Ni-catalysed assembly of axially chiral alkenes from alkynyl tetracoordinate borons via 1,3-metallate shift.

Asymmetric synthesis based on a metallate shift of tetracoordinate borons is an intriguing and challenging topic. Despite the construction of central chirality from tetracoordinate boron species via a 1,2-metallate shift, catalytic asymmetric synthesis of axially chiral compounds from such boron 'ate' complexes is an ongoing challenge. Axially chiral alkenes have received great attention due to their unique characteristics and intriguing molecular scaffolds. Here we report an enantioselective nickel-catalysed strategy for the construction of axially chiral alkenes via a 1,3-metallate shift of alkynyl tetracoordinate boron species. The chemoselectivity, regioselectivity and atroposelectivity can be regulated and well-controlled from readily accessible starting materials with a cheap transition-metal catalyst. Downstream transformations indicate the powerful conversion ability of such compounds in this protocol, and late-stage elaborations of bioactive compounds can also be achieved. Mechanistic experiments reveal that regioselective syn-addition of an aryl-Ni complex with a carbon-carbon triple bond and subsequent 1,3-phenyl migration are the two key steps for the synthesis of axially chiral alkenes.

Bibliometric analysis of 100 top cited articles of heart failure-associated diseases in combination with machine learning.

Objective: The aim of this paper is to analyze the application of machine learning in heart failure-associated diseases using bibliometric methods and to provide a dynamic and longitudinal bibliometric analysis of heart failure-related machine learning publications. Materials and methods: Web of Science was screened to gather the articles for the study. Based on bibliometric indicators, a search strategy was developed to screen the title for eligibility. Intuitive data analysis was employed to analyze the top-100 cited articles and VOSViewer was used to analyze the relevance and impact of all articles. The two analysis methods were then compared to get conclusions. Results: The search identified 3,312 articles. In the end, 2,392 papers were included in the study, which were published between 1985 and 2023. All articles were analyzed using VOSViewer. Key points of the analysis included the co-authorship map of authors, countries and organizations, the citation map of journal and documents and a visualization of keyword co-occurrence analysis. Among these 100 top-cited papers, with a mean of 122.9 citations, the most-cited article had 1,189, and the least cited article had 47. Harvard University and the University of California topped the list among all institutes with 10 papers each. More than one-ninth of the authors of these 100 top-cited papers wrote three or more articles. The 100 articles came from 49 journals. The articles were divided into seven areas according to the type of machine learning approach employed: Support Vector Machines, Convolutional Neural Networks, Logistic Regression, Recurrent Neural Networks, Random Forest, Naive Bayes, and Decision Tree. Support Vector Machines were the most popular method. Conclusions: This analysis provides a comprehensive overview of the artificial intelligence (AI)-related research conducted in the field of heart failure, which helps healthcare institutions and researchers better understand the prospects of AI in heart failure and formulate more scientific and effective research plans. In addition, our bibliometric evaluation can assist healthcare institutions and researchers in determining the advantages, sustainability, risks, and potential impacts of AI technology in heart failure.

[Progress in the application of preparative gas chromatography in separating volatile compounds].

Gas chromatography (GC) yields superior separations of low boiling point volatile compounds. Therefore, preparative gas chromatography (Prep GC) was established by combining analytical GC with a sample collection system at the end of the column, enabling the efficient isolation of the volatile components from complex matrices and their subsequent collection after GC. As Prep GC is based on an analytical gas chromatograph, its injection, separation, detection, and fraction collection systems are continuously optimized and upgraded to improve the recoveries and purities of the target compounds. Prep GC, in combination with modern spectroscopic techniques (such as UV-Vis absorption spectroscopy, infrared absorption spectroscopy, Raman spectroscopy, mass spectrometry, X-ray diffraction, and nuclear magnetic resonance spectroscopy), enables accurate structural elucidation of a target compound. Reports of the separations of various volatile components from complex matrices using Prep GC have recently increased annually, revealing promising application prospects. However, Prep GC also displays several disadvantages, such as the failure to separate thermolabile compounds, high separation costs, and the likely introduction of exogenous contamination. Based on the recent related research, this review summarizes the evolution of the structure of Prep GC and its application in isolating essential oil monomers, insect pheromones, volatile food and plant components, geological biomarkers, and persistent environmental pollutants. Finally, this review also summarizes and prospects the use of Prep GC in separating volatile components to provide a reference for the expansion of its applications.

A clustering-triggered emission strategy for tunable multicolor persistent phosphorescence.

A clustering-triggered emission (CTE) strategy, namely the formation of heterogeneous clustered chromophores and conformation rigidification, for achieving tunable multicolor phosphorescence in single-component compounds is proposed. Non-conventional luminophores comprising just oxygen functionalities and free of π-bonding, i.e., d-(+)-xylose (d-Xyl), pentaerythritol (PER), d-fructose (d-Fru) and d-galactose (d-Gal), were adopted as a simple model system with an explicit structure and molecular packing to address the hypothesis. Their concentrated solutions and crystals at 77 K or under ambient conditions demonstrate remarkable multicolor phosphorescence afterglows in response to varying excitation wavelengths, because of the formation of diverse oxygen clusters with sufficiently rigid conformations. The intra- and inter-molecular O⋯O interactions were definitely illustrated by both single crystal structure analysis and theoretical calculations. These findings shed new light on the origin and simple achievement of tunable multicolor phosphorescence in single-component pure organics, and in turn, have strong implications for the emission mechanism of non-conventional luminophores.