Critical Care Ultrasonography and Its Application for COVID-19

Ultrasound has developed as an invaluable tool in diagnosis and proper management in the intensive care unit (ICU). Application of critical care ultrasonography is quite distinct from the routine comprehensive diagnostic ultrasound exam, because the urgent setting mandates a goal-directed approach. Performing accurate and efficient critical care ultrasound requires ultrasound providers to first understand the pathophysiology of the disease and related imaging findings, and then follow the protocols to perform a focused ultrasound exam. In the ongoing coronavirus disease 2019 (COVID-19) pandemic, ultrasound plays an essential role in diagnosing and monitoring critically ill COVID-19 patients in the ICU. Our review focuses on the basics and clinical application of critical care ultrasound in diagnosing common lung disease, COVID-19 pulmonary lesions, pediatric COVID-19, and cardiovascular dysfunction as well as its role in ECMO and interventional ultrasonography

Topological edge state transfer via topological adiabatic passage

The study of quantum state transfer has led to a variety of research efforts utilizing quantum simulators. By exploiting the tunability of the qubit frequency and qubit-qubit coupling, a superconducting qubit chain can simulate various topological band models. In our study, we demonstrate that a spin-up state can be transported along a topological qubit chain by modulating the coupling strengths and the qubit frequencies. We here propose another more straightforward approach to theoretically interpret this state transfer process. We show that the Hilebert space of the qubit chain can be restricted into the subspace of the only two edge states when investigating this process, and the Hamiltonian can degenerate to a two-state Landau-Zener (LZ) model. Therefore the state transfer process in this topological qubit chain is equivalent to the same process through the adiabatic passage of the LZ model. Further more, we show how to use this approach to generalize the state transfer process from one-qubit Fock state to two-qubit Bell state.Comment: arXiv admin note: substantial text overlap with arXiv:1711.0682

catena-Poly[[[tetra­aqua­cobalt(II)]-μ-4,4′-bipyridine-κ2 N:N′] 2-[4-(2-carboxyl­ato­eth­yl)phen­oxy]acetate]

In the title complex, {[Co(C10H8N2)(H2O)4](C11H10O5)}n, the unique CoII ion lies on an inversion center and is coordinated by two N atoms from two 4,4′-bipyridine ligands and four O atoms from four water mol­ecules in a slightly distorted octa­hedral coordination geometry. The 4,4′-bipyridine ligands bridge CoII ions into a one-dimensional chain structure. In the crystal structure, inter­molecular O—H⋯O hydrogen bonds link cations and anions into a three-dimensional network. The dianions are completely disordered about an inversion center

ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT

Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human natural language. However, LLMs currently have difficulty in bridging perception, language understanding and reasoning capabilities due to incompatibility of the underlying information flow among them, making it challenging to accomplish tasks autonomously. On the other hand, abductive learning (ABL) frameworks for integrating the two abilities of perception and reasoning has seen significant success in inverse decipherment of incomplete facts, but it is limited by the lack of semantic understanding of logical reasoning rules and the dependence on complicated domain knowledge representation. This paper presents a novel method (ChatABL) for integrating LLMs into the ABL framework, aiming at unifying the three abilities in a more user-friendly and understandable manner. The proposed method uses the strengths of LLMs' understanding and logical reasoning to correct the incomplete logical facts for optimizing the performance of perceptual module, by summarizing and reorganizing reasoning rules represented in natural language format. Similarly, perceptual module provides necessary reasoning examples for LLMs in natural language format. The variable-length handwritten equation deciphering task, an abstract expression of the Mayan calendar decoding, is used as a testbed to demonstrate that ChatABL has reasoning ability beyond most existing state-of-the-art methods, which has been well supported by comparative studies. To our best knowledge, the proposed ChatABL is the first attempt to explore a new pattern for further approaching human-level cognitive ability via natural language interaction with ChatGPT

Structure of the human smoothened receptor bound to an antitumour agent

The smoothened (SMO) receptor, a key signal transducer in the Hedgehog (Hh) signaling pathway is both responsible for the maintenance of normal embryonic development and implicated in carcinogenesis. The SMO receptor is classified as a class Frizzled (class F) G protein-coupled receptor (GPCR), although the canonical Hh signaling pathway involves the transcription factor Gli and the sequence similarity with class A GPCRs is less than 10%. Here we report the crystal structure at 2.5 Å resolution of the transmembrane domain of the human SMO receptor bound to the small molecule antagonist LY2940680. Although the SMO receptor shares the seven transmembrane helical (7TM) fold, most conserved motifs for class A GPCRs are absent, and the structure reveals an unusually complex arrangement of long extracellular loops stabilized by four disulfide bonds. The ligand binds at the extracellular end of the 7TM bundle and forms extensive contacts with the loops