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From fibril to framework: P. abyssi AbpX illuminates a calcium-responsive family of microbial biomatrix proteins that form thermostable hydrogels
No full textEvolutionary pressure on microbial communities propagating under extreme environmental conditions often results in unique structural adaptations to promote cell survival. Here, we report an investigation of AbpX, a biomatrix protein identified in cultures of the hyperthermophilic archaeon Pyrodictium abyssi. Under ex vivo and in vitro conditions, AbpX assembles into a para-crystalline lattice composed of semiflexible fibrils. CryoEM analysis of recombinant AbpX fibrils reveals that the precursor protein polymerizes through donor strand complementation (DSC), a process previously reported for chaperone-usher fimbriae in Gram-negative bacteria. Unlike the latter DSC protein polymers, AbpX undergoes chaperone-free polymerization in the presence of calcium ions, which are sequestered at the donor strand-acceptor groove interface between protomers in the fibril. Using a combination of cryoEM and crystallographic structural information, an atomic model is proposed for the AbpX lattice that provides insight into its potential role in biofilm formation. These findings suggest that calcium ion coordination triggers fibril assembly and pre-organizes the fibrils for incorporation into the protein lattice. Bioinformatic analysis indicates that AbpX exemplifies a distinct and broadly distributed clade of calcium ion responsive biomatrix proteins within the TasA superfamily that can be fabricated into hydrogel biomaterials in vitro under environmentally benign conditions
Sleep-dependent infraslow rhythms are evolutionarily conserved across reptiles and mammals
No full textBodily rhythms and the Brain: Critical links to cognition in health and disease. Comment on ‘A body-brain (dis)equilibrium regulating transitions from health to pathology’ by Antonio Criscuolo, Anna Czepiel, Michael Schwartze and Sonja A. Kotz
No full textCavity-QED-controlled two-dimensional Moiré excitons without twisting
No full textWe propose an all-optical Moiré-like exciton confinement by means of spatially periodic optical cavities. Such periodic photonic structures can control the material properties by coupling the matter excitations to the confined photons and their quantum fluctuations. We develop a low energy non-perturbative quantum electro-dynamical description of strongly coupled excitons and photons at finite momentum transfer. We find that in the classical limit of a laser driven cavity the induced optical confinement directly emulates Moiré physics. In a dark cavity instead, the sole presence of quantum fluctuations of light generates a sizable renormalization of the excitonic bands and effective mass. We attribute these effects to long-range cavity-mediated exciton-exciton interactions which can only be captured in a non-perturbative treatment. With these findings we propose spatially structured cavities as a promising avenue for cavity material engineering
Discorditarianism: a new paradigm for geological interpretation
No full textIntroduction Limitations of uniformitarianism Introduction discorditarianis
Inhibitory effect of low-voltage electrostatic field on postharvest black spot development in cauliflower
No full textPostharvest cauliflower rapidly deteriorates, typically exhibiting yellowing, tissue softening, off-flavor development, and black spot decay. effectively delayed quality loss and inhibited decay-associated microorganisms. LVEF reduced black spot formation and sensory degradation by limiting carbohydrate and amino acid catabolism and by modulating energy metabolism. Moreover, LVEF regulated the biosynthesis of aromatic and sulfur-containing amino acids and glucosinolates, thereby suppressing unpleasant odors and preserving cauliflower flavor up to 8 days postharvest. The treatment enhanced curd antioxidant capacity by preventing reactive oxygen species (ROS) bursts and promoting scavenging activity. Molecularly, LVEF altered the expression of genes involved in starch and sucrose metabolism (sucrose synthase, β-glucosidase, β-fructofuranosidase), the TCA cycle (malate dehydrogenase, citrate synthase, ATP citrate lyase, aconitate hydratase), and oxidative phosphorylation (V-type ATPase subunit D-like, ATPase 2, plasma membrane-type-like), thereby stabilizing postharvest energy metabolism. Microbial suppression correlated mainly with changes in vitamin C, polyphenols, flavonoids, and lipid contents. This study presents the first integrated transcriptomic, metabolomic, and metagenomic analysis, revealing that a LVEF extends the postharvest preservation of cauliflower by synergistically activating host defense-related metabolic pathways and suppressing the proliferation of surface spoilage microorganisms, thereby reducing black spot incidence and delaying senescence
Topology-informed graph transformer
No full textTransformers have revolutionized performance in Natural Language Processing and Vision, paving the way for their integration with Graph Neural Networks (GNNs). One key challenge in enhancing graph transformers is strengthening the discriminative power of distinguishing isomorphisms of graphs, which plays a crucial role in boosting their predictive performances. To address this challenge, we introduce 'Topology-Informed Graph Transformer (TIGT)', a novel transformer enhancing both discriminative power in detecting graph isomorphisms and the overall performance of Graph Transformers. TIGT consists of four components: A topological positional embedding layer using non-isomorphic universal covers based on cyclic subgraphs of graphs to ensure unique graph representation: A dual-path message-passing layer to explicitly encode topological characteristics throughout the encoder layers: A global attention mechanism: And a graph information layer to recalibrate channel-wise graph features for better feature representation. TIGT outperforms previous Graph Transformers in classifying synthetic dataset aimed at distinguishing isomorphism classes of graphs. Additionally, mathematical analysis and empirical evaluations highlight our model's competitive edge over state-of-the-art Graph Transformers across various benchmark datasets
