated virus-mediated overexpression of ARC in the hippocampus in vivo. This recovered defective synaptic plasticity and improved memory dysfunction. Using the enriched environment paradigm as a non-invasive rescue intervention, we found improvement of defective long-term potentiation, memory, and anxiety. The beneficial effects of an enriched environment were accompanied by an increase in brain-derived neurotrophic factor (BDNF) and ARC expression in the hippocampus, suggesting that activation of the BDNF-TrkB pathway leads to restoration of the PCI-induced reduction of ARC. Collectively, our findings identify synaptic pathomechanisms underlying SAE and provide a conceptual approach to target SAE-induced synaptic dysfunction with potential therapeutic applications to patients with SAE., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)