Arnoldernst9707

By introducing metallic ring structural dipole resonances in the microwave regime, we have designed and realized a metamaterial absorber with hierarchical structures that can display an averaged -19.4 dB reflection loss (∼99% absorption) from 3 to 40 GHz. The measured performance is independent of the polarizations of the incident wave at normal incidence, while absorption at oblique incidence remains considerably effective up to 45°. We provide a conceptual basis for our absorber design based on the capacitive-coupled electrical dipole resonances in the lateral plane, coupled to the standing wave along the incident wave direction. To realize broadband impedance matching, resistive dissipation of the metallic ring is optimally tuned by using the approach of dispersion engineering. To further extend the absorption spectrum to an ultrabroadband range, we employ a double-layer self-similar structure in conjunction with the absorption of the diffracted waves at the higher end of the frequency spectrum. The overall thickness of the final sample is 14.2 mm, only 5% over the theoretical minimum thickness dictated by the causality limit.The development of high-performance photoacoustic (PA) probes that can monitor disease biomarkers in deep tissue has the potential to replace invasive medical procedures such as a biopsy. However, such probes must be optimized for in vivo performance and exhibit an exceptional safety profile. In this study, we have developed PACu-1, a PA probe designed for biopsy-free assessment (BFA) of hepatic Cu via photoacoustic imaging. PACu-1 features a Cu(I)-responsive trigger appended to an aza-BODIPY dye platform that has been optimized for ratiometric sensing. Owing to its excellent performance, we were able to detect basal levels of Cu in healthy wild-type mice as well as elevated Cu in a Wilson's disease model and in a liver metastasis model. To showcase the potential impact of PACu-1 for BFA, we conducted two blind studies in which we were able to successfully identify Wilson's disease animals from healthy control mice in each instance.Type I interferons (IFNs) are critical effectors of emerging cancer immunotherapies designed to activate pattern recognition receptors (PRRs). A challenge in the clinical translation of these agents is the lack of noninvasive pharmacodynamic biomarkers that indicate increased intratumoral IFN signaling following PRR activation. Positron emission tomography (PET) imaging enables the visualization of tissue metabolic activity, but whether IFN signaling-induced alterations in tumor cell metabolism can be detected using PET has not been investigated. We found that IFN signaling augments pancreatic ductal adenocarcinoma (PDAC) cell nucleotide metabolism via transcriptional induction of metabolism-associated genes including thymidine phosphorylase (TYMP). TYMP catalyzes the first step in the catabolism of thymidine, which competitively inhibits intratumoral accumulation of the nucleoside analog PET probe 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT). Accordingly, IFN treatment up-regulates cancer cell [18F]FLT uptake in the presence of thymidine, and this effect is dependent upon TYMP expression. In vivo, genetic activation of stimulator of interferon genes (STING), a PRR highly expressed in PDAC, enhances the [18F]FLT avidity of xenograft tumors. Additionally, small molecule STING agonists trigger IFN signaling-dependent TYMP expression in PDAC cells and increase tumor [18F]FLT uptake in vivo following systemic treatment. These findings indicate that [18F]FLT accumulation in tumors is sensitive to IFN signaling and that [18F]FLT PET may serve as a pharmacodynamic biomarker for STING agonist-based therapies in PDAC and possibly other malignancies characterized by elevated STING expression.Brain microstructure plays a key role in driving the transport of drug molecules directly administered to the brain tissue, as in Convection-Enhanced Delivery procedures. The proposed research analyzes the hydraulic permeability of two white matter (WM) areas (corpus callosum and fornix) whose three-dimensional microstructure was reconstructed starting from the acquisition of electron microscopy images. We cut the two volumes with 20 equally spaced planes distributed along two perpendicular directions, and, on each plane, we computed the corresponding permeability vector. Then, we considered that the WM structure is mainly composed of elongated and parallel axons, and, using a principal component analysis, we defined two principal directions, parallel and perpendicular, with respect to the axons' main direction. The latter were used to define a reference frame onto which the permeability vectors were projected to finally obtain the permeability along the parallel and perpendicular directions. The results show a statistically significant difference between parallel and perpendicular permeability, with a ratio of about two in both the WM structures analyzed, thus demonstrating their anisotropic behavior. Moreover, we find a significant difference between permeability in corpus callosum and fornix, which suggests that the WM heterogeneity should also be considered when modeling drug transport in the brain. Our findings, which demonstrate and quantify the anisotropic and heterogeneous character of the WM, represent a fundamental contribution not only for drug-delivery modeling, but also for shedding light on the interstitial transport mechanisms in the extracellular space.We propose a deep learning-based knockoffs inference framework, DeepLINK, that guarantees the false discovery rate (FDR) control in high-dimensional settings. DeepLINK is applicable to a broad class of covariate distributions described by the possibly nonlinear latent factor models. It consists of two major parts an autoencoder network for the knockoff variable construction and a multilayer perceptron network for feature selection with the FDR control. The empirical performance of DeepLINK is investigated through extensive simulation studies, where it is shown to achieve FDR control in feature selection with both high selection power and high prediction accuracy. We also apply DeepLINK to three real data applications to demonstrate its practical utility.RalA is a small GTPase and a member of the Ras family. This molecular switch is activated downstream of Ras and is widely implicated in tumor formation and growth. Previous work has shown that the ubiquitous Ca2+-sensor calmodulin (CaM) binds to small GTPases such as RalA and K-Ras4B, but a lack of structural information has obscured the functional consequences of these interactions. Here, we have investigated the binding of CaM to RalA and found that CaM interacts exclusively with the C terminus of RalA, which is lipidated with a prenyl group in vivo to aid membrane attachment. Biophysical and structural analyses show that the two RalA membrane-targeting motifs (the prenyl anchor and the polybasic motif) are engaged by distinct lobes of CaM and that CaM binding leads to removal of RalA from its membrane environment. The structure of this complex, along with a biophysical investigation into membrane removal, provides a framework with which to understand how CaM regulates the function of RalA and sheds light on the interaction of CaM with other small GTPases, including K-Ras4B.The O-acetylation of exopolysaccharides, including the essential bacterial cell wall polymer peptidoglycan, confers resistance to their lysis by exogenous hydrolases. Like the enzymes catalyzing the O-acetylation of exopolysaccharides in the Golgi of animals and fungi, peptidoglycan O-acetyltransferase A (OatA) is predicted to be an integral membrane protein comprised of a membrane-spanning acyltransferase-3 (AT-3) domain and an extracytoplasmic domain; for OatA, these domains are located in the N- and C-terminal regions of the enzyme, respectively. The recombinant C-terminal domain (OatAC) has been characterized as an SGNH acetyltransferase, but nothing was known about the function of the N-terminal AT-3 domain (OatAN) or its homologs associated with other acyltransferases. We report herein the experimental determination of the topology of Staphylococcus aureus OatAN, which differs markedly from that predicted in silico. Bak apoptosis We present the biochemical characterization of OatAN as part of recombinant OatA and demonstrate that acetyl-CoA serves as the substrate for OatAN Using in situ and in vitro assays, we characterized 35 engineered OatA variants which identified a catalytic triad of Tyr-His-Glu residues. We trapped an acetyl group from acetyl-CoA on the catalytic Tyr residue that is located on an extracytoplasmic loop of OatAN Further enzymatic characterization revealed that O-acetyl-Tyr represents the substrate for OatAC We propose a model for OatA action involving the translocation of acetyl groups from acetyl-CoA across the cytoplasmic membrane by OatAN and their subsequent intramolecular transfer to OatAC for the O-acetylation of peptidoglycan via the concerted action of catalytic Tyr and Ser residues.Complexity-defined in terms of the number of components and the nature of the interdependencies between them-is clearly a relevant feature of all tasks that groups perform. Yet the role that task complexity plays in determining group performance remains poorly understood, in part because no clear language exists to express complexity in a way that allows for straightforward comparisons across tasks. Here we avoid this analytical difficulty by identifying a class of tasks for which complexity can be varied systematically while keeping all other elements of the task unchanged. We then test the effects of task complexity in a preregistered two-phase experiment in which 1,200 individuals were evaluated on a series of tasks of varying complexity (phase 1) and then randomly assigned to solve similar tasks either in interacting groups or as independent individuals (phase 2). We find that interacting groups are as fast as the fastest individual and more efficient than the most efficient individual for complex tasks but not for simpler ones. Leveraging our highly granular digital data, we define and precisely measure group process losses and synergistic gains and show that the balance between the two switches signs at intermediate values of task complexity. Finally, we find that interacting groups generate more solutions more rapidly and explore the solution space more broadly than independent problem solvers, finding higher-quality solutions than all but the highest-scoring individuals.Quantum error correction is an essential tool for reliably performing tasks for processing quantum information on a large scale. However, integration into quantum circuits to achieve these tasks is problematic when one realizes that nontransverse operations, which are essential for universal quantum computation, lead to the spread of errors. Quantum gate teleportation has been proposed as an elegant solution for this. Here, one replaces these fragile, nontransverse inline gates with the generation of specific, highly entangled offline resource states that can be teleported into the circuit to implement the nontransverse gate. As the first important step, we create a maximally entangled state between a physical and an error-correctable logical qubit and use it as a teleportation resource. We then demonstrate the teleportation of quantum information encoded on the physical qubit into the error-corrected logical qubit with fidelities up to 0.786. Our scheme can be designed to be fully fault tolerant so that it can be used in future large-scale quantum technologies.